Hydrology and Water Resources Management

Topic Information

Dear Colleagues,

Climatic warming is intensifying and complicating hydrological and associated processes worldwide, thereby affecting water security. The coupling of water, sediment, carbon, and nutrients in watersheds is a central challenging bottleneck that needs to be elucidated. The subsequent transport and transformation of waterborne materials can also affect river ecosystem health and greenhouse gas emissions. However, the mechanisms of these processes in response to environmental change is largely unknown. Addressing these problems will contribute to the rational management of water resources and effective response of water disasters in the world. Most countries are facing unprecedented pressure on water resources today. Water scarcity affects more than 40% of the global population, and a deficit of 40% continues to be present between water demand and available supply by 2030. Chronic water scarcity and extreme weather events (floods and droughts) have become the biggest threats to global prosperity and sustainability, associated with rapid economic development. Better understanding the effects of changing environment on water resources is therefore desired to strengthen water security against hydrological uncertainty and anthropogenic complexity.

In this Topic, innovative ideas and new modeling techniques are welcome for assisting hydrological and associated processes and sustainable water resources management from a multidisciplinary background. We encourage submissions on, but not limited to, surface and subsurface hydrological processes and coupled water–sediment modeling, riverine carbon–nitrogen transport, and riverine greenhouse emissions, Trade-off of water–grain–energy–ecological systems and coordinated development of ecology–water–economy, water resources conservation and optimization allocation, water policies adapting to extreme weather events, decision support systems and/or decision-making frameworks, risk assessment on water scarcity and flooding/drought disasters, information systems development for water resources monitoring, modeling, forecasting, and warning, as well as recycling and reuse schemes for storm water, wastewater, and non-conventional water sources are topics of interest.

Prof. Dr. Genxu Wang
Prof. Dr. Hongwei Lu
Prof. Dr. Lei Wang
Dr. Bahman Naser
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Atmosphere atmosphere	2.5	4.6	2010	16.1 Days	CHF 2400
Hydrology hydrology	3.1	4.9	2014	15.3 Days	CHF 1800
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400
Water water	3.0	5.8	2009	17.5 Days	CHF 2600

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Published Papers (73 papers)

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26 pages, 56682 KiB  

Open AccessArticle

Multi-Model Assessment of Climate Change Impacts on the Streamflow Conditions in the Kasai River Basin, Central Africa

by Samane Lesani, Salomon Salumu Zahera, Elmira Hassanzadeh, Musandji Fuamba and Ali Sharifinejad

Hydrology 2024, 11(12), 207; https://doi.org/10.3390/hydrology11120207 - 30 Nov 2024

Viewed by 1385

Abstract

The Congo River Basin is the second-largest watershed globally, flowing through nine countries before reaching the Atlantic Ocean. The Kasai River Basin (KARB), containing about one-fourth of Congo’s freshwater resources, plays a strategic role in sustaining navigation, food production, and hydroelectricity generation in [...] Read more.

The Congo River Basin is the second-largest watershed globally, flowing through nine countries before reaching the Atlantic Ocean. The Kasai River Basin (KARB), containing about one-fourth of Congo’s freshwater resources, plays a strategic role in sustaining navigation, food production, and hydroelectricity generation in Central Africa. This study applies a multi-model framework suited for data-scarce regions to assess climate change impacts on water availability in the KARB. Using two conceptual hydrological models calibrated with four reanalysis datasets and fed with bias-corrected outputs from 19 climate models under two representative climate pathways (RCPs), we project changes in the mean annual discharge ranging from −18% to +3%, highlighting the sensitivity of impact assessments to model and input data choices. Additionally, streamflow signatures (Q10, Q50, Q90) are projected to decline by approximately 9%, 18%, and 13%, respectively, under RCP 8.5. Annual hydropower potential is estimated to decrease by 14% and 5% under RCPs 4.5 and 8.5, respectively. These findings provide actionable insights for water management practices in the KARB, including guiding the development of adaptive strategies to optimize water allocation, mitigate risks of scarcity, and support sustainable agricultural and industrial activities in the region. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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28 pages, 7017 KiB  

Open AccessReview

Review on the Collaborative Research of Water Resources–Water Environment–Water Ecology in Hulun Lake

by Xianglong Dai, Yinglan A, Libo Wang, Baolin Xue, Yuntao Wang, Xiyin Zhou, Guangwen Ma, Hui Li, He Chen, Tongkui Liao and Yunling Li

Water 2024, 16(17), 2508; https://doi.org/10.3390/w16172508 - 4 Sep 2024

Viewed by 1291

Abstract

Managing water resources amidst the pressures of climate change and human activities is a significant challenge, especially in regions experiencing shrinking lakes, deteriorating water quality, and ecological degradation. This review focuses on achieving integrated river basin management by learning from the governance experiences [...] Read more.

Managing water resources amidst the pressures of climate change and human activities is a significant challenge, especially in regions experiencing shrinking lakes, deteriorating water quality, and ecological degradation. This review focuses on achieving integrated river basin management by learning from the governance experiences of typical watersheds globally, using the Hulun Lake Basin as a case study. Hulun Lake, China’s fifth-largest lake, experienced severe ecological problems from 2000 to 2009 but saw improvements after comprehensive management efforts from 2012 onward. This review systematically explores methods to address water resource, environment, and ecological challenges through the lenses of data acquisition, mechanism identification, model simulation, and regulation and management. Drawing lessons from successful basins such as the Rhine, Ganges, Mississippi, and Murray–Darling, the review proposes key goals for comprehensive management, including establishing extensive monitoring networks, developing predictive models, and creating contingency plans for routine and emergency management. Leveraging advanced technologies like satellite imagery and IoT sensors, alongside continuous improvement mechanisms, will ensure the sustainable use and protection of river basins. This review provides a detailed roadmap for achieving comprehensive watershed management in Hulun Lake, summarizing effective strategies and outcomes from data acquisition to regulation, thus serving as a model for similar regions globally. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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11 pages, 4957 KiB  

Open AccessCommunication

A ‘Nuclear Bomb’ or Just ‘a Joke’? Groundwater Models May Help Communicate Nuanced Risks to the Great Salt Lake

by Matthew D. LaPlante, Piyush Dahal, Shih-Yu Simon Wang, Kirsti Hakala and Avik Mukherjee

Water 2024, 16(16), 2221; https://doi.org/10.3390/w16162221 - 6 Aug 2024

Cited by 2 | Viewed by 1494

Abstract

The Great Salt Lake entered the zeitgeist of environmental concern in 2022 when a coalition of scientists and activists warned in a highly publicized report that the lake might be just five years away from complete desiccation, a possibility one state official warned [...] Read more.

The Great Salt Lake entered the zeitgeist of environmental concern in 2022 when a coalition of scientists and activists warned in a highly publicized report that the lake might be just five years away from complete desiccation, a possibility one state official warned was tantamount to an “environmental nuclear bomb”. Shortly thereafter, an unpredicted and unprecedented pluvial winter resulted in an increase in inflow, temporarily halting the lake’s decline and prompting Utah’s governor to mock the dire prediction as “a joke”, an outcome that speaks to the tension between agenda-setting and trust-building that researchers face when sharing worst-case warnings, particularly those based on short-term variability. Here, we describe a robust relationship between the lake and groundwater in the surrounding region and demonstrate how coupled models can thus be used to improve lake elevation predictions, suggesting that while the situation may not be as dire as some have warned, the lake remains at long-term risk as a result of climate warming. We further suggest that efforts to communicate the risk of future desiccation should be informed by stochastic variability and guided by long-term fluctuations in the total water storage of the endorheic lake’s watershed. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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1 pages, 127 KiB  

Open AccessCorrection

Correction: LaPlante et al. Ocean Temperatures Do Not Account for a Record-Setting Winter in the U.S. West. Atmosphere 2024, 15, 284

by Matthew D. LaPlante, Liping Deng, Luthiene Dalanhese and Shih-Yu Wang

Atmosphere 2024, 15(8), 892; https://doi.org/10.3390/atmos15080892 - 26 Jul 2024

Viewed by 604

Abstract

The corresponding author for this article [...] Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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25 pages, 3542 KiB  

Open AccessArticle

Strategy for Adapting Environmental Flow Proposals to Situations with High Agricultural Demands

by Domingo Baeza, Patricia Chacón and Eugenio Rico

Water 2024, 16(15), 2106; https://doi.org/10.3390/w16152106 - 25 Jul 2024

Viewed by 873

Abstract

Managing water in catchments with high agricultural demands, particularly during periods of low natural flows, is a challenging task. Environmental flow regimes, which are based on monthly minimum values, may not be adequate to address issues associated with rivers that have complex hydrological [...] Read more.

Managing water in catchments with high agricultural demands, particularly during periods of low natural flows, is a challenging task. Environmental flow regimes, which are based on monthly minimum values, may not be adequate to address issues associated with rivers that have complex hydrological alteration patterns. The technical solution that provides values to create a flow regime can often be impractical for addressing large problems that planners need to solve, especially when demands are high and resources are limited. This work proposes a new approach to the problem by recognising established agricultural uses and demands that reduce river flow. The focus is on reducing the changes in the hydrological regime by proposing an alternative environmental flow regime that is compatible with agriculture. Deviation from the natural flow of these rivers has been minimized through various processes. Initially, this was achieved by reducing irrigation flows through more efficient demand calculations. The results provide solutions for various hydrological alteration problems, in three rivers, Riaza, Duratón, and Eresma; the inverted regime was corrected, in Cega, Tormes, and Adaja, whose main problem was the reduction of peak flows; controlled peak flows that are compatible with the available water and demands are proposed; and finally in the Agueda river, the reduction in monthly flows was increased on a monthly basis. A new strategy is proposed for considering environmental aspects in the management of rivers with high demands, which improves the fixed schemes for determining environmental flows used in Mediterranean basins. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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17 pages, 5577 KiB  

Open AccessArticle

Game Theory Applications in Equilibrium Water Pricing of Multiple Regional Sources and Users

by Shiwu Wang, Shangbin Liu, Shuiping Yao, Xi Guo, Shan-e-hyder Soomro, Chaojie Niu, Liyu Quan and Caihong Hu

Water 2024, 16(13), 1845; https://doi.org/10.3390/w16131845 - 28 Jun 2024

Cited by 1 | Viewed by 1486

Abstract

China has been facing a contradiction between its water supply and demand for a long time, and it is urgent that it builds a “water-saving society”. Previous research on water pricing mainly focused on the policy level, only considering the supply and demand [...] Read more.

China has been facing a contradiction between its water supply and demand for a long time, and it is urgent that it builds a “water-saving society”. Previous research on water pricing mainly focused on the policy level, only considering the supply and demand sides and ignoring the participation of local governments. Due to the inconsistent approval mechanisms, different times of cost formation, and lack of a scientific pricing relationship between multiple water sources and multiple users, with the current water pricing in China, it is difficult to solve the complex problem of water resource allocation. This study aimed to promote the qualitative supply of water and the reuse of reclaimed water, achieve a high-quality and low-cost water supply, and explore the role of water-pricing mechanisms in the regulation of multi-source water supply configurations. The mechanism of regulation is constructed for the complex, multi-source, multi-user water resource system, and a three-party game model is established among local governments, water supply enterprises, and water users. A reasonable pricing system with a rational price relationship is obtained, and Pinghu City in Zhejiang Province is taken as the research area. The prices of the external water supply to residential users, non-resident users, and special users are 4.48 CNY/m³, 6.28 CNY/m³, and 7.12 CNY/m³. The external supply prices for resident users, non-resident users, and special users are 3.81 CNY/m³, 5.25 CNY/m³, and 6.05 CNY/m³. The external supply price for non-resident users is 2.62 CNY/m³ for reclaimed water. The results of the study showed that when the government’s contribution did not exceed the amount that it would have been without the inclusion of recycled water and the annual payment of water users did not exceed their ability to pay, the income of water suppliers increased by 69%. The three balanced objectives of rational water resource configuration by the local government, reasonable profit for the water supply enterprise, and reasonable payment by water users have been achieved. This study provides theoretical and methodological support for the implementation of water pricing for multi-source and multi-user water supplies in water-scarce areas. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 6109 KiB  

Open AccessArticle

Evaluating the Performance and Applicability of Satellite Precipitation Products over the Rio Grande–San Juan Basin in Northeast Mexico

by Dariela A. Vázquez-Rodríguez, Víctor H. Guerra-Cobián, José L. Bruster-Flores, Carlos R. Fonseca and Fabiola D. Yépez-Rincón

Atmosphere 2024, 15(7), 749; https://doi.org/10.3390/atmos15070749 - 22 Jun 2024

Viewed by 1199

Abstract

Accurate observation of precipitation data is crucial for hydrometeorological applications, requiring temporal and spatial precision. Satellite precipitation products offer a promising solution for obtaining precipitation estimates, facilitating long-term observations from global to local scales. However, assessing their accuracy compared to rain gauge observations [...] Read more.

Accurate observation of precipitation data is crucial for hydrometeorological applications, requiring temporal and spatial precision. Satellite precipitation products offer a promising solution for obtaining precipitation estimates, facilitating long-term observations from global to local scales. However, assessing their accuracy compared to rain gauge observations is essential. This study aims to assess the accuracy and applicability of precipitation data from CMORPH, IMERG, and PERSIANN CCS in the Rio Grande–San Juan Basin in northeast Mexico. The evaluation of estimated precipitation was assessed using the Pearson and Spearman correlations, RMSE, MAE, and BIAS for both monthly and yearly averages. CMORPH showed minimal errors and low underestimation, while IMERG exhibited high correlations with consistent underestimation. PERSIANN CCS had lower correlations, significant overestimation, and higher errors. The Mann–Kendall (MK) test was used to determinate the precipitation trends of observed and estimated data. The observed data showed a significant positive trend in monthly averages, which is not reflected in the annual trend. Furthermore, negative annual trends were found in at least 10 stations across the basin. The application of satellite precipitation data yielded mixed outcomes, with CMORPH showing the highest level of agreement with the trend analysis results from rain gauge data. This demonstrates its reliability for weather and climate studies and suggests the potential for CMORPH to be used as an input in hydrological modeling. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 11489 KiB  

Open AccessArticle

Prioritization of Hydrological Restoration Areas Using AHP and GIS in Dulcepamba River Basin in Bolivar–Ecuador

by Eddy Fernando Sanchez and Cesar Ivan Alvarez

Hydrology 2024, 11(6), 81; https://doi.org/10.3390/hydrology11060081 - 12 Jun 2024

Cited by 6 | Viewed by 1578

Abstract

In this study, we performed a preliminary soil analysis and collected environmental data for the Dulcepamba River Basin in Bolivar–Ecuador, before carrying out its hydrological restoration (HR). A geographic information system (GIS) and the multicriterion Analytical Hierarchy Process (AHP) decision-making method were used. [...] Read more.

In this study, we performed a preliminary soil analysis and collected environmental data for the Dulcepamba River Basin in Bolivar–Ecuador, before carrying out its hydrological restoration (HR). A geographic information system (GIS) and the multicriterion Analytical Hierarchy Process (AHP) decision-making method were used. The comprehensive evaluation included morphological aspects, soil properties, climatic conditions, vegetation, and land use. The terrain conditions were investigated using indicators such as the flow capacity, topographic moisture, soil resistance, sediment transport, current density, curve number, NDVI, precipitation, and distance to rivers. The results and analysis are presented in a series of maps, which establish a starting point for the HR of the Dulcepamba watershed. The key factors for assessing soil degradation in the watershed include land use, vegetation cover, sedimentation, humidity, and precipitation. Of the studied territory, 10.7 do not require HR, while 20.28% demand HR in the long term. In addition, 30.67% require HR in the short term, and 33.35% require HR immediately. Based on the findings, it is suggested that authorities consider the environmental remediation of the watershed and propose various HR measures. This analytical approach could prove valuable as a tool for the environmental restoration of watersheds in Ecuador. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 6733 KiB  

Open AccessArticle

Quantifying the Impacts of Dry–Wet Combination Events on Vegetation Vulnerability in the Loess Plateau under a Changing Environment

by Haixia Dong, Yuejiao Gao, Shengzhi Huang, Tiejun Liu, Qiang Huang and Qianqian Cao

Water 2024, 16(12), 1660; https://doi.org/10.3390/w16121660 - 11 Jun 2024

Viewed by 1286

Abstract

Extreme drought and flood events, as well as their combined events, pose significant challenges to global sustainable socio-economic development and ecological health. However, the impact of dry–wet combination events (DWCEs) on vegetation vulnerability remains to be investigated. The Loess Plateau (LP) was selected [...] Read more.

