Hydrology

22 pages, 7273 KiB

Open AccessArticle

Hydrological Modelling and Remote Sensing for Assessing the Impact of Vegetation Cover Changes

by Ángela M. Moreno-Pájaro, Aldhair Osorio-Gastelbondo, Dalia A. Moreno-Egel, Oscar E. Coronado-Hernández, María A. Narváez-Cuadro, Manuel Saba and Alfonso Arrieta-Pastrana

Hydrology 2025, 12(5), 107; https://doi.org/10.3390/hydrology12050107 - 29 Apr 2025

Abstract

This study presents a multi-temporal analysis of vegetation cover changes in the Guayepo stream watershed (Cartagena de Indias, Colombia) for 2000, 2010, and 2020 and their impact on surface runoff generation. Hydrological data from 1974 to 2019 were processed to model intensity–duration–frequency (IDF) [...] Read more.

This study presents a multi-temporal analysis of vegetation cover changes in the Guayepo stream watershed (Cartagena de Indias, Colombia) for 2000, 2010, and 2020 and their impact on surface runoff generation. Hydrological data from 1974 to 2019 were processed to model intensity–duration–frequency (IDF) curves and simulate heavy rainfall events using six storms of nine-hour duration. Following the Soil Conservation Service guidelines, these were used to estimate runoff flows for return periods of 25, 50, and 100 years via the curve number method in HEC-HMS. Vegetation cover was assessed using the CORINE land cover methodology applied to official land use maps. The analysis revealed a significant loss of natural vegetation: dense forest cover declined dramatically from 14.38% in 2000 to 0% in 2020, and clean pastures were reduced by 46%. In contrast, weedy pastures and pasture mosaics with natural areas increased by 299% and 136%, respectively, reflecting a shift towards more degraded land cover types. As a result of these changes, total runoff flows of the model increased by 9.7% and 4.3% under antecedent moisture conditions I and II, respectively, for the 100-year return period. These findings reveal ongoing degradation of the watershed’s natural cover, linked to expanding agricultural uses and changes in vegetation structure. The decline in forested areas has increased surface runoff, elevating flood risk and compromising the watershed’s hydrological regulation. The study suggests that integrated land management and ecological restoration strategies could be key in preserving hydrological ecosystem services and reducing the negative impacts of land use change. Full article

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43 pages, 90873 KiB

Open AccessArticle

A Null Space Sensitivity Analysis for Hydrological Data Assimilation with Ensemble Methods

by Nick Martin, Jeremy White and Paul Southard

Hydrology 2025, 12(5), 106; https://doi.org/10.3390/hydrology12050106 - 28 Apr 2025

Abstract

Predictive uncertainty analysis focuses on defensible variability in model projected values after estimation of the posterior parameter distribution. Inverse-style parameter estimation selects posterior parameters through history matching where parameters are varied and resulting model simulation values are compared to observations, and parameters are [...] Read more.

Predictive uncertainty analysis focuses on defensible variability in model projected values after estimation of the posterior parameter distribution. Inverse-style parameter estimation selects posterior parameters through history matching where parameters are varied and resulting model simulation values are compared to observations, and parameters are selected balancing goodness-of-fit between simulated and observed values and expert knowledge. When inverse-style parameter estimation approaches are used, parameter sensitivity, which is the change in simulated outputs relative to the change in parameter values, is an important consideration. Variation in null space parameters has a limited impact on history matching skill; however, these parameters become important when they impact predictions. A new null space sensitivity analysis for ensemble methods of data assimilation (DA) using observation error models is developed and implemented for an integrated hydrological model. Empirical parameter sensitivity is estimated by comparing the spreads of prior and posterior parameter distributions. Sensitivity analysis is generated by an ensemble of models with insensitive parameters varying across the prior parameter distribution and sensitive parameters fixed to best-fit model values. The result is identification of insensitive aquifer storage parameters that change storage-related model predictions by as much as two times. This null space analysis describes uncertainty from data insufficiency. Ensemble methods using observation error models also describe predictive uncertainty from noisy measurements and imperfect models. Full article

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

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16 pages, 21540 KiB

Open AccessArticle

Responses of Terrestrial Water Storage to Climate Change in the Closed Alpine Qaidam Basin

by Liang Chang, Qunhui Zhang, Xiaofan Gu, Rui Duan, Qian Wang and Xiangzhi You

Hydrology 2025, 12(5), 105; https://doi.org/10.3390/hydrology12050105 - 28 Apr 2025

Abstract

Terrestrial water storage (TWS) in the Qaidam Basin in western China is highly sensitive to climate change. The GRACE mascon products provide variations of TWS anomalies (TWSAs), greatly facilitating the exploration of water storage dynamics. However, the main meteorological factors affecting the TWSA [...] Read more.

