Hydrology

19 pages, 3934 KB

Open AccessArticle

Evaluating the Influence of Terracing Induced Modifications of Runoff Patterns on Soil Redistribution Using In Situ ¹³⁷Cs Measurements with a LaBr₃ Scintillation Detector

by Leticia Gaspar and Ana Navas

Hydrology 2026, 13(4), 118; https://doi.org/10.3390/hydrology13040118 - 21 Apr 2026

Viewed by 265

Abstract

In subhumid Mediterranean agroecosystems, runoff drives soil erosion by controlling particle detachment and transport, with its generation and connectivity strongly influenced by land use. In areas affected by land abandonment and reforestation, terracing modifies hillslope morphology and flow pathways, thereby altering soil redistribution [...] Read more.

In subhumid Mediterranean agroecosystems, runoff drives soil erosion by controlling particle detachment and transport, with its generation and connectivity strongly influenced by land use. In areas affected by land abandonment and reforestation, terracing modifies hillslope morphology and flow pathways, thereby altering soil redistribution patterns. Fallout ¹³⁷Cs has been widely used to assess medium term soil redistribution, and in situ gamma ray spectrometry using scintillation detectors provides an alternative for improving spatial coverage, yet the influence of factors specific to the site on measurements remains insufficiently explored. This study investigates how ¹³⁷Cs counts obtained in situ with a LaBr₃ detector can be used to interpret soil redistribution patterns in two paired catchments that experienced land abandonment since the mid-1960s. Following abandonment, catchment A underwent natural revegetation, whereas catchment B was terraced for reforestation, allowing the effects of water erosion and terracing on soil mobilisation to be analyzed through the spatial distribution of ¹³⁷Cs. By linking ¹³⁷Cs counts with catchment physiography, land use, flow pathways, and NDVI, the study aims to identify the main controls on soil redistribution in both catchments. ¹³⁷Cs counts were significantly higher in catchment A (156.8 ± 108.2 counts) than in catchment B (53.2 ± 68.1), with coefficients of variation of 69% and 128%, respectively. The in situ ¹³⁷Cs measurements provide reliable indicators of soil redistribution patterns controlled not only by runoff but also by anthropogenic modifications of hillslope morphology that alter flow pathways and hydrological connectivity following terracing. The paired catchment approach, combined with in situ ¹³⁷Cs measurements, provides valuable insights into the key controls on soil redistribution, which is essential for effective land management. Full article

(This article belongs to the Special Issue The Influence of Landscape Disturbance on Catchment Processes)

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25 pages, 7615 KB

Open AccessArticle

Regional Copula Modeling of Rainfall Duration and Intensity: Derivation and Validation of IDF Curves in the Kastoria Basin

by Evangelos Leivadiotis, Aris Psilovikos and Silvia Kohnová

Hydrology 2026, 13(4), 117; https://doi.org/10.3390/hydrology13040117 - 20 Apr 2026

Viewed by 536

Abstract

Intensity–Duration–Frequency (IDF) curves are the cornerstone of hydraulic infrastructure design, yet standard methodologies often fail to account for the complex dependence structure of rainfall characteristics and the non-stationary effects of climate change. This study develops a robust Regional Copula Framework for the Kastoria [...] Read more.

Intensity–Duration–Frequency (IDF) curves are the cornerstone of hydraulic infrastructure design, yet standard methodologies often fail to account for the complex dependence structure of rainfall characteristics and the non-stationary effects of climate change. This study develops a robust Regional Copula Framework for the Kastoria Lake basin, Greece, utilizing sub-hourly rainfall records from four meteorological stations (2007–2024). We employ a forensic data quality control process to pool 277 independent storm events. Unlike traditional approaches, our analysis demonstrates that the Generalized Extreme Value (GEV) distribution (ξ = 0.348) significantly outperforms the standard Lognormal distribution in modeling heavy-tailed rainfall intensities. The dependence between storm duration and intensity was found to be consistently negative (τ = −0.35), a structure best captured by the Rotated Gumbel (90°) copula, which physically reflects the region’s convective storm dynamics. Trend analysis revealed a statistically significant decrease in peak intensity (τ = −0.14) coupled with an increase in storm duration (τ = 0.22), a hydro-climatic shift that contrasts with increasing intensity trends reported in the wider Balkan region. These findings suggest a regime transition from flash-flood dominance to volume-critical events, necessitating updated design criteria that integrate both multivariate dependence and local climatic non-stationarity. Full article

(This article belongs to the Special Issue Integrated Approaches to Hydraulic and Sediment Transport Modeling for Flood Risk Management Using Advanced Models, Remote Sensing, GIS, and IoT)

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15 pages, 5925 KB

Open AccessArticle

Development of the Boundary Water Level Method: A New Approach for Continuous Flow Monitoring in Open Channels

by Marin Paladin, Josip Paladin and Dijana Oskoruš

Hydrology 2026, 13(4), 116; https://doi.org/10.3390/hydrology13040116 - 18 Apr 2026

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Abstract

This research develops a new low-cost method for continuous flow monitoring in open channels. Flow is calculated using a standard 1D hydraulic model that integrates surveyed cross-sections and water level measurements at the boundaries of a studied reach, from which the name Boundary [...] Read more.