Extreme drought and flood events, as well as their combined events, pose significant challenges to global sustainable socio-economic development and ecological health. However, the impact of dry–wet combination events (DWCEs) on vegetation vulnerability remains to be investigated. The Loess Plateau (LP) was selected as the study area to explore the response time of vegetation to precipitation index changes by optimal correlation coefficient; then, the impact of different DWCEs on vegetation vulnerability under moderate and severe scenarios was analyzed; finally, a vegetation loss probability model was constructed based on the copula function and Bayesian framework, to quantify the vegetation loss probability under DWCEs stress. The results indicate that: (1) normalized difference vegetation index (NDVI) shows an upward trend in spring, summer, and autumn, with the proportion of areas are 90.5%, 86.2%, and 95.4%, respectively, and show an insignificant trend in winter; (2) the response time of vegetation to precipitation index changes tends to be one or two seasons; (3) moderate scenarios have more influence than severe scenarios, dry-to-wet events (DWEs), wet-to-dry events (WDE) and continuous dry events (CDE) in spring-summer have a significant impact on summer vegetation of Ningxia and Shanxi, and WDE and CDE have a higher impact on autumn vegetation. (4) in terms of the probability of vegetation loss, DWE, and CDE cause higher losses to summer vegetation, while WDE and CDE cause higher losses to autumn vegetation. This study quantifies the impact of adjacent seasonal DWCE stress on future vegetation vulnerability. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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15 pages, 2764 KiB  

Open AccessArticle

Comparative Study of Low Flow Frequency Analysis Using Bivariate Copula Model at Soyanggang Dam and Chungju Dam

by Jiyoung Sung and Boosik Kang

Hydrology 2024, 11(6), 79; https://doi.org/10.3390/hydrology11060079 - 31 May 2024

Viewed by 1063

Abstract

A univariate analysis that relies solely on precipitation data in low flow frequency analysis is a technique to express meteorological drought, so it is limited to analyzing the characteristics of hydrological drought related to available water resources. In addition, if the data for [...] Read more.

A univariate analysis that relies solely on precipitation data in low flow frequency analysis is a technique to express meteorological drought, so it is limited to analyzing the characteristics of hydrological drought related to available water resources. In addition, if the data for the model calibration are insufficient, the uncertainty of a single variable limits the construction of a reliable model. To improve this problem, a frequency analysis was performed by constructing a bivariate copula model as a multivariate model with a high correlation between variables targeting reservoir inflows. The methodology utilizes the theory of runs to identify low flow events, establishing a threshold based on the mandatory regional water supply plan, and determining the low flow duration and cumulative water deficit. The Gumbel copula function, effective in capturing correlations between hydrological variables, was applied to derive a joint bivariate probability distribution, facilitating the calculation of combined low flow event return periods. This study compared low flow frequencies at Soyanggang dam (’74–’22) and Chungju dam (’86–’22), which are in the same Han River basin but have different capacities and water demands, using a bivariate copula model. The top four extreme low flow events for the two adjacent dam basins did not occur in the same year and, in the years of the extreme low flow events at one of the two dam basins, there was an insignificant magnitude at the remaining dam basin. This result is noteworthy because it shows that the possibility of extreme low flow events appearing simultaneously in both watersheds is not as high as expected. The operational efficiency can be improved by setting the coordinated operation rules of the two reservoirs using the copula dependency structure. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 15769 KiB  

Open AccessArticle

Evaluation of Gridded Rainfall Products in Three West African Basins

by Omar Goudiaby, Ansoumana Bodian, Alain Dezetter, Ibrahima Diouf and Andrew Ogilvie

Hydrology 2024, 11(6), 75; https://doi.org/10.3390/hydrology11060075 - 29 May 2024

Cited by 2 | Viewed by 2085

Abstract

In recent years, accessing rainfall data from ground observation networks maintained by national meteorological services in West Africa has become increasingly challenging. This is primarily due to high acquisition costs and the often sparse distribution of rainfall gauges across the region, which limits [...] Read more.

In recent years, accessing rainfall data from ground observation networks maintained by national meteorological services in West Africa has become increasingly challenging. This is primarily due to high acquisition costs and the often sparse distribution of rainfall gauges across the region, which limits their use in hydrological studies and related research. At the same time, the rising availability of precipitation products derived from satellite/earth observations, reanalysis datasets, and in situ measurements presents exciting prospects for hydrological applications. Nonetheless, these datasets constitute indirect measurements, necessitating rigorous validation against ground-based rainfall data. This study comprehensively assesses twenty-three gridded rainfall products, including sixteen from satellites, six from reanalysis data, and one from in situ measurements, across the Senegal, Gambia, and Casamance River basins. Performance evaluation is conducted across distinct climatic zones, both pre- and post-resampling against observed rainfall data gathered from forty-nine rainfall stations over a six-year period (2003–2008). Evaluation criteria include the Kling–Gupta Efficiency (KGE) and Percentage of Bias (PBIAS) metrics, assessed at daily, monthly, and seasonal time steps. The results reveal distinct performance levels among the evaluated rainfall products. RFE, ARC2, and CPC notably yield the highest KGE scores at the daily time step, while GPCP, CHIRP, CHIRPS, RFE, MSWEP, ARC2, CPC, TAMSAT, and CMORPHCRT demonstrate superior performance at the monthly time step. During the rainy season, these products generally exhibit robustness. However, rainfall estimates derived from reanalysis datasets (ERA5, EWEMBI, MERRA2, PGF, WFDEICRU, and WFDEIGPCC) perform poorly in the studied basins. Based on the PBIAS metric, most products tend to underestimate precipitation values, while only PERSIANN and PERSIANNCCS lead to significant overestimations. Spatially, optimal performance of the products is observed in the Casamance basin and the Sudanian and Sahelian climatic zones within the Gambia and Senegal basins. Conversely, in the Guinean zone of the Gambia and Senegal Rivers, the rainfall products displayed the poorest performance. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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20 pages, 10411 KiB  

Open AccessArticle

Spatiotemporal Evaluation of Water Resources in Citarum Watershed during Weak La Nina and Weak El Nino

by Armi Susandi, Arief Darmawan, Albertus Sulaiman, Mouli De Rizka Dewantoro, Aristyo Rahadian Wijaya, Agung Riyadi, Agus Salim, Rafif Rahman Darmawan and Angga Fauzan Pratama

Hydrology 2024, 11(6), 73; https://doi.org/10.3390/hydrology11060073 - 22 May 2024

Cited by 1 | Viewed by 1904

Abstract

This study investigates the dynamics of water resources in the Citarum watershed during periods of weak La Niña, normal, and weak El Niño conditions occurring sequentially. The Citarum watershed serves various purposes, being utilized not only by seven (7) districts and two (2) [...] Read more.

This study investigates the dynamics of water resources in the Citarum watershed during periods of weak La Niña, normal, and weak El Niño conditions occurring sequentially. The Citarum watershed serves various purposes, being utilized not only by seven (7) districts and two (2) cities in West Java, Indonesia but also as a source of raw water for drinking in the City of Jakarta. Using a time-series analysis of surface water data, data-driven (machine learning) methods, and statistical analysis methods, spatiotemporal predictions of surface water have been made. The surface water time series data (2017–2021), obtained from in situ instruments, are used to assess water resources, predict groundwater recharge, and analyze seasonal patterns. The results indicate that surface water follows a seasonal pattern, particularly during the monsoon season, corresponding to the groundwater recharge pattern. In upstream areas, water resources exhibit an increasing trend during both weak La Nina and weak El Niño, except for Jatiluhur Dam, where a decline is observed in both seasons. Machine learning predictions suggest that water levels and groundwater recharge tend to decrease in both upstream and downstream areas. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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14 pages, 2852 KiB  

Open AccessArticle

On the Optimized Management of Activated Distributed Storage Systems: A Novel Approach to Flood Mitigation

by Riley Post, Felipe Quintero and Witold F. Krajewski

Water 2024, 16(11), 1476; https://doi.org/10.3390/w16111476 - 22 May 2024

Cited by 2 | Viewed by 1246

Abstract

New flood records are being set across the world as precipitation patterns change due to a warming climate. Despite the presence of longstanding water management infrastructure like levees and reservoirs, this rise in flooding has been met with property damage, loss of life, [...] Read more.

New flood records are being set across the world as precipitation patterns change due to a warming climate. Despite the presence of longstanding water management infrastructure like levees and reservoirs, this rise in flooding has been met with property damage, loss of life, and hundreds of billions in economic impact, suggesting the need for new solutions. In this work, the authors suggest the active management of distributed networks of ponds, wetlands and retention basins that already exist across watersheds for the mitigation of flood damages. As an example of this approach, we investigate optimal control of the gated outlets of 130 such locations within a small watershed using linear programming, genetic algorithms, and particle swarm optimization, with the objective of reducing downstream flow and maximizing basin storage. When compared with passive operation (i.e., no gated outlets) and a uniformly applied active management scheme designed to store water during heavy rainfall, the optimal control techniques (1) reduce the magnitudes of peak flow events by up to 10%, (2) reduce the duration of flood crests for up to several days, and (3) preserve additional storage across the watershed for future rainfall events when compared with active management. Combined, these findings provide both a better understanding of dynamically controlled distributed storage as a flood fighting technique and a springboard for future work aimed at its use for reducing flood impacts. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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25 pages, 11676 KiB  

Open AccessArticle

Deep Learning-Based Automatic River Flow Estimation Using RADARSAT Imagery

by Samar Ziadi, Karem Chokmani, Chayma Chaabani and Anas El Alem

Remote Sens. 2024, 16(10), 1808; https://doi.org/10.3390/rs16101808 - 20 May 2024

Cited by 3 | Viewed by 3694

Abstract

Estimating river flow is a key parameter for effective water resource management, flood risk prevention, and hydroelectric facilities planning. Yet, traditional gauging methods are not reliable under very high flows or extreme events. Hydrometric network stations are often sparse, and their spatial distribution [...] Read more.

Estimating river flow is a key parameter for effective water resource management, flood risk prevention, and hydroelectric facilities planning. Yet, traditional gauging methods are not reliable under very high flows or extreme events. Hydrometric network stations are often sparse, and their spatial distribution is not optimal. Therefore, many river sections cannot be monitored using traditional flow measurements and observations. In the last few decades, satellite sensors have been considered as complementary observation sources to traditional water level and flow measurements. This kind of approach has provided a way to maintain and expand the hydrometric observation network. Remote sensing data can be used to estimate flow from rating curves that relate instantaneous flow (Q) to channel cross-section geometry (effective width or depth of the water surface). Yet, remote sensing has limitations, notably its dependence on rating curves. Due to their empirical nature, rating curves are limited to specific river sections (reaches) and cannot be applied to other watercourses. Recently, deep-learning techniques have been successfully applied to hydrology. The primary goal of this study is to develop a deep-learning approach for estimating river flow in the Boreal Shield ecozone of Eastern Canada using RADARSAT-1 and -2 imagery and convolutional neural networks (CNN). Data from 39 hydrographic sites in this region were used in modeling. A new CNN architecture was developed to provide a straightforward estimation of the instantaneous river flow rate. Our results yielded a coefficient of determination (R²) and a Nash–Sutcliffe value of 0.91 and a root mean square error of 33 m³/s. Notably, the model performs exceptionally well for rivers wider than 40 m, reflecting its capability to adapt to varied hydrological contexts. These results underscore the potential of integrating advanced satellite imagery with deep learning to enhance hydrological monitoring across vast and remote areas. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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19 pages, 16506 KiB  

Open AccessArticle

Evaluation of Near Real-Time Global Precipitation Measurement (GPM) Precipitation Products for Hydrological Modelling and Flood Inundation Mapping of Sparsely Gauged Large Transboundary Basins—A Case Study of the Brahmaputra Basin

by Muhammad Jawad, Biswa Bhattacharya, Adele Young and Schalk Jan van Andel

Remote Sens. 2024, 16(10), 1756; https://doi.org/10.3390/rs16101756 - 15 May 2024

Cited by 1 | Viewed by 1262

Abstract

Limited availability of hydrometeorological data and lack of data sharing practices have added to the challenge of hydrological modelling of large and transboundary catchments. This research evaluates the suitability of latest near real-time global precipitation measurement (GPM)-era satellite precipitation products (SPPs), IMERG-Early, IMERG-Late [...] Read more.

Limited availability of hydrometeorological data and lack of data sharing practices have added to the challenge of hydrological modelling of large and transboundary catchments. This research evaluates the suitability of latest near real-time global precipitation measurement (GPM)-era satellite precipitation products (SPPs), IMERG-Early, IMERG-Late and GSMaP-NRT, for hydrological and hydrodynamic modelling of the Brahmaputra Basin. The HEC-HMS modelling system was used for the hydrological modelling of the Brahmaputra Basin, using IMERG-Early, IMERG-Late, and GSMaP-NRT. The findings showed good results using GPM SPPs for hydrological modelling of large basins like Brahmaputra, with Nash–Sutcliffe efficiency (NSE) and R² values in the range of 0.75–0.85, and root mean square error (RMSE) between 7000 and 9000 m³ s⁻¹, and the average discharge was 20611 m³ s⁻¹. Output of the GPM-based hydrological models was then used as input to a 1D hydrodynamic model to assess suitability for flood inundation mapping of the Brahmaputra River. Simulated flood extents were compared with Landsat satellite-captured images of flood extents. In critical areas along the river, the probability of detection (POD) and critical success index (CSI) values were above 0.70 with all the SPPs used in this study. The accuracy of the models was found to increase when simulated using SPPs corrected with ground-based precipitation datasets. It was also found that IMERG-Late performed better than the other two precipitation products as far as hydrological modelling was concerned. However, for flood inundation mapping, all of the three selected products showed equally good results. The conclusion is reached that for sparsely gauged large basins, particularly for trans-boundary ones, GPM-era SPPs can be used for discharge simulation and flood inundation mapping. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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25 pages, 9428 KiB  

Open AccessArticle

The Effects of Climate Change on Streamflow, Nitrogen Loads, and Crop Yields in the Gordes Dam Basin, Turkey

by Ayfer Özdemir, Martin Volk, Michael Strauch and Felix Witing

Water 2024, 16(10), 1371; https://doi.org/10.3390/w16101371 - 11 May 2024

Viewed by 1536

Abstract

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using [...] Read more.

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m³/s and 4 m³/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 6222 KiB  

Open AccessArticle

Timescale of Groundwater Recharge in High Percolation Coastal Plain Soils

by Qing Du and Mark Ross

Water 2024, 16(10), 1320; https://doi.org/10.3390/w16101320 - 7 May 2024

Viewed by 1556

Abstract

Understanding and modeling the timing and magnitude of groundwater recharge from rainfall infiltration through vadose-zone percolation is important for many reasons but especially because the flux is being acted on by root-zone evapotranspiration (ET), and very little rainfall infiltration ever becomes water-table recharge. [...] Read more.

Understanding and modeling the timing and magnitude of groundwater recharge from rainfall infiltration through vadose-zone percolation is important for many reasons but especially because the flux is being acted on by root-zone evapotranspiration (ET), and very little rainfall infiltration ever becomes water-table recharge. This study elaborates on the considerable time of the wetting front’s arrival and ultimate bulk recharge of rainfall infiltration in the shallow water table with fine-sandy soil typical of coastal plain environments such as Florida. Calibrated Hydrus-1D modeling of Florida (Myakka) soil was evaluated at varying depths of the water table and hydraulic conductivities to bracket the timing of arrival of the wetting front and bulk fluxes. Useful normalized timing parameters are defined. In addition, this research further quantifies the concept of “wet equilibrium”, and the considerable vadose-zone storage potential over and above the hydrostatic pressure equilibrium that must be overcome to achieve any significant water-table recharge in typical seasonal hydrologic timescales. The results indicate recharge timescales for water-table depths of 1 m are approximately 1 day but are considerably longer for 2 m (2 weeks), 3 m (1 month), and 4 m (50 days) conditions. Given that daily vadose-zone potential ET demand can exceed 0.5 cm/day in this environment, estimating recharge from rainfall infiltration is likely unreliable unless this timescale and the plant-root-zone uptake processes are properly modeled in surface-groundwater models. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 2513 KiB  

Open AccessArticle

Construction and Change Analysis of Water Ecosystem Service Flow Networks in the Xiangjiang River Basin (XRB)

by Yaoting Gu, Xianlan Lao, Lilisha Zhuo, Xiaochang Li and Chuxiong Deng

Sustainability 2024, 16(9), 3813; https://doi.org/10.3390/su16093813 - 1 May 2024

Cited by 2 | Viewed by 1798

Abstract

Clearing and successfully characterizing ecosystem service flow paths has become a key bottleneck restricting in-depth research on the supply and demand relationships of ecosystem services. At present, although some explorations have been performed using water ecosystem services as a pioneer, the nature of [...] Read more.

Clearing and successfully characterizing ecosystem service flow paths has become a key bottleneck restricting in-depth research on the supply and demand relationships of ecosystem services. At present, although some explorations have been performed using water ecosystem services as a pioneer, the nature of its network and the fact that ecological base flow needs to be eliminated have been ignored. This study used InVEST and network models to consider ecological base flow, quantifying the supply, demand, and flow paths of freshwater ecosystem services in the Xiangjiang River Basin. The results showed that the overall distribution of the water supply in the Xiangjiang River Basin from 2000 to 2020 shows a pattern of higher supply in the south and lower supply in the north. The distribution of water demand shows higher levels in the north and lower levels in the south. The network density remains at its maximum level. The results of this study have provided a scientific basis for water resource management in river basins and improving ecological compensation mechanisms. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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16 pages, 5657 KiB  

Open AccessArticle

Use of Soil Moisture as an Indicator of Climate Change in the SUPer System

by Josicleda Domiciano Galvincio, Rodrigo de Queiroga Miranda and Gabrielly Gregorio da Luz

Hydrology 2024, 11(5), 65; https://doi.org/10.3390/hydrology11050065 - 30 Apr 2024

Cited by 1 | Viewed by 2143

Abstract

Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study [...] Read more.