Terrestrial water storage (TWS) in the Qaidam Basin in western China is highly sensitive to climate change. The GRACE mascon products provide variations of TWS anomalies (TWSAs), greatly facilitating the exploration of water storage dynamics. However, the main meteorological factors affecting the TWSA dynamics in this region need to be comprehensively investigated. In this study, variations in TWSAs over the Qaidam Basin from 2002 to 2024 were analyzed using three GRACE mascon products with CSR, JPL, and GSFC. The groundwater storage anomalies (GWAs) were extracted through GRACE and GLDAS products. The impact of meteorological elements on TWSAs and GWAs was identified. The results showed that the GRACE mascon products showed a significant increasing trend with a rate of 0.51 ± 0.13 mm per month in TWSAs across the entire basin from 2003 to 2016. The groundwater part accounted for the largest proportion and was the main contributor to the increase in TWS for the entire basin. In addition to the dominant role of precipitation, other meteorological elements, particularly air humidity and solar radiation, were also identified as important contributors to TWSA and GWA variations. This study highlighted the climatic effect on water storage variations, which have important implications for local water resource management and ecological conservation under ongoing climate change. Full article

(This article belongs to the Special Issue GRACE Observations for Global Groundwater Storage Analysis)

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19 pages, 5313 KiB

Open AccessArticle

A New Custom Deep Learning Model Coupled with a Flood Index for Multi-Step-Ahead Flood Forecasting

by Jianming Shen, Moyuan Yang, Juan Zhang, Nan Chen and Binghua Li

Hydrology 2025, 12(5), 104; https://doi.org/10.3390/hydrology12050104 - 26 Apr 2025

Abstract

Accurate and prompt flood forecasting is essential for effective decision making in flood control to help minimize or prevent flood damage. We propose a new custom deep learning model, IF-CNN-GRU, for multi-step-ahead flood forecasting that incorporates the flood index (

I_{F}

) [...] Read more.

Accurate and prompt flood forecasting is essential for effective decision making in flood control to help minimize or prevent flood damage. We propose a new custom deep learning model, IF-CNN-GRU, for multi-step-ahead flood forecasting that incorporates the flood index (

I_{F}

) to improve the prediction accuracy. The model integrates convolutional neural networks (CNNs) and gated recurrent neural networks (GRUs) to analyze the spatiotemporal characteristics of hydrological data, while using a custom recursive neural network that adjusts the neural unit output at each moment based on the flood index. The IF-CNN-GRU model was applied to forecast floods with a lead time of 1–5 d at the Baihe hydrological station in the middle reaches of the Han River, China, accompanied by an in-depth investigation of model uncertainty. The results showed that incorporating the flood index

I_{F}

improved the forecast precision by up to 20%. The analysis of uncertainty revealed that the contributions of modeling factors, such as the datasets, model structures, and their interactions, varied across the forecast periods. The interaction factors contributed 17–36% of the uncertainty, while the contribution of the datasets increased with the forecast period (32–53%) and that of the model structure decreased (32–28%). The experiment also demonstrated that data samples play a critical role in improving the flood forecasting accuracy, offering actionable insights to reduce the predictive uncertainty and providing a scientific basis for flood early warning systems and water resource management. Full article

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20 pages, 3878 KiB

Open AccessArticle

Extraction of Major Groundwater Ions from Total Dissolved Solids and Mineralization Using Artificial Neural Networks: A Case Study of the Aflou Syncline Region, Algeria

by Mohammed Elamin Stamboul, Azzaz Habib, Abderrahmane Hamimed, Mousaab Zakhrouf, Il-Moon Chung and Sungwon Kim

Hydrology 2025, 12(5), 103; https://doi.org/10.3390/hydrology12050103 - 25 Apr 2025

Abstract

Global water demand due to population growth and agricultural development has led to widespread overexploitation of groundwater, particularly in semi-arid regions. The traditional hydrochemistry monitoring system still suffers from limited laboratory accessibility and high costs. This study aims to predict the major ions [...] Read more.

Global water demand due to population growth and agricultural development has led to widespread overexploitation of groundwater, particularly in semi-arid regions. The traditional hydrochemistry monitoring system still suffers from limited laboratory accessibility and high costs. This study aims to predict the major ions of groundwater, including Ca²⁺, Mg²⁺, Na⁺, SO₄²⁻, Cl⁻, K⁺, HCO₃⁻, and NO₃⁻, utilizing two field-measurable parameters (i.e., total dissolved solids (TDS) and mineralization (MIN)) in the Aflou syncline region, Algeria. A multilayer perceptron (MLP) model optimized with Levenberg–Marquardt backpropagation (LMBP) provided the greatest predictive accuracy for the different ions of SO₄²⁻, Mg²⁺, Na⁺, Ca²⁺, and Cl⁻ with R² = (0.842, 0.980, 0.759, 0.945, 0.895), RMSE = (53.660, 12.840, 14.960, 36.460, 30.530) (mg/L), and NSE = (0.840, 0.978, 0.754, 0.941, 0.892) in the testing phase, respectively. However, the predictive accuracy for the remaining ions of K⁺, HCO₃⁻, and NO₃⁻ was supplied as R² = (0.045, 0.366, 0.004), RMSE = (6.480, 41.720, 40.460) (mg/L), and NSE = (0.003, 0.361, −0.933), respectively. The performance of our model (LMBP-MLP) was validated in adjacent and similar geological locations, including Aflou, Madna, and Ain Madhi. In addition, LMBP-MLP showed very promising results, with performance similar to that in the original research region. Full article

