Hydrology

20 pages, 4109 KiB

Open AccessArticle

Quantifying Baseflow with Radon, H and O Isotopes and Field Parameters in the Urbanized Catchment of the Little Jukskei River, Johannesburg

by Khutjo Diphofe, Roger Diamond and Francois Kotze

Hydrology 2025, 12(8), 203; https://doi.org/10.3390/hydrology12080203 - 2 Aug 2025

Abstract

Understanding groundwater and surface water interaction is critical for managing water resources, particularly in water-stressed and rapidly urbanizing areas, such as many parts of Africa. A survey was conducted of borehole, spring, seep and river water radon, δ²H, δ¹⁸O [...] Read more.

Understanding groundwater and surface water interaction is critical for managing water resources, particularly in water-stressed and rapidly urbanizing areas, such as many parts of Africa. A survey was conducted of borehole, spring, seep and river water radon, δ²H, δ¹⁸O and field parameters in the Jukskei River catchment, Johannesburg. Average values of electrical conductivity (EC) were 274 and 411 μS·cm⁻¹ for groundwater and surface water, and similarly for radon, 37,000 and 1100 Bq·m⁻³, with a groundwater high of 196,000 Bq·m⁻³ associated with a structural lineament. High radon was a good indicator of baseflow, highest at the end of the rainy season (March) and lowest at the end of the dry season (September), with the FINIFLUX model computing groundwater inflow as 2.5–4.7 L·m⁻¹s⁻¹. High EC was a poorer indicator of baseflow, also considering the possibility of wastewater with high EC, typical in urban areas. Groundwater δ²H and δ¹⁸O values are spread widely, suggesting recharge from both normal and unusual rainfall periods. A slight shift from the local meteoric water line indicates light evaporation during recharge. Surface water δ²H and δ¹⁸O is clustered, pointing to regular groundwater input along the stream, supporting the findings from radon. Given the importance of groundwater, further study using the same parameters or additional analytes is advisable in the urban area of Johannesburg or other cities. Full article

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20 pages, 7673 KiB

Open AccessArticle

Impact of Elevation and Hydrography Data on Modeled Flood Map Accuracy Using ARC and Curve2Flood

by Taylor James Miskin, L. Ricardo Rosas, Riley C. Hales, E. James Nelson, Michael L. Follum, Joseph L. Gutenson, Gustavious P. Williams and Norman L. Jones

Hydrology 2025, 12(8), 202; https://doi.org/10.3390/hydrology12080202 - 1 Aug 2025

Abstract

This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These [...] Read more.

This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These comparisons are notable because they build on operational global hydrology models so subsequent work can develop global modeled flood products. Models were made using the Automated Rating Curve (ARC) and Curve2Flood tools. Accuracy was measured against USGS reference maps using the F-statistic. Our results show that flood map accuracy generally increased with higher return periods. The most consistent and reliable improvements in accuracy occurred when both the DEM and hydrography datasets were upgraded to higher-resolution sources. While DEM improvements generally had a greater impact, hydrography refinements were more important for lower return periods when flood extents were the smallest. Generally, DEM resolution improved accuracy metrics more as the return period increased and hydrography and bare earth DEMs mattered more as the return period decreased. There was a 38.9% increase in the mean F-statistic between the two principal pairings of interest (FABDEM-RFS2 and SRTM 30 m DEM-RFS1). FABDEM’s bare-earth representation combined with RFS2 sometimes outperformed higher-resolution non-bare-earth DEMs, suggesting that there remains a need for site-specific investigation. Using ARC and Curve2Flood with FABDEM and RFS2 is a suitable baseline combination for general flood extent application. Full article

(This article belongs to the Special Issue Advances in Flood Studies: Enhancing Data Collection, Rating Curves, and Hydrological Analyses)

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17 pages, 4148 KiB

Open AccessArticle

Disastrous Effects of Hurricane Helene in the Southern Appalachian Mountains Including a Review of Mechanisms Producing Extreme Rainfall

by Jeff Callaghan

Hydrology 2025, 12(8), 201; https://doi.org/10.3390/hydrology12080201 - 31 Jul 2025

Abstract

Hurricane Helene made landfall near Perry (Latitude 30.1 N) in the Big Bend area of Florida with a central pressure of 939 hPa. It moved northwards creating devastating damage and loss of life; however, the greatest damage and number of fatalities occurred well [...] Read more.