Soil moisture can be an important indicator of climate change in humid and semi-arid areas. This indicator can more efficiently propose different public policies related to climate change than just using precipitation and temperature data. Given the above, the objective of this study is to evaluate changes in soil moisture in the state of Pernambuco during the period 1961–2021, using the System of Hydrological Response Units for Pernambuco. In this study, two river basins in the state of Pernambuco that represent the different climatic conditions of the state were chosen. The results show that in the coastal region there is a tendency towards more saturated soils, and in the semi-arid region there is a tendency towards drier soils. With these results, it is possible to conclude that public policy decisions for the economy, environment, and society must consider this vital water balance variable. Leveraging soil moisture and precipitation data makes it possible to differentiate between flood risks and landslide vulnerabilities, particularly in regions characterized by higher levels of rainfall. Monitoring soil water content in humid and semi-arid areas can significantly enhance early warning systems, thereby preventing loss of life and minimizing the socio-economic impacts of such natural events. As such, this study provides a holistic understanding of the relationship between climatic patterns, soil moisture dynamics, and the occurrence of droughts and floods, ultimately contributing to more effective disaster preparedness and response measures in Pernambuco and similar regions. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 4960 KiB  

Open AccessArticle

Water Resource Management of Salalah Plain Aquifer Using a Sustainable Approach

by Mahaad Issa Shammas

Sustainability 2024, 16(9), 3670; https://doi.org/10.3390/su16093670 - 27 Apr 2024

Viewed by 1593

Abstract

A sustainable approach is proposed for managing the effects of salinity ingression in Salalah coastal aquifer, Oman. This paper aims to analyze and compare the groundwater levels and salinity of the aquifer from 1993 to 2027, considering both predictive and actual transient scenarios. [...] Read more.

A sustainable approach is proposed for managing the effects of salinity ingression in Salalah coastal aquifer, Oman. This paper aims to analyze and compare the groundwater levels and salinity of the aquifer from 1993 to 2027, considering both predictive and actual transient scenarios. Two novel scenarios were proposed, established, and examined in this study to bring back the aquifer to steady-state condition. The first scenario entails ceasing groundwater pumping from both Salalah and Saada wellfields, while compensating for the groundwater supply from these sources with surplus desalinated water. This scenario is projected to occur during the predictive period spanning from 2023 to 2027, denoted Scenario A. The second scenario is business as usual and involves continuing pumping from both wellfields during the same predictive period, denoted Scenario B. A numerical model for 3D flow simulation and advective transport modeling showed that on the eastern side of the Salalah coastal aquifer, the extent of seawater intrusion (SWI) was identified stretching from the shoreline to a distance of 1800 m, 1200 m, 0 m, and 600 m, in years 2011, 2014, 2018, and 2022 under the transient period, whereas SWI was delineated in land up to 0 m and 700 m in the predictive year 2027 under Scenarios A and B, respectively. In the western side of Salalah coastal aquifer, SWI was delineated in land up to 2000 m, 1700 m, 0 m, and 800 m, in years 2011, 2014, 2018, and 2022 under the transient period, whereas SWI was delineated in land up to 0 m and 750 m in the predictive year 2027 under Scenarios A and B, respectively. This study claims that Scenario A effectively pushed the seawater interface back to the coastline, projecting its reach to the shoreline (0 m) by 2027. In contrast, in baseline Scenario B, the wedge of saline intrusion in the Salalah coastal aquifer was delineated from the shoreline, up to 800 m inland, which accounted for continuation of pumping from both wellfields during the predictive period. The study concludes that Scenario A has the capability to efficiently reduce the impact of saline inflows from the coast, while Scenario B results in a more pronounced impact of salinity intrusion. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 6834 KiB  

Open AccessArticle

Elevational Patterns of Forest Evapotranspiration and Its Sensitivity to Climatic Variation in Dryland Mountains

by Hongyu Li, Xiaohuang Liu, Wenbo Zhang, Haoyang Zhu, Xiaofeng Zhao, Jiufen Liu, Xinping Luo, Ran Wang, Honghui Zhao and Chao Wang

Water 2024, 16(9), 1252; https://doi.org/10.3390/w16091252 - 27 Apr 2024

Cited by 2 | Viewed by 1467

Abstract

Elevational climatic heterogeneity, complex terrains, and varying subsurface properties affect the sensitivity of evapotranspiration (ET) in dryland mountain forests to hydrometeorological changes. However, the elevational distribution of ET sensitivity and its major influencing factors remain poorly understood. This study focused on the mid-altitude [...] Read more.

Elevational climatic heterogeneity, complex terrains, and varying subsurface properties affect the sensitivity of evapotranspiration (ET) in dryland mountain forests to hydrometeorological changes. However, the elevational distribution of ET sensitivity and its major influencing factors remain poorly understood. This study focused on the mid-altitude zone (1000–3500 m) forests in the Chinese Western Tianshan Mountains and assessed ET sensitivity to multiple climate variables, including precipitation (P) and potential evapotranspiration (PET), from 2000 to 2020. To evaluate the multi-year mean and trends in ET sensitivity, multi-source remote sensing data and regional survey data were analyzed using Spearman’s correlation coefficient, the sliding window method, and Kendall’s test. Furthermore, the relative importance of environmental variables (topography, geology, soil, and vegetation) was investigated. P and PET showed no significant trends, while ET exhibited a significant increasing trend (5.81 mm/yr, p < 0.01), particularly at elevations above 2000 m. Most forests (93.5%) showed a positive sensitivity of ET to P, and 70.0% showed a positive sensitivity of ET to PET, mainly at elevations of 1500–2500 m. Additionally, the trend in ET sensitivity to P decreased with an increasing elevation, with 64.5% showing a positive trend. Meanwhile, the trend in ET sensitivity to PET increased with elevation, with 88.1% showing a positive trend. Notably, 53.2% of the forests showed increasing ET sensitivity trends to both P and PET, primarily at elevations of 2000–3000 m with a mean normalized difference vegetation index (NDVI) of 0.56. Geological factors, particularly the hydrological properties of weathered bedrock, contributed the most (~47%) to mean sensitivity. However, geological and vegetative factors, including the NDVI and root zone water availability, were the main contributors (35% each) to the sensitivity. This study highlights the elevation-dependent sensitivity of dryland mountain forests to hydrothermal changes, with higher-elevation forests (>2000 m) being more sensitive to global warming. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 1803 KiB  

Open AccessArticle

A Novel Method for Anomaly Detection and Signal Calibration in Water Quality Monitoring of an Urban Water Supply System

by Jincheng Liu, Di Wu, Hadi Mohammed and Razak Seidu

Water 2024, 16(9), 1238; https://doi.org/10.3390/w16091238 - 26 Apr 2024

Cited by 2 | Viewed by 1535

Abstract

Water quality monitoring plays a crucial role in urban water supply systems for the production of safe drinking water. However, the traditional approach to water monitoring in Norway relies on a periodic (weekly/biweekly/monthly) sampling and analysis of biological indicators, which fails to provide [...] Read more.

Water quality monitoring plays a crucial role in urban water supply systems for the production of safe drinking water. However, the traditional approach to water monitoring in Norway relies on a periodic (weekly/biweekly/monthly) sampling and analysis of biological indicators, which fails to provide a timely response to changes in water quality. This research addresses this issue by proposing a data-driven solution that enhances the timeliness of water quality monitoring. Our research team applied a case study in Ålesund Kommune. A sensor platform has been deployed at Lake Brusdalsvatnet, the water source reservoir in Ålesund. This sensor module is capable of collecting data for 10 different physico-chemical indicators of water quality. Leveraging this sensor platform, we developed a CNN-AutoEncoder-SOM solution to automatically monitor, process, and evaluate water quality evolution in the lake. There are three components in this solution. The first one focuses on anomaly detection. We employed a recurrence map to encode the temporal dynamics and sensor correlations, which were then fed into a convolutional neural network (CNN) for classification. It is noted that this network achieved an impressive accuracy of up to $99.6\%$. Once an anomaly is detected, the data are calibrated in the second component using an AutoEncoder-based network. Since true values for calibration are unavailable, the results are evaluated through data analysis. With high-quality calibrated data in hand, we proceeded to cluster the data into different categories to establish water quality standards in the third component, where a self-organizing map (SOM) is applied. The results revealed that this solution demonstrated significant performance, with a silhouette score of 0.73, which illustrates a small in-cluster distance and large intra-cluster distance when the water was clustered into three levels. This system not only achieved the objective of developing a comprehensive solution for continuous water quality monitoring but also offers the potential for integration with other cyber–physical systems (CPSs) in urban water management. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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19 pages, 3625 KiB  

Open AccessArticle

Water and Energy Sustainability of Swimming Pools: A Case Model on the Costa Brava, Catalonia

by Juan-Jose Gomez-Guillen, Núria Arimany-Serrat, David Tapias Baqué and David Giménez

Water 2024, 16(8), 1158; https://doi.org/10.3390/w16081158 - 19 Apr 2024

Cited by 4 | Viewed by 3187

Abstract

The aim of this research is to propose a more sustainable swimming pool, in terms of water and energy, in the Costa Brava area. The methodology is focused on the creation of a descriptive water and energy model for swimming pools and their [...] Read more.

The aim of this research is to propose a more sustainable swimming pool, in terms of water and energy, in the Costa Brava area. The methodology is focused on the creation of a descriptive water and energy model for swimming pools and their monitoring, to propose the transition to a more sustainable swimming pool, in the context of climate change. The research is characterized by an exploratory, descriptive, and simulation approach to adapt swimming pools to the new requirements. Two significant impacts are highlighted from the perspective of water and energy stress—the carbon footprint, related to environmental impact and climate change, and the new business models of the sector, for a more sustainable tourism, with more sustainable pools. In terms of water balance, evaporation is an important variable and there are technical solutions on the market to control it, such as the use of covers. Furthermore, the modeling and simulation carried out helps to calculate the variable as a tool for improvement. For energy balance, in outdoor pools, pumping is an important variable and there are technologies, such as speed variation, that make it possible to reduce this. Furthermore, it should be noted that this research represents an important tool for the improvement of sustainability and operability for the various stakeholders, especially owners and governments, to face climate change, which is becoming increasingly critical for many regions. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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25 pages, 2073 KiB  

Open AccessArticle

Assessing Satellite-Derived OpenET Platform Evapotranspiration of Mature Pecan Orchard in the Mesilla Valley, New Mexico

by Zada M. Tawalbeh, A. Salim Bawazir, Alexander Fernald, Robert Sabie and Richard J. Heerema

Remote Sens. 2024, 16(8), 1429; https://doi.org/10.3390/rs16081429 - 17 Apr 2024

Cited by 5 | Viewed by 1746

Abstract

Pecan is a major crop in the Mesilla Valley, New Mexico. Due to prolonged droughts, growers face challenges related to water shortages. Therefore, irrigation management is crucial for farmers. Advancements in satellite-derived evapotranspiration (ET) models and accessibility to data from web-based platforms like [...] Read more.

Pecan is a major crop in the Mesilla Valley, New Mexico. Due to prolonged droughts, growers face challenges related to water shortages. Therefore, irrigation management is crucial for farmers. Advancements in satellite-derived evapotranspiration (ET) models and accessibility to data from web-based platforms like OpenET provide farmers with new tools to improve crop irrigation management. This study evaluates the evapotranspiration (ET) of a mature pecan orchard using OpenET platform data generated by six satellite-based models and their ensemble. The ET values obtained from the platform were compared with the ET values obtained from the eddy covariance (ETec) method from 2017 to 2021. The six models assessed included Google Earth Engine implementation of the Surface Energy Balance Algorithm for Land (geeSEBAL), Google Earth Engine implemonthsmentation of the Mapping Evapotranspiration at High Resolution with Internalized Calibration (eeMETRIC) model, Operational Simplified Surface Energy Balance (SSEBop), Satellite Irrigation Management Support (SIMS), Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), and Atmosphere–Land Exchange Inverse and associated flux disaggregation technique (ALEXI/DisALEXI). The average growing season ET of mature pecan estimated from April to October of 2017 to 2021 by geeSEBAL, eeMETRIC, SSEBop, SIMS, PT-JPL, ALEXI/DisALEXI, and the ensemble were 1061, 1230, 1232, 1176, 1040, 1016, and 1130 mm, respectively, and 1108 mm by ETec. Overall, the ensemble model-based monthly ET of mature pecan during the growing season was relatively close to the ETec (R² of 0.9477) with a 2% mean relative difference (MRD) and standard error of estimate (SEE) of 15 mm/month for the five years (N = 60 months). The high agreement of the OpenET ensemble of the six satellite-derived models’ estimates of mature pecan ET with the ETec demonstrates the utility of this promising approach to enhance the reliability of remote sensing-based ET data for agricultural and water resource management. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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17 pages, 6307 KiB  

Open AccessArticle

High Spatiotemporal Estimation of Reservoir Evaporation Water Loss by Integrating Remote-Sensing Data and the Generalized Complementary Relationship

by Yuran Li, Shiqiong Li, Lei Cheng, Lihao Zhou, Liwei Chang and Pan Liu

Remote Sens. 2024, 16(8), 1320; https://doi.org/10.3390/rs16081320 - 9 Apr 2024

Cited by 3 | Viewed by 2047

Abstract

Accurately estimating the reservoir evaporation loss is crucial for water resources management. The existing research on reservoir evaporation loss estimates primarily focuses on large spatiotemporal scales and neglects the rapid dynamic changes to reservoirs’ surface area. For reservoirs essential for frequent flood control [...] Read more.

Accurately estimating the reservoir evaporation loss is crucial for water resources management. The existing research on reservoir evaporation loss estimates primarily focuses on large spatiotemporal scales and neglects the rapid dynamic changes to reservoirs’ surface area. For reservoirs essential for frequent flood control and regular water supply, high spatiotemporal evaporation data are crucial. By integrating remote sensing and the evaporation model, this study proposes a new method for the high spatiotemporal estimation of the evaporation losses from reservoirs. The proposed method is applied to the largest artificial freshwater lake in Asia, i.e., Danjiangkou (DJK) Reservoir. The daily reservoir water surface area is extracted at a spatial resolution of 30 m during the period 2014–2018 based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). The daily evaporation rate is estimated at a spatial resolution of 100 m using the generalized complementary relationship (GCR). The results show that the water surface area of the DJK Reservoir exhibits rapid and frequent fluctuations from 2015 to 2018, with a multi-year average area of 731.9 km² and a maximum and minimum difference of 304 km². Significant seasonal variations are observed in both the evaporation rate and volume, with a multi-year average evaporation rate of 806 mm and evaporation volume of 595 million m³. The estimated results align well with three other independent estimates, indicating that the GCR is capable of water surface evaporation estimation. Further analysis suggests that the data resolution has a great influence on the evaporative water loss from the reservoir. The estimated mean annual evaporation volume based on the 1000 m resolution water surface area data is 14% lower than that estimated using the 30 m resolution water surface area data. This study not only provides a new method for the high spatiotemporal estimation of reservoir evaporation by integrating remote-sensing data and the GCR method but also highlights that reservoir evaporation water loss should be quantified using the volume rather than the rate and that the estimated loss is noticeably affected by the estimation spatial resolution. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 2438 KiB  

Open AccessArticle

Runoff Simulation of the Upstream Watershed of the Feiling Hydrological Station in the Qinhe River Based on the SWAT Model

by Kun Wang, Dafen Yue and Huadong Zhang

Water 2024, 16(7), 1044; https://doi.org/10.3390/w16071044 - 4 Apr 2024

Cited by 3 | Viewed by 1859

Abstract

This study examined the impacts of climate change and human activities on runoff within the Feiling Hydrological Station watershed in the Qinhe River basin, utilizing the SWAT (Soil and Water Assessment Tool) model. Several climate change and extreme land-use scenarios were evaluated for [...] Read more.