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

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21 pages, 5045 KiB

Open AccessArticle

Evaluating Water Level Variability Under Different Sluice Gate Operation Strategies: A Case Study of the Long Xuyen Quadrangle, Vietnam

by Dinh Van Duy, Nguyen Thai An, Tran Van Ty, Lam Tan Phat, Ngo Thanh Toan, Huynh Vuong Thu Minh, Nigel K. Downes and Hitoshi Tanaka

Hydrology 2025, 12(5), 102; https://doi.org/10.3390/hydrology12050102 - 23 Apr 2025

Abstract

The Vietnamese Mekong Delta (VMD) faces increasing challenges due to upstream hydrological fluctuations and climate change, necessitating optimized water management strategies. Sluice gates play a critical role in regulating water levels, yet their effectiveness under different operational modes remains insufficiently assessed. This study [...] Read more.

The Vietnamese Mekong Delta (VMD) faces increasing challenges due to upstream hydrological fluctuations and climate change, necessitating optimized water management strategies. Sluice gates play a critical role in regulating water levels, yet their effectiveness under different operational modes remains insufficiently assessed. This study examines water level fluctuations under three sluice gate operation scenarios implemented along the West Sea dike in the Long Xuyen Quadrangle, Kien Giang Province, using the MIKE 11 hydrodynamic model. The model was calibrated and validated using the observed data, yielding high accuracy at key sluice gates, including Kien River and Ba Hon. Three sluice gate management scenarios were tested: (1) the current automatic and partially forced operation, (2) fully automatic gate control, and (3) fully forced hydraulic operation. The simulation results indicate that Scenario 3 maintained water levels above +0.6 m more frequently, ensuring better water availability for irrigation and domestic use, while Scenarios 1 and 2 resulted in lower water levels at certain locations. Additionally, forced operation led to higher gate opening and closing frequencies at key sluices, allowing for more adaptive control over water levels. These findings emphasize the benefits of proactive sluice gate management in improving water regulation and mitigating the water scarcity risks. This study is among the first to provide empirical, scenario-based evidence comparing fully forced, automatic, and mixed sluice gate strategies under varying hydrological conditions in the Long Xuyen Quadrangle. Full article

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

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18 pages, 5765 KiB

Open AccessArticle

River Meanders, Tributary Junctions, and Antecedent Morphology

by Jonathan D. Phillips

Hydrology 2025, 12(5), 101; https://doi.org/10.3390/hydrology12050101 - 22 Apr 2025

Abstract

Tributaries to meandering rivers rarely join the river on the interior of bends. The limited drainage area on bend interiors explains why tributaries seldom form there, but not why existing tributaries are redirected as meanders develop. Other relevant factors include flow dynamics at [...] Read more.

Tributaries to meandering rivers rarely join the river on the interior of bends. The limited drainage area on bend interiors explains why tributaries seldom form there, but not why existing tributaries are redirected as meanders develop. Other relevant factors include flow dynamics at junctions, runoff partitioning on inner vs. outer bends, and tributary deflection as the main channel migrates laterally. This study investigated whether the lack of confluences on bend interiors applies to lower coastal plain rivers in South and North Carolina, USA, where the factors above are not necessarily active, and if so how tributaries at sites of developing meanders are redirected. Of the 121 confluences examined using GIS data supplemented with field observations, none occurred on meander bend interiors. A total of 17 cases of potentially deflected tributaries were identified. Of these, 11 had sufficient evidence for a confident interpretation of how redirection occurred. In all 11 cases, pre-bend river paleochannels were involved in redirecting the tributaries away from the bend interior. This is explained by a model showing that the local slope gradient and mean depth advantages of the paleochannels provide velocity, stream power, and shear stress advantages over extension of the tributary channel into the bend interior. The results illustrate the importance of local hydraulic selection, and the influence of antecedent morphology on river hydrology and geomorphology. Full article

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20 pages, 1702 KiB

Open AccessArticle

Estimation of Hydraulic Properties of Growing Media from Numerical Inversion of Mini Disk Infiltrometer Data

by Hadi Hamaaziz Muhammed, Ruediger Anlauf and Diemo Daum

Hydrology 2025, 12(5), 100; https://doi.org/10.3390/hydrology12050100 - 22 Apr 2025

Abstract

Accurately determining the hydraulic properties of soilless growing media is essential for optimizing water management in container-based horticulture and agriculture. The very rapid estimation of hydraulic properties using a Mini Disk Infiltrometer has great potential for practical use compared to the very time-consuming [...] Read more.