Hurricane Helene made landfall near Perry (Latitude 30.1 N) in the Big Bend area of Florida with a central pressure of 939 hPa. It moved northwards creating devastating damage and loss of life; however, the greatest damage and number of fatalities occurred well to the north around the City of Ashville (Latitude 35.6 N) where extreme rainfall fell and some of the strongest wind gusts were reported. This paper describes the change in the hurricane’s structure as it tracked northwards, how it gathered tropical moisture from the Atlantic and a turning wind profile between the 850 hPa and 500 hPa elevations, which led to such extreme rainfall. This turning wind profile is shown to be associated with extreme rainfall and loss of life from drowning and landslides around the globe. The area around Ashville suffered 157 fatalities, which is a considerable proportion of the 250 fatalities so far recorded in the whole United Stares from Helene. This is of extreme concern and should be investigated in detail as the public expect the greatest impact from hurricanes to be confined to coastal areas near the landfall site. It is another example of increased death tolls from tropical cyclones moving inland and generating heavy rainfall. As the global population increases and inland centres become more urbanised, run off from such rainfall events increases, which causes greater devastation. Full article

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28 pages, 2566 KiB

Open AccessArticle

Simulating Effectiveness of Low Impact Development (LID) for Different Building Densities in the Face of Climate Change Using a Hydrologic-Hydraulic Model (SWMM₅)

by Helene Schmelzing and Britta Schmalz

Hydrology 2025, 12(8), 200; https://doi.org/10.3390/hydrology12080200 - 31 Jul 2025

Abstract

To date, few studies have been published for cities in Germany that take into account climate change and changing hydrologic patterns due to increases in building density. This study investigates the efficiency of LID for past and future climate in the polycentric agglomeration [...] Read more.

To date, few studies have been published for cities in Germany that take into account climate change and changing hydrologic patterns due to increases in building density. This study investigates the efficiency of LID for past and future climate in the polycentric agglomeration area Frankfurt, Main (Central Germany) using observed and projected climate (model) data for a standard reference period (1961–1990) and a high emission scenario (RCP 8.5) as well as a climate protection scenario (RCP 2.6), under 40 to 75 percent building density. LID elements included green roofs, permeable pavement and bioretention cells. SWMM₅ was used as model for simulation purposes. A holistic evaluation of simulation results showed that effectiveness increases incrementally with LID implementation percentage and inverse to building density if implemented onto at least 50 percent of available impervious area. Building density had a higher adverse effect on LID efficiency than climate change. The results contribute to the understanding of localized effects of climate change and the implementation of adaption strategies to that end. The results of this study can be helpful for the scientific community regarding future investigations of LID implementation efficiency in dense residential areas and used by local governments to provide suggestions for urban water balance revaluation. Full article

(This article belongs to the Topic Water Management in the Age of Climate Change)

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26 pages, 3711 KiB

Open AccessArticle

Probability Characteristics of High and Low Flows in Slovakia: A Comprehensive Hydrological Assessment

by Pavla Pekárová, Veronika Bačová Mitková and Dana Halmová

Hydrology 2025, 12(8), 199; https://doi.org/10.3390/hydrology12080199 - 31 Jul 2025

Abstract

Frequency analysis is essential for designing hydraulic structures and managing water resources, as it helps assess hydrological extremes. However, changes in river basins can impact their accuracy, complicating the link between discharge and return periods. This study aims to comprehensively assess the probability [...] Read more.

Frequency analysis is essential for designing hydraulic structures and managing water resources, as it helps assess hydrological extremes. However, changes in river basins can impact their accuracy, complicating the link between discharge and return periods. This study aims to comprehensively assess the probability characteristics of long-term M-day maximum/minimum discharges in the Carpathian region of Slovakia. We analyze the long-term data from 26 gauging stations covering 90 years of observation. Slovak rivers show considerable intra-annual variability, especially between the summer–autumn (SA) and winter–spring (WS) seasons. To allow consistent comparisons, we apply a uniform methodology to estimate T-year daily maximum and minimum specific discharges over durations of 1 and 7 days for both seasons. Our findings indicate that 1-day maximum specific discharges are generally higher during the SA season compared to the WS season. The 7-day minimum specific discharges are lower during the WS season compared to the SA season. Slovakia’s diverse orographic and climatic conditions cause significant spatial variability in extreme discharges. However, the estimated T-year 7-day minimum and 1-day maximum specific discharges, based on the mean specific discharge and the altitude of the water gauge, exhibit certain nonlinear dependences. These relationships could support the indirect estimation of T-year M-day discharges in regions with similar runoff characteristics. Full article

(This article belongs to the Section Water Resources and Risk Management)

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27 pages, 10190 KiB

Open AccessArticle

Assessing the Impact of Assimilated Remote Sensing Retrievals of Precipitation on Nowcasting a Rainfall Event in Attica, Greece

by Aikaterini Pappa, John Kalogiros, Maria Tombrou, Christos Spyrou, Marios N. Anagnostou, George Varlas, Christine Kalogeri and Petros Katsafados

Hydrology 2025, 12(8), 198; https://doi.org/10.3390/hydrology12080198 - 28 Jul 2025

Abstract

Accurate short-term rainfall forecasting, an essential component of the broader framework of nowcasting, is crucial for managing extreme weather events. Traditional forecasting approaches, whether radar-based or satellite-based, often struggle with limited spatial coverage or temporal accuracy, reducing their effectiveness. This study tackles these [...] Read more.