This study examined the impacts of climate change and human activities on runoff within the Feiling Hydrological Station watershed in the Qinhe River basin, utilizing the SWAT (Soil and Water Assessment Tool) model. Several climate change and extreme land-use scenarios were evaluated for their effects on runoff. Results demonstrated the SWAT model’s suitability for runoff simulation in the watershed, revealing a negative correlation between runoff and temperature changes, and a positive correlation with precipitation changes. Significantly, runoff responses to precipitation variations of ±10% and ±20% were more marked than those to temperature changes of ±1 °C and ±2 °C. In scenarios of extreme woodland and fallow land, runoff decreased, whereas in scenarios of extreme cropland and grassland, it increased, particularly in the extreme farmland scenario. The study’s findings are important for the sensible management of soil and water resources and the enhancement of the natural environment in the studied area. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 8267 KiB  

Open AccessArticle

Characteristics of Runoff Components in the Mingyong Glacier Basin, Meili Snow Mountains

by Zichen Zhang, Lihua Wu, Jun Feng, Zhiwen Dong, Xiong Zhao, Yi Sun, Xiping Cheng, Liqin Dong and Tingting Liu

Water 2024, 16(7), 937; https://doi.org/10.3390/w16070937 - 24 Mar 2024

Cited by 2 | Viewed by 1346

Abstract

As an important hydrological ecosystem component, the glacier basin has great significance for climate and environment, and it is also linked to regional water sustainability. In this paper, the sampling and isotope analysis of glacial ice, ice-melt water, river water (river midstream and [...] Read more.

As an important hydrological ecosystem component, the glacier basin has great significance for climate and environment, and it is also linked to regional water sustainability. In this paper, the sampling and isotope analysis of glacial ice, ice-melt water, river water (river midstream and river downstream), groundwater (spring), and precipitation were carried out in a hydrological year of the Mingyong Glacier basin, which is located at the Meili Snow Mountains, Southeastern Tibetan Plateau. At the same time, the hydrograph separation of the recharge sources of the lower mountain pass is studied. The results show that the range of δD, δ¹⁸O, and d-excess (deuterium excess) in natural water bodies are significantly different, and the precipitation is the most obvious. The high values of δD and δ¹⁸O in the water samples all appeared in spring and summer, and the low values appeared in autumn and winter, while glacial ice showed opposite trends. Meanwhile, the local meteoric water line (LMWL) of the Mingyong Glacier basin is δD = 8.04δ¹⁸O + 13.06. The End-Member Mixing Analysis (EMMA) was adopted to determine the sources proportion of river water (river downstream) according to the δD, δ¹⁸O, and d-excess ratio relationships. The results showed that the proportion of ice-melt water, groundwater, and precipitation in the ablation period was 80.6%, 17.2%, and 2.2% as well as 19.2%, 73.1%, and 7.7% in the accumulation period, respectively. Ice-melt water has a higher conversion recharge rate to groundwater and indirectly recharges river water, especially in nonmonsoon seasons. In other words, the main recharge source of river water in the lower reaches of the Mingyong Glacier basin during the ablation period is ice-melt water. In the accumulation period, the main recharge source of river water in the lower reaches of the Mingyong Glacier basin is groundwater, while nearly half of the recharge of groundwater comes from ice-melt water. Therefore, regardless of the ablation period or the accumulation period, ice-melt water is sustainable and important to this region. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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16 pages, 1044 KiB  

Open AccessArticle

Territorial Pluralism in China: Local Water Users’ Adaptation Strategies in the South–North Water Transfer Project

by Chengting Zhou, Jing Chen, Chen Li and Bo Bi

Water 2024, 16(6), 885; https://doi.org/10.3390/w16060885 - 19 Mar 2024

Cited by 2 | Viewed by 1620

Abstract

China’s South–North Water Transfer Project has been questioned as it has resulted in significantly negative issues. Drawing on the notion of hydrosocial territories, this article examines the contested hydraulic configuration and counter-imaginaries from local water users’ perspectives and their specific adaptation strategies in [...] Read more.

China’s South–North Water Transfer Project has been questioned as it has resulted in significantly negative issues. Drawing on the notion of hydrosocial territories, this article examines the contested hydraulic configuration and counter-imaginaries from local water users’ perspectives and their specific adaptation strategies in the South–North Water Transfer Project. This article argues that local water users in a Chinese context can only adopt adaptation strategies that are determined by their socio-economic backgrounds. This has led to significant social and environmental injustice. Addressing these issues is crucial for tackling inequities in the South–North Water Transfer Project and achieving the ambitious development goals of the project. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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26 pages, 23951 KiB  

Open AccessArticle

Propagation Dynamics from Meteorological Drought to GRACE-Based Hydrological Drought and Its Influencing Factors

by Aihong Cui, Jianfeng Li, Qiming Zhou, Honglin Zhu, Huizeng Liu, Chao Yang, Guofeng Wu and Qingquan Li

Remote Sens. 2024, 16(6), 976; https://doi.org/10.3390/rs16060976 - 10 Mar 2024

Cited by 2 | Viewed by 2057

Abstract

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 [...] Read more.

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 4842 KiB  

Open AccessArticle

Soil Salt and Water Regulation in Saline Agriculture Based on Physical Measures with Model Analysis

by Wenyuan Fu, Jinyi Yu, Qiuli Hu, Haixia Wang and Ying Zhao

Water 2024, 16(5), 719; https://doi.org/10.3390/w16050719 - 28 Feb 2024

Cited by 1 | Viewed by 2119

Abstract

Enhancing crop production in the saline regions of the Yellow River Delta (YRD), where shallow saline groundwater is prevalent, hinges on optimizing water and salt conditions in the root zone. This study explored the effects of various physical methods on soil water and [...] Read more.

Enhancing crop production in the saline regions of the Yellow River Delta (YRD), where shallow saline groundwater is prevalent, hinges on optimizing water and salt conditions in the root zone. This study explored the effects of various physical methods on soil water and salt dynamics during the cotton growing season in these saline areas. Three approaches were tested: plastic film mulching (FM), plastic film mulching with an added compacted soil layer (FM+CL), and ridge-furrow planting (RF). The HYDRUS-2D model (Version 3.02) was used to analyze changes in soil water and salt content in the root zone over time. The results showed that subsoil compaction significantly lowered salt build-up in the root zone, especially in the top 20 cm. Film mulching was crucial for reducing water loss in the Yellow River Delta. Crop transpiration increased by 7.0% under FM and 10.5% under FM+CL compared to RF planting. Additionally, FM+CL reduced soil salinity in the top 10 cm by 11.5% at cotton harvest time compared to FM alone. The study concludes that combining film mulching with a soil compaction layer is a promising strategy for local farmers, addressing soil water retention, salt management, and boosting cotton yields. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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15 pages, 1937 KiB  

Open AccessFeature PaperArticle

Catchment-Scale Challenges for Water Resources Management: Assessing ‘Reasonable’ Peak Needs for Irrigated Agriculture in a Humid Climate

by Jerry W. Knox and Keith Weatherhead

Hydrology 2024, 11(3), 33; https://doi.org/10.3390/hydrology11030033 - 27 Feb 2024

Viewed by 2071

Abstract

Rising demands and competition for water resources within all sectors are placing increasing pressure on the environment. Almost all direct abstractions in England require a licence (permit) from the regulatory authority, the Environment Agency. Assessing and setting ‘reasonable’ peak quantities of water that [...] Read more.

Rising demands and competition for water resources within all sectors are placing increasing pressure on the environment. Almost all direct abstractions in England require a licence (permit) from the regulatory authority, the Environment Agency. Assessing and setting ‘reasonable’ peak quantities of water that can be legally abstracted in an environmentally sustainable manner is central to the whole licence determination process. To protect environmental flows and other abstractors within each catchment, the regulatory authority needs to be able to set sensible limits in the licence conditions, including total seasonal volumes and peak rates of water use, particularly for abstractions from hydrologically sensitive surface water sources. This paper describes the development of a methodology to assess the ‘reasonable’ peak rates of water use for agricultural irrigation in support of catchment water resources management and planning. A daily time step water balance model was used to simulate peak monthly and daily water requirements for irrigation using long-term historical weather records for agroclimatically contrasting sites. The model-simulated outputs were then compared against observed data from selected case study farms, and against data reported in a national water abstraction database. Guidelines were then developed for setting peak monthly, daily, hourly, and absolute abstraction rates for irrigation, taking into account the environmental sensitivity of different types of water source. The application of the procedure and its relevance in other countries where catchment water resources are under intense pressure from agriculture are described. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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12 pages, 4336 KiB  

Open AccessCommunication

Ocean Temperatures Do Not Account for a Record-Setting Winter in the U.S. West

by Matthew D. LaPlante, Liping Deng, Luthiene Dalanhese and Shih-Yu Wang

Atmosphere 2024, 15(3), 284; https://doi.org/10.3390/atmos15030284 - 26 Feb 2024

Cited by 3 | Viewed by 1785 | Correction

Abstract

The record-setting winter of 2022–2023 came as an answer to both figurative and literal prayers for political leaders, policy makers, and water managers reliant on snowpacks in the Upper Colorado River Basin, a vital source of water for tens of millions of people [...] Read more.

The record-setting winter of 2022–2023 came as an answer to both figurative and literal prayers for political leaders, policy makers, and water managers reliant on snowpacks in the Upper Colorado River Basin, a vital source of water for tens of millions of people across the Western United States. But this “drought-busting” winter was not well-predicted, in part because while interannual patterns of tropical ocean temperatures have a well-known relationship to precipitation patterns across much of the American West, the Upper Colorado is part of a liminal region where these connections tend to be comparatively weak. Using historical sea surface temperature and snowpack records, and leveraging a long-term cross-basin relationship to extend the timeline for evaluation, this analysis demonstrates that the 2022–2023 winter did not present in accordance with other high-snowpack winters in this region, and that the associative pattern of surface temperatures in the tropical Pacific, and snow water equivalent in the regions that stored and supplied most of the water to the Colorado River during the 2022–2023 winter, was not substantially different from a historically incoherent arrangement of long-term correlation. These findings suggest that stochastic variability plays an outsized role in influencing water availability in this region, even in extreme years, reinforcing the importance of other trends to inform water policy and management. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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23 pages, 9605 KiB  

Open AccessArticle

Development of a Model to Evaluate Water Conservation Function for Various Tree Species

by Toshiharu Kojima, Ryoma Shimono, Takahiro Ota, Hiroshi Hashimoto and Yasuhiro Hasegawa

Water 2024, 16(4), 588; https://doi.org/10.3390/w16040588 - 16 Feb 2024

Viewed by 1507

Abstract

The ecosystem services of forests, such as the water conservation function, are the combined results of diverse processes, and the modification of one part of a forest affects each ecosystem service separately via complex processes. It is necessary to develop an ecosystem service [...] Read more.

The ecosystem services of forests, such as the water conservation function, are the combined results of diverse processes, and the modification of one part of a forest affects each ecosystem service separately via complex processes. It is necessary to develop an ecosystem service assessment model for various tree species to ensure proper forest management. In this study, a model to evaluate three ecosystem services, namely, the water supply, wood supply, and carbon sink, for various tree species in Japan is developed using many observation data from the previous literature. The integrated evaluation model consists of the forest model, hydrological model, and carbon stock assessment model. The forest model consists of the forest growth model and LAI estimation model, based on allometry. The results of the simulations for the major tree species yield the following findings: (1) Water supply varies with tree species but decreases until about 40 years of age, after which it is near constant. (2) Although beech has a larger LAI than needleleaf forests, water supply is not significantly different. (3) Broadleaf forests are more affected by thinning than needleleaf forests and tend to receive increased water supply as a result of processes such as thinning. This study enabled the evaluation of water conservation function in watersheds containing various tree species. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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23 pages, 18880 KiB  

Open AccessArticle

Optimizing Recharge Area Delineation for Small- to Medium-Sized Groundwater Systems through Coupling Methods and Numerical Modeling: A Case Study of Linfen City, China

by Kewei Lyu, Qiulan Zhang, Yali Cui, Yaobin Zhang, Yan Zhou, Lu Lyu, Yihan Dong and Jingli Shao

Sustainability 2024, 16(4), 1465; https://doi.org/10.3390/su16041465 - 8 Feb 2024

Cited by 1 | Viewed by 1333

Abstract

In previous investigations, the demarcation of capture zones within a specific research area predominantly relied on a singular method, leading to pronounced limitations and uncertainties. To address this challenge, an extensive field survey was conducted, focusing on the systematic classification of water sources [...] Read more.

In previous investigations, the demarcation of capture zones within a specific research area predominantly relied on a singular method, leading to pronounced limitations and uncertainties. To address this challenge, an extensive field survey was conducted, focusing on the systematic classification of water sources in the Linfen City region. Building upon this classification, an intricate fusion of a hydrogeological analysis and formulaic methodology was employed. This integrated approach, coupled with independent numerical simulation methods, was applied to delineate recharge areas for both alluvial fan pore water in piedmont regions and exposed karst water in small- to medium-sized water sources. Simultaneously, precise spatial interpolation was carried out on water quality monitoring data from supply wells within the water source area for the year 2020. This meticulous analysis facilitated the determination of the spatial distribution characteristics of hydrochemical elements. To assess the water quality within the capture zone, the class III groundwater quality standards of China were employed as a pivotal tool for validating the results of the delineation of water source recharge areas. In the final analysis, a comparative study between the integrated coupling method and numerical simulation outcomes revealed the successful delineation of the boundaries for the water supply areas of Tumen and Caojiapo in Linfen City, covering areas of 5.5 km² and 22.29 km², respectively. Simultaneously, the combination of the three methods accurately outlined the boundary of the Hexi water supply area, encompassing an area of 2.5224 km². These results vividly illustrate that the amalgamation of various methodologies proves more beneficial for the precise delineation of capture zones, particularly in diverse types and scales of groundwater sources. The synergy exhibited by these three methods underscores their collective efficacy, providing a more comprehensive and intuitive delineation of the recharge areas for small- to medium-sized water sources. Consequently, these findings significantly enhance the practical application value of the study and hold promise in making substantial contributions to local groundwater security and management initiatives. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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14 pages, 3532 KiB  

Open AccessArticle

Quantifying Uncertainty in Runoff Simulation According to Multiple Evaluation Metrics and Varying Calibration Data Length

by Ghaith Falah Ziarh, Jin Hyuck Kim, Jae Yeol Song and Eun-Sung Chung

Water 2024, 16(4), 517; https://doi.org/10.3390/w16040517 - 6 Feb 2024

Cited by 2 | Viewed by 1571

Abstract

In this study, the uncertainty in runoff simulations using hydrological models was quantified based on the selection of five evaluation metrics and calibration data length. The calibration data length was considered to vary from 1 to 11 years, and runoff analysis was performed [...] Read more.

In this study, the uncertainty in runoff simulations using hydrological models was quantified based on the selection of five evaluation metrics and calibration data length. The calibration data length was considered to vary from 1 to 11 years, and runoff analysis was performed using a soil and water assessment tool (SWAT). SWAT parameter optimization was then performed using R-SWAT. The results show that the uncertainty was lower when using a calibration data length of five to seven years, with seven years achieving the lowest uncertainty. Runoff simulations using a calibration data length of more than seven years yielded higher uncertainty overall but lower uncertainty for extreme runoff simulations compared to parameters with less than five years of calibration data. Different uncertainty evaluation metrics show different levels of uncertainty, which means it is necessary to consider multiple evaluation metrics rather than relying on any one single metric. Among the evaluation metrics, the Nash–Sutcliffe model efficiency coefficient (NSE) and normalized root-mean-squared error (NRMSE) had large uncertainties at short calibration data lengths, whereas the Kling–Gupta efficiency (KGE) and Percent Bias (Pbias) had large uncertainties at long calibration data lengths. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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20 pages, 2385 KiB  

Open AccessArticle

The Socioeconomic Dimensions of Water Scarcity in Urban and Rural Mexico: A Comprehensive Assessment of Sustainable Development

by Silvana Pacheco-Treviño and Mario G. Manzano-Camarillo

Sustainability 2024, 16(3), 1011; https://doi.org/10.3390/su16031011 - 24 Jan 2024

Cited by 4 | Viewed by 4440

Abstract

Mexico faces severe water scarcity due to population growth, industrial activities, and climate change. The arid and semidesert conditions prevalent in northern Mexico, particularly in Nuevo Leon, significantly accentuate the challenges associated with water scarcity. This region is vulnerable to water scarcity due [...] Read more.

Mexico faces severe water scarcity due to population growth, industrial activities, and climate change. The arid and semidesert conditions prevalent in northern Mexico, particularly in Nuevo Leon, significantly accentuate the challenges associated with water scarcity. This region is vulnerable to water scarcity due to minimal rainfall, recurrent droughts, and the increasing pressure of water demand from the densely populated Monterrey. We examined the disparities that contribute to water poverty by comparing water scarcity between rural and urban populations in Nuevo Leon. The results revealed significant contrasts in water scarcity between the two populations, indicating that different factors contribute to water poverty based on regional, territorial, and cultural characteristics. We selected the water poverty index (WPI) as an evaluation metric due to its inherent compatibility with available data sources, which facilitates its application to stakeholders and ensures comparability with other regions. This study contributes to studies on water scarcity assessment by addressing a critical limitation of the WPI. We compared three weighting methods—equal weight, principal component analysis (PCA), and analytic hierarchy process (AHP)—and identified that PCA and AHP demonstrated a superior performance compared to the standard methodology. These findings underscore the importance of considering region-specific conditions, as well as socioeconomic disparities between rural and urban populations and their role in vulnerability to water scarcity in calculating water poverty. These insights provide valuable information for customized solutions to regional challenges, representing leading actions toward sustainable development. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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17 pages, 19548 KiB  

Open AccessArticle

Evaluation of Multi-Source Precipitation Products in the Hinterland of the Tibetan Plateau

by Min Sun, Aili Liu, Lin Zhao, Chong Wang and Yating Yang

Atmosphere 2024, 15(1), 138; https://doi.org/10.3390/atmos15010138 - 22 Jan 2024

Cited by 4 | Viewed by 1634

Abstract

High-resolution precipitation products have been crucial for hydrology, meteorology, and environmental ecosystems over the Tibetan Plateau (TP). However, these products are usually subject to systematic errors, which may vary with time and topographic conditions. The study evaluated the suitability of four satellite-derived products [...] Read more.