Accurately determining the hydraulic properties of soilless growing media is essential for optimizing water management in container-based horticulture and agriculture. The very rapid estimation of hydraulic properties using a Mini Disk Infiltrometer has great potential for practical use compared to the very time-consuming standard methods. The objectives of this study were (1) to calibrate simulated cumulative stepwise infiltration under different suctions with the measured data from Mini Disk Infiltrometer, (2) to evaluate the efficiency of the Hydrus-2D inverse model to predict water dynamics through substrates, (3) to compare the substrate hydraulic parameters obtained through the numerical inversion model to those obtained via laboratory methods, and (4) to provide recommendations on how to effectively use the MDI-based method for practical applications. This study employs numerical inversion of Mini Disk Infiltrometer (MDI) data to estimate the hydraulic parameters of three different growing media, namely white peat, thermally treated wood fibre (WF4), and Seedling substrate. Infiltration experiments were conducted under suction-controlled conditions using varying initial moisture contents, followed by numerical simulations using the Hydrus-2D model and the Van Genuchten equation to describe the hydraulic parameters. The results demonstrated strong agreement between observed and simulated infiltration data, particularly under moistened conditions, with high R² > 0.9 values indicating the model’s effectiveness. However, discrepancies were observed for substrates in their initial dry state, suggesting limitations in capturing early-stage infiltration dynamics. The findings highlighted the potential of numerical inversion methods for estimating substrate hydraulic properties but also revealed the need for methodological refinements. Modifying the Van Genuchten model or exploring alternative approaches such as the Brooks and Corey model may enhance accuracy. Extending the suction range of measurement techniques is also recommended to improve parameter estimation. This study provides important evidence that the inverse method based on MDI is an effective tool for rapidly determining the hydraulic functions of substrates, which are important in promoting sustainable horticultural practices. Future research should focus on refining parameter estimation methods and addressing model limitations to enhance the reliability of hydraulic property assessments in soilless growing media. Full article

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22 pages, 8440 KiB

Open AccessArticle

Comparison and Prediction of the Ecological Footprint of Water Resources—Taking Guizhou Province as an Example

by Yongtao Wang, Wenfeng Yang, Jian Liu, Enhui Lu, Ye Li and Ning Chen

Hydrology 2025, 12(5), 99; https://doi.org/10.3390/hydrology12050099 - 22 Apr 2025

Abstract

Water resources are considered to be of paramount importance to the natural world on a global scale, being critical for the sustenance of ecosystems, the support of life, and the achievement of sustainable development. However, these resources are under threat from climate change, [...] Read more.

Water resources are considered to be of paramount importance to the natural world on a global scale, being critical for the sustenance of ecosystems, the support of life, and the achievement of sustainable development. However, these resources are under threat from climate change, population growth, urbanization and pollution. This necessitates the development of robust and effective assessment methods to ensure their sustainable use. Although assessing the ecological footprint (EF) of urban water systems plays a critical role in advancing sustainable cities and managing water assets, existing research has largely overlooked the application of geospatial visualization techniques in evaluating resource allocation strategies within karst mountain watersheds, an oversight this study aims to correct through innovative methodological integration. This research establishes an evaluation framework for predicting water resource availability in Guizhou through the synergistic application of three methodologies: (1) the water-based ecological accounting framework (WEF), (2) ecosystem service thresholds defined by the water ecological carrying capacity of water resources (WECC) thresholds, and (3) composite sustainability metrics, all correlated with contemporary hydrological utilization profiles. Spatiotemporal patterns were quantified across the province’s nine administrative divisions during the 2013–2022 period through time-series analysis, with subsequent WEF projections for 2023–2027 generated via Long Short-Term Memory (LSTM) temporal forecasting techniques. Full article

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30 pages, 6041 KiB

Open AccessReview

Global Perspectives on Groundwater Decontamination: Advances and Challenges of the Role of Permeable Reactive Barriers

by Graciela Cecilia Sánchez Hidalgo, Jessie Ábrego-Bonilla, Euclides Deago and Maria De Los Angeles Ortega Del Rosario

Hydrology 2025, 12(4), 98; https://doi.org/10.3390/hydrology12040098 - 21 Apr 2025

Abstract

Ensuring access to clean water for drinking, agriculture, and recreational activities remains a global challenge. Groundwater, supplying approximately 50% of domestic water and 40% of agricultural irrigation, faces increasing threats from climate change, population growth, and unsustainable agricultural practices. These factors contribute to [...] Read more.