This research develops a new low-cost method for continuous flow monitoring in open channels. Flow is calculated using a standard 1D hydraulic model that integrates surveyed cross-sections and water level measurements at the boundaries of a studied reach, from which the name Boundary Water Level Method (BWLM) is derived. By implementing low-cost ultrasonic sensors for water level measurement, the method gains advantage for application on smaller channels, which are often not included in national hydrological monitoring networks due to limited budgets. New and innovative monitoring methods in hydrology are a necessary alternative to increasing the monitoring budgets, especially for continuous, real-time flow monitoring. Like any novel method, it requires validation under the intended environmental conditions, especially when designed primarily for ungauged channels. Validation was conducted on two test-sites by comparing the BWLM discharge and the discharge from official hydrological stations, with an error of up to 15%. BWLM provides reliable discharges using estimated hydraulic roughness values based on the literature and experience. Sensitivity analysis of the estimated hydraulic roughness coefficient demonstrated a substantial influence on the resulting discharge values. This has to be considered when implementing the method in unstudied basins. Full article

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

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22 pages, 8095 KB

Open AccessArticle

Long-Term Spatiotemporal Dynamics of Snow Cover in the Arys River Basin (Western Tien Shan)

by Asyma Koshim, Zhassulan Takibayev, Abror Gafurov, Aida Munaitpassova, Damir Kanatkaliyev, Aktoty Bekzhanova, Aidar Zhumalipov and Zhanerke Sharapkhanova

Hydrology 2026, 13(4), 115; https://doi.org/10.3390/hydrology13040115 - 17 Apr 2026

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Abstract

Seasonal snow cover in mountainous regions represents a critical natural freshwater reserve for arid and semi-arid areas of Central Asia. This study evaluates the long-term (2000–2024) spatiotemporal dynamics of snow cover in the Arys River basin, located within the Western Tien Shan. The [...] Read more.

Seasonal snow cover in mountainous regions represents a critical natural freshwater reserve for arid and semi-arid areas of Central Asia. This study evaluates the long-term (2000–2024) spatiotemporal dynamics of snow cover in the Arys River basin, located within the Western Tien Shan. The research utilizes daily satellite data from MODIS Terra and Aqua, along with data from the MODSNOW automated processing system. Terra-Aqua composite imagery was employed to minimize cloud cover effects. Satellite-derived estimates were validated against observational data from five meteorological stations of the Republican State Enterprise (RSE) “Kazhydromet”. The results indicate significant interannual variability in snow cover extent: the snow-covered area during the cold season ranged from 16.2% to 54.1%, with a mean value of 34.4%. Trend analysis revealed a weak negative trend, while Sen’s slope estimator showed an average annual reduction in snow cover area of 0.37% per year. The most pronounced decline in snow accumulation was observed in mid-elevation mountain zones. These findings suggest potential increased risks to seasonal water availability in the Arys River basin and, more broadly, across the Syr Darya basin under ongoing climate change conditions. The results provide a scientific basis for quantifying climate impacts and developing adaptation strategies for integrated water resources management in Central Asia. Full article

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21 pages, 3975 KB

Open AccessArticle

Multi-Objective Calibration of a Pre-Modern Nile Hydrologic Model Using Recovered Records

by Irenee Felix Munyejuru and James H. Stagge

Hydrology 2026, 13(4), 114; https://doi.org/10.3390/hydrology13040114 - 15 Apr 2026

Viewed by 457

Abstract

Hydrologic models are instrumental in understanding the behavior of the Nile River Basin (NRB), yet their effectiveness is often limited by the basin’s complex hydrology and sparse observational records. This study applies a basin-scale hydrological modeling approach to simulate near-natural, pre-reservoir flow conditions [...] Read more.

Hydrologic models are instrumental in understanding the behavior of the Nile River Basin (NRB), yet their effectiveness is often limited by the basin’s complex hydrology and sparse observational records. This study applies a basin-scale hydrological modeling approach to simulate near-natural, pre-reservoir flow conditions in the NRB, while incorporating lake and wetland submodels. The basin was discretized into 34 sub-watersheds with an outlet at Aswan. The conceptual GR4J rainfall–runoff model was implemented within the Raven modeling framework, chosen for its parsimony and suitability for data-limited conditions. Multi-objective calibration used discharge data from the Global Runoff Data Centre (GRDC), supplemented by digitized historical records to improve spatial and temporal coverage. A stepwise calibration strategy was applied at 18 sites, focusing on pre-reservoir periods to capture natural flow dynamics. The calibrated model reproduces observed discharges with high skill. At the Aswan outlet, Nash–Sutcliffe Efficiency (NSE) values were 0.87 (calibration) and 0.80 (validation), with percent bias (PBIAS) values of 6.1% and 5.0%, respectively. Model performance was strongest in the Blue Nile, White Nile headwaters, and the Nile main stem. The model also successfully simulated the hydrological step-change observed in Lake Victoria during the 1960s, underscoring its robustness in simulating regional hydroclimate disruptions. This calibrated model enables reconstruction of historical Nile discharge and simulation of past hydrologic disturbances, including those driven by major volcanic eruptions over the past millennia. Full article

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

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31 pages, 20257 KB

Open AccessArticle

Research on Recognition of Check Dams Considering Suitable Construction Areas and Microtopography Standard Deviation Based on Faster R-CNN

by Jinjin Shi, Xin Tong, Meng He, Panrui Xia, Xuemian Wei, Xin Sun, Xiaomin Liu, Ping Miao, Haixia Wu and Jiwen Wang

Hydrology 2026, 13(4), 113; https://doi.org/10.3390/hydrology13040113 - 13 Apr 2026

Viewed by 376

Abstract

Accurate spatial identification of check dams is a key prerequisite for evaluating soil and water conservation benefits and optimizing dam system planning on the Loess Plateau. Current deep learning models face severe misclassification and omission issues under complex terrain due to the scarcity [...] Read more.

