Hydrology

20 pages, 4200 KB

Open AccessArticle

Spatiotemporal Characteristics and Identification of Typical Hydrological Patterns of Interval Inflow in the Three Gorges Reservoir Basin, China

by Qi Zhang, Zhifei Li, Yaoyao Dong, Hongyan Wang, Yu Wang, Zhonghe Li, Quanqing Feng and Hefei Huang

Hydrology 2026, 13(2), 75; https://doi.org/10.3390/hydrology13020075 - 23 Feb 2026

Viewed by 529

Abstract

The Three Gorges Reservoir (TGR) in China is one of the world’s largest hydropower projects. Interval inflow, originating from ungauged areas between the upstream gauging control stations (Zhutuo, Beibei, Wulong) and the TGR dam site, is a critical component of total reservoir inflow, [...] Read more.

The Three Gorges Reservoir (TGR) in China is one of the world’s largest hydropower projects. Interval inflow, originating from ungauged areas between the upstream gauging control stations (Zhutuo, Beibei, Wulong) and the TGR dam site, is a critical component of total reservoir inflow, but its hydrological characteristics have not been fully clarified. The accurate estimation and prediction of interval inflow are essential for reservoir safety and flood control operations. Using daily hydrological data from 2009 to 2017, we propose an integrated analytical framework combining (i) flow travel time estimation using cross-correlation analysis, (ii) multi-scale statistical characterization, and (iii) K-means clustering with bootstrap validation and algorithm comparison. This framework systematically identified hydrological regimes of interval inflow and their associated flood control risks. The key findings are as follows. (1) The optimal flow travel time from the upstream gauging stations to the dam site is 1 day (correlation coefficient

ρ = 0.9809, p < 0.001

), and it remains stable across different flow regimes. (2) The interval inflow exhibited a highly right-skewed distribution (mean 1279 m³/s, standard deviation 1651 m³/s) and contributed on average 10.1% to the total inflow. The contribution ratio exhibited an inverted U-shaped relationship with increasing total inflow, peaking at 11.4% when the total inflow (

Q

) was 13,014 m³/s. The quartile thresholds were 5788 m³/s, 9575 m³/s, and 16,869 m³/s (corresponding to Q1, Q2, and Q3, respectively), and the 10th and 90th percentiles (P10 and P90) were 4865 m³/s and 24,625 m³/s, respectively. (3) Five distinct hydrological patterns (C1–C5) were successfully identified, among which Cluster C4 (5.7% of days) was defined as the high-impact pattern based on reservoir operational criteria, with a mean

I

of 6425 m³/s, a mean

R

of 27.8% (up to 44% in extreme events), a mean flood duration of 5.8 days, a mean flood volume of 36.1 × 10⁸ m³, and a flashiness index of 1.48. (4) C4 is predominantly triggered by localized heavy rainfall, and its flashy nature implies a substantially shorter forecast lead time compared with mainstream-dominated floods, posing major challenges to real-time reservoir operations. This study demonstrates that interval inflow risk is pattern-dependent and that the proposed framework provides a scientific basis for developing pattern-specific reservoir operation strategies. The proposed framework is transferable to other large river-type reservoirs facing similar ungauged interval inflow challenges. Full article

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

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21 pages, 27614 KB

Open AccessArticle

Beyond Vertical Accuracy: Benchmarking Global DEMs for Hydrologic Connectivity and Flood Sensitivity in Flat Coastal Plains

by Jose Miguel Fragozo Arevalo, Jairo R. Escobar Villanueva and Jhonny I. Pérez-Montiel

Hydrology 2026, 13(2), 74; https://doi.org/10.3390/hydrology13020074 - 22 Feb 2026

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Abstract

We assessed the vertical accuracy of six global digital elevation models—FABDEM (SRTM-enhanced), SRTM, ASTER GDEM, ALOS AW3D30, DeltaDTM and GEDTM—against a local photogrammetry-derived DEM as a benchmark in a flat coastal plain of the Colombian Caribbean. Using GNSS-RTK ground points and a high-accuracy [...] Read more.

We assessed the vertical accuracy of six global digital elevation models—FABDEM (SRTM-enhanced), SRTM, ASTER GDEM, ALOS AW3D30, DeltaDTM and GEDTM—against a local photogrammetry-derived DEM as a benchmark in a flat coastal plain of the Colombian Caribbean. Using GNSS-RTK ground points and a high-accuracy reference DEM, we computed BIAS, RMSE, and MAE. Errors were analyzed by land cover class and along transverse profiles relative to the reference DEM. We also evaluated hydrologic suitability by comparing flow accumulation and drainage patterns derived from each model, treating the photogrammetry-derived model as the control and the global DEMs as treatments to gauge their ability to represent hydraulic/hydrologic behavior. DeltaDTM, GEDTM and FABDEM showed the best overall performance, with the lowest vertical error (particularly in non-urban areas with sparse vegetation) and the highest drainage agreement, along with their flood extent sensitivity to a 0.5 m water level rise, all of which were comparable to the benchmark. These results provide practical guidance for selecting and preprocessing topographic models for risk management and territorial planning in flat regions. Full article