Accurate short-term rainfall forecasting, an essential component of the broader framework of nowcasting, is crucial for managing extreme weather events. Traditional forecasting approaches, whether radar-based or satellite-based, often struggle with limited spatial coverage or temporal accuracy, reducing their effectiveness. This study tackles these challenges by implementing the Local Analysis and Prediction System (LAPS) enhanced with a forward advection nowcasting module, integrating multiple remote sensing rainfall datasets. Specifically, we combine weather radar data with three different satellite-derived rainfall products (H-SAF, GPM, and TRMM) to assess their impact on nowcasting performance for a rainfall event in Attica, Greece (29–30 September 2018). The results demonstrate that combined high-resolution radar data with the broader coverage and high temporal frequency of satellite retrievals, particularly H-SAF, leads to more accurate predictions with lower uncertainty. The assimilation of H-SAF with radar rainfall retrievals (HX experiment) substantially improved forecast skill, reducing the unbiased Root Mean Square Error by almost 60% compared to the control experiment for the 60 min rainfall nowcast and 55% for the 90 min rainfall nowcast. This work validates the effectiveness of the specific LAPS/advection configuration and underscores the importance of multi-source data assimilation for weather prediction. Full article

(This article belongs to the Topic Advances in Hydrological Remote Sensing)

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21 pages, 4181 KiB

Open AccessArticle

Addressing Volatility and Nonlinearity in Discharge Modeling: ARIMA-iGARCH for Short-Term Hydrological Time Series Simulation

by Mahshid Khazaeiathar and Britta Schmalz

Hydrology 2025, 12(8), 197; https://doi.org/10.3390/hydrology12080197 - 27 Jul 2025

Abstract

Selecting an appropriate model for discharge simulation remains a fundamental challenge in modeling. While artificial neural networks (ANNs) have been widely accepted due to detecting streamflow patterns, they require large datasets for efficient training. However, when short-term datasets are available, training ANNs becomes [...] Read more.

Selecting an appropriate model for discharge simulation remains a fundamental challenge in modeling. While artificial neural networks (ANNs) have been widely accepted due to detecting streamflow patterns, they require large datasets for efficient training. However, when short-term datasets are available, training ANNs becomes problematic. Autoregressive integrated moving average (ARIMA) models offer a promising alternative; however, severe volatility, nonlinearity, and trends in hydrological time series can still lead to significant errors. To address these challenges, this study introduces a new adaptive hybrid model, ARIMA-iGARCH, designed to account volatility, variance inconsistency, and nonlinear behavior in short-term hydrological datasets. We apply the model to four hourly discharge time series from the Schwarzbach River at the Nauheim gauge in Hesse, Germany, under the assumption of normally distributed residuals. The results demonstrate that the specialized parameter estimation method achieves lower complexity and higher accuracy. For the four events analyzed, R² values reached 0.99, 0.96, 0.99, and 0.98; RMSE values were 0.031, 0.091, 0.023, and 0.052. By delivering accurate short-term discharge predictions, the ARIMA-iGARCH model provides a basis for enhancing water resource planning and flood risk management. Overall, the model significantly improves modeling long memory, nonlinear, nonstationary shifts in short-term hydrological datasets by effectively capturing fluctuations in variance. Full article

(This article belongs to the Special Issue Advancing Hydrological Science Through Artificial Intelligence: Innovations and Applications)

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11 pages, 15673 KiB

Open AccessArticle

Automating GIS-Based Cloudburst Risk Mapping Using Generative AI: A Framework for Scalable Hydrological Analysis

by Alexander Adiyasa, Andrea Niccolò Mantegna and Irma Kveladze

Hydrology 2025, 12(8), 196; https://doi.org/10.3390/hydrology12080196 - 23 Jul 2025

Abstract

Accurate dynamic hydrological models are often too complex and costly for the rapid, broad-scale screening necessitated for proactive land-use planning against increasing cloudburst risks. This paper demonstrates the use of GPT-4 to develop a GUI-based Python 3.13.2 application for geospatial flood risk assessments. [...] Read more.

