Journal Description
Hydrology
Hydrology
is an international, peer-reviewed, open access journal on hydrology published monthly online by MDPI. The American Institute of Hydrology (AIH) and Japanese Society of Physical Hydrology (JSPH) are affiliated with Hydrology and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), PubAg, GeoRef, and other databases.
- Journal Rank: JCR - Q2 (Water Resources) / CiteScore - Q1 (Earth-Surface Processes)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.8 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.1 (2023);
5-Year Impact Factor:
3.0 (2023)
Latest Articles
Effects of Forest Logging Systems on the River Flow Regime Indices Using Graphical Techniques: A Case Study in a Small Natural Forest
Hydrology 2024, 11(7), 94; https://doi.org/10.3390/hydrology11070094 - 28 Jun 2024
Abstract
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This study aims to investigate the impact of forest exploitation methods on monthly discharge and hydrological indices of river flow using graphical methods in a forested watershed in North Iran. To achieve this, 10 hydrological index changes related to river flow regime influenced
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This study aims to investigate the impact of forest exploitation methods on monthly discharge and hydrological indices of river flow using graphical methods in a forested watershed in North Iran. To achieve this, 10 hydrological index changes related to river flow regime influenced by the Shelterwood/clear cutting, Femel cutting, and the Near Nature approach forest cutting methods were assessed. According to the results, it can be stated that the Shelterwood/clear cutting method influenced monthly flow indices by increasing the coefficient of variations and intensifying runoff production, while the Femel cutting and the Near Nature approach methods contributed to regulating the flow regime and sustaining river flow. The influence of various tree-cutting techniques on river flow values and fluctuations is more evident during the wettest months compared to low-water months. The period of Shelterwood/clear cutting disrupted the natural correlation between precipitation and runoff production. Furthermore, the shift from Shelterwood/clear cutting to Femel cutting and the Near Nature approach progressively diminished the slope of the curve, indicating a reduction in monthly runoff at both measurement stations. In conclusion, opting for an appropriate method, such as the Near Nature approach, is preferable from both ecological and hydrological perspectives when managing forest areas in the study region and similar conditions involving comparable topography, climate, soil, and forest stands. The index-based coupled with graphical methodology employed appropriately demonstrates the influence of logging techniques on monthly flow patterns, which provides valuable insights into evaluating the repercussions of alternative management interventions on river flow dynamics.
Full article
Open AccessArticle
Analysis of Landscape Pattern Evolution and Impact Factors in the Mainstream Basin of the Tarim River from 1980 to 2020
by
Lili Jiang and Yating Li
Hydrology 2024, 11(7), 93; https://doi.org/10.3390/hydrology11070093 - 27 Jun 2024
Abstract
The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river
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The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River.
Full article
Open AccessReview
Integrating Remote Sensing Methods for Monitoring Lake Water Quality: A Comprehensive Review
by
Anja Batina and Andrija Krtalić
Hydrology 2024, 11(7), 92; https://doi.org/10.3390/hydrology11070092 - 26 Jun 2024
Abstract
Remote sensing methods have the potential to improve lake water quality monitoring and decision-making in water management. This review discusses the use of remote sensing methods for monitoring and assessing water quality in lakes. It explains the principles of remote sensing and the
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Remote sensing methods have the potential to improve lake water quality monitoring and decision-making in water management. This review discusses the use of remote sensing methods for monitoring and assessing water quality in lakes. It explains the principles of remote sensing and the different methods used for retrieving water quality parameters in complex waterbodies. The review highlights the importance of considering the variability of optically active parameters and the need for comprehensive studies that encompass different seasons and time frames. The paper addresses the specific physical and biological parameters that can be effectively estimated using remote sensing, such as chlorophyll-α, turbidity, water transparency (Secchi disk depth), electrical conductivity, surface salinity, and water temperature. It further provides a comprehensive summary of the bands, band combinations, and band equations commonly used for remote sensing of these parameters per satellite sensor. It also discusses the limitations of remote sensing methods and the challenges associated with satellite systems. The review recommends integrating remote sensing methods using in situ measurements and computer modelling to improve the understanding of water quality. It suggests future research directions, including the importance of optimizing grid selection and time frame for in situ measurements by combining hydrodynamic models with remote sensing retrieval methods, considering variability in water quality parameters when analysing satellite imagery, the development of advanced technologies, and the integration of machine learning algorithms for effective water quality problem-solving. The review concludes with a proposed workflow for monitoring and assessing water quality parameters in lakes using remote sensing methods.