Accurate spatial identification of check dams is a key prerequisite for evaluating soil and water conservation benefits and optimizing dam system planning on the Loess Plateau. Current deep learning models face severe misclassification and omission issues under complex terrain due to the scarcity of check dam samples and the lack of prior geographic knowledge. This study proposes a recognition method based on Faster R-CNN, constrained by suitable areas and microtopography. The Xiliugou watershed in Inner Mongolia was selected as the study area. Based on Google Earth imagery and field survey data, a check dam sample dataset was constructed, integrating the morphological features of “linear dam body with a trapezoidal slope.” Using the construction suitable area constraints defined by the Technical Specifications for Check Dams and microtopography standard deviation (δ) derived from DEM as dual spatial filtering mechanisms, these were deeply embedded into the Faster R-CNN model to limit the search space and enhance geographic plausibility. Experimental results show that the constrained Faster R-CNN model achieved a precision and recall of 92.86% and 96.89%, compared with the accuracy rate of only deep learning model recognition (60.61%), which significantly increased by 32.25%, indicating that geographical constraints have an enhancing effect. Using this method, a total of 191 embankment dams were identified in the Xiliugou Basin. New 30 unrecorded embankment dams (21 small dams and 9 micro-dams) were discovered. The model’s good generalization ability was verified in the Han Tiechuan geographical isolation area, which contained 153 embankment dam samples, with an accuracy rate of 72.94%. Spatial analysis further revealed the “successive interception along tributaries” distribution pattern and strong spatial aggregation characteristics (box dimension D ≈ 0.36) of check dams in the Xiliugou watershed. This study confirms the critical role of suitable area and microtopography constraints in improving the accuracy and reliability of deep learning models and provides a transferable technical paradigm for automated, high-precision surveys of regional soil and water conservation projects. Full article

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25 pages, 5768 KB

Open AccessArticle

A Study on the Discrimination Criteria and the Formation Mechanism of the Extreme Drought-Runoff in the Yangtze River Basin

by Xuewen Guan, Wei Li, Jianping Bing and Xianyan Chen

Hydrology 2026, 13(4), 112; https://doi.org/10.3390/hydrology13040112 - 10 Apr 2026

Viewed by 339

Abstract

The middle and lower reaches of the Yangtze River Basin occupy a strategically pivotal position in regional development; yet extreme drought-runoff events pose severe threats to water supply and ecological security. Despite this, systematic research gaps persist, including the lack of a unified [...] Read more.

The middle and lower reaches of the Yangtze River Basin occupy a strategically pivotal position in regional development; yet extreme drought-runoff events pose severe threats to water supply and ecological security. Despite this, systematic research gaps persist, including the lack of a unified definition, standardized identification criteria, and clear understanding of formation mechanisms for extreme drought-runoff. To address these limitations, this study focused on extreme drought-runoff in the basin, utilizing 1956–2024 discharge data from four mainstream hydrological stations and meteorological data from 171 stations. Quantitative discrimination criteria were established via Pearson-III frequency analysis; meteorological characteristics were analyzed using the Meteorological Drought Comprehensive Index; and formation mechanisms were explored through partial correlation analysis and multiple linear regression. This study innovatively proposed a basin-wide three-level quantitative discrimination criterion for drought-runoff based on the June–November flow frequency of key mainstream stations, which is distinguished from single-indicator drought identification methods (SPI/SPEI/SSI) by integrating basin-scale hydrological coherence and seasonal drought characteristics. The results revealed basin-wide extreme drought-runoff in 2006 and 2022, severe drought-runoff in 1972 and 2011, and relatively severe drought-runoff in 1959, 1992, and 2024. Typical extreme drought-runoff events were characterized by sustained low precipitation and high temperatures. Meteorological factors emerged as the primary driver during June–September, while reservoir operation and riverine water intake played secondary roles. Notably, the large-scale reservoir group in the Yangtze River Basin (53 key control reservoirs) helped alleviate drought-runoff impacts from December to May (non-flood season) via water supplementation. These findings provide a robust scientific basis for precise drought-runoff prediction and the development of targeted adaptation strategies in the Yangtze River Basin. Full article

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

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22 pages, 10222 KB

Open AccessArticle

Model-Based Evaluation of SUDS Efficiency in Urban Stormwater Management: A Case Study in Montería, Colombia

by Juan Pablo Medrano-Barboza, Luisa Martínez-Acosta, Alberto Flórez Soto, Guillermo J. Acuña, Fausto A. Canales, Rafael David Gómez Vásquez, Diego Armando Ayala Caballero and Suanny Sejin Cogollo

Hydrology 2026, 13(4), 111; https://doi.org/10.3390/hydrology13040111 - 10 Apr 2026

Viewed by 768

Abstract

The rapid growth of cities and expansion of impervious surfaces have intensified surface runoff problems and urban flooding risk. This scenario, exacerbated by the effects of climate change, demands sustainable and integrated solutions. Thus, this study evaluates the pre-feasibility of implementing sustainable urban [...] Read more.