(This article belongs to the Special Issue Hydrological Modeling and Sustainable Water Resources Management, 2nd Edition)

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25 pages, 5064 KB

Open AccessArticle

Spatiotemporal Drought Assessment Projections for Climate-Resilient Planning in Distinct Mediterranean Agroecosystems

by Stavros Sakellariou, Nicolas Dalezios, Marios Spiliotopoulos, Nikolaos Alpanakis, Stergios Kartsios, Ioannis Faraslis, Georgios A. Tziatzios, Pantelis Sidiropoulos, Nicholas Dercas, Apostolos Tsiovoulos, Konstantina Giannousa, Alfonso Domínguez, José Antonio Martínez-López, Ramón López-Urrea, Fadi Karam, Hacib Amami and Radhouan Nsiri

Hydrology 2026, 13(2), 73; https://doi.org/10.3390/hydrology13020073 - 15 Feb 2026

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Abstract

Drought is expected to intensify under climate change, posing significant risks to Mediterranean agroecosystems. This study provides long-term projections of drought and wetness conditions for three representative Mediterranean regions—Eastern Mancha (Spain), Sidi Bouzid Governorate (Tunisia), and the Beqaa Valley (Lebanon)—to support climate-resilient planning. [...] Read more.

Drought is expected to intensify under climate change, posing significant risks to Mediterranean agroecosystems. This study provides long-term projections of drought and wetness conditions for three representative Mediterranean regions—Eastern Mancha (Spain), Sidi Bouzid Governorate (Tunisia), and the Beqaa Valley (Lebanon)—to support climate-resilient planning. Future monthly precipitation (2020–2050) was dynamically downscaled using the Weather Research and Forecasting (WRF) model under the RCP4.5 scenario, and the Standardized Precipitation Index (SPI12) was subsequently applied to quantify drought severity at annual and monthly scales. By integrating dynamically downscaled WRF projections with pixel-based SPI analysis across three spatially distinct Mediterranean regions, the study provides a novel, spatially explicit and comparative framework for assessing future drought and wetness extremes in support of climate-resilient planning. The results reveal spatial variability and moderate temporal fluctuations across the three regions, reflected in differing timings and intensities of their driest and wettest hydrological years. Spain is projected to experience its driest hydrological year in 2046–2047, Tunisia in 2030–2031, and Lebanon in 2047–2048. The wettest years are projected to occur in 2045–2046 for Spain and Tunisia, and in 2028–2029 for Lebanon. Although extreme drought events are not widely anticipated, localised severe dry periods emerge in many parts of the study areas. while in Lebanon, these conditions also extend into the winter and spring. These findings underscore the need for spatially targeted adaptation rather than uniform regional measures. Identifying both driest and wettest projected years enhances preparedness, informs water-resource optimisation, and supports agricultural land-use planning, especially in areas with favourable future climatic conditions. Integrating drought projections into multi-hazard planning (i.e., drought and floods) frameworks can further strengthen territorial resilience in regions facing increasing climate-related extremes. Full article

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

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23 pages, 13507 KB

Open AccessArticle

Deciphering Spatial Patterns in Groundwater Quality Across Nouvelle-Aquitaine, France: A Multivariate Analysis of Two Decades of Monitoring Data

by Mouna El Jirari, Abdoul Azize Barry, Abderrahim Bousouis, Zouhair Zeiki, Meryem Ayach, Mohamed Sadiki, Abdelhak Bouabdli, Meryem Touzani, Muriel Guiraud, Vincent Valles and Laurent Barbiero

Hydrology 2026, 13(2), 72; https://doi.org/10.3390/hydrology13020072 - 14 Feb 2026

Viewed by 559

Abstract

Groundwater, a vital resource for drinking water supply, must be managed sustainably to ensure its availability and quality. In France, the SISE-Eaux database on water intended for human consumption, archived by the Regional Health Agencies (ARS) since 1990, constitutes a rich source of [...] Read more.

Groundwater, a vital resource for drinking water supply, must be managed sustainably to ensure its availability and quality. In France, the SISE-Eaux database on water intended for human consumption, archived by the Regional Health Agencies (ARS) since 1990, constitutes a rich source of information. This study focused on the groundwater of the Nouvelle-Aquitaine region, the largest administrative region in metropolitan France, covering 84,061 km² with 6 million inhabitants. It is based on a 22-year data extraction, resulting in a matrix of 121,649 observations and 51 physico-chemical and bacteriological parameters. Following logarithmic transformation of the data and fitting of variograms using the mean value of each parameter for each sampling point, the spatial distribution of numerous parameters across the region is presented. From this initial sparse matrix, a dense matrix of 23,319 samples (rows) and 15 key parameters (columns) was selected for a multivariate approach. A Principal Component Analysis (PCA) was used to condense the information and create summary maps capturing over 68% of the information contained in the dense matrix. The combined results of the multivariate analysis (dense matrix) and the distribution of individual parameters (sparse matrix) highlight the diversity of sources contributing to the spatial variability of groundwater, such as the role of lithology, the origin and pathways of fecal contamination, and the influence of redox processes. Neither the large size of the study area nor the high number of parameters proved to be an obstacle to the analysis. The understanding of ongoing processes and the factorial axis distribution maps, which enable the spatial representation of these mechanisms, can be used to facilitate groundwater monitoring and protection. Full article