Full article
(This article belongs to the Special Issue Hydrodynamics and Water Quality of Rivers and Lakes)
Open AccessArticle
Reference Evapotranspiration in Climate Change Scenarios in Mato Grosso, Brazil
by
Marlus Sabino, Andréa Carvalho da Silva, Frederico Terra de Almeida and Adilson Pacheco de Souza
Hydrology 2024, 11(7), 91; https://doi.org/10.3390/hydrology11070091 - 26 Jun 2024
Abstract
Our understanding of spatiotemporal variability in reference evapotranspiration (ETo) and its long-term trends is of paramount importance for water cycle studies, modeling, and water resource management, especially in the context of climate change. Therefore, the primary aim of this study is to critically
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Our understanding of spatiotemporal variability in reference evapotranspiration (ETo) and its long-term trends is of paramount importance for water cycle studies, modeling, and water resource management, especially in the context of climate change. Therefore, the primary aim of this study is to critically evaluate the performance of various CMIP5 global climate models in simulating the Penman–Monteith reference evapotranspiration and its associated climate variables (maximum and minimum air temperature, incident solar radiation, relative humidity, and wind speed). This evaluation is based on data from nine climate models and 33 automatic meteorological stations (AWSs) in the state of Mato Grosso, spanning the period 2007–2020, within the areas of the biomes Amazon and Cerrado and around the Pantanal biome. The statistical metrics used for evaluation include bias, root mean square error, and Pearson and Spearman correlation coefficients. The projections of the most accurate model were then used to analyze the spatial and temporal changes and trends in ETo under the Representative Concentration Pathways (RCPs) of 2.6, 4.5, and 8.5 scenarios from 2007 to 2100. The HadGEM2-ES model projections indicate static averages similar to current conditions until the end of the century in the RCP 2.6 scenario. However, in the RCP 4.5 and 8.5 scenarios, there is a continuous increase in ETo, with the most significant increase occurring during the dry period (May to September). The areas of the Amazon biome in the north of Mato Grosso exhibit the largest increases in ETo when comparing the observed (2007–2020) and projected (2020–2100) averages. The trend analysis reveals significant changes in ETo and its variables across the state of Mato Grosso in the RCP 4.5 and 8.5 scenarios. In the RCP 2.6 scenario, significant trends in ETo are observed only in the northern Amazon areas. Despite not being observed in all AWSs, the trend analysis of the observed data demonstrates more intense changes in ETo and the existence of the evapotranspiration paradox, with an increase in the Cerrado areas and reductions in the Pantanal and southern Amazon areas.
Full article
(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables)
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Open AccessArticle
A Modified Xinanjiang Model for Quantifying Streamflow Components in a Typical Watershed in Eastern China
by
Kaibin Wu, Minpeng Hu, Yu Zhang, Jia Zhou and Dingjiang Chen
Hydrology 2024, 11(7), 90; https://doi.org/10.3390/hydrology11070090 - 25 Jun 2024
Abstract
An accurate quantification of flow components and an understanding of water source dynamics are essential for effective water resource and quality management. However, the complexity of hydrological processes and the interference of intensive human activities pose significant challenges in precisely separating water discharge
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An accurate quantification of flow components and an understanding of water source dynamics are essential for effective water resource and quality management. However, the complexity of hydrological processes and the interference of intensive human activities pose significant challenges in precisely separating water discharge into distinct components such as surface runoff, interflow, and groundwater. The Xinanjiang (XAJ) model, a conceptual watershed hydrological model, has been developed and successfully implemented for rainfall–runoff simulations and hydrograph separations across various Chinese watersheds. While the model framework is robust, it fails to account for agricultural irrigation water withdrawals and the variations in in-stream water travel times across different hydrological regimes, introducing considerable uncertainty in simulating low-flow conditions. This study introduced modifications to the XAJ model by allowing parameter adjustments across different flow regimes and incorporating irrigation withdrawals into the runoff routing process. Utilizing a decade of hydrometeorological data (2013–2022) from the Yongan River watershed in eastern China, the modified model demonstrated improved efficiency metrics in low- and medium-flow regimes compared to the original model, with a Nash–Sutcliffe coefficient improvement from −4.43~−0.49 to 0.40~0.46, R2 from 0.21~0.36 to 0.53~0.63, and BIAS reduction from 7.60~89.08% to 2.06~12.71%. Furthermore, the modified XAJ model provided a more accurate estimation of the spatial and temporal distribution of streamflow components across sub-watersheds. The original model tended to overestimate groundwater contributions (13%) and underestimate interflow (14%), particularly in low-flow conditions. The enhanced XAJ model, thus, offers a more effective tool for identifying streamflow components, providing essential insights into hydrological processes for better management decisions.