Accurate dynamic hydrological models are often too complex and costly for the rapid, broad-scale screening necessitated for proactive land-use planning against increasing cloudburst risks. This paper demonstrates the use of GPT-4 to develop a GUI-based Python 3.13.2 application for geospatial flood risk assessments. The study used instructive prompt techniques to script a traditional stream and catchment delineation methodology, further embedding it with a custom GUI. The resulting application demonstrates high performance, processing a 29.63 km² catchment at a 1 m resolution in 30.31 s, and successfully identifying the main upstream contributing areas and flow paths for a specified area of interest. While its accuracy is limited by terrain data artifacts causing stream breaks, this study demonstrates how human–AI collaboration, with the LLM acting as a coding assistant guided by domain expertise, can empower domain experts and facilitate the development of advanced GIS-based decision-support systems. Full article

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15 pages, 2467 KiB

Open AccessArticle

Definition of Groundwater Management Zones for a Fissured Karst Aquifer in Semi-Arid Northeastern Brazil

by Hailton Mello da Silva, Luiz Rogério Bastos Leal, Cezar Augusto Teixeira Falcão Filho, Thiago dos Santos Gonçalves and Harald Klammler

Hydrology 2025, 12(8), 195; https://doi.org/10.3390/hydrology12080195 - 23 Jul 2025

Abstract

The objective of this study is to define groundwater management zones for a complex deformed and fissured Precambrian karst aquifer, which underlies one of the most important agricultural areas in the semi-arid region of Irecê, Bahia, Brazil. It is an unconfined aquifer, hundreds [...] Read more.

The objective of this study is to define groundwater management zones for a complex deformed and fissured Precambrian karst aquifer, which underlies one of the most important agricultural areas in the semi-arid region of Irecê, Bahia, Brazil. It is an unconfined aquifer, hundreds of meters thick, resulting from a large sequence of carbonates piled up by thrust faults during tectonic plate collisions. Groundwater recharge and flow in this aquifer are greatly influenced by karst features, through the high density of sinkholes and vertical wells. Over the past four decades, population and agricultural activities have increased in the region, resulting in unsustainable groundwater withdrawal and, at the same time, water quality degradation. Therefore, it is important to develop legal and environmental management strategies. This work proposes the division of the karst area into three well-defined management zones by mapping karst structures, land use, and urban occupation, as well as the concentrations of chloride and nitrate in the region’s groundwater. Zone 1 in the north possesses the lowest levels of karstification, anthropization, and contamination, while zone 2 in the central region has the highest levels and zone 3 in the south ranging in-between (except for stronger karstification). The delimitation of management zones will contribute to the development and implementation of optimized zone-specific groundwater preservation and restoration strategies. Full article

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28 pages, 12894 KiB

Open AccessFeature PaperArticle

Evolution of Rainfall Characteristics in Catalonia, Spain, Using a Moving-Window Approach (1950–2022)

by Carina Serra, María del Carmen Casas-Castillo, Raül Rodríguez-Solà and Cristina Periago

Hydrology 2025, 12(7), 194; https://doi.org/10.3390/hydrology12070194 - 19 Jul 2025

Abstract

A comprehensive analysis of the evolution of rainfall characteristics in Catalonia, NE Spain, was conducted using monthly data from 72 rain gauges over the period 1950–2022. A moving-window approach was applied at annual, seasonal, and monthly scales, calculating mean values, coefficients of variation [...] Read more.

A comprehensive analysis of the evolution of rainfall characteristics in Catalonia, NE Spain, was conducted using monthly data from 72 rain gauges over the period 1950–2022. A moving-window approach was applied at annual, seasonal, and monthly scales, calculating mean values, coefficients of variation (CV), and trends across 43 overlapping 31-year periods. To assess trends in these moving statistics, a modified Mann–Kendall test was applied to both the 31-year means and CVs. Results revealed a significant 10% decrease in annual rainfall, with summer showing the most pronounced decline, as nearly 90% of stations exhibited negative trends, while the CV showed negative trends in coastal areas and mostly positive trends inland. At the monthly scale, February, March, June, August, and December exhibited negative trends at more than 50% of stations, with rainfall reductions ranging from 20% to 30%. Additionally, the temporal evolution of Mann–Kendall trend coefficients within each 31-year moving window displayed a fourth-degree polynomial pattern, with a periodicity of 30–35 years at annual and seasonal scales, and for some months. Finally, at the annual scale and in two centennial series, the 80-year oscillations found were inversely correlated with the large-scale climate indices North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO). Full article

(This article belongs to the Special Issue Advances in the Measurement, Utility and Evaluation of Precipitation Observations)

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24 pages, 5725 KiB

Open AccessArticle

Modeling of Hydrological Processes in a Coal Mining Subsidence Area with High Groundwater Levels Based on Scenario Simulations

by Shiyuan Zhou, Hao Chen, Qinghe Hou, Haodong Liu and Pingjia Luo

Hydrology 2025, 12(7), 193; https://doi.org/10.3390/hydrology12070193 - 19 Jul 2025

Abstract

The Eastern Huang–Huai region of China is a representative mining area with a high groundwater level. High-intensity underground mining activities have not only induced land cover and land use changes (LUCC) but also significantly changed the watershed hydrological behavior. This study integrated the [...] Read more.