Ensuring access to clean water for drinking, agriculture, and recreational activities remains a global challenge. Groundwater, supplying approximately 50% of domestic water and 40% of agricultural irrigation, faces increasing threats from climate change, population growth, and unsustainable agricultural practices. These factors contribute to groundwater contamination, notably nitrate pollution resulting from excessive fertilizer use, which poses risks to water quality and public health. Addressing this issue demands innovative, efficient, and sustainable remediation technologies. Permeable reactive barriers (PRBs) have emerged as promising solutions for in situ groundwater treatment, using reactive media to transform contaminants into less toxic forms. PRBs offer advantages like low energy consumption and minimal maintenance. This study uses bibliometric analysis to explore the scientific production of PRBs for nitrate remediation, revealing research trends, key focus areas, and significant contributions. It included 141 articles published from 1975 to 2023. Early research focused on basic mechanisms and materials like zero-valent iron (ZVI), while recent studies emphasize sustainability and cost-effectiveness using low-cost materials such as agricultural byproducts. The findings highlight a growing focus on the circular economy and the need for more in situ studies to assess PRB performance under varying conditions. PRBs show significant potential for enhancing groundwater management and long-term water quality in agricultural contexts. Full article

(This article belongs to the Special Issue Groundwater Pollution: Sources, Mechanisms, and Prevention (Second Edition))

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25 pages, 14713 KiB

Open AccessReview

From Flood Mitigation to Environmental and Socioeconomic Disruption: A Case Study of the Langue de Barbarie Sand Spit Breach

by Souleymane Fall

Hydrology 2025, 12(4), 97; https://doi.org/10.3390/hydrology12040097 - 19 Apr 2025

Abstract

In October 2003, an artificial canal was dug across the Langue de Barbarie sand spit at the mouth of the Senegal River to prevent the city of Saint-Louis (Senegal) from being submerged by floods. This study aimed to explore the multiple facets of [...] Read more.

In October 2003, an artificial canal was dug across the Langue de Barbarie sand spit at the mouth of the Senegal River to prevent the city of Saint-Louis (Senegal) from being submerged by floods. This study aimed to explore the multiple facets of this sudden environmental change to provide a holistic overview of the situation and a better understanding of man-made alterations of coastal features, a crucial step for implementing efficient management of such situations and developing appropriate mitigation and adaptation policies. Satellite imagery from the US Geological Survey was used to show the historical evolution of the breach, and a comprehensive overview of the existing literature was conducted to explore its hydrological, geomorphological, ecological, and socioeconomic impacts. Although the canal facilitated the rapid evacuation of floodwaters and saved the city from a major flooding event, the breach widened considerably, becoming the new river mouth and resulted in unforeseen adverse consequences. Environmental consequences included the partial dismantling of the spit, increased tidal range, salinization of land and water, and loss of habitat and local biodiversity. Socioeconomic consequences were severe, including the loss of agricultural land and reduced yields, declining fishing productivity, the destruction of villages, the displacement of entire communities, and the forced migration of many young people. Affected communities developed resilience strategies, with women playing a leading role in these adaptive responses. This study highlights the need for integrated coastal management and policies that consider both environmental and human factors, as well as for future research that will help improve the management of coastal ecosystem alterations. Full article

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

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14 pages, 4599 KiB

Open AccessArticle

Towards a Classification of Tunisian Dams for Enhanced Water Scarcity Governance: Parametric or Non-Parametric Approaches?

by Safouane Mouelhi, Sabri Kanzari, Sana Ben Mariem and Nesrine Zemni

Hydrology 2025, 12(4), 96; https://doi.org/10.3390/hydrology12040096 - 18 Apr 2025

Abstract

Classifying dams is important to ensure proper management, safety, and maintenance based on their size, purpose, and risk level. This helps in planning for emergency responses, structural inspections, and efficient water resource utilization. This study used the analysis of variance (ANOVA) technique to [...] Read more.

Classifying dams is important to ensure proper management, safety, and maintenance based on their size, purpose, and risk level. This helps in planning for emergency responses, structural inspections, and efficient water resource utilization. This study used the analysis of variance (ANOVA) technique to categorize the main Tunisian dams according to their precipitation to potential evapotranspiration (P/PET) ratio. The data were obtained from the NASA POWER platform, with potential evapotranspiration estimated using the Oudin model. Despite the violation of the normality assumption, the robustness of the ANOVA test for classification purposes remained unaffected. A comparison between Duncan’s test (parametric) and the Kruskal–Wallis test (non-parametric) revealed similar class structures, although Duncan’s test provided greater precision. The analysis identified four primary dam classes, reflecting regional differences in water availability and evaporative demand, and included dams in north-west Tunisia, considered the ‘water tower’ of the country, and those in semi-arid and arid regions. Full article

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23 pages, 1120 KiB

Open AccessReview

Leaky Dams as Nature-Based Solutions in Flood Management Part I: Introduction and Comparative Efficacy with Conventional Flood Control Infrastructure

by Umanda Hansamali, Randika K. Makumbura, Upaka Rathnayake, Hazi Md. Azamathulla and Nitin Muttil

Hydrology 2025, 12(4), 95; https://doi.org/10.3390/hydrology12040095 - 17 Apr 2025

Abstract

Natural flood management strategies are increasingly recognized as sustainable alternatives to conventional engineered flood control measures. Among these, leaky dams, also known as woody debris dams or log dams, have emerged as effective nature-based solutions for mitigating flood risks while preserving essential ecosystem [...] Read more.