Full article
Open AccessArticle
Performance Evaluation of Regression-Based Machine Learning Models for Modeling Reference Evapotranspiration with Temperature Data
by
Maria J. Diamantopoulou and Dimitris M. Papamichail
Hydrology 2024, 11(7), 89; https://doi.org/10.3390/hydrology11070089 - 21 Jun 2024
Abstract
In this study, due to their flexibility in forecasting, the capabilities of three regression-based machine learning models were explored, specifically random forest regression (RFr), generalized regression neural network (GRNN), and support vector regression (SVR). The above models were assessed for their suitability in
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In this study, due to their flexibility in forecasting, the capabilities of three regression-based machine learning models were explored, specifically random forest regression (RFr), generalized regression neural network (GRNN), and support vector regression (SVR). The above models were assessed for their suitability in modeling daily reference evapotranspiration (ETo), based only on temperature data (Tmin, Tmax, Tmean), by comparing their daily ETo results with those estimated by the conventional FAO 56 PM model, which requires a broad range of data that may not be available or may not be of reasonable quality. The RFr, GRNN, and SVR models were subjected to performance evaluation by using statistical criteria and scatter plots. Following the implementation of the ETo models’ comparisons, it was observed that all regression-based machine learning models possess the capability to accurately estimate daily ETo based only on temperature data requirements. In particular, the RFr model outperformed the others, achieving the highest R value of 0.9924, while the SVR and GRNN models had R values of 0.9598 and 0.9576, respectively. Additionally, the RFr model recorded the lowest values in all error metrics. Once these regression-based machine learning models have been successfully developed, they will have the potential to serve as effective alternatives for estimating daily ETo, under current and climate change conditions, when temperature data are available. This information is crucial for effective water resources management and especially for predicting agricultural production in the context of climate change.
Full article
(This article belongs to the Special Issue GIS Modelling of Evapotranspiration with Remote Sensing)
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Open AccessArticle
Determination of Contaminant Transport Parameters for a Local Aquifer by Numerical Modeling of Two Plumes: Trichloroethylene and Hexavalent Chromium
by
Mahade Ibn Salam, Brian Waldron, Scott Schoefernacker and Farhad Jazaei
Hydrology 2024, 11(7), 88; https://doi.org/10.3390/hydrology11070088 - 21 Jun 2024
Abstract
The municipal wellfield in Collierville, Tennessee, is contaminated with trichloroethylene (TCE) and hexavalent chromium (Cr (VI)) due to industrial operations dating back to the 1970s and 1980s. This study aims to elucidate the aquifer’s contaminant transport mechanisms by determining longitudinal and transverse dispersivities
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The municipal wellfield in Collierville, Tennessee, is contaminated with trichloroethylene (TCE) and hexavalent chromium (Cr (VI)) due to industrial operations dating back to the 1970s and 1980s. This study aims to elucidate the aquifer’s contaminant transport mechanisms by determining longitudinal and transverse dispersivities through inverse modeling. Utilizing MT3DMS for contaminant transport simulation, based on a well-calibrated groundwater flow model, and leveraging Python’s multiprocessing library for efficiency, the study employs a trial-and-error methodology. Key findings reveal that longitudinal dispersivity values range from 5.5 m near the source to 20.5 m further away, with horizontal and vertical transverse dispersivities between 0.28 m and 3.88 m and between 0.03 m and 0.08 m, respectively. These insights into the aquifer’s dispersivity coefficients, which reflect the scale-dependent nature of longitudinal dispersivity, are crucial for optimizing remediation strategies and achieving cleanup goals. This study underscores the importance of accurate parameter estimation in contaminant transport modeling and contributes to a better understanding of contaminant dynamics in the Collierville wellfield.