The Eastern Huang–Huai region of China is a representative mining area with a high groundwater level. High-intensity underground mining activities have not only induced land cover and land use changes (LUCC) but also significantly changed the watershed hydrological behavior. This study integrated the land use prediction model PLUS and the hydrological simulation model MIKE 21. Taking the Bahe River Watershed in Huaibei City, China, as an example, it simulated the hydrological response trends of the watershed in 2037 under different land use scenarios. The results demonstrate the following: (1) The land use predictions for each scenario exhibit significant variation. In the maximum subsidence scenario, the expansion of water areas is most pronounced. In the planning scenario, the increase in construction land is notable. Across all scenarios, the area of cultivated land decreases. (2) In the maximum subsidence scenario, the area of high-intensity waterlogging is the greatest, accounting for 31.35% of the total area of the watershed; in the planning scenario, the proportion of high-intensity waterlogged is the least, at 19.10%. (3) In the maximum subsidence scenario, owing to the water storage effect of the subsidence depression, the flood peak is conspicuously delayed and attains the maximum value of 192.3 m³/s. In the planning scenario, the land reclamation rate and ecological restoration rate of subsidence area are the highest, while the regional water storage capacity is the lowest. As a result, the total cumulative runoff is the greatest, and the peak flood value is reduced. The influence of different degrees of subsidence on the watershed hydrological behavior varies, and the coal mining subsidence area has the potential to regulate and store runoff and perform hydrological regulation. The results reveal the mechanism through which different land use scenarios influence hydrological processes, which provides a scientific basis for the territorial space planning and sustainable development of coal mining subsidence areas. Full article

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17 pages, 1939 KiB

Open AccessFeature PaperArticle

Comprehensive Assessment of Water Quality of China’s Largest Freshwater Lake Under the Impact of Extreme Floods and Droughts

by Zhiyu Mao, Junxiang Cheng, Ligang Xu, Mingliang Jiang and Hailin You

Hydrology 2025, 12(7), 192; https://doi.org/10.3390/hydrology12070192 - 14 Jul 2025

Abstract

Poyang Lake, a large floodplain lake, plays a crucial role in the ecological safety and quality of life in surrounding areas. Over the past decade (2013–2022), amid economic development and environmental changes, the water environment of Poyang Lake has encountered complex challenges. This [...] Read more.

Poyang Lake, a large floodplain lake, plays a crucial role in the ecological safety and quality of life in surrounding areas. Over the past decade (2013–2022), amid economic development and environmental changes, the water environment of Poyang Lake has encountered complex challenges. This study evaluated the water quality of Poyang Lake in a recent 10-year span by the water quality index (WQI), trophic level index (TLI) and a newly constructed comprehensive evaluation index, and it analyzed the trend of water quality change under extreme events. Meanwhile, the main factors affecting the water quality of Poyang Lake were analyzed by partial least squares (PLS), a multivariate statistical method that accounts for multicollinearity. The results indicate that: (1) The water quality of Poyang Lake in summer and autumn is slightly worse than that in spring and winter. Each water quality index reflects the distinct states of the water environment in Poyang Lake. (2) Each water quality evaluation index responds differently to influencing factors. (3) Extreme flood and drought events have markedly different impacts on the water environment of Poyang Lake, exhibiting significant spatial heterogeneity. Domestic sewage discharge and total water resources have a relatively great impact on the water environment of Poyang Lake. The results of this study provide important insights for water quality management and policy formulation in Poyang Lake, supporting sustainable regional development. Full article

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19 pages, 2285 KiB

Open AccessReview

Aquatic Pollution in the Bay of Bengal: Impacts on Fisheries and Ecosystems

by Nowrin Akter Shaika, Saleha Khan, Sadiqul Awal, Md. Mahfuzul Haque, Abul Bashar and Halis Simsek

Hydrology 2025, 12(7), 191; https://doi.org/10.3390/hydrology12070191 - 11 Jul 2025

Abstract

Aquatic pollution in the Bay of Bengal has become a major environmental issue with long-term impacts on fisheries, biodiversity, and ecosystems. The review paper examines the major pathways, sources, and ecological consequences of aquatic pollution in the Bay of Bengal. Pollutants such as [...] Read more.