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18 pages, 3307 KB

Open AccessArticle

Coupling of Multi-Hydrochemical and Statistical Methods for Identifying Apparent Background Levels of Major Components in Shallow Groundwater in Shanghai, China

by Qingqing Li, Min Ji, Shiyang Zhang, Jie Yang and Hainan Lu

Hydrology 2026, 13(2), 71; https://doi.org/10.3390/hydrology13020071 - 12 Feb 2026

Viewed by 457

Abstract

The determination of groundwater background levels is a prerequisite for assessing and analyzing groundwater characteristics. Shanghai is among the most economically developed regions in China and is located in the estuary of the Yangtze River, where frequent hydrogeochemical processes occur. Moreover, the frequency [...] Read more.

The determination of groundwater background levels is a prerequisite for assessing and analyzing groundwater characteristics. Shanghai is among the most economically developed regions in China and is located in the estuary of the Yangtze River, where frequent hydrogeochemical processes occur. Moreover, the frequency of anthropogenic activities in Shanghai is very high. Consequently, assessing groundwater background levels in Shanghai is inherently limited if only statistical methods are adopted or anthropogenic impacts are ignored. In this study, hydrochemical and statistical methods were coupled to identify groundwater anomalies and background levels. The results revealed distinct differences in hydrochemical characteristics between the two selected independent units (Chongming and Qingpu units), highlighting the necessity of reasonably delineating hydrogeological units for obtaining background values. Furthermore, for these two independent units, different optimal methods for identifying and eliminating anthropogenic groundwater anomalies were determined. The use of coupled methods was demonstrated to be substantially superior to the use of purely statistical approaches. Hydro-HCA was identified as the optimal identification method for the Chongming unit, whereas Hydro-Grubbs was determined as the most suitable method for the Qingpu unit. This could be attributed mainly to the coupled methods accounting for not only the dispersion of the data itself but also the intrinsic relationships and evolutionary processes of hydrochemical components. These findings could provide reliable information for subsequent groundwater background surveys and studies on groundwater pollution characteristics in Shanghai and to guide future endeavors aimed at protecting groundwater resources. Full article

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8 pages, 216 KB

Open AccessEditorial

Editorial: Hydrodynamics and Water Quality of Rivers and Lakes

by Gabriela Elena Dumitran, Liana Ioana Vuta, Elisabeta Cristina Timis and Minxue He

Hydrology 2026, 13(2), 70; https://doi.org/10.3390/hydrology13020070 - 12 Feb 2026

Viewed by 604

Abstract

The hydrodynamics and water quality of rivers and lakes are governed by complex interactions among flow, mixing, stratification, sediment transport, and biogeochemical processes (Ji, 2017) [...] Full article

(This article belongs to the Special Issue Hydrodynamics and Water Quality of Rivers and Lakes)

25 pages, 19199 KB

Open AccessArticle

Spatiotemporal Evolution of Groundwater System Sustainability in Northeast China’s Transboundary River Basins Under Agricultural Expansion and Climate Variability: Insights from GRACE Satellite Observations

by Yujia Liu, Yang Liu, Kaiwen Zhang and Changlei Dai

Hydrology 2026, 13(2), 69; https://doi.org/10.3390/hydrology13020069 - 11 Feb 2026

Viewed by 991

Abstract

Groundwater is a critical strategic resource supporting agricultural production and ecological security in the transboundary river basins of Northeast China. However, intensified climate variability and rapid agricultural expansion over the past two decades have imposed increasing pressure on regional groundwater systems. In this [...] Read more.

Groundwater is a critical strategic resource supporting agricultural production and ecological security in the transboundary river basins of Northeast China. However, intensified climate variability and rapid agricultural expansion over the past two decades have imposed increasing pressure on regional groundwater systems. In this study, we integrated GRACE-derived terrestrial water storage anomalies, GLDAS land surface data, meteorological datasets, land-use information, and agricultural statistics to construct a comprehensive assessment framework consisting of groundwater storage anomalies (ΔGWS), the GRACE Groundwater Drought Index (GGDI), and sustainability indicators—REL (Reliability), RES (Resilience), VUL (Vulnerability), and SI (Sustainability Index). By integrating GRACE-derived groundwater dynamics with sustainability indicators (REL, RES, VUL, and SI), enabling a basin-scale, long-term assessment of groundwater sustainability across Northeast China’s transboundary basins, and clarifying the relative roles of climatic variability and intensive human water use. We systematically examined the spatiotemporal evolution of groundwater conditions in the Heilongjiang, Suifen, Tumen, and Yalu River basins from 2002 to 2022, and quantified the relative roles of climatic and anthropogenic drivers. The results indicate that groundwater storage exhibited pronounced seasonal fluctuations alongside a persistent downward trend, with GGDI remaining predominantly negative after 2018, reflecting the development of structural groundwater drought. The SI declined markedly from 0.32 to 0.06, and areas with extremely low sustainability accounted for more than 90% of the study region in recent years. MIC-based dependence analysis showed that sown area (MIC = 0.98) and nighttime light intensity (MIC = 0.92) were the dominant drivers of groundwater degradation, exerting far greater influence than precipitation or potential evapotranspiration. These patterns highlight that policy-driven agricultural expansion and increased irrigation demand have surpassed natural recharge capacity, becoming the fundamental cause of long-term groundwater depletion. This study underscores the urgency of promoting agricultural green transformation, optimizing crop planting structures, improving irrigation efficiency, and enhancing ecological conservation to rebuild groundwater resilience. Moreover, coordinated cross-border groundwater monitoring and management will be essential for ensuring the sustainable use of water resources in Northeast Asia’s transboundary river basins. Full article