Full article
(This article belongs to the Special Issue Groundwater Pollution: Sources, Mechanisms, and Prevention)
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Open AccessArticle
Estimating Drainage from Forest Water Reclamation Facilities Based on Drain Gauge Measurements
by
Madeline Schwarzbach, Erin S. Brooks, Robert Heinse, Eureka Joshi and Mark D. Coleman
Hydrology 2024, 11(6), 87; https://doi.org/10.3390/hydrology11060087 - 20 Jun 2024
Abstract
A growing human population requires sustainable solutions to regulate and dispose of municipal wastewater. Water treatment facilities in northern Idaho are permitted to apply reclaimed wastewater to forest land during the growing season at specified monthly hydraulic loading rates. We assessed the spatial
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A growing human population requires sustainable solutions to regulate and dispose of municipal wastewater. Water treatment facilities in northern Idaho are permitted to apply reclaimed wastewater to forest land during the growing season at specified monthly hydraulic loading rates. We assessed the spatial and temporal variability of drainage below the rooting zone between non-irrigated (control) and irrigated (effluent) stands during the growing and dormant seasons in 2021. No drainage was observed during the two months of annual seasonal drought, but large magnitudes of drainage were recorded during the dormant season (38–94 cm), which was consistent with seasonal precipitation. The overall effect of effluent treatment on the drain gauge measurements did not differ from the controls, as effluent only increased the drainage at some facilities. The measured drainage averaged from 35 to 62 cm among facilities. We then used the drainage measurements to calibrate hydrological models (Hydrus-1D and Water Erosion Prediction Project [WEPP]) and predict the drainage in 50 measurement plots distributed evenly among five forest water reclamation facilities. As with the observed drainage, there were no statistically significant growing season differences in the predicted monthly drainage during the growing season between the effluent and control plots, suggesting the successful use of hydrologic models to support the measured drainage findings. While both models struggled to accurately predict the quantity of drainage during the dormant season, they both successfully predicted that drainage would continue through May. WEPP also successfully predicted that the treated plots began to drain in September and October following late-season irrigation at some facilities. The models showed that the prescribed crop coefficient used by the Idaho Department of Environmental Quality was adequate in avoiding drainage during the peak summer months.
Full article
(This article belongs to the Section Water Resources and Risk Management)
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Open AccessArticle
Modeling the Impacts of Sea Level Rise Scenarios on the Amazon River Estuary
by
Jonathan Luz P. Crizanto, Carlos Henrique M. de Abreu, Everaldo B. de Souza and Alan C. da Cunha
Hydrology 2024, 11(6), 86; https://doi.org/10.3390/hydrology11060086 - 20 Jun 2024
Abstract
The rise in the global mean sea level (MSL) is a significant consequence of climate change, attributed to both natural and anthropogenic forces. This phenomenon directly affects the dynamic equilibrium of Earth’s oceanic and estuarine ecosystems, particularly impacting the Amazon estuary. In this
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The rise in the global mean sea level (MSL) is a significant consequence of climate change, attributed to both natural and anthropogenic forces. This phenomenon directly affects the dynamic equilibrium of Earth’s oceanic and estuarine ecosystems, particularly impacting the Amazon estuary. In this study, a numerical model was employed to investigate the long-term impacts of MSL fluctuations on key hydrodynamic parameters crucial to regional environmental dynamics. Our investigation was based on scenarios derived from Representative Concentration Pathways (RCPs) and Coupled Model Intercomparison Project Phase 5 (CMIP5) projections, incorporating MSL variations ranging from 30 to 150 cm above the current mean level. Following careful calibration and validation procedures, which utilized observational and in situ data, notably from field expeditions conducted in 2019, our simulations unveiled significant impacts on certain hydrodynamic parameters. Specifically, we observed a pronounced increase in diurnal tidal amplitude (p < 0.05) within the upstream sections of the North and South channels. Additionally, discernible alterations in water renewal rates throughout the estuary were noted, persisting for approximately 2 days during the dry season (p < 0.05). These findings provide valuable insights into the vulnerability of key parameters to hydrologic instability within the Amazonian coastal region. In conclusion, this study represents a pivotal scientific endeavor aimed at enhancing the preservation of aquatic ecosystems and advancing the environmental knowledge of the Lower Amazon River, with the goal of proactively informing measures to safeguard the current and future sustainability of these vital ecosystems.