Aquatic pollution in the Bay of Bengal has become a major environmental issue with long-term impacts on fisheries, biodiversity, and ecosystems. The review paper examines the major pathways, sources, and ecological consequences of aquatic pollution in the Bay of Bengal. Pollutants such as heavy metals, pesticides, petroleum hydrocarbons, and microplastics have been reported at concerning levels in the soil and water in aquatic ecosystems. Rivers act as key routes, transporting pollutants from inland sources to the Bay of Bengal. These contaminants disrupt metabolic and physiological functions in fish and other aquatic species and pose serious threats to food safety and public health through bioaccumulation. Harmful algal blooms (HABs), caused by nutrient enrichment, further exacerbate ecosystem degradation in the Bay of Bengal. The review highlights the immediate need for strengthened pollution control regulations, real-time water quality monitoring, sustainable farming practices, and community-based policy interventions to preserve biodiversity and safeguard fisheries. Full article

(This article belongs to the Section Surface Waters and Groundwaters)

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19 pages, 3696 KiB

Open AccessArticle

Reproducibility Limits of the Frequency Equation for Estimating Long-Linear Internal Wave Periods in Lake Biwa

by Hibiki Yoneda, Chunmeng Jiao, Keisuke Nakayama, Hiroki Matsumoto and Kazuhide Hayakawa

Hydrology 2025, 12(7), 190; https://doi.org/10.3390/hydrology12070190 - 11 Jul 2025

Abstract

In a large deep lake, the generation of internal Kelvin waves and internal Poincaré waves due to wind stress on the lake surface is a significant phenomenon. These internal waves play a crucial role in material transport within the lake and have profound [...] Read more.

In a large deep lake, the generation of internal Kelvin waves and internal Poincaré waves due to wind stress on the lake surface is a significant phenomenon. These internal waves play a crucial role in material transport within the lake and have profound effects on its ecosystem and environment. Our study, which investigated the modes of internal waves in Lake Biwa using the vertical temperature distribution from field observations, has yielded important findings. We have demonstrated the applicability of the frequency equation solutions, considering the Coriolis force. The period of the internal Poincaré waves, as observed in the field, was found to match the solutions of the frequency equation. For example, observational data collected in late October revealed excellent agreement with the theoretical solutions derived from the frequency equation, showing periods of 14.7 h, 11.8 h, 8.2 h, and 6.3 h compared to the theoretical values of 14.4 h, 11.7 h, 8.5 h, and 6.1 h, respectively. However, the periods of the internal Kelvin waves in the field observation results were longer than those of the theoretical solutions. The Modified Mathew function uses a series expansion around

q_{i} = 0

, making it difficult to estimate the periods of internal Kelvin waves under conditions where

|q_{i}| > 1.0

. Furthermore, in lakes with an elliptical shape, such as Lake Biwa, the elliptical cylinder showed better reproducibility than the circular cylinder. These findings have significant implications for the rapid estimation of internal wave periods using the frequency equation. Full article

(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)

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26 pages, 7164 KiB

Open AccessArticle

Evapotranspiration Partitioning in Selected Subtropical Fruit Tree Orchards Based on Sentinel 2 Data Using a Light Gradient-Boosting Machine (LightGBM) Learning Model in Malelane, South Africa

by Prince Dangare, Zama E. Mashimbye, Paul J. R. Cronje, Joseph N. Masanganise, Shaeden Gokool, Zanele Ntshidi, Vivek Naiken, Tendai Sawunyama and Sebinasi Dzikiti

Hydrology 2025, 12(7), 189; https://doi.org/10.3390/hydrology12070189 - 11 Jul 2025

Abstract

The accurate estimation of evapotranspiration (

E T

) and its components are vital for water resource management and irrigation planning. This study models tree transpiration (

T

) and

E T

for grapefruit, litchi, and mango orchards using light gradient-boosting machine (LightGBM) [...] Read more.