(This article belongs to the Topic Groundwater Sustainability: Innovations in Resource Management and Environmental Protection)

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21 pages, 4975 KB

Open AccessArticle

Spatiotemporal Variability and Extreme Precipitation Characteristics in Arid Region of Ordos, China

by Shengjie Cui, Shuixia Zhao, Chao Li, Yingjie Wu, Xiaomin Liu, Ping Miao, Shiming Bai, Yajun Zhou and Jinrong Li

Hydrology 2026, 13(2), 68; https://doi.org/10.3390/hydrology13020068 - 11 Feb 2026

Viewed by 617

Abstract

Studying the precipitation characteristics and extreme precipitation events in arid and semi-arid regions is of significant baseline value for optimizing water resource allocation and utilizing precipitation resources. Utilizing multi-scale ERA5 precipitation data from 1960 to 2023, this study focuses on the typical arid [...] Read more.

Studying the precipitation characteristics and extreme precipitation events in arid and semi-arid regions is of significant baseline value for optimizing water resource allocation and utilizing precipitation resources. Utilizing multi-scale ERA5 precipitation data from 1960 to 2023, this study focuses on the typical arid and semi-arid region of Ordos as the research area. Precipitation exceeding the 90th percentile was defined as extreme precipitation, and three indices—extreme precipitation amount (EPA), extreme precipitation frequency (EPF), and extreme precipitation proportion (EPP)—were used to investigate its characteristics in the study area. Additionally, three typical extreme precipitation events in recent years were analyzed to study the precipitation process of these typical events. The main results are as follows: The annual average precipitation in the study area ranges from 170.3 to 606.1 mm, with an average of 378.5 mm, which has been on a declining trend over the years, with an average annual decrease of 1.2 mm. Overall, 70% of the precipitation is concentrated in the months of June to September. The daily average of extreme precipitation in Ordos is 18.7 mm and the annual average number of extreme precipitation days ranges from 8 to 13 days, with an average annual number of extreme precipitation days being 11. Extreme precipitation accounts for more than 50% of the total precipitation. Among all areas analyzed, Jungar Banner demonstrates the greatest vulnerability to intense rainfall events. Typical extreme precipitation events in Ordos are characterized by short-duration heavy rainfall, with the rain peak ratio coefficients of the three events ranging from 0.62 to 0.72, exhibiting a distinct “post-peak” pattern. These findings provide scientific support for water resource management and disaster prevention strategies in arid and semi-arid regions. Full article

(This article belongs to the Special Issue Global Rainfall-Runoff Modelling)

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24 pages, 4620 KB

Open AccessArticle

Quasi-Global (50° S–50° N) of Soil Moisture and Precipitation Extremes

by Aoqi Shi, Jun Liu, Taoyu Jin, Zhuhe Li, Wenfu Yang, Wenwen Wang and Wenmin Zhang

Hydrology 2026, 13(2), 67; https://doi.org/10.3390/hydrology13020067 - 9 Feb 2026

Viewed by 1036

Abstract

Clarifying the interplay between extreme soil moisture (SM) and precipitation (P) is imperative to understand the impacts of extreme events on ecosystems in a changing climate. However, the detailed relationships, pathways, and quantitative characterization of SM-P extremes at a quasi-global (50° S–50° N) [...] Read more.