Full article
(This article belongs to the Special Issue Climate Change Effects on Coastal Management)
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Open AccessArticle
Water Uptake by Mountain Big Sagebrush (Artemisia tridentata subsp. vaseyana) and Environmental Variables Affecting Water Availability in Semiarid Rangeland Ecosystems
by
Carlos G. Ochoa, Mohamed A. B. Abdallah and Daniel G. Gómez
Hydrology 2024, 11(6), 85; https://doi.org/10.3390/hydrology11060085 - 19 Jun 2024
Abstract
The sagebrush steppe ecosystem plays a critical role in water cycling in arid and semiarid landscapes of the western United States; yet, there is limited information regarding individual sagebrush plant water uptake. We used the stem heat balance (SHB) method to measure transpiration
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The sagebrush steppe ecosystem plays a critical role in water cycling in arid and semiarid landscapes of the western United States; yet, there is limited information regarding individual sagebrush plant water uptake. We used the stem heat balance (SHB) method to measure transpiration in mountain big sagebrush (Artemisia tridentata subsp. vaseyana) plants in a semiarid rangeland ecosystem in central Oregon, Pacific Northwest Region, USA. We evaluated the relationship between sagebrush transpiration and environmental factors from July 2022 to May 2023 for two individual plants representative of the average sagebrush stand height and crown width at the study site; transpiration rates varied by plant and by season. This study encompassed one below-average (2022; 278 mm) and one above-average (2023; 414 mm) precipitation years. Study results showed that the average water use during the entire period of study was 2.1 L d−1 for Plant 1 and 5.0 L d−1 for Plant 2. During the dry year, maximum transpiration was observed during the summer (Plant 1 = 4.8 L d−1; Plant 2 = 11.1 L d−1). For the wet year, both plants showed maximum transpiration levels at the end of the recording period in mid-May (Plant 1 = 9.6 L d−1; Plant 2 = 8.6 L d−1). The highest seasonal transpiration of both plants occurred in summer (2.87 L d−1), whereas the lowest transpiration was obtained in winter (0.21 L d−1). For all seasons but winter, soil moisture (SM), soil temperature (ST), and vapor pressure deficit (VPD) variables generally showed positive correlations with transpiration. Transpiration rates decreased in the summer of 2022 as the surface soil gradually dried. The two plants’ most significant water uptake differences were obtained during the dry year. It is possible that the larger stem diameter of plant 2 may have contributed to its higher transpiration rates during times of limited water availability. The study results add to the understanding of water use by sagebrush and its potential impact on the water balance of cool-climate rangeland ecosystems. The findings also highlight the sensitivity of sagebrush to variations in seasonal soil moisture availability, soil temperature, and vapor pressure deficit. Future research should involve studying the combined effects of water use by various dominant vegetation species and its effects on the water budget at the watershed scale.