The rapid growth of cities and expansion of impervious surfaces have intensified surface runoff problems and urban flooding risk. This scenario, exacerbated by the effects of climate change, demands sustainable and integrated solutions. Thus, this study evaluates the pre-feasibility of implementing sustainable urban drainage systems (SUDS) in the Monteverde neighborhood in Montería, Colombia; an area that is critically affected by floods during rainfall events. Using the storm water management model (SWMM) and hydrological simulations based on design hyetographs for different return periods, the performance of a conventional drainage system was compared with five scenarios using SUDS. To determine the modeling scenarios, a decision-making method through the analytic hierarchy process, AHP, was used to select the most appropriate SUDS. The results showed that implementing storage tanks reduces peak flows at outlets 1 and 2 up to 50%, while bioretention zones and rain gardens in isolation showed reduced effectiveness (<6%). Combining strategies slightly improves overall efficiency, although the impact keeps being dominated by tanks. This study demonstrates that the incorporation of SUDS in vulnerable urban areas lessens water risks, strengthens urban resilience, promotes rainwater harvesting, and eases the transition to a more sustainable infrastructure. In addition, it proposes a methodology that can be replicated in other similar Latin American cities. Full article

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

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27 pages, 10569 KB

Open AccessArticle

Operational Discharge Severity Analysis and Multi-Horizon Forecasting Based on Reservoir Operation Data: A Case Study of Ba Ha Hydropower Reservoir, Vietnam

by Nguyen Thi Huong, Vo Quang Tuong and Ho Huu Loc

Hydrology 2026, 13(4), 110; https://doi.org/10.3390/hydrology13040110 - 10 Apr 2026

Viewed by 419

Abstract

Reservoir release induced flooding is a major downstream hazard worldwide, yet most warning systems rely on hydraulic modeling and underuse real time reservoir operation data. This study presents a data driven framework to detect flood discharge events, assess downstream operational severity, and forecast [...] Read more.

Reservoir release induced flooding is a major downstream hazard worldwide, yet most warning systems rely on hydraulic modeling and underuse real time reservoir operation data. This study presents a data driven framework to detect flood discharge events, assess downstream operational severity, and forecast daily discharges using deep learning. The approach was validated at the Ba Ha hydropower reservoir (Vietnam) with inflow, discharge, water level, and CHIRPS rainfall data to represent basin-scale precipitation forcing. More than 160 discharge events were identified using a composite Operational Severity Index (OSI) based on peak discharge, duration, and rise rate; although only ~2% were extreme, they posed the greatest risks. Among three Transformer-based models, Informer achieved the best short-term forecasting performance (RMSE ≈ 78 m³/s, R² ≈ 0.80), while Autoformer showed greater stability at longer horizons (3–7 days). In contrast, all models exhibited reduced skill under abrupt and extreme discharge conditions. These results demonstrate that combining trend and anomaly-aware modeling enables reliable discharge prediction and severity assessment without complex hydraulic simulations. The proposed framework provides a practical foundation for reservoir early warning systems by transforming routine operational data into actionable flood-risk information. Full article

(This article belongs to the Special Issue Digital Twin-Enabled Hydrological and Hydropower Systems for Reservoir Inflow Modelling)

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17 pages, 3399 KB

Open AccessArticle

The Contribution of Natural Isotopes in Understanding Groundwater Circulation: Case Studies in Carbonate Aquifers of Central Apennines

by Alessia Di Giovanni and Sergio Rusi

Hydrology 2026, 13(4), 109; https://doi.org/10.3390/hydrology13040109 - 10 Apr 2026

Viewed by 590

Abstract

Groundwater quantification is essential for sustainable water resources management, yet it is often hampered by limited data availability and difficulties in measuring spring discharges. This study investigates three carbonate aquifers in Central Italy’s Abruzzo region: the Genzana–Greco, Morrone, and Marsicano mountains. The aim [...] Read more.

Groundwater quantification is essential for sustainable water resources management, yet it is often hampered by limited data availability and difficulties in measuring spring discharges. This study investigates three carbonate aquifers in Central Italy’s Abruzzo region: the Genzana–Greco, Morrone, and Marsicano mountains. The aim is to resolve uncertainties in spring attribution, and groundwater flow patterns using isotopic analyses combined with field surveys. The Genzana–Greco aquifer was examined to clarify the sources of the Acquachiara spring and the previously unreported Germina spring, assessing whether recharge occurs locally or from the carbonate massif. In this case, the results indicate that the Germina, together with a similar known spring of Capolaia, share a common recharge sector, while the Acquachiara spring is mainly fed by higher-elevation carbonate areas, excluding significant contributions from local alluvial deposits. In the Morrone mountain aquifer, discharge gains along the Pescara River through the Gole di Popoli were quantified, and spring isotopic compositions were compared to the main basal spring Giardino to better define groundwater contributions. In this case study, the stable isotopes and tritium data confirm recharge from the central–southern massif and support the identification of basal springs and Pescara River gains as primary discharge points, with minimal influence from surface water. For the Marsicano mountain aquifer, the role of Lake Scanno in feeding the Villalago springs was investigated through isotopic analysis of inflows, downstream springs, and basal aquifer discharge points to constrain the hydrogeological water budget. The results highlight Lake Scanno’s role in the recharge of Villalago springs and delineate the Cavuto group as a major discharge system receiving inputs from central and northern sectors of the massif. Overall, the integration of isotopic tracers with hydrological measurements allowed a more precise characterization of aquifer recharge areas, Mean Residence Times, and groundwater flow paths, improving the understanding of regional water resources in a complex carbonate setting. Full article