High-resolution precipitation products have been crucial for hydrology, meteorology, and environmental ecosystems over the Tibetan Plateau (TP). However, these products are usually subject to systematic errors, which may vary with time and topographic conditions. The study evaluated the suitability of four satellite-derived products (GPM IMERG, GSMaP, CMORPH, and PERSIANN-CDR) and four fusion precipitation products (ERA5-Land, CHIRPS, CMFD, and TPHiPr) by comparing with 22 rain gauges at a daily scale from 1 January 2014 to 31 December 2018 over the hinterland of the TP. The main findings are as follows: (1) TPHiPr and CMFD are better than the satellite-derived products, while the performance of CHIRPS is worse; (2) among the satellite-derived products, the quality of GPM IMERG is the highest on different time scales, and PERSIANN-CDR is better in the months of June to October, while GSMaP and CMORPH have poor performance; (3) the eight precipitation products have weaker detection capability for heavy precipitation events, and the quality of each product decreases with the increase in the precipitation threshold, while the rate of descent of fusion precipitation products is slower than that of satellite-derived products. This study demonstrates the performance of eight precipitation products over the hinterland of the TP, which is expected to provide valuable information for hydrometeorology applications. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 3116 KiB  

Open AccessArticle

Comparison of Multiple Machine Learning Methods for Correcting Groundwater Levels Predicted by Physics-Based Models

by Guanyin Shuai, Yan Zhou, Jingli Shao, Yali Cui, Qiulan Zhang, Chaowei Jin and Shuyuan Xu

Sustainability 2024, 16(2), 653; https://doi.org/10.3390/su16020653 - 11 Jan 2024

Cited by 5 | Viewed by 1355

Abstract

Accurate groundwater level (GWL) prediction is crucial in groundwater resource management. Currently, it relies mainly on physics-based models for prediction and quantitative analysis. However, physics-based models used for prediction often have errors in structure, parameters, and data, resulting in inaccurate GWL predictions. In [...] Read more.

Accurate groundwater level (GWL) prediction is crucial in groundwater resource management. Currently, it relies mainly on physics-based models for prediction and quantitative analysis. However, physics-based models used for prediction often have errors in structure, parameters, and data, resulting in inaccurate GWL predictions. In this study, machine learning algorithms were used to correct the prediction errors of physics-based models. First, a MODFLOW groundwater flow model was created for the Hutuo River alluvial fan in the North China Plain. Then, using the observed GWLs from 10 monitoring wells located in the upper, middle, and lower parts of the alluvial fan as the test standard, three algorithms—random forest (RF), extreme gradient boosting (XGBoost), and long short-term memory (LSTM)—were compared for their abilities to correct MODFLOW’s predicted GWLs of these 10 wells under two sets of feature variables. The results show that the RF and XGBoost algorithms are not suitable for correcting predicted GWLs that exhibit continuous rising or falling trends, but the LSTM algorithm has the ability to correct them. During the prediction period, the LSTM2 model, which incorporates additional source–sink feature variables based on MODFLOW’s predicted GWLs, can improve the Pearson correlation coefficient (PR) for 80% of wells, with a maximum increase of 1.26 and a minimum increase of 0.02, and can reduce the root mean square error (RMSE) for 100% of the wells with a maximum decrease of 1.59 m and a minimum decrease of 0.17 m. And it also outperforms the MODFLOW model in capturing the long-term trends and short-term seasonal fluctuations of GWLs. However, the correction effect of the LSTM1 model (using only MODFLOW’s predicted GWLs as a feature variable) is inferior to that of the LSTM2 model, indicating that multiple feature variables are superior to a single feature variable. Temporally and spatially, the greater the prediction error of the MODFLOW model, the larger the correction magnitude of the LSTM2 model. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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17 pages, 4249 KiB  

Open AccessArticle

Spatiotemporal Variability and Impact Factors of Domestic Water Prices in China

by Xing Xie, Xinjun Tu, Jinglei Zhu, Vijay P. Singh and Yuanyuan Chai

Water 2024, 16(1), 115; https://doi.org/10.3390/w16010115 - 28 Dec 2023

Viewed by 2026

Abstract

Given China’s status as one of the most water-scarce countries globally, its rapid development of urbanization and sustained economic growth have led to increasing pressure on the urban water supply. Water pricing is also receiving increasing attention as an important tool for water [...] Read more.

Given China’s status as one of the most water-scarce countries globally, its rapid development of urbanization and sustained economic growth have led to increasing pressure on the urban water supply. Water pricing is also receiving increasing attention as an important tool for water resource management. This study analyzes the spatial and temporal characteristics of domestic water prices in China and their drivers. To this end, domestic water price data from 285 cities in China were collected. Spatial statistical analysis and geodetector were used to examine the spatial distribution and temporal patterns of domestic water prices from 2007 to 2020, as well as to identify the primary factors influencing these prices. The following results are noted: (1) The national average domestic water price has increased from 2 RMB/m³ to 3.12 RMB/m³, where the northeast and eastern regions have higher prices than the national average, while the central and western regions have lower prices. (2) The spatial distribution of urban domestic water prices presents clear differences characteristic of north–south and spatial agglomeration effects; the high-value area of domestic water prices is mainly concentrated in Beijing–Tianjin–Hebei. (3) On a national and regional scale, the price of domestic water is closely related to economic development, water resources, and resident’s income level. Furthermore, this study revealed that the interaction between pairwise factors played a more significant role in influencing domestic water prices compared with the individual impact of each factor. This finding contributes to a deeper understanding of the spatiotemporal heterogeneity in domestic water pricing and offers valuable insights and guidance for water pricing reform in China. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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13 pages, 3165 KiB  

Open AccessArticle

Evaluation of High-Intensity Precipitation Prediction Using Convolutional Long Short-Term Memory with U-Net Structure Based on Clustering

by Taeyong Kwon, Seong-Sim Yoon, Hongjoon Shin and Sanghoo Yoon

Water 2024, 16(1), 97; https://doi.org/10.3390/w16010097 - 26 Dec 2023

Cited by 1 | Viewed by 1685

Abstract

Recently, Asia has experienced significant damage from extreme precipitation events caused by climate change. Improving the accuracy of quantitative precipitation forecasts over wide regions is essential to mitigate the damage caused by precipitation-related natural disasters. This study compared the predictive performances of a [...] Read more.

Recently, Asia has experienced significant damage from extreme precipitation events caused by climate change. Improving the accuracy of quantitative precipitation forecasts over wide regions is essential to mitigate the damage caused by precipitation-related natural disasters. This study compared the predictive performances of a global model trained on the entire dataset and a clustered model that clustered precipitation types. The precipitation prediction model was constructed by combining convolutional long short-term memory with a U-Net structure. Research data consisted of precipitation events recorded at 10 min intervals from 2017 to 2021, utilizing radar data covering the entire Korean Peninsula. The model was trained on radar precipitation data from 30 min before the current time (t − 30 min, t − 20 min, t − 10 min, and t − 0 min) to predict the precipitation after 10 min (t + 10 min). The prediction performance was assessed using the root mean squared error and mean absolute error for continuous precipitation data and precision, recall, F1 score, and accuracy for the presence or absence of precipitation. The research findings indicate that, with sufficient training data for each precipitation type, models trained on clustered precipitation types outperform those trained on the entire dataset, particularly for predicting high-intensity precipitation events. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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25 pages, 33171 KiB  

Open AccessEditor’s ChoiceArticle

Spatial Estimation of Snow Water Equivalent for Glaciers and Seasonal Snow in Iceland Using Remote Sensing Snow Cover and Albedo

by Andri Gunnarsson and Sigurdur M. Gardarsson

Hydrology 2024, 11(1), 3; https://doi.org/10.3390/hydrology11010003 - 26 Dec 2023

Cited by 1 | Viewed by 3178

Abstract

Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed [...] Read more.

Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed energy balance model combining satellite-based retrievals of albedo and snow cover was applied. Incoming short-wave energy, contributing to daily estimates of melt energy, was constrained by remotely sensed surface albedo for snow-covered surfaces. Fractional snow cover was used for non-glaciated areas, as it provides estimates of snow cover for each pixel to better constrain snow melt. Thus, available daily estimates of melt energy in a given area were the product of the possible melt energy and the fractional snow cover of the area or pixel for non-glaciated areas. This provided daily estimates of melt water to determine seasonal snow and glacier ablation in Iceland for the period 2000–2019. Observations from snow pits on land and glacier summer mass balance were used for evaluation, and observations from land and glacier-based automatic weather stations were used to evaluate model inputs for the energy balance model. The results show that the interannual SWE variability was generally high both for seasonal snow and glaciers. For seasonal snow, the largest SWE (>1000 mm) was found in mountainous and alpine areas close to the coast, notably in the East- and Westfjords, Tröllaskaga, and in the vicinity of glacier margins. Lower SWE values were observed in the central highlands, flatter inland areas, and at lower elevations. For glaciers, more SWE (glacier ablation) was associated with lower glacier elevations while less melt was observed at higher elevations. For the impurity-rich bare-ice areas that are exposed annually, observed SWE was more than 3000 mm. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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Supplementary File 1 (ZIP, 416 KiB)

16 pages, 2952 KiB  

Open AccessArticle

Effects of Seasonal and Diel Variations in Thermal Stratification on Phytoplankton in a Regulated River

by Eunsong Jung, Gea-Jae Joo, Hyo Gyeom Kim, Dong-Kyun Kim and Hyun-Woo Kim

Sustainability 2023, 15(23), 16330; https://doi.org/10.3390/su152316330 - 27 Nov 2023

Cited by 2 | Viewed by 2783

Abstract

Thermal stratification is an important driver shaping phytoplankton community and their habitat condition in freshwater ecosystems. However, studies on river stratification have been restricted to rivers below dams or reservoirs affected by their water release and lacked examination of diel stratification and its [...] Read more.

Thermal stratification is an important driver shaping phytoplankton community and their habitat condition in freshwater ecosystems. However, studies on river stratification have been restricted to rivers below dams or reservoirs affected by their water release and lacked examination of diel stratification and its impact on phytoplankton, in particular. Therefore, this study aimed to determine the degree of thermal stratification, its environmental drivers, and the response of water quality and phytoplankton community against stratification in the mid-lower reach of the Nakdong River, whose morphology has been highly modified, including the construction of eight weirs. We implemented vertical temperature profiling at three study sites, both seasonally and diurnally. From this data, we calculated three stratification indices: relative water column stability (RWCS), Schmidt stability (S), and maximum temperature gradient (Max). These indices showed that most sites experienced diel stratification during summer (mean = RWCS 74.3, S 41.5 J m⁻², Max 0.9 °C m⁻¹). Principal component analysis showed that stratification significantly led to seasonal and diel variations in the water environment. Solar radiation and air temperature were positive controllers, while a negative controller (in this case, the river flow rate) existed only for diel variation in the stratification. The seasonal shifts in phytoplankton community structure were either insensitive or showed a limited response to the stratification indices. In summer, Microcystis cell abundance and accumulation into the surface water was positively affected by the diel variations in the stratification indices and thermocline instead of with other temperature and nutrient variables. Overall, the results suggest that the river has summer stratification, which is involved in amplifying cyanobacterial bloom intensity. Without a suppressing factor, summer stratification is expected to be recurrent in the river, and thus mitigating the developed stratification is needed by promptly regulating the river flow. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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19 pages, 9240 KiB  

Open AccessArticle

Study on the Optimal Allocation of Water Resources Based on the Perspective of Water Rights Trading

by Guangyao Wang, Xinyue Zhang, Lijuan Du, Bo Lei and Zhenghe Xu

Sustainability 2023, 15(23), 16214; https://doi.org/10.3390/su152316214 - 22 Nov 2023

Cited by 3 | Viewed by 1417

Abstract

Water rights trading plays an important role in the market mechanism to optimize the allocation of water resources. This study takes Luxian county of Sichuan province as the research area. Based on the prediction of water supply and demand, this study aims to [...] Read more.

Water rights trading plays an important role in the market mechanism to optimize the allocation of water resources. This study takes Luxian county of Sichuan province as the research area. Based on the prediction of water supply and demand, this study aims to achieve minimum water shortage and maximum economic benefits for regional water distribution, and introduces a water-saving reward and water price punishment mechanism to construct a two-layer collaborative regulation model of water rights trading for water users. The self-improved elite strategy and cogenetic algorithm (NSGA II-S) are used to solve the optimization model, and the optimal allocation of water resources and water rights trading in different towns in the planning year (2025 and 2030) under different flat and dry scenarios is studied. The results show that there would be an obvious problem in the uneven distribution of water resources between supply and demand in 2025 and 2030. The overall water shortage rates in the flat and dry scenario areas in 2025 are 13.71% and 31.99%, respectively, and the overall water shortage rates in the flat and dry scenario areas in 2030 are 11.55% and 31.94%, respectively. Water rights trading can increase the economic benefit value, with the economic benefit increasing by an average of CNY 614 million in all scenarios, an average increase of 8.68%. The research results could be helpful in alleviating the contradiction between the supply and demand of regional water resources and provide a theoretical basis for optimizing water resource allocation by means of water rights trading in the region. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 3667 KiB  

Open AccessArticle

Impact Evaluation Using Nonstationary Parameters for Historical and Projected Extreme Precipitation

by Muhammad Usman Khan, Muhammad Wajid Ijaz, Mudassar Iqbal, Rizwan Aziz, Muhammad Masood and Muhammad Atiq Ur Rehman Tariq

Water 2023, 15(22), 3958; https://doi.org/10.3390/w15223958 - 14 Nov 2023

Cited by 2 | Viewed by 1654

Abstract

Recent improvements in time series studies of hydro-climatological variables have led to the belief that the effects of nonstationarity are substantial enough to call the idea of traditional stationary approaches into doubt. The mean and variability of annual and seasonal rainfall in Pakistan [...] Read more.

Recent improvements in time series studies of hydro-climatological variables have led to the belief that the effects of nonstationarity are substantial enough to call the idea of traditional stationary approaches into doubt. The mean and variability of annual and seasonal rainfall in Pakistan are changing due to anthropogenic climate change. With the use of stationary and nonstationary frequency analysis techniques, this study set out to assess the impacts of nonstationarity in Southern Punjab, Pakistan, over the historical period of 1970–2015 and the future periods of 2020–2060 and 2060–2100. Four frequency distributions, namely Generalized Extreme Value (GEV), Gumbel, normal, and lognormal, were used. The findings of the nonstationarity impact across Southern Punjab showed different kinds of impacts, such as an increase or reduction in the return level of extreme precipitation. In comparison to other distributions, GEV provided the finest fit. In Bahawalnagar, Bahawalpur, Multan, Rahim Yar Khan and DG. Khan, the annual nonstationarity impacts for the 100-year return level were increased up to 15.2%, 8.7%, 58.3%, 18.7%, and 20%, respectively. Moreover, extreme precipitation was found to be increasing during the historical and projected periods, which may increase floods, while less water availability appeared at a seasonal scale (summer) during 2061–2100. The increased nonstationarity effects emphasized adapting these nonstationarities induced by climate change into the design of water resource structures. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 6200 KiB  

Open AccessArticle

A Comprehensive Model for Assessing Synergistic Revenue–Cost for the Joint Operation of a Complex Multistakeholder Reservoir System

by Yufei Quan, Yang Xu, Ran Mo, Xin Huang, Saijin Ji, Huili Wang, Zirui Li and Bin Xu

Water 2023, 15(22), 3896; https://doi.org/10.3390/w15223896 - 8 Nov 2023

Viewed by 1307

Abstract

The joint operation of a multiobjective multistakeholder reservoir system enhances the revenues of downstream-compensated reservoirs at the expense of increasing the operation cost of upstream-compensating reservoirs. Challenges in quantifying the synergistic revenue–cost tradeoffs with incomplete information arise from difficulties in multistakeholder, high-dimensional, and [...] Read more.