Full article
(This article belongs to the Special Issue Climate Change and Human-Induced Changes on Hydrological and Fluvial Process)
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Open AccessArticle
Assessment and Mitigation of Groundwater Contamination from Phosphate Mining in Tunisia: Geochemical and Radiological Analysis
by
Younes Hamed, Matteo Gentilucci, Naziha Mokadem, Rayan Khalil, Yosra Ayadi, Riheb Hadji and Elimame Elaloui
Hydrology 2024, 11(6), 84; https://doi.org/10.3390/hydrology11060084 - 17 Jun 2024
Abstract
Groundwater contamination in the Mediterranean Basin is a severe problem that has a significant impact on environmental ecosystems and human health. The unconventional uranium and the potentially toxic elements (PTEs) of phosphate rocks are the principal contaminants in the phosphate mining industry in
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Groundwater contamination in the Mediterranean Basin is a severe problem that has a significant impact on environmental ecosystems and human health. The unconventional uranium and the potentially toxic elements (PTEs) of phosphate rocks are the principal contaminants in the phosphate mining industry in Tunisia. Phosphogypsum (PG) results from the valorization of phosphate to fertilizers and phosphoric acid. PG stocks can be used in cement production, brick manufacturing, and soil amendments in desertic land, and can be resolved by using nanomaterial adsorbents. In the flat area of the study area, the increase in radioactivity (40K) is due to abusive fertilizer use. Geochemical and radiological analyses in the northern part of Tunisia and its karst shallow aquifer indicate significant contamination levels. The northern part exhibits moderate contamination, whereas the karst shallow aquifer shows higher contamination levels, particularly with elevated nitrate concentrations. In the phosphate basin, both washing phosphate and phosphogypsum reveal high levels of radioactive elements, with the latter showing especially high concentrations of radium. The shallow aquifer in this region has moderate contamination levels, while the deep geothermal aquifer also shows noticeable contamination but to a lesser degree compared to the shallow aquifer. The shallow groundwater is characterized by a higher value of radioactivity than the groundwater due to the contamination impact from the phosphate industry and the cumulative radioactivity disintegration. Finally, the nanoparticles and the electrostatic adsorption can decrease the PTEs and radionuclides from the contaminated water in the study area. Moreover, other key issues for advancing research on groundwater contamination are proposed in this study. It is time to valorize this PG and the other mines of (Fe, Pb, and Zn) in the socioeconomic sector in Tunisia and to minimize the environmental impact of the industrial sector’s extraction on groundwater and human health in the study area.
Full article
(This article belongs to the Special Issue Novel Approaches in Contaminant Hydrology and Groundwater Remediation)
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Open AccessArticle
Climate Change Projections of Potential Evapotranspiration for the North American Monsoon Region
by
Eylon Shamir, Lourdes Mendoza Fierro, Sahar Mohsenzadeh Karimi, Norman Pelak, Emilie Tarouilly, Hsin-I Chang and Christopher L. Castro
Hydrology 2024, 11(6), 83; https://doi.org/10.3390/hydrology11060083 - 14 Jun 2024
Abstract
We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed
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We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes.
Full article
(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)
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Open AccessArticle
Anthropogenic Activity in the Topo-Climatic Interaction of the Tapajós River Basin, in the Brazilian Amazon
by
Vânia dos Santos Franco, Aline Maria Meiguins de Lima, Rodrigo Rafael Souza de Oliveira, Everaldo Barreiros de Souza, Giordani Rafael Conceição Sodré, Diogo Correa Santos, Marcos Adami, Edivaldo Afonso de Oliveira Serrão and Thaiane Soeiro da Silva Dias
Hydrology 2024, 11(6), 82; https://doi.org/10.3390/hydrology11060082 - 13 Jun 2024
Abstract
This research aimed to analyze the relationship between deforestation (DFT) and climatic variables during the rainy (CHU+) and less-rainy (CHU−) seasons in the Tapajós River basin. Data were sourced from multiple institutions, including the Climatic Research Unit (CRU), Center for Weather Forecasts and
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This research aimed to analyze the relationship between deforestation (DFT) and climatic variables during the rainy (CHU+) and less-rainy (CHU−) seasons in the Tapajós River basin. Data were sourced from multiple institutions, including the Climatic Research Unit (CRU), Center for Weather Forecasts and Climate Studies (CPTEC), PRODES Program (Monitoring of Brazilian Amazon Deforestation Project), National Water Agency (ANA) and National Centers for Environmental Prediction/National Oceanic and Atmospheric Administration (NCEP/NOAA). The study assessed anomalies (ANOM) in maximum temperature (TMAX), minimum temperature (TMIN) and precipitation (PREC) over three years without the occurrence of the El Niño–Southern Oscillation (ENSO) atmospheric–oceanic phenomenon. It also examined areas with higher DFT density using the Kernel methodology and analyzed the correlation between DFT and climatic variables. Additionally, it assessed trends using the Mann–Kendall technique for both climatic and environmental data. The results revealed significant ANOM in TEMP and PREC. In PREC, the highest values of ANOM were negative in CHU+. Regarding temperature, the most significant values were positive ANOM in the south, southwest and northwestern regions of the basin. Concerning DFT density, data showed that the highest concentration was of medium density, primarily along the highways. The most significant correlations were found between DFT and TEMP during the CHU− season in the Middle and Lower Tapajós sub-basins, regions where the forest still exhibits more preserved characteristics. Furthermore, the study identified a positive trend in TEMP and a negative trend in PREC.