(This article belongs to the Special Issue Tracing Groundwater Recharge Sources Using Stable Isotopes)

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27 pages, 3774 KB

Open AccessArticle

Evapotranspiration and Crop Coefficient of Economically Important Fruit Trees in the Eastern Amazon

by Matheus Lima Rua, Gabriel Siqueira Tavares Fernandes, Tayssa Menezes Franco, Miguel Gabriel Moraes Santos, Maryelle Kleyce Machado Nery, Andressa Julia Santos Vasconcelos, Leandro Monteiro Navarro, Juliane Samara da Costa Dias, Joshuan Bessa da Conceição, Israel Alves de Oliveira, Marcus José Alves de Lima, Vivian Dielly da Silva Farias, Hildo Giuseppe Garcia Caldas Nunes, Adriano Marlisom Leão de Sousa, Everaldo Barreiros de Souza, Glauco de Souza Rolim, Mirta Teresinha Petry, Samuel Orlando Ortega-Farias and Paulo Jorge de Oliveira Ponte de Souza

Hydrology 2026, 13(4), 108; https://doi.org/10.3390/hydrology13040108 - 10 Apr 2026

Viewed by 459

Abstract

This study aimed to determine the actual crop evapotranspiration (ET_{c act}) and the crop coefficient (K_c) of economically important fruit crops in the Amazon, under both irrigated and non-irrigated conditions. The ET_{c act} was determined using the soil [...] Read more.

This study aimed to determine the actual crop evapotranspiration (ET_{c act}) and the crop coefficient (K_c) of economically important fruit crops in the Amazon, under both irrigated and non-irrigated conditions. The ET_{c act} was determined using the soil water balance method, while K_c was determined using the ratio of ET_{c act} to reference evapotranspiration (ET_o). The treatments were evaluated during the rainy period (RP) and the less rainy period (LRP). During the RP, ET_{c act} showed no significant differences between treatments, ranging from 2.26 to 3.03 mm day⁻¹. During the LRP, the irrigated treatment (2.91 to 4.02 mm day⁻¹) showed higher ET_{c act} compared to the non-irrigated treatment (1.53 to 2.87 mm day⁻¹). For the non-irrigated treatment, only the dwarf green coconut and the acid lime had a higher ET_{c act} in the LRP than the RP, while the açaí palm and the cocoa showed lower values during the LRP. In general, ET_{c act} remained below ET_o, with K_c values ranging from 0.81 to 0.85 during the RP and increasing to 0.89–0.93 during the LRP. Irrigation provided water support to the studied fruit crops during periods of lower rainfall, meeting the higher atmospheric demand during the less rainy period. Full article

(This article belongs to the Special Issue Water Resources Management Under Uncertainty and Climate Change (Second Edition))

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29 pages, 4903 KB

Open AccessArticle

Sediment Yield Assessment and Erosion Risk Analysis Using the SWAT Model in the Amman–Zarqa Basin, Jordan

by Motasem R. AlHalaigah, Michel Rahbeh, Nisrein H. Alnizami, Mutaz M. Zoubi, Heba F. Al-Jawaldeh, Shahed H. Alsoud, Yazan A. Alta’any, Qusay Y. Abu-Afifeh, Ali Brezat, Rasha Al-Rkebat, Safa E. El-Mahroug, Bassam Al Qarallah and Ahmad J. Alzubaidi

Hydrology 2026, 13(4), 107; https://doi.org/10.3390/hydrology13040107 - 9 Apr 2026

Viewed by 577

Abstract

Sediment accumulation in reservoirs represents a critical challenge for sustainable water resources management in semi-arid regions. In Jordan, accelerated sedimentation threatens the operational capacity of major dams, including the King Talal Dam (KTD), which serves as a key water resource in the Amman–Zarqa [...] Read more.

Sediment accumulation in reservoirs represents a critical challenge for sustainable water resources management in semi-arid regions. In Jordan, accelerated sedimentation threatens the operational capacity of major dams, including the King Talal Dam (KTD), which serves as a key water resource in the Amman–Zarqa Basin (AZB). This study assesses sediment yield and erosion risk at the catchment scale using the Soil and Water Assessment Tool (SWAT) integrated with the Modified Universal Soil Loss Equation (MUSLE). The AZB was subdivided into 31 sub-basins and 586 Hydrological Response Units (HRUs) based on land use, soil characteristics, topography, and slope. The model was calibrated for the period 1993–2002 and validated for 2003–2012 using hydrological and sediment observations from 17 monitoring stations. Long-term simulations covering more than two decades were conducted to quantify spatial and temporal sediment yield patterns across the basin. Results indicate a mean annual sediment yield of 2.79 t ha⁻¹ yr⁻¹, corresponding to approximately 0.59 MCM yr⁻¹ of sediment inflow to the reservoir. These estimates closely agree with bathymetric survey results reported by the Jordan Valley Authority, which indicate sedimentation rates of 2.59 t ha⁻¹ yr⁻¹ (0.55 MCM yr⁻¹). Overall, the model demonstrates strong agreement between observed and simulated sediment loads, confirming its reliability for sediment dynamics assessment. The findings are relevant to Sustainable Development Goals (SDGs) 6 (clean water and sanitation) and 15 (life on land) by informing sustainable watershed and soil erosion management practices. Full article