The joint operation of a multiobjective multistakeholder reservoir system enhances the revenues of downstream-compensated reservoirs at the expense of increasing the operation cost of upstream-compensating reservoirs. Challenges in quantifying the synergistic revenue–cost tradeoffs with incomplete information arise from difficulties in multistakeholder, high-dimensional, and combinational joint optimal operation modeling. This study proposed an equivalent aggregated reservoir multiobjective operation and synergistic revenue–cost assessment model. The proposed methodology includes three parts. Module I constructs revenue indexes covering energy production, water supply, ecological protection, and shipping objectives and uses the maximum outflow change degree as a surrogate “cost” index. Module II defines “aggregated reservoirs” that aggregate upstream reservoirs within the same river system as a single reservoir, reducing model complexity with the least information. Module III evaluates the revenue–cost tradeoffs under various operation scenarios. The following conclusions were derived from a 27-reservoir system: (1) The model complexity was reduced by 67.18% with precision preserved. (2) Key compensating reservoirs are identified via tradeoff curves, which are reservoirs controlling high streamflow with large storage. (3) Upstream compensating reservoirs homogenize the inflows of downstream-compensated reservoirs to increase the downstream synergistic revenue by sacrificing upstream benefit. The proposed method provides a new approach for revenue–cost estimation via the joint optimal operation of a multistakeholder-reservoir system. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 6645 KiB  

Open AccessArticle

River Recreational Activity Vulnerability Assessment and the Hydraulic Index Proposal

by Jaehyun Shin, Tae Geom Ku, Il Won Seo and Young Do Kim

Water 2023, 15(20), 3587; https://doi.org/10.3390/w15203587 - 13 Oct 2023

Cited by 1 | Viewed by 1910

Abstract

In this study, a vulnerability index and hydraulic index for recreational activities were developed for assessments in riverside areas to provide water quality and hydraulic information to the public. These novel indices consist of several river recreation activities such as swimming, water skiing, [...] Read more.

In this study, a vulnerability index and hydraulic index for recreational activities were developed for assessments in riverside areas to provide water quality and hydraulic information to the public. These novel indices consist of several river recreation activities such as swimming, water skiing, canoeing, etc., and are calculated using hydraulic information. The hydraulic information is integrated with fuzzy synthetic evaluation, with parameters such as velocity, water surface elevation, and water surface width. Also, a water quality index was created using information integrated with parameters such as DO, pH, and chlorophyll a, and then these parameters were combined into the vulnerability index. The proposed vulnerability index and hydraulic index were applied to the Nakdong River, downstream of a large weir. The hydraulic index was also combined with the results from a two-dimensional flow model for the spatial representation of the index for the categorization of safe recreational acceptability levels in the river. The results showed that the calculated index was sufficient to reflect changes in the hydraulic parameters, shown with spatial data, with comparisons to the index calculation from the gauge site measured data, with differences ranging from 0.8% to 6.5%. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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13 pages, 2659 KiB  

Open AccessArticle

Edge-of-Field Runoff Analysis following Grazing and Silvicultural Best Management Practices in Northeast Texas

by Kevin L. Wagner, Lucas Gregory, Jason A. Gerlich, Edward C. Rhodes and Stephanie deVilleneuve

Water 2023, 15(20), 3537; https://doi.org/10.3390/w15203537 - 11 Oct 2023

Cited by 2 | Viewed by 1860

Abstract

Landowners and natural resource agencies are seeking to better understand the benefits of best management practices (BMPs) for addressing water quality issues. Using edge-of-field and edge-of-farm runoff analysis, we compared runoff volumes and water quality between small watersheds where BMPs (e.g., prescribed grazing, [...] Read more.

Landowners and natural resource agencies are seeking to better understand the benefits of best management practices (BMPs) for addressing water quality issues. Using edge-of-field and edge-of-farm runoff analysis, we compared runoff volumes and water quality between small watersheds where BMPs (e.g., prescribed grazing, silvicultural practices) were implemented and control watersheds managed using conventional practices (i.e., continuous grazing, natural forest revegetation). Flow-weighted samples, collected over a 2-year period using automated samplers, were analyzed for nitrate/nitrite nitrogen (NNN), total Kjeldahl nitrogen (TKN), total phosphorus (P), ortho-phosphate phosphorous (OP), total suspended solids (TSS), and Escherichia coli (E. coli). Comparison of silvicultural planting to conventional reforestation practices showed a significant decrease in NNN loads (p < 0.05) but no significant differences in TKN, P, OP, TSS, or E. coli. Continuously grazed sites yielded >24% more runoff than sites that were under prescribed grazing regimes, despite receiving less total rainfall. Likewise, NNN, TSS, and TKN loadings were significantly lower under prescribed grazing management than on conventionally grazed sites (p < 0.05). Data suggests that grazing BMPs can be an effective tool for rapidly improving water quality. However, silvicultural BMPs require more time (i.e., >2 years) to establish and achieve detectable improvements. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 3124 KiB  

Open AccessReview

Multivariate Statistical Analysis for Water Quality Assessment: A Review of Research Published between 2001 and 2020

by Daphne H. F. Muniz and Eduardo C. Oliveira-Filho

Hydrology 2023, 10(10), 196; https://doi.org/10.3390/hydrology10100196 - 5 Oct 2023

Cited by 20 | Viewed by 8895

Abstract

Research on water quality is a fundamental step in supporting the maintenance of environmental and human health. The elements involved in water quality analysis are multidimensional, because numerous characteristics can be measured simultaneously. This multidimensional character encourages researchers to statistically examine the data [...] Read more.

Research on water quality is a fundamental step in supporting the maintenance of environmental and human health. The elements involved in water quality analysis are multidimensional, because numerous characteristics can be measured simultaneously. This multidimensional character encourages researchers to statistically examine the data generated through multivariate statistical analysis (MSA). The objective of this review was to explore the research on water quality through MSA between the years 2001 and 2020, present in the Web of Science (WoS) database. Annual results, WoS subject categories, conventional journals, most cited publications, keywords, water sample types analyzed, country or territory where the study was conducted and most used multivariate statistical analyses were topics covered. The results demonstrate a considerable increase in research using MSA in water quality studies in the last twenty years, especially in developing countries. River, groundwater and lake were the most studied water sample types. In descending order, principal component analysis (PCA), hierarchical cluster analysis (HCA), factor analysis (FA) and discriminant analysis (DA) were the most used techniques. This review presents relevant information for researchers in choosing the most appropriate methods to analyze water quality data. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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20 pages, 13232 KiB  

Open AccessArticle

Evaluation of Satellite-Derived Precipitation Products for Streamflow Simulation of a Mountainous Himalayan Watershed: A Study of Myagdi Khola in Kali Gandaki Basin, Nepal

by Aashutosh Aryal, Thanh-Nhan-Duc Tran, Brijesh Kumar and Venkataraman Lakshmi

Remote Sens. 2023, 15(19), 4762; https://doi.org/10.3390/rs15194762 - 28 Sep 2023

Cited by 21 | Viewed by 3476

Abstract

This study assesses four Satellite-derived Precipitation Products (SPPs) that are corrected and validated against gauge data such as Soil Moisture to Rain—Advanced SCATterometer V1.5 (SM2RAIN-ASCAT), Multi-Source Weighted-Ensemble Precipitation V2.8 (MSWEP), Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM Final run V6 (GPM IMERGF), [...] Read more.

This study assesses four Satellite-derived Precipitation Products (SPPs) that are corrected and validated against gauge data such as Soil Moisture to Rain—Advanced SCATterometer V1.5 (SM2RAIN-ASCAT), Multi-Source Weighted-Ensemble Precipitation V2.8 (MSWEP), Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM Final run V6 (GPM IMERGF), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). We evaluate the performance of these SPPs in Nepal’s Myagdi Khola watershed, located in the Kali Gandaki River basin, for the period 2009–2019. The SPPs are evaluated by validating the gridded precipitation products using the hydrological model, Soil and Water Assessment Tool (SWAT). The results of this study show that the SM2RAIN-ASCAT and GPM IMERGF performed better than MSWEP and CHIRPS in accurately simulating daily and monthly streamflow. GPM IMERGF and SM2RAIN-ASCAT are found to be the better-performing models, with higher NSE values (0.63 and 0.61, respectively) compared with CHIRPS and MSWEP (0.45 and 0.41, respectively) after calibrating the model with monthly data. Moreover, SM2RAIN-ASCAT demonstrated the best performance in simulating daily and monthly streamflow, with NSE values of 0.57 and 0.63, respectively, after validation. This study’s findings support the use of satellite-derived precipitation datasets as inputs for hydrological models to address the hydrological complexities of mountainous watersheds. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 9371 KiB  

Open AccessArticle

Water Area Extraction and Water Level Prediction of Dongting Lake Based on Sentinel-1 Dual-Polarization Data Decomposition

by Qing Song, Rong Zhao, Haiqiang Fu, Jianjun Zhu and Yi Li

Remote Sens. 2023, 15(19), 4655; https://doi.org/10.3390/rs15194655 - 22 Sep 2023

Cited by 8 | Viewed by 2115

Abstract

The Sentinel-1 imaging radar mission provides a short revisit-time, continuous all-weather, and day-and-night imagery at the C-band, which brings opportunities for the dynamic extraction of lake water areas. For wetland-type lakes, it is difficult to distinguish between the water, submerged plants, and mudflats [...] Read more.

The Sentinel-1 imaging radar mission provides a short revisit-time, continuous all-weather, and day-and-night imagery at the C-band, which brings opportunities for the dynamic extraction of lake water areas. For wetland-type lakes, it is difficult to distinguish between the water, submerged plants, and mudflats at the edge of a lake, which leads to difficulty in recognizing the water edge of a lake and affects the accuracy of lake water area extraction. In this paper, a water area extraction and water level prediction algorithm based on Sentinel-1 dual-polarization data decomposition is proposed to solve the problem. We can accurately extract lake water through generalized Stokes polarization decomposition. At the same time, we can verify the accuracy of water area extraction by establishing the water area and in situ water level elevation (A–E) relationship, and predicting the water level according to the calculated water area. In this study, dual-polarization Sentinel-1 time series SAR data covering the Dongting Lake wetland from 2018 to 2022 are used to verify the proposed water area extraction algorithm and establish the A–E relationship of the East Dongting Lake basin. The results show that the generalized Stokes decomposition parameters are very sensitive to the water boundary, and the R² of the water area and the water level can reach 0.98 by using the piecewise linear function. It confirms the accuracy of the water area inversion, which is of extremely important significance for the high-precision monitoring of the water area of Dongting Lake with long-term Sentinel-1 data. Meanwhile, the predicted lake water level acquired using the A–E relationship established in this paper is compared with the field water level, with an RMSE of 0.4857 m and R² of 0.9930. This means that the water level derived using the method in this study is quite compatible with the field observations, which provides a good idea for the water level monitoring of lakes lacking hydrological monitoring stations. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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28 pages, 8631 KiB  

Open AccessArticle

Evaluating Climate Change Effects on a Snow-Dominant Watershed: A Multi-Model Hydrological Investigation

by Ali Sharifinejad and Elmira Hassanzadeh

Water 2023, 15(18), 3281; https://doi.org/10.3390/w15183281 - 17 Sep 2023

Cited by 5 | Viewed by 2355

Abstract

Assessing the impact of climate change on water systems often requires employing a hydrological model to estimate streamflow. However, the choice of hydrological model, process representation, input data resolution, and catchment discretization can potentially influence such analyses. This study aims to evaluate the [...] Read more.

Assessing the impact of climate change on water systems often requires employing a hydrological model to estimate streamflow. However, the choice of hydrological model, process representation, input data resolution, and catchment discretization can potentially influence such analyses. This study aims to evaluate the sensitivity of climate change impact assessments to various hydrological modeling configurations in a snow-dominated headwater system in Alberta, Canada. The HBV-MTL and GR4J models, coupled with the Degree-Day and CemaNeige snowmelt modules, were utilized and calibrated using point- and grid-based climate data on lumped and semi-distributed catchment discretization. The hydrological models, in conjunction with a water allocation model, were supplied with climate model outputs to project changes in the basin. While all models revealed a unanimous increase in peak flow, the difference between their estimations could be as substantial as 42%. In contrast, their divergence was minimal in projecting median flow. Furthermore, most models projected an aggravated water supply deficit between 16% and 40%. Overall, the quantified climate change impacts were the most sensitive to the choice of snow routine module, followed by the model type, catchment discretization, and data resolution in this snow-dominant basin. Therefore, particular attention should be given to the proper representation of snowmelt processes. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 2507 KiB  

Open AccessArticle

Exploring a Novel Reservoir Impoundment Operation Framework for Facilitating Hydropower Sustainability

by Zhihao Ning, Yanlai Zhou, Fanqi Lin, Ying Zhou and Qi Luo

Sustainability 2023, 15(18), 13400; https://doi.org/10.3390/su151813400 - 7 Sep 2023

Cited by 3 | Viewed by 1483

Abstract

Reservoir impoundment operation has far-reaching effects on the synergies of hydropower output, floodwater utilization, and carbon fluxes, but flood risk is significantly increasing, which is especially true when shifting to earlier impoundment timings and lifting reservoir water levels. This study proposed a novel [...] Read more.

Reservoir impoundment operation has far-reaching effects on the synergies of hydropower output, floodwater utilization, and carbon fluxes, but flood risk is significantly increasing, which is especially true when shifting to earlier impoundment timings and lifting reservoir water levels. This study proposed a novel reservoir impoundment operation framework driven by flood prevention, hydropower production, floodwater utilization, and carbon emission management. The Three Gorges Reservoir in the Yangtze River was selected as a case study. The results demonstrated that flood prevention safety could be guaranteed with the initial impoundment timings on and after the first of September. The best scheme of reservoir impoundment operation could efficiently boost synergistic benefits by enhancing 2.98 billion kW·h (8.8%) hydropower output and 6.4% water impoundment rate and decreasing greenhouse gas (GHG) fluxes and carbon budget by 28.15 GgCO_2e/yr (4.6%) and 0.44 (23.1%), respectively, compared with the standard operation policy. This study can not only provide scientific and technical support for reservoir impoundment operations, benefiting water–carbon synergies, but can also suggest policymakers with various favorable advancing impoundment timing and lifting reservoir water level schemes to experience related risks and benefits in the interest of hydropower sustainability. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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27 pages, 5918 KiB  

Open AccessArticle

Exploring Random Forest Machine Learning and Remote Sensing Data for Streamflow Prediction: An Alternative Approach to a Process-Based Hydrologic Modeling in a Snowmelt-Driven Watershed

by Khandaker Iftekharul Islam, Emile Elias, Kenneth C. Carroll and Christopher Brown

Remote Sens. 2023, 15(16), 3999; https://doi.org/10.3390/rs15163999 - 11 Aug 2023

Cited by 21 | Viewed by 5384

Abstract

Physically based hydrologic models require significant effort and extensive information for development, calibration, and validation. The study explored the use of the random forest regression (RFR), a supervised machine learning (ML) model, as an alternative to the physically based Soil and Water Assessment [...] Read more.

Physically based hydrologic models require significant effort and extensive information for development, calibration, and validation. The study explored the use of the random forest regression (RFR), a supervised machine learning (ML) model, as an alternative to the physically based Soil and Water Assessment Tool (SWAT) for predicting streamflow in the Rio Grande Headwaters near Del Norte, a snowmelt-dominated mountainous watershed of the Upper Rio Grande Basin. Remotely sensed data were used for the random forest machine learning analysis (RFML) and RStudio for data processing and synthesizing. The RFML model outperformed the SWAT model in accuracy and demonstrated its capability in predicting streamflow in this region. We implemented a customized approach to the RFR model to assess the model’s performance for three training periods, across 1991–2010, 1996–2010, and 2001–2010; the results indicated that the model’s accuracy improved with longer training periods, implying that the model trained on a more extended period is better able to capture the parameters’ variability and reproduce streamflow data more accurately. The variable importance (i.e., IncNodePurity) measure of the RFML model revealed that the snow depth and the minimum temperature were consistently the top two predictors across all training periods. The paper also evaluated how well the SWAT model performs in reproducing streamflow data of the watershed with a conventional approach. The SWAT model needed more time and data to set up and calibrate, delivering acceptable performance in annual mean streamflow simulation, with satisfactory index of agreement (d), coefficient of determination (R²), and percent bias (PBIAS) values, but monthly simulation warrants further exploration and model adjustments. The study recommends exploring snowmelt runoff hydrologic processes, dust-driven sublimation effects, and more detailed topographic input parameters to update the SWAT snowmelt routine for better monthly flow estimation. The results provide a critical analysis for enhancing streamflow prediction, which is valuable for further research and water resource management, including snowmelt-driven semi-arid regions. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 3247 KiB  

Open AccessFeature PaperArticle

Modeled Forest Conversion Influences Humid Tropical Watershed Hydrology More than Projected Climate Change

by Taylor Joyal, Alexander K. Fremier and Jan Boll

Hydrology 2023, 10(8), 160; https://doi.org/10.3390/hydrology10080160 - 31 Jul 2023

Cited by 1 | Viewed by 2208

Abstract

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. [...] Read more.

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this study, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent shallow subsurface soil pathways and saturation-excess runoff while low flows are most sensitive to macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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16 pages, 2455 KiB  

Open AccessArticle

Influences of the Runoff Partition Method on the Flexible Hybrid Runoff Generation Model for Flood Prediction

by Bin Yi, Lu Chen, Binlin Yang, Siming Li and Zhiyuan Leng

Water 2023, 15(15), 2738; https://doi.org/10.3390/w15152738 - 28 Jul 2023

Cited by 2 | Viewed by 1497

Abstract

The partition of surface runoff and infiltration is crucial in hydrologic modeling. To improve the flood prediction, we designed four strategies to explore the influences of the runoff partition method on the flexible hybrid runoff generation model. The runoff partition strategies consist of [...] Read more.