Full article
(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables)
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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
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.
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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.
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(This article belongs to the Topic Hydrology and Water Resources Management)
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Open AccessArticle
The Use of Unmanned Aerial Systems for River Monitoring: A Bibliometric Analysis Covering the Last 25 Years
by
Alonso Pizarro, Desirée Valera-Gran, Eva-María Navarrete-Muñoz and Silvano Fortunato Dal Sasso
Hydrology 2024, 11(6), 80; https://doi.org/10.3390/hydrology11060080 - 7 Jun 2024
Abstract
Cutting-edge technology for fluvial monitoring has revolutionised the field, enabling more comprehensive data collection, analysis, and interpretation. Traditional monitoring methods were limited in their spatial and temporal resolutions, but advancements in remote sensing, unmanned aerial systems (UASs), and other innovative technologies have significantly
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Cutting-edge technology for fluvial monitoring has revolutionised the field, enabling more comprehensive data collection, analysis, and interpretation. Traditional monitoring methods were limited in their spatial and temporal resolutions, but advancements in remote sensing, unmanned aerial systems (UASs), and other innovative technologies have significantly enhanced the fluvial monitoring capabilities. UASs equipped with advanced sensors enable detailed and precise fluvial monitoring by capturing high-resolution topographic data, generate accurate digital elevation models, and provide imagery of river channels, banks, and riparian zones. These data enable the identification of erosion and deposition patterns, the quantification of sediment transport, the evaluation of habitat quality, and the monitoring of river flows. The latter allows us to understand the dynamics of rivers during various hydrological events, including floods, droughts, and seasonal variations. This manuscript aims to provide an update on the main research themes and topics in the literature on the use of UASs for river monitoring. The latter is achieved through a bibliometric analysis of the publication trends and identifies the field’s key themes and collaborative networks. The bibliometric analysis shows trends in the number of publications, number of citations, top contributing countries, top publishing journals, top contributing institutions, and top authors. A total of 1085 publications on UAS monitoring in rivers are identified, published between 1999 and 2023, showing a steady annual growth rate of 24.44%. Bibliographic records are exported from the Web of Science (WoS) database using a comprehensive set of keywords. The bibliometric analysis of the raw data obtained from the WoS database is performed using the R software. The results highlight important trends and valuable insights related to the use of UASs in river monitoring, particularly in the last decade. The most frequently used author keywords outline the core themes of UASs monitoring research and highlight the interdisciplinary nature and collaborative efforts within the field. “River”, “topography”, “photogrammetry”, and “Structure-from-Motion” are the core themes of UASs monitoring research. These findings can guide future research and promote new interdisciplinary collaborations.
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(This article belongs to the Special Issue UAS and Satellite-Based Remote Sensing for Hydrological Observations and Applications)
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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
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
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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.