Natural flood management strategies are increasingly recognized as sustainable alternatives to conventional engineered flood control measures. Among these, leaky dams, also known as woody debris dams or log dams, have emerged as effective nature-based solutions for mitigating flood risks while preserving essential ecosystem services. This review traces the historical evolution of leaky dams from ancient water management practices to contemporary applications, highlighting their development and adaptation over time. It presents a comparative examination of leaky dams and conventional flood control structures, outlining their respective strengths and limitations across ecological, hydrological, and economic dimensions. The review also introduces a conceptual classification of leaky dams into naturally occurring, engineered, hybrid, and movable systems, showing how each form aligns with varying catchment characteristics and management objectives. By synthesizing foundational knowledge and strategic insights, this paper establishes a theoretical and contextual framework for understanding leaky dams as distinct yet complementary tools in integrated flood management, laying the groundwork for further technical evaluations. The findings offer valuable insights for end users by highlighting the potential of leaky dams as integral components of sustainable flood management systems, elucidating their roles in mitigating flood risks, enhancing water retention, and supporting ecosystem resilience. Full article

(This article belongs to the Special Issue Advances in Nature-Based Solutions for Hydrometeorological Risk Reduction)

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27 pages, 3344 KiB

Open AccessArticle

Runoff Variations and Quantitative Analysis in the Qinghai Lake Basin Under Changing Environments

by Li Mo, Xinxiao Yu, Yonghan Feng and Tao Jiang

Hydrology 2025, 12(4), 94; https://doi.org/10.3390/hydrology12040094 - 17 Apr 2025

Abstract

This study examines runoff variations and their drivers in the Buha and Shaliu Rivers of the Qinghai Lake Basin (1960–2016), a key ecological area in China. Abrupt changes were detected using the Mann–Kendall and cumulative anomaly methods, while the Budyko framework attributed runoff [...] Read more.

This study examines runoff variations and their drivers in the Buha and Shaliu Rivers of the Qinghai Lake Basin (1960–2016), a key ecological area in China. Abrupt changes were detected using the Mann–Kendall and cumulative anomaly methods, while the Budyko framework attributed runoff variations to dominant factors. Correlation and grey relational analyses assessed multicollinearity, and a lake water balance model with climate elasticity theory quantified the effects of climate and land surface changes on runoff components and lake levels. Results indicate that the Buha River experienced an abrupt runoff change in 2004, while the Shaliu River exhibited a change beginning in 2003. Based on the trends and abrupt change points of each factor, the study period was divided into four segments: 1960–1993, 1994–2016, 1960–2003, and 2004–2016. The correlation coefficients are significantly different in different periods. The climate elasticity coefficients were as follows: P (precipitation), 1.98; ET₀ (potential evapotranspiration), −0.98; Rn (net radiation), 0.66; T (average temperature), 0.02; U₂ (wind speed at 2 m height), 0.16; RHU (relative umidity), −0.56. The elasticity coefficient of runoff with respect to precipitation is significantly higher than that for other climate variables. Net radiation and relative humidity contribute equally to runoff, while wind speed and temperature have relatively smaller effects. In the Qinghai Lake Basin, runoff is sensitive to precipitation (0.38), potential evapotranspiration (−0.07), and the underlying surface parameter ω (−98.32). Specifically, a 1 mm increase in precipitation raises runoff by 0.38 mm, while a 1 mm rise in potential evapotranspiration reduces it by 0.07 mm. A one-unit increase in ω leads to a significant runoff decrease of 98.32 mm. According to the lake water balance model, climate contributes 88.43% to groundwater runoff, while land surface changes contribute −11.57%. Climate change and land surface changes contribute 93.02% and 6.98%, respectively, to lake water levels. This study quantitatively evaluates the impacts of climate and land surface changes on runoff, providing insights for sustainable hydrological and ecological management in the Qinghai Lake Basin. Full article

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30 pages, 10990 KiB

Open AccessArticle

Numerical Modeling of the Concentration of Microplastics in Lakes and Rivers in Kazakhstan

by Natalya S. Salikova, María-Elena Rodrigo-Clavero, Lyudmila A. Makeyeva, Zinep M. Shaimerdenova and Javier Rodrigo-Ilarri

Hydrology 2025, 12(4), 93; https://doi.org/10.3390/hydrology12040093 - 16 Apr 2025

Abstract

This research presents a detailed numerical modeling study focused on estimating the concentration of microplastics (MPs) in freshwater ecosystems. This research covers three lakes (Kopa, Zerendinskoye, and Borovoe) and the Yesil River, applying differential equations to model the spatial distribution and seasonal variations [...] Read more.