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

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21 pages, 3317 KB

Open AccessArticle

Assessing Nonstationary Hydroclimatic Impacts on Streamflow in the Soan River Basin, Pakistan, Using Mann–Kendall Test and Artificial Neural Network Technique

by Rafi Ul Din, Saddam Hussain, Adeel Ahmad Khan, Muhammad Naveed Anjum, A. T. M. Sakiur Rahman and Saif Ullah

Hydrology 2026, 13(4), 106; https://doi.org/10.3390/hydrology13040106 - 1 Apr 2026

Viewed by 754

Abstract

Analysis of the hydroclimatic variations in complex topographic and climatic regimes is important in determining the freshwater availability and its response. Although several previous studies have assessed the changing patterns of hydroclimatic variables in South Asian River basins, most of them have considered [...] Read more.

Analysis of the hydroclimatic variations in complex topographic and climatic regimes is important in determining the freshwater availability and its response. Although several previous studies have assessed the changing patterns of hydroclimatic variables in South Asian River basins, most of them have considered traditional statistical methods, which may inadequately reflect potential non-linear hydroclimatic trends. This study determines long-term variations in precipitation, temperature, and streamflow in the Soan River Basin of Pakistan, using three decades of in situ records (1991–2020). A non-parametric (Mann–Kendall) trend test along with an artificial neural network (ANN) approach was used to check the linear and non-linear trends. The results exhibited that the basin was getting warmer at a consistent rate, although the amount of precipitation varied significantly with location and season. The annual average amount of precipitation over the entire basin was decreasing at the rate of −7.33 mm/year. As compared to the westerly season, the trend of monsoon precipitation was less certain. Changes in streamflow patterns generally demonstrated the consequences of changing precipitation and rising temperature patterns. The annual average streamflow was decreasing at the rate of −0.47 (−1.30) m³/year, as per the results of MK (ANN). A moderate positive correlation between precipitation and streamflow indicates that precipitation mainly governed the flows in the basin. The results of the MK test and the machine-learning approach demonstrated the similar decreasing tendencies of hydroclimatic variables. However, the ANN approach more precisely demonstrates the non-linear behavior of hydroclimatic variables. It was concluded that the streamflow patterns were considerably responsive to the warming of the Soan River Basin, as well as to the changing behavior of precipitation. These findings emphasized the significance of integrating statistical and machine-learning approaches to enhance the comprehension of hydroclimatic trends. Results of this research could be applicable in sustainable management and planning of the water resources within the basin. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

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23 pages, 2514 KB

Open AccessArticle

Estimation of Water Balance and Nitrate Load in the Upper Basin of Aguascalientes, Mexico, Using SWAT

by Victor Hugo Santiago-Ayala, Arturo Corrales-Suastegui, David Avalos-Cueva, Saúl Hernández-Amparan, Cesar O. Monzon, Víctor Manuel Martínez-Calderón and Lidia Elizabeth Verduzco-Grajeda

Hydrology 2026, 13(4), 105; https://doi.org/10.3390/hydrology13040105 - 30 Mar 2026

Viewed by 996

Abstract

Intensive agriculture in semi-arid watersheds is considered a threat to global water security; however, the hydro-agronomic mechanisms that control diffuse pollution sources are often insufficiently characterized at the watershed scale. This study evaluates the hydrological response and nitrate leaching dynamics in the Upper [...] Read more.

Intensive agriculture in semi-arid watersheds is considered a threat to global water security; however, the hydro-agronomic mechanisms that control diffuse pollution sources are often insufficiently characterized at the watershed scale. This study evaluates the hydrological response and nitrate leaching dynamics in the Upper Aguascalientes watershed by implementing the SWAT model, forced with meteorological data and calibrated using runoff derived from ERA5 reanalysis. Methodologically, the Potential Nitrate Leaching Risk Index (IRP_N) was formulated and coupled to the hydrological results. The comparative analysis shows that ERA captures the temporal dynamics of the HRUs, although it tends to significantly overestimate runoff volumes. The basin exhibits a marked scale-dependent duality, with the upper zone operating under a Hortonian regime, while the lower basin exhibits attenuation at the basin scale due to spatial integration and distributed storage processes. The

(I R P_{N})

analysis demonstrates a critical disconnect between fertilization rates (>1300 kg N·ha⁻¹) and crop absorption capacity, turning excess nitrogen into a rapid transport vector during runoff events. Finally, the results underscore the need to complement water management and infrastructure strategies with technical training programs and regulatory frameworks that promote modern agricultural practices aligned with the system’s retention capacity. Full article

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

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18 pages, 5453 KB

Open AccessArticle

Bivariate Characterization of Long-Term Hydrological Drought Risks Using SRI and Archimedean Copulas

by Mohammed Achite, Tolga Barış Terzi, Osman Üçüncü, Kusum Pandey and Tommaso Caloiero

Hydrology 2026, 13(4), 104; https://doi.org/10.3390/hydrology13040104 - 30 Mar 2026

Viewed by 585

Abstract

Hydrological drought poses a major threat to water security-y in semi-arid regions, where prolonged runoff deficits can severely affect reservoir reliability and ecosystem sustainability. This study presents a bivariate probabilistic framework to characterize long-term hydrological drought risk in the Wadi Sahouat basin (northwestern [...] Read more.