Clarifying the interplay between extreme soil moisture (SM) and precipitation (P) is imperative to understand the impacts of extreme events on ecosystems in a changing climate. However, the detailed relationships, pathways, and quantitative characterization of SM-P extremes at a quasi-global (50° S–50° N) scale remain unclear. Here, we systematically evaluated the co-occurrence and temporal dependencies of SM-P extremes from 2000 to 2022, quantified their synchronous probability, used statistical modeling to reveal the directional pathways among evapotranspiration (ET), P, and SM, and detected long-term trends in P and SM extremes. Our results show a significant increase in the co-occurrence frequency of SM-P extremes globally, with strong spatiotemporal co-occurrence patterns. A lower conditional probability (62%) of extreme SM anomalies was observed within a short term (34 days) after P extremes occurred, while a significantly higher conditional probability (88%) of P extremes was found following extreme SM anomalies. Path analysis (structural equation modeling) indicates a strong direct positive pathway from P to SM, whereas SM influences P indirectly through ET. Compared to satellite-based observations, the BCC-ESM1 model within the CMIP6 framework reproduces the synchrony of SM-P extremes reasonably well, offering a feasible alternative for predicting SM-P relationships in regions lacking satellite observations and aiding future projections of their trends. Our study broadens the perspective on land–atmosphere interactions and coupling mechanisms, providing a solid theoretical basis for predicting and managing the effects of extreme events on ecosystems. Full article

(This article belongs to the Topic Advances in Hydrogeological Research)

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35 pages, 5155 KB

Open AccessEditor’s ChoiceArticle

Hydrological Model Calibration in Data-Scarce Mediterranean Catchments: A Comparative Assessment of Three Strategies

by Afshin Jahanshahi, Felice D. Pacia, Pasquale Perrini, Angelo Avino, Awais Naeem Sarwar, Ruodan Zhuang, Umberto Terracciano, Pasquale Coccaro, Luciana Giuzio and Salvatore Manfreda

Hydrology 2026, 13(2), 66; https://doi.org/10.3390/hydrology13020066 - 9 Feb 2026

Viewed by 1009

Abstract

Hydrological calibration in data-scarce catchments is challenged by non-stationary regimes, fragmented data, and systematic measurement errors. Conventional calibration approaches often assume continuous records and rely on standard performance metrics, which can bias calibration toward high flows and exacerbate parameter equifinality—ultimately reducing robustness under [...] Read more.

Hydrological calibration in data-scarce catchments is challenged by non-stationary regimes, fragmented data, and systematic measurement errors. Conventional calibration approaches often assume continuous records and rely on standard performance metrics, which can bias calibration toward high flows and exacerbate parameter equifinality—ultimately reducing robustness under data limitations. This study provides a systematic comparison of three calibration strategies—Kling–Gupta Efficiency (KGE), a non-parametric variant (R_NP), and Flow Duration Curve (FDC)-based calibration—together with their time-consistent counterparts (SKGE, SR_NP, and SRMSE). All schemes are implemented for the lumped HBV-type TUW model across nine catchments in southern Italy and evaluated using independent metrics targeting overall hydrograph agreement, high-flow behavior, and FDC quantile matching (Q5–Q95). The results reveal that the time-consistent KGE-based strategy excels during in calibration (NSE = 0.56, RMSE = 4.65 m³/s) but shows notable declines in validation (NSE = 0.40, RMSE = 3.91 m³/s), indicating sensitivity to non-stationarity. The R_NP-based approach demonstrates enhanced validation robustness (NSE = 0.51, RMSE = 3.60 m³/s) and low-flow accuracy, with NSE_lnQ = 0.30 and low-flow accuracy, leveraging its non-parametric structure. The SR_NP variant further enhances performance in validation (NSE = 0.52, RMSE = 3.42 m³/s), along with superior low-flow performance (NSE_lnQ = 0.48). The FDC-based strategy effectively reproduces flow distributions during calibration (NSE = 0.41, minimal PBIAS = −0.03%) but exhibits limited temporal transferability (validation NSE = 0.25, RMSE = 4.50 m³/s). Time-consistent variants reduce parameter dispersion by approximately 2–8% (relative to full-period calibration) and improve validation metrics by 5–15% across all catchments. Overall, time-consistent calibration provides a practical pathway to increase robustness under non-stationary, data-scarce Mediterranean conditions, highlighting a systematic trade-off between calibration accuracy and validation reliability. Full article

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33 pages, 8706 KB

Open AccessArticle

Effects of River Channel Structural Modifications on High-Flow Characteristics Using 2D Rain-on-Grid HEC-RAS Modelling: A Case of Chongwe River Catchment in Zambia

by Frank Mudenda, Hosea M. Mwangi, John M. Gathenya and Caroline W. Maina

Hydrology 2026, 13(2), 65; https://doi.org/10.3390/hydrology13020065 - 6 Feb 2026

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Abstract

Rapid urbanization has led to increasing structural modification of river catchments through dam construction and concrete-lining of natural channels as flood management measures. These interventions can alter the natural hydrology. This necessitates assessment of their influence on hydrology at a catchment scale. However, [...] Read more.