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Open AccessArticle
Land-Use–Land Cover Changes in the Urban River’s Buffer Zone and Variability of Discharge, Water, and Sediment Quality—A Case of Urban Catchment of the Ngerengere River in Tanzania
by
Silaji S. Mbonaga, Amina A. Hamad and Stelyus L. Mkoma
Hydrology 2024, 11(6), 78; https://doi.org/10.3390/hydrology11060078 - 31 May 2024
Abstract
The physical integrity of the Ngerengere River and its three tributaries drains within Morogoro Municipality were evaluated by assessing the variations in land-use–land cover (LULC) in the river’s buffer zone, the discharge, and the contamination of river water and sediment from nutrients and
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The physical integrity of the Ngerengere River and its three tributaries drains within Morogoro Municipality were evaluated by assessing the variations in land-use–land cover (LULC) in the river’s buffer zone, the discharge, and the contamination of river water and sediment from nutrients and heavy metals. Integrated geospatial techniques were used to classify the LULC in the river’s buffer zone. In contrast, the velocity area method and monitoring data from the Wami-Ruvu Basin were used for the discharge measurements. Furthermore, atomic absorption spectrophotometry was used during the laboratory analysis to determine the level of nutrients and heavy metals in the water and river sediment across the 13 sampling locations. The LULC assessment in the river’s buffer during the sampling year of 2023 showed that bare land and built-up areas dominate the river’s buffer, with a coverage of 28% and 38% of the area distribution. The higher discharge across the sampling stations was in the upstream reaches at 3.73 m3/s and 2.36 m3/s at the confluences. The highest concentrations of heavy metals in the water for the dry and wet seasons were 0.09 ± 0.01, 0.25 ± 0.01, 0.03 ± 0.02, 0.73 ± 0.04, 4.07 ± 0.08, and 3.07 ± 0.04 mg/L, respectively, for Pb, Cr, Cd, Cu, Zn, and Ni. The order of magnitude of the heavy metal concentration in the sediments was Zn > Ni > Cr > Cu > Cd > Pb, while the highest NO2−, NO3−, NH3, and PO43− in the water and sediment were 2.05 ± 0.01, 0.394 ± 0.527, 0.66 ± 0.05, and 0.63 ± 0.01 mg/L, and 2.64 ± 0.03, 0.63 ± 0.01, 2.36 ± 0.01, and 48.16 ± 0.01 mg/kg, respectively, across all sampling seasons. This study highlights the significant impact of urbanization on river integrity, revealing elevated levels of heavy metal contamination in both water and sediment, the variability of discharge, and alterations in the LULC in the rivers’ buffer. This study recommends the continuous monitoring of the river water quality and quantity of the urban rivers, and the overall land-use plans for conserving river ecosystems.
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(This article belongs to the Special Issue Advances in Catchments Hydrology and Sediment Dynamics)
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Open AccessArticle
Trend Analysis of Hydro-Meteorological Variables in the Wadi Ouahrane Basin, Algeria
by
Mohammed Achite, Tommaso Caloiero, Andrzej Wałęga, Alessandro Ceppi and Abdelhak Bouharira
Hydrology 2024, 11(6), 77; https://doi.org/10.3390/hydrology11060077 - 31 May 2024
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In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity,
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In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen’s slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors.
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Open AccessArticle
Hydrogeochemical Characterization of an Intermontane Aquifer Contaminated with Arsenic and Fluoride via Clustering Analysis
by
José Rafael Irigoyen-Campuzano, Diana Barraza-Barraza, Mélida Gutiérrez, Luis Arturo Torres-Castañón, Liliana Reynoso-Cuevas and María Teresa Alarcón-Herrera
Hydrology 2024, 11(6), 76; https://doi.org/10.3390/hydrology11060076 - 31 May 2024
Abstract
The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na+, K+, Ca2+, Mg2+, F−, Cl
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The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na+, K+, Ca2+, Mg2+, F−, Cl−, SO42−, NO3−, HCO3−, As, pH and electrical conductivity in 40 groundwater samples collected from shallow and deep wells, where As and F− are contaminants of concern. The effectiveness of each hierarchical and k-means clustering method in explaining solute concentrations within the aquifer and the co-occurrence of arsenic and fluoride was tested by comparing two datasets containing samples from 40 and 36 wells, the former including ionic balance outliers (>10%). When tested without outliers, cluster quality improved by about 5.4% for k-means and 7.3% for HCA, suggesting that HCA is more sensitive to ionic balance outliers. Both algorithms yielded similar clustering solutions in the outlier-free dataset, aligning with the k-means solution for all 40 samples, indicating that k-means was the more robust of the two methods. k-means clustering resolved fluoride and arsenic concentrations into four clusters (K1 to K4) based on variations in Na+, Ca2+, As, and F−. Cluster K2 was a Na-HCO3 water type with high concentrations of As and F. Clusters K1, K3, and K4 exhibited a Ca-HCO3, Na-Ca-HCO3, and Ca-Na-HCO3 water types, respectively, with decreasing As and F concentrations following the order K2 > K3 > K1 > K4. The weathering of evaporites and silicates and Na-Ca ion exchange with clays were the main processes controlling groundwater geochemistry. The dissolution of felsic rocks present in the aquifer fill is a likely source of As and F−, with evaporation acting as an important concentration factor.
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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
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
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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.
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