The partition of surface runoff and infiltration is crucial in hydrologic modeling. To improve the flood prediction, we designed four strategies to explore the influences of the runoff partition method on the flexible hybrid runoff generation model. The runoff partition strategies consist of a hydrological model without the runoff partition module, a two-source runoff partition method, an improved two-source runoff partition method considering the heterogeneity of the subsurface topography and land cover, and a three-source runoff partition method. The Xin’anjiang hydrological model was used as the modeling framework to simulate a six-hourly stream flow for the Xun River watershed in Shaanxi Province, China. And the saturation-excess runoff generation and infiltration-excess runoff generation mechanisms were combined to construct the flexible hybrid runoff generation model. The performances of the four strategies were compared and analyzed based on the continuous flow discharge as well as the flood events. The runoff components analysis method was used to test the model’s conformity with the reality of the watershed. The results showed that the three-source runoff partition method was not applicable to the flexible hybrid runoff generation model because it overestimated the surface runoff and almost ignored the subsurface stormflow runoff. The improved two-source runoff partition method outperformed the others as it considered the heterogeneity of the watershed. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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20 pages, 8958 KiB  

Open AccessArticle

Quantitative Mechanisms of the Responses of Abrupt Seasonal Temperature Changes and Warming Hiatuses in China to Their Influencing Factors

by Xing Huang, Long Ma, Tingxi Liu, Bolin Sun, Yang Chen and Zixu Qiao

Atmosphere 2023, 14(7), 1090; https://doi.org/10.3390/atmos14071090 - 29 Jun 2023

Cited by 2 | Viewed by 1469

Abstract

Abrupt temperature changes and warming hiatuses have a great impact on socioeconomic systems; however, their mechanisms remain unclear. In this study, the quantitative mechanisms of the responses of abrupt seasonal temperature changes and warming hiatuses in China to their influencing factors were analysed [...] Read more.

Abrupt temperature changes and warming hiatuses have a great impact on socioeconomic systems; however, their mechanisms remain unclear. In this study, the quantitative mechanisms of the responses of abrupt seasonal temperature changes and warming hiatuses in China to their influencing factors were analysed using the monthly mean temperature (Tav), mean minimum temperature (Tnav), and mean maximum temperature (Txav) from 622 meteorological stations in China covering 1951–2018, the CMIP6 model data, and data at large spatial scales, including Atlantic multidecadal oscillation (AMO) data. The results showed that the contributions of the influencing factors to the abrupt changes in Tav, Tnav, and Txav showed large spatial variability and peaked in the spring and summer and bottomed out in the autumn. The Pacific decadal oscillation (PDO) greatly impacted the abrupt temperature changes in Northeast China and North China at a contribution rate of approximately 12%, strongly influenced the abrupt temperature changes south of the Yangtze River, and markedly influenced the abrupt temperature changes in Northwest China. The AMO had a large impact on temperature in most regions of China in all seasons except for the summer. The MEI mainly affected the abrupt seasonal temperature changes in the region between 25° N and 35° N. The Arctic oscillation (AO) substantially impacted the warming hiatuses in Northeast China in the winter at a contribution rate of approximately 12%. These influencing factors contributed less to warming hiatuses than to abrupt temperature changes. Among the regional influencing factors, AP and WS greatly impacted warming hiatuses, more so than abrupt temperature changes, while relative humidity (RH) and solar radiation (SR) contributed little to warming hiatuses. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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23 pages, 10546 KiB  

Open AccessArticle

Bengal Delta, Charland Formation, and Riparian Hazards: Why Is a Flexible Planning Approach Needed for Deltaic Systems?

by C. Emdad Haque and Md. Jakariya

Water 2023, 15(13), 2373; https://doi.org/10.3390/w15132373 - 27 Jun 2023

Cited by 2 | Viewed by 4996

Abstract

A comprehensive understanding of the dynamic characteristics of geomorphological, ecological, and human systems is essential to explaining complex charland (mid-channel island) processes and crafting and implementing policy measures. This work demonstrates that the characteristics and outcomes of riparian hazards are determined by [...] Read more.

A comprehensive understanding of the dynamic characteristics of geomorphological, ecological, and human systems is essential to explaining complex charland (mid-channel island) processes and crafting and implementing policy measures. This work demonstrates that the characteristics and outcomes of riparian hazards are determined by the interactive dynamics between hydrogeology and human conditions, which constitutes a novel contribution to the literature in this research area. We further contend that such dynamic social-ecological systems demand a flexible, adaptive management and planning approach. The present research has three key interdisciplinary objectives: (i) to analyze the salient features and characteristics of the geomorphological and riparian systems of the Bengal Delta; (ii) to analyze the evolutionary discourse of the legal systems concerning eroded (diluvion) and accreted (alluvion) land in Bangladesh; and (iii) to assess the characteristics of the coping and adaptation strategies employed by charland inhabitants. The findings of this research reveal that delta-building processes, which are characterized by dynamic shifts in the river channels, along with the erosion and accretion of charlands have made Bangladesh’s land and water systems very dynamic and unstable. The destabilization of these systems increases the inhabitants’ vulnerability to riparian hazards, which consistently results in the displacement of settlers and, consequently, a serious deterioration in their socioeconomic status. At present, Bangladesh does not have an effective institutional framework and structure for resettlement planning; therefore, the formulation of a comprehensive national resettlement policy with adequate flexibility to adapt to changing scenarios is urgently needed. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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21 pages, 9616 KiB  

Open AccessArticle

Spatial Distribution of Water Risk Based on Atlas Compilation in the Shaanxi Section of the Qinling Mountains, China

by Xinyue Ke, Ni Wang, Long Yu, Zihan Guo and Tianming He

Sustainability 2023, 15(12), 9792; https://doi.org/10.3390/su15129792 - 19 Jun 2023

Cited by 1 | Viewed by 1466

Abstract

Global climate change and rapid socio-economic development have increased the uncertainty in water resource systems and the complexity of water risk issues. Analyzing water risk and its spatial distribution is integral to the attainment of Sustainable Development Goal (SDG) 6, as this contributes [...] Read more.

Global climate change and rapid socio-economic development have increased the uncertainty in water resource systems and the complexity of water risk issues. Analyzing water risk and its spatial distribution is integral to the attainment of Sustainable Development Goal (SDG) 6, as this contributes to effective water resource partition management. In this paper, a compiling method of risk atlas with multiple layers is proposed, and the water risk system is divided into five sub-systems including the risk of resource, management, engineering, quality, and disaster. The information used for the risk atlas is calculated by a risk evaluation model based on a Pressure–State–Response (PSR) framework, hierarchical cluster, and set pair analysis (SPA). Risks in the Qinling Mountains of Shaanxi (as a case study) are evaluated and visualized. The results show that grades IV and V of engineering, disaster, and resource risk exceed 40%, indicating that they require prior control. The quality and management risks are not major, but there is still room for improvement. Overall, the risk atlas can effectively and objectively reflect the spatial distribution of water risk and provide a basis for the layout of water risk control measures. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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24 pages, 16426 KiB  

Open AccessArticle

Driving Factors of the Hydrological Response of a Tropical Watershed: The Ankavia River Basin in Madagascar

by Zonirina Ramahaimandimby, Alain Randriamaherisoa, Marnik Vanclooster and Charles L. Bielders

Water 2023, 15(12), 2237; https://doi.org/10.3390/w15122237 - 14 Jun 2023

Cited by 3 | Viewed by 2496

Abstract

Understanding the hydrological behavior of watersheds (WS) and their driving factors is crucial for sustainable water resources management. However, at large scales, this task remains challenging due to the spatial heterogeneity in landscapes, topography and morphology (T), land cover (LC), geology (G), and [...] Read more.

Understanding the hydrological behavior of watersheds (WS) and their driving factors is crucial for sustainable water resources management. However, at large scales, this task remains challenging due to the spatial heterogeneity in landscapes, topography and morphology (T), land cover (LC), geology (G), and soil properties (S). In this context, the aim of this study was to identify the key factors that influence the hydrological signatures of four watersheds: Ankavia (WS1: 55% forest cover), Ankaviabe (WS2: 77% forest cover), Sahafihitry (WS3: 41% forest cover), and Antsahovy (WS4: 48% forest cover), over a 10-month study period. These catchments are located within the SAVA region of northeastern Madagascar and have a humid tropical climate. We investigated the relationship between selected catchment descriptors and hydrological signatures by using a Pearson coefficient-based correlation matrix. More specifically, catchment descriptors (extracted from T, LC, G, and S) were correlated with the following hydrological signatures: base flow index (BFI), mean runoff coefficient (rc), mean peak flow (Qp), mean runoff event time scales (ts), high flows (Q5), low flows (Q95), and mean discharge (q_mean). The analysis revealed that land cover, soil properties, and geology seem to be the best predictors for BFI and Q95, while soil properties mainly govern rc, Qp, Q5, ts, and q_mean. These findings provide valuable insights into the key drivers of hydrological behavior that can inform water resource management strategies. In particular, WS2 exhibits better flood buffering capacity but also experiences lower base flows in the dry season, potentially due to higher evapotranspiration. Conversely, WS3 and WS4 (and to a lesser extent WS1) have lower flood buffering capacity, but these watersheds encounter less pronounced low flows in the dry season due to higher BFIs, possibly attributable to lower evapotranspiration rates. The results underscore the importance of responsible land use practices and conservation efforts, which are essential for the sustainable development of the region. By incorporating these practices into water management strategies, we can help ensure a more stable and reliable water supply for communities and ecosystems within the region. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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13 pages, 7982 KiB  

Open AccessArticle

Study on the Water Level–Discharge Relationship Changes in Dongting Lake Outlet Section over 70 Years and the Impact of Yangtze River Backwater Effect

by Yizhuang Liu, Changbo Jiang, Yuannan Long, Bin Deng, Jieyu Jiang, Yang Yang and Zhiyuan Wu

Water 2023, 15(11), 2057; https://doi.org/10.3390/w15112057 - 29 May 2023

Cited by 6 | Viewed by 2180

Abstract

The hydrological characteristics of the river–lake connecting section are determined by their interaction and studying them can help to understand the changing relationship between these two water bodies over time. The Lujiao–Luosan section is the connecting section of Dongting Lake and the Yangtze [...] Read more.

The hydrological characteristics of the river–lake connecting section are determined by their interaction and studying them can help to understand the changing relationship between these two water bodies over time. The Lujiao–Luosan section is the connecting section of Dongting Lake and the Yangtze River, and the hydrological data for this section over the past 70 years has been analyzed. It has been found that the lowest water level is consistently rising at the same discharge at Chenglingji station, which is the joint point of Dongting Lake and the Yangtze River. While this could alleviate the drought situation in the Dongting Lake area during dry seasons, it could pose a more significant flood-control challenge during high water levels in the flood season. The water surface slope shows a decreasing trend especially during the dry season, except for the high flood period (July–September), which indicates that the water slope in the connecting section of Dongting Lake has become flatter. The backwater effect of the Yangtze River on Dongting Lake becomes increasingly stronger as the water surface slope difference between the Chenglingji–Luoshan section and the Lujiao–Chenglingji section changes from negative to positive between January and April. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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19 pages, 7626 KiB  

Open AccessArticle

Attribution of Extreme Drought Events and Associated Physical Drivers across Southwest China Using the Budyko Framework

by Xupeng Sun, Jinghan Wang, Mingguo Ma and Xujun Han

Remote Sens. 2023, 15(11), 2702; https://doi.org/10.3390/rs15112702 - 23 May 2023

Cited by 5 | Viewed by 2378

Abstract

Drought is a meteorological phenomenon that negatively impacts agricultural production. In recent years, southwest China has frequently experienced agricultural droughts; these have significantly impacted the economy and the ecological environment. Although several studies have been conducted on agricultural droughts, few have examined the [...] Read more.

Drought is a meteorological phenomenon that negatively impacts agricultural production. In recent years, southwest China has frequently experienced agricultural droughts; these have significantly impacted the economy and the ecological environment. Although several studies have been conducted on agricultural droughts, few have examined the factors driving agricultural droughts from the perspective of water and energy balance. This study aimed to address this gap by utilizing the Standardized Soil Moisture Index (SSMI) and the Budyko model to investigate agricultural drought in southwest China. The study identified four areas in Southwest China with a high incidence of agricultural drought from 2000 to 2020. Yunnan and the Sichuan-Chongqing border regions experienced drought in 10% of the months during the study period, while Guangxi and Guizhou had around 8% of months with drought. The droughts in these regions exhibited distinct seasonal characteristics, with Yunnan experiencing significantly higher drought frequency than other periods from January to June, while Guizhou and other areas were prone to severe droughts in summer and autumn. The Budyko model is widely used as the mainstream international framework for studying regional water and energy balance. In this research, the Budyko model was applied to analyze the water and energy balance characteristics in several arid regions of southwest China using drought monitoring data. Results indicate that the water and energy balances in Yunnan and Sichuan-Chongqing are more moisture-constrained, whereas those in Guizhou and Guangxi are relatively stable, suggesting lower susceptibility to extreme droughts. Furthermore, during severe drought periods, evapotranspiration becomes a dominant component of the water cycle, while available water resources such as soil moisture decrease. After comparing the causes of drought and non-drought years, it was found that the average rainfall in southwest China is approximately 30% below normal during drought years, and the temperature is 1–2% higher than normal. These phenomena are most noticeable during the spring and winter months. Additionally, vegetation transpiration is about 10% greater than normal during dry years in Southwest China, and soil evaporation increases by about 5% during the summer and autumn months compared to normal conditions. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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18 pages, 18155 KiB  

Open AccessArticle

Recognition of the Interaction Mechanisms between Water and Land Resources Based on an Improved Distributed Hydrological Model

by Jianwei Wang, Xizhi Lv, Tianling Qin, Yongxin Ni, Li Ma, Qiufen Zhang, Hanjiang Nie, Zhenyu Lv, Chenhao Li, Xin Zhang and Jianming Feng

Water 2023, 15(10), 1946; https://doi.org/10.3390/w15101946 - 21 May 2023

Viewed by 2100

Abstract

Conflicts between humans and land use in the process of using water and conflicts between humans and water resources in the process of using land have led to an imbalance between natural ecosystems and socio-economic systems. It is difficult to understand the impact [...] Read more.

Conflicts between humans and land use in the process of using water and conflicts between humans and water resources in the process of using land have led to an imbalance between natural ecosystems and socio-economic systems. It is difficult to understand the impact of the processes of water production and consumption on land patches and their ecological effects. A grid-type, basin-distributed hydrological model was established in this study, which was based on land-use units and coupled with groundwater modules to simulate the water production and consumption processes in different units. By combining land use and net primary productivity, the runoff coefficient and the water use efficiency (NPP/ET) of different land units were used as indicators to characterize the interaction between water and land resources. The results showed that the average runoff coefficients of cultivated land, forest land and grassland were 0.7, 0.5 and 0.9, respectively. Moreover, the average runoff coefficients of hills, plains and basins were 0.7, 0.7 and 0.8, respectively. The NPP produced by the average unit, evapotranspiration, in cultivated land, forest land and grassland was 7 (gC/(m²•a))/mm, 0.7 (gC/(m²•a))/mm and 0.2 (gC/(m²•a))/mm, respectively. These results provide quantitative scientific and technological support in favor of the comprehensive ecological management of river basins. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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19 pages, 3156 KiB  

Open AccessArticle

Use of Analytic Hierarchy Process Method to Identify Potential Rainwater Harvesting Sites: Design and Financial Strategies in Taxco de Alarcón, Southern Mexico

by Blanca Itzany Rivera Vázquez, Edith Rosalba Salcedo Sánchez, Juan Manuel Esquivel Martínez, Miguel Ángel Gómez Albores, Felipe Gómez Noguez, Carina Gutiérrez Flores and Oscar Talavera Mendoza

Sustainability 2023, 15(10), 8220; https://doi.org/10.3390/su15108220 - 18 May 2023

Cited by 5 | Viewed by 2110

Abstract

Mexico is among the countries that are facing the greatest water stress, where factors such as climate change, contamination of surface water, groundwater sources, and inefficient management have limited the availability of water resources. Consequently, new supply sources need to be implemented. Rainwater [...] Read more.