This research presents a detailed numerical modeling study focused on estimating the concentration of microplastics (MPs) in freshwater ecosystems. This research covers three lakes (Kopa, Zerendinskoye, and Borovoe) and the Yesil River, applying differential equations to model the spatial distribution and seasonal variations in MP concentrations. The methodology integrates field survey data collected during three different seasons (spring, summer, and autumn) from both sediment and water samples. The MP concentrations were found to follow an exponential decay pattern from the shore toward the center of the lakes, with higher concentrations near the shoreline. The modeling framework is calibrated using regression analysis, which provides the best-fit parameters for the distance–concentration curves. This study employs sensitivity analysis to justify the decay coefficient, resulting in a selected value of k = 0.09. Model performance is assessed using statistical metrics such as the root mean square error (RMSE) and the coefficient of determination (R²), ensuring accuracy in predicting MP concentrations across different environmental compartments. This work represents a novel contribution to the field by applying numerical modeling techniques to an understudied geographical area. The findings highlight significant seasonal and spatial variations in MP concentrations, emphasizing the need for comprehensive monitoring. This study’s results contribute valuable insights into the environmental behavior of MPs in freshwater systems and support efforts to develop effective management strategies to mitigate pollution. Full article

(This article belongs to the Special Issue Recent Research Advances in Microplastics in Water and the Environment)

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19 pages, 12753 KiB

Open AccessArticle

Impact Assessment of Floating Photovoltaic Systems on the Water Quality of Kremasta Lake, Greece

by Angeliki Mentzafou, Elias Dimitriou, Ioannis Karaouzas and Stamatis Zogaris

Hydrology 2025, 12(4), 92; https://doi.org/10.3390/hydrology12040092 - 16 Apr 2025

Abstract

Floating photovoltaic systems (FPV) are one of the emerging technologies that are able to support the “green” energy transition. In Greece, the environmental impact assessment of such projects is still under early development. The scope of the present study was to provide insights [...] Read more.

Floating photovoltaic systems (FPV) are one of the emerging technologies that are able to support the “green” energy transition. In Greece, the environmental impact assessment of such projects is still under early development. The scope of the present study was to provide insights into the potential impacts of a small-scale FPV system on the water quality of the oligotrophic Kremasta Lake, an artificial reservoir. For this reason, a hydrodynamic and water quality model was employed. The results showed that the water quality parameter variations were insignificant and limited only in the immediate area of the FPV construction and gradually disappeared toward the shoreline. Likewise, this variation was restricted to the first few meters of depth of the water column and was eliminated onwards. The water temperature slightly decreased only in the area of close proximity to the installation. Average annual dissolved oxygen, chlorophyll-a, and nutrient concentrations were predicted not to change considerably after the panels’ construction. FPV systems can provide an attractive alternative for energy production in artificial reservoirs, especially in regions of land use conflicts that are associated with land allocation for alternative energy development. Given the limited data on the long-term impact of such projects, robust monitoring programs are essential. These initiatives rely on public support, making collaboration between stakeholders and the local community crucial. Full article

(This article belongs to the Special Issue Novel Procedures and Methodologies for Surface and Underground Water Quality Analysis: Theory and Application)

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25 pages, 699 KiB

Open AccessReview

Leaky Dams as Nature-Based Solutions in Flood Management Part II: Mechanisms, Effectiveness, Environmental Impacts, Technical Challenges, and Emerging Trends

by Umanda Hansamali, Randika K. Makumbura, Upaka Rathnayake, Hazi Md. Azamathulla and Nitin Muttil

Hydrology 2025, 12(4), 91; https://doi.org/10.3390/hydrology12040091 - 16 Apr 2025

Abstract

Leaky dams have become essential nature-based solutions for flood management, providing sustainable alternatives to traditional engineered flood control methods. This review delves into the mechanisms by which leaky dams operate, including the regulation of water flow through velocity reduction and distribution across floodplains, [...] Read more.

Leaky dams have become essential nature-based solutions for flood management, providing sustainable alternatives to traditional engineered flood control methods. This review delves into the mechanisms by which leaky dams operate, including the regulation of water flow through velocity reduction and distribution across floodplains, effective sediment trapping and soil quality enhancement, and the facilitation of groundwater recharge and water table stabilization. These structures not only mitigate peak flood flows and reduce erosion but also contribute to enhanced biodiversity by creating diverse aquatic habitats and maintaining ecological connectivity. The effectiveness of leaky dams is assessed through various performance metrics, demonstrating significant reductions in peak flows, improved sediment management, and increased groundwater levels, which collectively enhance ecosystem resilience and water quality. However, the implementation of leaky dams presents several technical challenges, such as design complexity, hydrological variability, maintenance requirements, and socio-economic factors like land use conflicts and economic viability. Additionally, while leaky dams offer numerous environmental benefits, potential negative impacts include habitat disruption, sediment accumulation, and alterations in water quality, which necessitate careful planning and adaptive management strategies. Emerging trends in leaky dam development focus on the integration of smart technologies, such as real-time monitoring systems and artificial intelligence, to optimize performance and resilience against climate-induced extreme weather events. Advances in modeling and monitoring technologies are facilitating the effective design and implementation of leaky dam networks, promoting their incorporation into comprehensive watershed management frameworks. This review highlights the significant potential of leaky dams as integral components of sustainable flood management systems, advocating for their broader adoption alongside conventional engineering solutions to achieve resilient and ecologically balanced water management. Full article