Rapid urbanization has led to increasing structural modification of river catchments through dam construction and concrete-lining of natural channels as flood management measures. These interventions can alter the natural hydrology. This necessitates assessment of their influence on hydrology at a catchment scale. However, such evaluations are particularly challenging in data-scarce regions such as the Chongwe River Catchment, where hydrometric records capturing conditions before and after structural modifications are limited. Therefore, we applied a 2D rain-on-grid approach in HEC-RAS to evaluate changes in high-flow responses to short-duration, high-intensity rainfall events in the Chongwe River Catchment in Zambia, where structural interventions have been implemented. The terrain was modified in HEC-RAS to represent 21 km of concrete drains and ten dams. Sensitivity analysis conducted on five key model parameters showed that parameters controlling surface runoff generation, particularly curve number, exerted the strongest influence on simulated peak flows, while routing-related parameters had a secondary effect. Model calibration and validation showed strong performance with R² = 0.99, NSE = 0.75 and PBIAS = −0.68% during calibration and R² = 0.95, NSE = 0.75, PBIAS = −2.49% during validation. Four scenarios were simulated to determine the hydrological effects of channel concrete-lining and dams. The results showed that concrete-lining of natural channels in the urban area increased high flows at the main outlet by approximately 4.6%, generated localized instantaneous maximum channel velocities of up to 20 m/s, increased flood depths by up to 11%, decreased lag times and expanded flood inundation widths by up to 15%. The existing dams reduced peak flows by about 28%, increased lag times, reduced flood depths by about 11%, and reduced flood inundation widths by up to 8% across the catchment. The findings demonstrate that enhancing stormwater conveyance through concrete-lining must be complemented by storage to manage high flows, while future work should explore nature-based solutions to reduce channel velocities and improve sustainable flood mitigation. Therefore, the study provides event-scale insights to support flood-risk management and infrastructure planning in rapidly urbanizing, data-scarce catchments. Full article

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

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2 pages, 114 KB

Open AccessEditorial

Hydrology Annual Report Card 2025

by Ezio Todini

Hydrology 2026, 13(2), 64; https://doi.org/10.3390/hydrology13020064 - 6 Feb 2026

Viewed by 494

Abstract

With 2024 marking the tenth anniversary of its establishment, 2025 was the first year of the second decade of Hydrology [...] Full article

34 pages, 6955 KB

Open AccessEditor’s ChoiceArticle

Seasonal Inflow Shifts and Increasing Hot–Dry Stress for Eagle Mountain Lake Reservoir, Texas: SWAT Modeling with Downscaled CMIP6 Daily Climate and Observed Operations

by Gehendra Kharel, Daniel A. Ayejoto, Brendan L. Lavy, Michele Birmingham, Tapos K. Chakraborty, Md Simoon Nice and Portia Asare

Hydrology 2026, 13(2), 63; https://doi.org/10.3390/hydrology13020063 - 6 Feb 2026

Viewed by 1458

Abstract

Climate change can alter both the amount and timing of inflows to water supply reservoirs while also increasing heat-driven demand and the likelihood of stressful warm-season conditions. Climate-driven changes in inflow to Eagle Mountain Lake Reservoir (Texas, USA) were quantified by integrating (i) [...] Read more.

Climate change can alter both the amount and timing of inflows to water supply reservoirs while also increasing heat-driven demand and the likelihood of stressful warm-season conditions. Climate-driven changes in inflow to Eagle Mountain Lake Reservoir (Texas, USA) were quantified by integrating (i) a calibrated SWAT model evaluated at four USGS stream gauges, (ii) statistically downscaled CMIP6 daily precipitation and minimum/maximum temperature at seven stations/grid points for a historical baseline (2003–2022) and two future windows (2031–2050 and 2081–2100) under SSP1-2.6, SSP2-4.5, and SSP5-8.5, and (iii) observed reservoir operations (lake level, water supply releases, and flood discharge; 1990–2022). A standard watershed climate workflow is reframed through an operations-focused lens, wherein projected inflow changes are translated into decision-relevant indicators via the utilization of observed thresholds and operating mode signals. Included within this framework are spring refill-season inflow shifts, a hot–dry month metric, and storage threshold performance measures, which are coupled with screening-level probabilities linked to multi-year inflow deficits. Across models and stations, mean annual temperature increases by 0.7–1.9 °C in the 2030s and by 0.7–6.1 °C in the 2080s, while annual precipitation changes remain uncertain (−24% to +55%). Daily projections show a strong increase in extreme heat days (daily Tmax above the historical 95th percentile), from about 18 days yr⁻¹ historically to about 30–33 days yr⁻¹ in the 2030s and about 34–82 days yr⁻¹ by the 2080s. Hot–dry months (monthly mean Tmax above the historical 90th percentile and monthly precipitation below the historical median) increase modestly by mid-century and rise to about 1.5 months yr⁻¹ on average by the 2080s under SSP5-8.5. SWAT simulations indicate that the mean annual inflow declines by 17–20% across scenarios, with the largest reductions during the spring refill period (March–June). Historical operations show that hot–dry months are associated with approximately double the mean water supply release (7.2 vs. 3.5 m³/s) and a lower monthly minimum lake level (about 0.30 m; about 1.0 ft lower on average). Flood discharges occur almost exclusively when lake elevation is at or above about 197.8 m and follow multi-day rainfall clusters (cross-validated AUC = 0.99). Together, these results indicate that earlier-season inflow reductions and more frequent hot–dry stress will tighten the operational margin between refill, summer demand, and flood management, underscoring the need for adaptive drought response triggers and integrated drought–flood planning for the Dallas–Fort Worth region. Full article