The accurate estimation of evapotranspiration (

E T

) and its components are vital for water resource management and irrigation planning. This study models tree transpiration (

T

) and

E T

for grapefruit, litchi, and mango orchards using light gradient-boosting machine (LightGBM) optimized using the Bayesian hyperparameter optimization. Grounds

T

and

E T

for these crops were measured using the heat ratio method of monitoring sap flow and the eddy covariance technique for quantifying

E T

. The Sentinel 2 satellite was used to compute field leaf area index (

L A I

). The modelled data were used to partition the orchard

E T

into beneficial (

T

) and non-beneficial water uses (orchard floor evaporation—

E_{s}

). We adopted the 10-fold cross-validation to test the model robustness and an independent validation to test performance on unseen data. The 10-fold cross-validation and independent validation on

E T

and

T

models produced high accuracy with coefficient of determination (

R^{2}

)

\geq

0.88, Kling–Gupta efficiency (

K G E

)

\geq

0.91, root mean square error (

R M S E

)

\leq

0.04 mm/h, and mean absolute error (

M A E

)

\leq

0.03 mm/h for all the crops. The study demonstrates that LightGBM can accurately model the transpiration and evapotranspiration for subtropical tree crops using Sentinel 2 data. The study found that

E_{s}

which combined soil evaporation and understorey vegetation transpiration contributed 35, 32, and 31% to the grapefruit, litchi and mango orchard evapotranspiration, respectively. We conclude that improvements on orchard floor management practices can be utilized to minimize non-beneficial water losses while promoting the productive water use (

T

). Full article

(This article belongs to the Special Issue GIS Modelling of Evapotranspiration with Remote Sensing)

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19 pages, 10696 KiB

Open AccessArticle

Dynamics of Nocturnal Evapotranspiration in a Dry Region of the Chinese Loess Plateau: A Multi-Timescale Analysis

by Fengnian Guo, Dengfeng Liu, Shuhong Mo, Qiang Li, Fubo Zhao, Mingliang Li and Fiaz Hussain

Hydrology 2025, 12(7), 188; https://doi.org/10.3390/hydrology12070188 - 10 Jul 2025

Abstract

Evapotranspiration (ET) is an important part of agricultural water consumption, yet little is known about nocturnal evapotranspiration (ETN) patterns. An eddy covariance system was used to observe ET over five consecutive years (2020–2024) during the growing season in a [...] Read more.

Evapotranspiration (ET) is an important part of agricultural water consumption, yet little is known about nocturnal evapotranspiration (ETN) patterns. An eddy covariance system was used to observe ET over five consecutive years (2020–2024) during the growing season in a dry farming area of the Loess Plateau. Daytime and nocturnal evapotranspiration were partitioned using the photosynthetically active radiation threshold to reveal the changing characteristics of ETN at multiple time scales and its control variables. The results showed the following: (1) In contrast to the non-significant trend in ETN on the diurnal and daily scales, monthly ETN dynamics exhibited two peak fluctuations during the growing season. (2) The contribution of ETN to ET exhibited seasonal characteristics, being relatively low in summer, with interannual variations ranging from 10.9% to 14.3% and an annual average of 12.8%. (3) The half-hourly ETN, determined by machine learning methods, was driven by a combination of factors. The main driving factors were the difference between surface temperature and air temperature (Ts-Ta) and net radiation (Rn), which have almost equivalent contributions. Regression analysis results suggested that Ta was the main factor influencing ETN/ET at the monthly scale. This study focuses on the nighttime water loss process in dry farming fields in Northwest China, and the results provide a basis for rational allocation and efficient utilization of agricultural water resources in arid regions. Full article

(This article belongs to the Section Hydrology–Climate Interactions)

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19 pages, 13316 KiB

Open AccessArticle

Mapping of Closed Depressions in Karst Terrains: A GIS-Based Delineation of Endorheic Catchments in the Alburni Massif (Southern Apennine, Italy)

by Libera Esposito, Guido Leone, Michele Ginolfi, Saman Abbasi Chenari and Francesco Fiorillo

Hydrology 2025, 12(7), 186; https://doi.org/10.3390/hydrology12070186 - 10 Jul 2025

Abstract

A deep interaction between groundwater and surface hydrology characterizes karst environments. These settings feature closed depressions, whose hydrological role varies depending on whether they have genetic and hydraulic relationships with overland–subsurface flow (epigenic) or deep groundwater circulation (hypogenic). Epigenic dolines and poljes are [...] Read more.

A deep interaction between groundwater and surface hydrology characterizes karst environments. These settings feature closed depressions, whose hydrological role varies depending on whether they have genetic and hydraulic relationships with overland–subsurface flow (epigenic) or deep groundwater circulation (hypogenic). Epigenic dolines and poljes are among the diagnostic landforms of karst terrains. In this study, we applied a hydrological criterion to map closed depressions—including dolines—across the Alburni karst massif, in southern Italy. A GIS-based, semi-automatic approach was employed, combining the sink-filling method (applied to a 5 m DEM) with the visual interpretation of various informative layers. This process produced a raster representing the location and depth of karst closed depressions. This raster was then used to automatically delineate endorheic areas using classic GIS tools. The resulting map reveals a thousand dolines and hundreds of adjacent endorheic areas. Endorheic areas form a complex mosaic across the massif, a feature that had been poorly emphasized in previous works. The main morphometric features of the dolines and endorheic areas were statistically analyzed and compared with the structural characteristics of the massif. The results of the proposed mapping approach provide valuable insights for groundwater management, karst area protection, recharge modeling, and tracer test planning. Full article