Hydrological drought poses a major threat to water security-y in semi-arid regions, where prolonged runoff deficits can severely affect reservoir reliability and ecosystem sustainability. This study presents a bivariate probabilistic framework to characterize long-term hydrological drought risk in the Wadi Sahouat basin (northwestern Algeria) using the 12-month Standardized Runoff Index (SRI-12) for the period 1973/74–2014/15. Drought events were identified through run theory with a threshold level of SRI ≤ −1.0, and some drought characteristics, duration, and severity were extracted. Marginal distributions were fitted and evaluated using AIC, BIC, and Kolmogorov–Smirnov tests, leading to the selection of the Weibull distribution for both variables. The dependence structure between duration and severity was modeled using Archimedean copulas, and the Gumbel copula provided the best fit at both hydrometric stations, indicating significant upper-tail dependence. Univariate and bivariate return periods were estimated for target intervals from 10 to 200 years. Results demonstrate that multivariate return periods substantially differ from univariate estimates, particularly for extreme events, highlighting the compounded risk of prolonged and severe droughts. Full article

(This article belongs to the Special Issue Trends and Variations in Hydroclimatic Variables: 2nd Edition)

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22 pages, 5685 KB

Open AccessArticle

Assessment of Flood-Prone Areas in the Lacramarca River Basin in the Santa Clemencia and Pampadura Region, Peru, Under Climate Change Effects

by Giovene Pérez Campomanes, Karla Karina Romero-Valdez, Víctor Manuel Martínez-García, Carlos Cacciuttolo, Jesús Manuel Bernal-Camacho and Carlos Carbajal Llosa

Hydrology 2026, 13(4), 103; https://doi.org/10.3390/hydrology13040103 - 26 Mar 2026

Viewed by 935

Abstract

Floods are among the extreme events associated with climate variability in the Lacramarca River basin, located in the department of Ancash, Peru. Meteorological phenomena such as El Niño during the periods 1982–1983 and 1997–1998, as well as the Coastal El Niño in 2017, [...] Read more.

Floods are among the extreme events associated with climate variability in the Lacramarca River basin, located in the department of Ancash, Peru. Meteorological phenomena such as El Niño during the periods 1982–1983 and 1997–1998, as well as the Coastal El Niño in 2017, constitute key reference events that motivated the development of the present study, based on a case study conducted in the area between the rural settlements of Santa Clemencia and Pampadura. This research is based on maximum precipitation data derived from historical climate records and from the climate scenarios ACCESS 1-3, HadGEM2-ES, and MPI-ESM-MR, as well as the median projected scenario for 2050, obtained from the National Meteorology and Hydrology Service of Peru (SENAMHI) data platform. This information was analyzed considering the spatial location of the basin and its position relative to the area of interest, using Intensity–Duration–Frequency (IDF) curves. To demonstrate the changes in the river hydrological behavior before and after the 2017 Coastal El Niño event, a Random Forest modeling approach was applied using Sentinel-2 satellite imagery. Design peak discharges for return periods of 50, 100, and 140 years were estimated using the HEC-HMS software. Hydraulic simulation of the Lacramarca River basin, carried out using HEC-RAS version 6.7 beta 3 and IBER version 3.3.1 software, made it possible to identify flood-prone areas affecting agricultural land and areas adjacent to population centers, covering 149,000 m² and 172,000 m² for return periods of 100 and 140 years, respectively, based on information from the historical scenario. In contrast, using data from the 2050 projection scenario, affected areas of 242,000 m² and 323,000 m² were estimated for the same return periods. Full article

(This article belongs to the Special Issue Advancing Flood Detection, Monitoring & Simulation: Integrating Machine Learning, Remote Sensing & Hydrodynamic Model)

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26 pages, 9531 KB

Open AccessArticle

Interpretable Deep Learning for Characterizing Sinkhole to Supply Well Transfer Dynamics in Karst Aquifers

by Benoit Nigon, Mathieu Godard, Abderrahim Jardani, Nicolas Massei and Matthieu Fournier

Hydrology 2026, 13(4), 102; https://doi.org/10.3390/hydrology13040102 - 25 Mar 2026

Viewed by 622

Abstract

In karstic environments, water supply wells are vulnerable to rapid sediment transfer during intense rainfall events, often generating turbidity peaks that disrupt water-treatment operations. In Normandy (France), the high density of sinkholes and the complexity of transport processes in karsts complicate the identification [...] Read more.