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

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35 pages, 3522 KB

Open AccessArticle

Reaction of Minimum Streamflow of Arid Kazakhstan Rivers to Climate Non-Stationarity

by Marat Moldakhmetov, Lyazzat Makhmudova, Ainur Mussina, Assel Abdullayeva, Lyazzat Birimbayeva, Marzhan Tursyngali, Bakyt Imamova, Makpal Dautalieva, Sagi Buralkhiyev and Harris Vangelis

Hydrology 2026, 13(2), 62; https://doi.org/10.3390/hydrology13020062 - 5 Feb 2026

Viewed by 509

Abstract

This article provides a comprehensive analysis of long-term changes in the minimum river flow of the southern rivers of Western Kazakhstan (Temir, Oiyil, Zhem) for the period 1940–2022, with an emphasis on summer minimum and winter low flow as key indicators of water [...] Read more.

This article provides a comprehensive analysis of long-term changes in the minimum river flow of the southern rivers of Western Kazakhstan (Temir, Oiyil, Zhem) for the period 1940–2022, with an emphasis on summer minimum and winter low flow as key indicators of water and environmental sustainability in conditions of increasing climate variability. The study combines a typology of the climate control mechanisms of minimum flow, analysis of structural homogeneity, and assessment of the internal organization of time series based on ITA and the integral IPTA method, which allow us to reveal the hidden fluctuations and stable phase states of the hydrological regime. The calculation of the climate sensitivity index (CSI_min) showed pronounced seasonal asymmetry: summer runoff is largely controlled by atmospheric precipitation, while winter minimum runoff is determined by temperature regime and soil freezing depth. Parametric and nonparametric tests (Pettitt, ADF, SNHT) revealed significant structural shifts in the 1960s–1990s period, corresponding to large-scale climatic anomalies in the region. Summer series are characterized by phases of prolonged low water levels and negative trends in the mid-20th century, while for the winter period, a steady increase in minimum flow has been established, due to regional warming and an increase in the share of underground recharge. IPTA confirmed the presence of long-term phases with high internal heterogeneity in the summer season and a more stable winter runoff structure. The results demonstrate the high climatic sensitivity of minimum runoff and confirm the need to move from static standards to dynamically adaptable methods of water resource assessment. The proposed approach can serve as a tool for developing adaptation strategies, assessing the risk profile of basins, and improving the sustainability of water management planning in arid regions. Full article

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25 pages, 4859 KB

Open AccessArticle

Exploring the Seven Climate Zones of China: How Soil Moisture and Vapor Pressure Deficit Influence Vegetation Productivity

by Yan Zhou, Changqing Meng, Yue Li and Qingqing Fang

Hydrology 2026, 13(2), 61; https://doi.org/10.3390/hydrology13020061 - 4 Feb 2026

Viewed by 708

Abstract

Reduced soil moisture (SM) together with elevated vapor pressure deficit (VPD) suppresses gross primary productivity (GPP) and thus weakens the capacity of the terrestrial carbon pool. Against the backdrop of global climate change, soil and atmospheric drought exert a more profound impact on [...] Read more.

Reduced soil moisture (SM) together with elevated vapor pressure deficit (VPD) suppresses gross primary productivity (GPP) and thus weakens the capacity of the terrestrial carbon pool. Against the backdrop of global climate change, soil and atmospheric drought exert a more profound impact on vegetation growth, and their combined impacts remain unclear. Based on multi-source remote sensing observations and reanalysis datasets, three vegetation remote sensing indices, GPP, SIF, and NDVI (collectively referred to as Vegetation Remote Sensing Indices, VSI), are employed in this study to assess the relative impacts of soil and atmospheric drought on terrestrial vegetation. First, Copula-based conditional probabilities are applied to identify which factor (reduced SM or high VPD) plays a dominant role under conditions of declining vegetation productivity and to determine their corresponding thresholds. Furthermore, the underlying driving mechanisms are elucidated by utilizing Structural Equation Modeling (SEM) for path analysis to clarify how climatic factors indirectly affect vegetation productivity by influencing SM and VPD. The results suggest that vegetation growth in China’s different climatic zones is affected by distinct factors. Specifically, SM is the primary factor influencing vegetation productivity, dominating 71.16% of the nation’s vegetated areas. Its influence is particularly pronounced in arid and semi-arid regions. In contrast, the impact of VPD is predominantly concentrated in semi-humid plain regions. Furthermore, the critical thresholds for SM in different climate zones are identified: the threshold averages approximately 0.33 m³/m³ in humid and plateau regions and 0.13 m³/m³ in arid and semi-arid regions. The SEM analysis further reveals the complex pathways by which climatic variables influence vegetation growth. In SM-dominated regions, higher SM directly promotes vegetation growth; in VPD-dominated regions, drier air imposes a stronger suppression on vegetation growth. Nonetheless, the plateau temperate semi-arid zone demonstrates distinct hydrometeorological characteristics. Attributed to the region’s unique hydrometeorological conditions, the negative effects of higher VPD are generally outweighed by the favorable conditions for photosynthesis with which it co-occurs. These findings clarify the intricate impacts of SM and VPD on vegetation productivity, providing a foundational framework for the development of tailored ecological management strategies and drought early warning systems. Full article