Mexico is among the countries that are facing the greatest water stress, where factors such as climate change, contamination of surface water, groundwater sources, and inefficient management have limited the availability of water resources. Consequently, new supply sources need to be implemented. Rainwater harvesting systems (RHS) are viable and sustainable alternatives, the implementation of which primarily depends on identifying suitable sites and applying technologies that are appropriate for different users. This research used the Analytical Hierarchy Process (AHP) technique in a GIS environment to select the optimal sites for designing RHS, taking into account hydrological, biophysical, and socioeconomic criteria. After determining the ideal sites, the study presents proposals and costs for the design of an urban and rural RHS based on the characteristics of the region and the needs of the community. The findings show that implementing RHS in the study area can be a practical, economical, and efficient alternative for water resource management, since these projects are aimed at sustainability. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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16 pages, 18670 KiB  

Open AccessArticle

Spatial–Temporal Variability of Climatic Water Balance in the Brazilian Savannah Region River Basins

by Fernanda Laurinda Valadares Ferreira, Lineu Neiva Rodrigues, Daniel Althoff and Ricardo Santos Silva Amorim

Water 2023, 15(10), 1820; https://doi.org/10.3390/w15101820 - 10 May 2023

Cited by 8 | Viewed by 2575

Abstract

The evaluation of water and energy cycles from the estimation of water balance is a fundamental instrument to assess the water potential of a region. Thus, the objective of this study was to evaluate the probable monthly water deficit and surplus in Cerrado [...] Read more.

The evaluation of water and energy cycles from the estimation of water balance is a fundamental instrument to assess the water potential of a region. Thus, the objective of this study was to evaluate the probable monthly water deficit and surplus in Cerrado river basins and the trend of monthly data on climatic water balance (CWB) and its input variables in the study region. Monthly data on precipitation (P) and reference evapotranspiration (ETo) from January 2003 to December 2019 were used. The deficit and the probable monthly water surplus were obtained from the CWB for each of the 4531 ottobasins. For this, the frequency equal to or greater than 80% of permanence in time was used as a reference. Trend analysis was applied. In the rainy season, most ottobasins showed positive CWB. On the other hand, in the period of lower water availability, most ottobasins showed a negative balance. In all months, there was some ottobasin with a significant trend both for CWB and for P and ETo. In most situations, these trends were a decrease in CWB and monthly P and an increase in monthly ETo. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 4212 KiB  

Open AccessArticle

Hydrogeochemical Appraisal of Groundwater Quality and Its Suitability for Drinking and Irrigation Purposes in the West Central Senegal

by Mathias Diédhiou, Seyni Ndoye, Helene Celle, Serigne Faye, Stefan Wohnlich and Philippe Le Coustumer

Water 2023, 15(9), 1772; https://doi.org/10.3390/w15091772 - 5 May 2023

Cited by 6 | Viewed by 3031

Abstract

Groundwater has been the main resource used for drinking, domestic and agricultural activities in West central Senegal for the past few decades. Thus, this study investigates the quality of groundwater and assesses its suitability for drinking and irrigation purposes. To this end, 42 [...] Read more.

Groundwater has been the main resource used for drinking, domestic and agricultural activities in West central Senegal for the past few decades. Thus, this study investigates the quality of groundwater and assesses its suitability for drinking and irrigation purposes. To this end, 42 samples were collected and analyzed for various chemical parameters (major ions, fluoride, pH, total dissolved solids (TDS)). Chemical data were interpreted using water quality indexes, Wilcox and USSL salinity diagrams, bivariate plots, ionic ratios and by comparing with the WHO standards. Results indicated that the groundwater is neutral to slightly alkaline with pH values between 7.1 and 8.2. Piper diagram shows that mixte-Ca-Na-Mg-HCO₃ is the dominant hydrochemical facies. TDS and water quality index (WQI) values indicated respectively that 69% and 64.3% of samples were suitable for drinking. Moreover, major ions concentrations were found below the desirable limits in most of groundwater samples. However, for fluoride, 69% of samples exceed the WHO guideline, limiting their use for drinking. The computed index of irrigation water quality and Wilcox diagram reveal that 87% and 78% of samples belong, respectively, to excellent to good category and excellent to good and good to permissible. Similarly, according to the US salinity classification, the majority of samples were acceptable for irrigation. Gibbs plots illustrate that water-rocks interaction with some extent evaporation is the main hydrochemical process controlling groundwater chemistry while bivariate plots and ionic ratios indicate that mineral dissolution and ion exchange play important role in groundwater chemistry. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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16 pages, 4752 KiB  

Open AccessArticle

Integrating Remote Sensing, Proximal Sensing, and Probabilistic Modeling to Support Agricultural Project Planning and Decision-Making for Waterlogged Fields

by Benjamin Bukombe, Sándor Csenki, Dora Szlatenyi, Ivan Czako and Vince Láng

Water 2023, 15(7), 1340; https://doi.org/10.3390/w15071340 - 29 Mar 2023

Cited by 3 | Viewed by 2424

Abstract

Waterlogging in agriculture poses severe threats to soil properties, crop yields, and farm profitability. Remote sensing data coupled with drainage systems offer solutions to monitor and manage waterlogging in agricultural systems. However, implementing agricultural projects such as drainage is associated with high uncertainty [...] Read more.

Waterlogging in agriculture poses severe threats to soil properties, crop yields, and farm profitability. Remote sensing data coupled with drainage systems offer solutions to monitor and manage waterlogging in agricultural systems. However, implementing agricultural projects such as drainage is associated with high uncertainty and risk, with substantial negative impacts on farm profitability if not well planned. Cost–benefit analyses can help allocate resources more effectively; however, data scarcity, high uncertainty, and risks in the agricultural sector make it difficult to use traditional approaches. Here, we combined a wide range of field and remote sensing data, unsupervised machine learning, and Bayesian probabilistic models to: (1) identify potential sites susceptible to waterlogging at the farm scale, and (2) test whether the installation of drainage systems would yield a positive benefit for the farmer. Using the K-means clustering algorithm on water and vegetation indices derived from Sentinel-2 multispectral imagery, we were able to detect potential waterlogging sites in the investigated field (elbow point = 2, silhouette coefficient = 0.46). Using a combination of the Bayesian statistical model and the A/B test, we show that the installation of a drainage system can increase farm profitability by 1.7 times per year compared to the existing farm management. The posterior effect size associated with yield, cropping area, and time (year) was 0.5, 1.5, and 1.9, respectively. Altogether, our results emphasize the importance of data-driven decision-making for agriculture project planning and resource management in the wake of smart agriculture for food security and adaptation to climate change. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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15 pages, 12520 KiB  

Open AccessArticle

New Remote Sensing Data on the Potential Presence of Permafrost in the Deosai Plateau in the Himalayan Portion of Pakistan

by Maria Teresa Melis, Francesco Gabriele Dessì and Marco Casu

Remote Sens. 2023, 15(7), 1800; https://doi.org/10.3390/rs15071800 - 28 Mar 2023

Cited by 2 | Viewed by 2332

Abstract

In this study, the presence of permafrost layer and its potential variation in the last three decades will be examined through the multitemporal analysis of satellite data in the area of the Deosai Plateau (Northern Pakistan). In the area, only global maps on [...] Read more.

In this study, the presence of permafrost layer and its potential variation in the last three decades will be examined through the multitemporal analysis of satellite data in the area of the Deosai Plateau (Northern Pakistan). In the area, only global maps on the potential presence of permafrost layer are known. The results are based on the evaluation of variation of the number and water levels of the small lakes, and the changes of the extensions of the wetlands. The adopted methodology is based on the use of spectral indices and visual interpretation of a time-series data of Landsat images in the range 1990–2019, and on the processing of radar data from Sentinel 1 satellites, adopting new methods to extract the vertical displacement. The main findings are: (i) a high temporal dynamic of the number and surface areas of small lakes, and (ii) the evidence of a subduction in a wetland area (Black Hole), coherent with its extension, and suggesting the potential presence of a permafrost layer slowly degrading. This analysis can play a useful role on the management of the Deosai National Park (DNP), adopting careful measures for the human activities inside the park. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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22 pages, 5612 KiB  

Open AccessArticle

Estimation of Urban Evapotranspiration at High Spatiotemporal Resolution and Considering Flux Footprints

by Lihao Zhou, Lei Cheng, Shujing Qin, Yiyi Mai and Mingshen Lu

Remote Sens. 2023, 15(5), 1327; https://doi.org/10.3390/rs15051327 - 27 Feb 2023

Cited by 3 | Viewed by 2805

Abstract

Evapotranspiration (ET) estimations at high spatiotemporal resolutions in urban areas are crucial for extreme weather forecasting and water management. However, urban ET estimation remains a major challenge in current urban hydrology and regional climate research due to highly heterogeneous environments, human interference, and [...] Read more.

Evapotranspiration (ET) estimations at high spatiotemporal resolutions in urban areas are crucial for extreme weather forecasting and water management. However, urban ET estimation remains a major challenge in current urban hydrology and regional climate research due to highly heterogeneous environments, human interference, and a lack of observations. In this study, an urban ET model, called the PT-Urban model, was proposed for half-hourly ET estimations at a 10 m resolution. The PT-Urban model was validated using observations from the Hotel Torni urban flux site during the 2018 growing season. The results showed that the PT-Urban model performed satisfactorily, with an R² and root-mean-square error of 0.59 and 14.67 W m⁻², respectively. Further analysis demonstrated that urban canopy heat storage and shading effects are essential for the half-hourly urban energy balance. Ignoring the shading effects led to a 38.7% urban ET overestimation. Modeling experiments further proved that flux footprint variations were critical for the accurate estimation of urban ET. The setting source areas either as an invariant 70% historical footprint or as a circle with a 1 km radius both resulted in poor performances. This study presents a practical method for the accurate estimation of urban ET with high spatiotemporal resolution and highlights the importance of real-time footprints in urban ET estimations. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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23 pages, 5222 KiB  

Open AccessArticle

Bivariate Hazard Assessment of Combinations of Dry and Wet Conditions between Adjacent Seasons in a Climatic Transition Zone

by Geer Cheng, Tiejun Liu, Sinan Wang, Ligao Bao, Wei Fang and Jianan Shang

Atmosphere 2023, 14(3), 437; https://doi.org/10.3390/atmos14030437 - 22 Feb 2023

Cited by 1 | Viewed by 1543

Abstract

Accumulated evidence reminds one that abrupt transitions between dry and wet spells, though attracting less attention, have harmful influences upon global continents as extensively investigated droughts and floods. This study attempts to incorporate dryness–wetness transitions into the current hazard assessment framework through bivariate [...] Read more.

Accumulated evidence reminds one that abrupt transitions between dry and wet spells, though attracting less attention, have harmful influences upon global continents as extensively investigated droughts and floods. This study attempts to incorporate dryness–wetness transitions into the current hazard assessment framework through bivariate frequency analysis and causal attribution from a teleconnection perspective. In the study, regional dry and wet conditions are monitored using the multivariate standardized drought index (MSDI) which facilitates the integrated evaluation of water deficits/surplus from a combined viewpoint of precipitation (largely denoting the received atmospheric water) and runoff (representing an important source of surface water). On such a basis, a copula-based method is subsequently utilized to calculate joint return periods of dryness–wetness combinations in three (i.e., moderate, severe and extreme) severity scenarios. The changing frequency of diverse dryness–wetness combinations is also estimated under a changing climate using a 25-year time window. Furthermore, the cross-wavelet transform is applied to attribute variations in dry and wet conditions to large-scale climate indices, which benefits the early warning of dryness–wetness combinations by providing predictive information. A case study conducted during 1952–2010 in the Huai River basin (HRB)—a typical climatic transition zone in China—shows that the HRB is subject to prolonged dryness with the highest frequency, followed by the abrupt transition from dryness to wetness. Spatially, abrupt dryness–wetness transitions are more likely to occur in the southern and central parts of the HRB than in the rest of the proportion. The past half-century has witnessed the dominantly higher frequency of occurrence of dryness–wetness combinations under three severity scenarios. In particular, the occurrence of the continued dry/wetness escalates more rapidly than transition events under climate change. Moreover, a preliminary attribution analysis discloses the link of the dry and wet conditions in the HRB with climate indices, such as the El Niño southern oscillation, the Pacific decadal oscillation and the Arctic oscillation, as well as sunspot activities. The results of the study enrich the current atlas of water-related hazards, which may benefit more effective hazard mitigation and adaptation. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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17 pages, 4044 KiB  

Open AccessArticle

A Machine-Learning Approach for Monitoring Water Distribution Networks (WDNs)

by Roberto Magini, Manuela Moretti, Maria Antonietta Boniforti and Roberto Guercio

Sustainability 2023, 15(4), 2981; https://doi.org/10.3390/su15042981 - 7 Feb 2023

Cited by 5 | Viewed by 2699

Abstract

The knowledge of the simultaneous nodal pressure values in a water distribution network (WDN) can favor its correct management, with advantages for both water utilities and end users, and guarantee higher sustainability in the use of the water resource. However, monitoring pressure in [...] Read more.

The knowledge of the simultaneous nodal pressure values in a water distribution network (WDN) can favor its correct management, with advantages for both water utilities and end users, and guarantee higher sustainability in the use of the water resource. However, monitoring pressure in all the nodes is not feasible, so it can be useful to develop methods that allow us to estimate the whole pressure field based on data from a limited number of nodes. For this purpose, the work employed an artificial neural network (ANN) as a machine-learning regression algorithm. Uncertainty of water demand is modeled through scaling laws, linking demand statistics to the number of users served by each node. Three groups of demand scenarios are generated by using a Latin Hypercube Random Sampling with three different cross-correlations matrices of the nodal demands. Each of the corresponding groups of pressure scenarios is employed for the training of an ANN, whose performance parameter is preliminarily used to solve the sampling design for the WDN. Most of the so-derived monitoring nodes coincide in the three cases. The performance of each ANN appears to be strongly influenced by cross-correlation values, with the best results provided by the ANN relating to the most correlated demands. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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20 pages, 8138 KiB  

Open AccessArticle

Analysis of Groundwater Storage Changes and Influencing Factors in China Based on GRACE Data

by Chunxiu Shao and Yonghe Liu

Atmosphere 2023, 14(2), 250; https://doi.org/10.3390/atmos14020250 - 27 Jan 2023

Cited by 16 | Viewed by 2854

Abstract

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery [...] Read more.

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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15 pages, 16352 KiB  

Open AccessEditor’s ChoiceArticle

Assessment of a Smartphone App for Open Channel Flow Measurement in Data Scarce Irrigation Schemes

by Menwagaw T. Damtie, Marshet B. Jumber, Fasikaw A. Zimale and Seifu A. Tilahun

Hydrology 2023, 10(1), 22; https://doi.org/10.3390/hydrology10010022 - 15 Jan 2023

Cited by 3 | Viewed by 3237

Abstract

Accurate water flow measurement ensures proper irrigation water management by allocating the desired amount of water to the irrigation fields. The present study evaluated whether the non-intrusive smartphone application “DischargeApp” could be applicable and precise to measure small canal flow rates in the [...] Read more.

Accurate water flow measurement ensures proper irrigation water management by allocating the desired amount of water to the irrigation fields. The present study evaluated whether the non-intrusive smartphone application “DischargeApp” could be applicable and precise to measure small canal flow rates in the Koga irrigation Scheme. The app was tested in unlined canals with flow rates ranging from 15 to 65 l/s using a 90° V-notch weir. The app is found to overestimate high flow rates. Another source of uncertainty is that the app employed a constant surface velocity conversion factor (C = 0.8) to compute discharge. The accuracy was enhanced by recalculating the measured discharge using a new surface velocity conversion factor that depends on depths. The new conversion factor decreased the errors of MAE and RMSE by 47% and 52%, respectively. Where channel and other optional measuring techniques are not available without interfering with the flow operation conditions in place, the DischargeApp devices can be used to measure flows. The DischargeApp could be used to collect data using local citizens in data-scarce areas. This study suggested reconfiguring the DischargeApp with a new surface velocity conversion coefficient based on flow depths in field conditions for better performance. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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13 pages, 2548 KiB  

Open AccessArticle

Forecasting the July Precipitation over the Middle-Lower Reaches of the Yangtze River with a Flexible Statistical Model

by Qixiao Jiang and Xiangjun Shi

Atmosphere 2023, 14(1), 152; https://doi.org/10.3390/atmos14010152 - 10 Jan 2023

Cited by 1 | Viewed by 1862

Abstract

The multiple regression method is still an important tool for establishing precipitation forecast models with a lead time of one season. This study developed a flexible statistical forecast model for July precipitation over the middle-lower reaches of the Yangtze River (MLYR) based on [...] Read more.

The multiple regression method is still an important tool for establishing precipitation forecast models with a lead time of one season. This study developed a flexible statistical forecast model for July precipitation over the middle-lower reaches of the Yangtze River (MLYR) based on the prophase winter sea surface temperature (SST). According to the characteristics of observed samples and related theoretical knowledge, some special treatments (i.e., more flexible and better-targeted methods) were introduced in the forecast model. These special treatments include a flexible MLYR domain definition, the extraction of indicative signals from the SST field, artificial samples, and the amplification of abnormal precipitation. Rolling forecast experiments show that the linear correlation between prediction and observation is around 0.5, more than half of the abnormal precipitation years can be successfully predicted, and there is no contradictory prediction of the abnormal years. These results indicate that the flexible statistical forecast model is valuable in real-life applications. Furthermore, sensitivity experiments show that forecast skills without these special treatments are obviously decreased. This suggests that forecast models can benefit from using statistical methods in a more flexible and better-targeted way. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

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