In karstic environments, water supply wells are vulnerable to rapid sediment transfer during intense rainfall events, often generating turbidity peaks that disrupt water-treatment operations. In Normandy (France), the high density of sinkholes and the complexity of transport processes in karsts complicate the identification and prioritization of sinkholes requiring mitigation to reduce sediment fluxes at water supply wells. This study aims to quantify the time-lagged impact of each sinkhole on turbidity peaks at a supply well using a cascade modeling approach that couples numerical surface erosion–runoff simulations with deep learning models representing hydrosedimentary responses through the karst network. Surface erosion–runoff was simulated using WaterSed. Hydroclimatic time series and WaterSed model outputs were used as inputs for our deep learning models. Several deep learning architectures were compared and optimized across multiple rounds to identify a best-performing model, which was then interpreted using interpretability methods. Interpretability analyses show that turbidity is primarily controlled by seasonal conditions and short-term rainfall accumulation, while multiple sinkholes contribute jointly to short time lags. Temporal attributions reveal rapid karst response followed by attenuation, consistent with reactive karst behavior. The contribution of each sinkhole to turbidity peaks allows us to identify the most important sinkholes requiring mitigation by stakeholders. Full article

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22 pages, 9878 KB

Open AccessArticle

Field Trial of a Low-Cost Sensor Network for Hydrometeorological Monitoring of Water Pans and Small Dams in Kenya

by Nils Michalke, John M. Gathenya, Joseph K. Sang and Rehema Ndeda

Hydrology 2026, 13(4), 101; https://doi.org/10.3390/hydrology13040101 - 24 Mar 2026

Viewed by 643

Abstract

Water pans and small dams play a vital role in supplying domestic water in rural regions characterised by seasonal rainfall regimes, with increasing importance as a climate change adaptation measure. Despite their small individual size, the collective impact of numerous water pans is [...] Read more.

Water pans and small dams play a vital role in supplying domestic water in rural regions characterised by seasonal rainfall regimes, with increasing importance as a climate change adaptation measure. Despite their small individual size, the collective impact of numerous water pans is significant. Commercially available monitoring systems are often too costly to be justified for these decentralised infrastructures, resulting in limited data availability that impedes detailed studies aimed at improving their performance. Here, we developed a low-cost monitoring station network that measures water level (JSN-SR04T ultrasonic sensor), precipitation (3D-printed tipping-bucket gauge), and air temperature and humidity (DHT22 sensor). Each station costs less than 12,000 KES (≈93 USD in March 2026), making it suitable for such decentralised multi-site monitoring. A field trial conducted from June to November 2025 at four water pans in the Kakia-Esamburmbur Catchment, Kenya, compared the collected data with an automatic weather station and manual observations. Water level measurements were more accurate than manual reference readings, while air temperature showed biases of

1.4

to

1.8

°C. Precipitation data were largely inaccurate due to inadequate sensor levelling. Overall operational reliability reached

83 %

, indicating potential for improvements to reduce maintenance efforts and fully exploit the advantages of its low-cost hardware. Full article

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11 pages, 1539 KB

Open AccessArticle

The Future of Snowpack Drought in the Upper Colorado River Basin (USA)

by Abel Andrés Ramírez Molina, Glenn Tootle, Zhixu Sun and Joshua Fu

Hydrology 2026, 13(4), 100; https://doi.org/10.3390/hydrology13040100 - 24 Mar 2026

Viewed by 930

Abstract

The Upper Colorado River Basin (UCRB), through the process of snow accumulation, to snowmelt, to streamflow runoff, provides a critical water source to approximately 40 million residents in the Southwestern United States. Given the importance of late fall–winter–early spring (October, November, December, January, [...] Read more.

The Upper Colorado River Basin (UCRB), through the process of snow accumulation, to snowmelt, to streamflow runoff, provides a critical water source to approximately 40 million residents in the Southwestern United States. Given the importance of late fall–winter–early spring (October, November, December, January, February, March, or ONDJFM), cumulative precipitation, future estimates of ONDJFM cumulative precipitation, and potential drought occurrence would provide a benefit to water managers and planners. Previous research efforts successfully reconstructed (extended the period of record) the regional April 1st Snow Water Equivalent (SWE) in the UCRB using tree-ring chronologies and reconstructed climate (El Niño–Southern Oscillation or ENSO). The current research efforts differ by (a) incorporating future [Shared Socioeconomic Pathway (SSP) 5-8.5] predictions of ONDJFM cumulative precipitation (in lieu of April 1st SWE) at a single station location (Kendall R.S.) in the UCRB; (b) reconstructing ONDJFM cumulative precipitation (in lieu of April 1st SWE) using tree-ring chronologies and ENSO; and (c) evaluating an alternative reconstructed ENSO index. The reconstructed record, recent past observations, and future (SSP 5-8.5) ONDJFM cumulative precipitation were then combined to provide a paleo perspective of future drought. Results indicate that extreme ONDJFM cumulative precipitation drought periods projected for the ~2040s were exceeded in the reconstructed record. A pattern of alternating wet and dry conditions was also identified, consisting of a wet (pluvial) period in the 2030s, followed by drought conditions in the 2040s, and another wet period in the 2050s. Many of the extreme future wet (pluvial) periods exceeded those in the recent record and reconstructed record. Full article

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

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Hydrology, Volume 13, Issue 4 (April 2026) – 19 articles

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