(This article belongs to the Special Issue Advances in Catchments Hydrology and Sediment Dynamics (Second Edition))

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15 pages, 2181 KiB

Open AccessArticle

The Impact of Shifts in Both Precipitation Pattern and Temperature Changes on River Discharge in Central Japan

by Bing Zhang, Jingyan Han, Jianbo Liu and Yong Zhao

Hydrology 2025, 12(7), 187; https://doi.org/10.3390/hydrology12070187 - 9 Jul 2025

Abstract

Rivers play a crucial role in the hydrological cycle and serve as essential freshwater resources for both human populations and ecosystems. Climate change significantly alters precipitation patterns and river discharge variability. However, the impact of precipitation patterns (rainfall and snowfall) and air temperature [...] Read more.

Rivers play a crucial role in the hydrological cycle and serve as essential freshwater resources for both human populations and ecosystems. Climate change significantly alters precipitation patterns and river discharge variability. However, the impact of precipitation patterns (rainfall and snowfall) and air temperature on river discharge in coastal zones remains inadequately understood. This study focused on Toyama Prefecture, located along the Sea of Japan, as a representative coastal area. We analyzed over 30 years of datasets, including air temperature, precipitation, snowfall, and river discharge, to assess the effects of climate change on river discharge. Trends in hydroclimatic datasets were assessed using the rescaled adjusted partial sums (RAPS) method and the Mann–Kendall (MK) non-parametric test. Furthermore, a correlation analysis and the Structural Equation Model (SEM) were applied to construct a relationship between precipitation, temperature, and river discharge. Our findings indicated a significant increase in air temperature at a rate of 0.2 °C per decade, with notable warming observed in late winter (January and February) and early spring (March). The average river fluxes for the Jinzu, Oyabe, Kurobe, Shou, and Joganji rivers were 182.52 m³/s, 60.37 m³/s, 41.40 m³/s, 38.33 m³/s, and 18.72 m³/s, respectively. The tipping point for snowfall decline occurred in 1992, marked by an obvious decrease in snowfall depth. The SEM showed that, although rainfall dominated the changes in river discharge (loading = 0.94), the transition from solid (snow) to liquid (rain) precipitation may alter the river discharge regime. The percentage of flood occurrence increased from 19% (1940–1992) to 41% (1993–2020). These changes highlight the urgent need to raise awareness about the impacts of climate change on river floods and freshwater resources in global coastal regions. Full article

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14 pages, 1711 KiB

Open AccessArticle

Using Machine Learning to Develop a Surrogate Model for Simulating Multispecies Contaminant Transport in Groundwater

by Thu-Uyen Nguyen, Heejun Suk, Ching-Ping Liang, Yu-Chieh Ho and Jui-Sheng Chen

Hydrology 2025, 12(7), 185; https://doi.org/10.3390/hydrology12070185 - 8 Jul 2025

Abstract

Traditional numerical models have been widely employed to simulate the transport of multispecies reactive contaminants in groundwater systems; however, their high computational cost limits their applicability in real-time or large-scale scenarios. Recent advances in artificial intelligence (AI) offer promising alternatives, particularly data-driven machine [...] Read more.

Traditional numerical models have been widely employed to simulate the transport of multispecies reactive contaminants in groundwater systems; however, their high computational cost limits their applicability in real-time or large-scale scenarios. Recent advances in artificial intelligence (AI) offer promising alternatives, particularly data-driven machine learning techniques, for accelerating such simulations. This study presents the development of a surrogate model based on artificial neural networks (ANNs) to simulate the transport and decay of interacting multispecies contaminants in groundwater. High-fidelity training datasets are generated through finite difference-based reactive transport simulations across a wide range of environmental and geochemical conditions. The ANN model is trained to learn the complex nonlinear relationships governing the multispecies transport and transformation processes. Model validation reveals that the ANN surrogate accurately reproduces the spatial–temporal concentration profiles of both original and degradation species, capturing key dynamic behaviors with high precision. Notably, the ANN model achieves up to a 100-fold reduction in computational time compared to traditional analytical or semi-analytical solutions. These results highlight the ANN’s potential as an efficient and accurate surrogate modeling tool for groundwater contamination assessment, offering a valuable advancement for decision-making in environmental risk analysis and remediation planning. Full article

(This article belongs to the Topic Advances in Groundwater Science and Engineering)

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