(This article belongs to the Special Issue Advances in Nature-Based Solutions for Hydrometeorological Risk Reduction)

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24 pages, 3748 KiB

Open AccessArticle

Leveraging Recurrent Neural Networks for Flood Prediction and Assessment

by Elnaz Heidari, Vidya Samadi and Abdul A. Khan

Hydrology 2025, 12(4), 90; https://doi.org/10.3390/hydrology12040090 - 16 Apr 2025

Abstract

Recent progress in Artificial Intelligence and Machine Learning (AIML) has accelerated improvements in the prediction performance of many hydrological processes. Yet, flood prediction remains a challenging task due to its complex nature. Two common challenges afflicting the task are flood volatility and the [...] Read more.

Recent progress in Artificial Intelligence and Machine Learning (AIML) has accelerated improvements in the prediction performance of many hydrological processes. Yet, flood prediction remains a challenging task due to its complex nature. Two common challenges afflicting the task are flood volatility and the sensitivity and complexity of flood generation attributes. This study explores the application of Recurrent Neural Networks (RNNs)—specifically Vanilla Recurrent Neural Networks (VRNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)—in flood prediction and assessment. By integrating catchment-specific hydrological and meteorological variables, the RNN models leverage sequential data processing to capture the temporal dynamics and seasonal patterns characteristic of flooding. These models were employed across diverse terrains, including mountainous watersheds in the state of South Carolina, USA, to examine their robustness and adaptability. To identify significant hydrological events for flash flood analysis, a discharge frequency analysis was conducted using the Pearson Type III distribution. The 1-year and 2-year return period flows were estimated based on this analysis, and the 1-year return flow was selected as a conservative threshold for flash flood event identification to ensure a sufficient number of training instances. Comparative benchmarking with the National Water Model (NWM v3.0) revealed that the RNN-based approaches offer notable enhancements in capturing the intensity and timing of flood events, particularly for short-duration and high-magnitude floods (flash floods). Comparison of predicted disharges with the discharge recorded at the gauges revealed that GRU had the best performance as it achieved the highest mean NSE values and exhibited low variability across diverse watersheds. LSTM results were slightly less consistent compared to the GRU albeit achieving satisfactory performance, proving its value in hydrological forecasting. In contrast, VRNN had the highest variability and the lowest NSE values among the three. The NWM model trailed the machine learning-based models. The study highlights the efficacy of the RNN models in advancing hydrological predictions. Full article

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

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22 pages, 4147 KiB

Open AccessArticle

Evaluation of the Extreme Precipitation and Runoff Flow Characteristics in a Semiarid Sub-Basin Based on Three Satellite Precipitation Products

by Rosalía López Barraza, María Teresa Alarcón Herrera, Ana Elizabeth Marín Celestino, Armando Daniel Blanco Jáquez and Diego Armando Martínez Cruz

Hydrology 2025, 12(4), 89; https://doi.org/10.3390/hydrology12040089 - 15 Apr 2025

Abstract

In this study, we analyzed the suitability of using the CHIRPS, CMORPH and TRMM platforms in monitoring extreme precipitation events, precipitation–runoff relationships, and seasonal/year-to-year variability in the Saltito semiarid sub-basin in the Mexican state of Durango. Satellite precipitation products (SPP) in 16 sites [...] Read more.

In this study, we analyzed the suitability of using the CHIRPS, CMORPH and TRMM platforms in monitoring extreme precipitation events, precipitation–runoff relationships, and seasonal/year-to-year variability in the Saltito semiarid sub-basin in the Mexican state of Durango. Satellite precipitation products (SPP) in 16 sites were contrasted point to point with data from rainfall gauge stations and with a daily temporal resolution for the period of four years (2015–2019). Using this information, we constructed Rx1d, Rx2d, R25mm, and RR95 extreme rainfall indices. For the precipitation–runoff relationships, a runoff model based on the Storm Water Management Model (SWMM) was calibrated and validated with gauge data, and we obtained the Qx1d, Qx2d, and Qx3d runoff indices. We used the bias volume (%), MSE, correlation coefficient, and median bias to evaluate the ability of satellite products to detect and analyze extreme precipitation and run flow events. Although these sensors tend to overestimate both precipitation levels and the occurrence of extreme precipitation events, their high spatial and temporal resolutions make them a reliable tool for the analysis of trends in climate change indices. As a result, they serve as a useful resource in evaluating the intensity of climate change in the region, particularly in terms of precipitation patterns. They also allow hydrological modeling and the observation of precipitation–runoff relationships. This is relevant in the absence of precipitation and hydrometric information, which is usually common in vast regions of the developing world. Full article

(This article belongs to the Section Hydrological Measurements and Instrumentation)

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