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

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24 pages, 11085 KB

Open AccessEditor’s ChoiceArticle

High-Frequency Multi-Satellite Observations of Brahmaputra River Hydrology and Floodplain Dynamics

by Faruque Abdullah, Jamal Khan, Nasreen Jahan, A.K.M. Saiful Islam and Sazzad Hossain

Hydrology 2026, 13(2), 60; https://doi.org/10.3390/hydrology13020060 - 4 Feb 2026

Viewed by 913

Abstract

Reliable observation of water resources is a major challenge for sustainable development, particularly in the river-centric deltaic countries like Bangladesh, where the data is generally scarce. Leveraging operational satellites, this study presents a real-time capable water level (WL), discharge (Q), and floodplain monitoring [...] Read more.

Reliable observation of water resources is a major challenge for sustainable development, particularly in the river-centric deltaic countries like Bangladesh, where the data is generally scarce. Leveraging operational satellites, this study presents a real-time capable water level (WL), discharge (Q), and floodplain monitoring framework implemented for the Brahmaputra River in Bangladesh. The multi-satellite approach presented here combined satellite altimetry, synthetic aperture radar (SAR), and optical imagery. A set of WL time series is obtained first from Jason-2/3 and Sentinel-3 altimetry, while a combination of Sentinel-1 SAR and Sentinel-2 optical images is used to extract the floodplain extent. Seasonal Rating Curve (RC) models are then developed to estimate Q from the river WL (altimetry) and width (imagery). The altimetry WL measurement is further complemented by the width-based Q utilizing an inverse RC. Furthermore, the water level is combined with a floodplain map to extract floodplain topography and its evolution. The proposed framework provides consistent and reliable observations in the Brahmaputra River, with a bias, root mean-squared errors (RMSEs), and correlation coefficient of 0.03 m, 0.68 m, and 0.96 for WL, and −168.22 m³/s, 4161.46 m³/s, and 0.97 for Q, respectively, relative to a mean discharge of approximately 30,000 m³/s. The locations of high erosion–accretion across the river reach are also well-captured in the evolving floodplain maps. By integrating multiple satellite altimetry missions with SAR and optical imagery, the multi-satellite approach reduces the effective monitoring interval for both water level and discharge from approximately 10 days (single-mission altimetry) to about 4 days, enabling improved capture of extreme events such as floods. As the operational satellites used in this study are expected to provide long-term observations, the proposed framework supports sustainable monitoring of floodplain dynamics in Bangladesh and other similar data-poor environments, towards informed water management under ongoing climatic and anthropogenic changes. Full article

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

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38 pages, 7167 KB

Open AccessArticle

Artificial Intelligence (AI) and Monte Carlo Simulation-Based Modeling for Predicting Groundwater Pollution Indices and Nitrate-Linked Health Risks in Coastal Areas Facing Agricultural Intensification

by Hatim Sanad, Rachid Moussadek, Latifa Mouhir, Abdelmjid Zouahri, Majda Oueld Lhaj, Yassine Monsif, Khadija Manhou and Houria Dakak

Hydrology 2026, 13(2), 59; https://doi.org/10.3390/hydrology13020059 - 3 Feb 2026

Cited by 2 | Viewed by 900

Abstract

This study assesses groundwater quality and nitrate-related health risks in the Skhirat coastal aquifer (Morocco) using a multidisciplinary approach. A total of thirty groundwater wells were sampled and analyzed for physico-chemical properties, including major ions and nutrients. Multivariate statistical analyses were employed to [...] Read more.

This study assesses groundwater quality and nitrate-related health risks in the Skhirat coastal aquifer (Morocco) using a multidisciplinary approach. A total of thirty groundwater wells were sampled and analyzed for physico-chemical properties, including major ions and nutrients. Multivariate statistical analyses were employed to explore contamination sources. Pollution indices such as the Groundwater Pollution Index (GPI) and Nitrate Pollution Index (NPI) were computed, and Monte Carlo simulations (MCSs) were conducted to assess nitrate-related health risks through ingestion and dermal exposure. Furthermore, Random Forest (RF), Gradient Boosting Regression (GBR), Support Vector Regression (SVR) with radial basis function kernel, and Artificial Neural Networks (ANN) models were tested for predicting groundwater pollution indices. Results of hydrochemical facies revealed Na⁺-Cl⁻ dominance in 47% of the samples, suggesting strong marine influence, while nitrate concentrations reached up to 89.3 mg/L, exceeding World Health Organization (WHO) limits in 26.7% of the sites. Pollution indices indicated that 33.3% of samples exhibited moderate to high GPI values, with 36.7% of the samples exceeding the threshold for NPI. The MCS for nitrate health risk revealed that 43% of the samples posed non-carcinogenic health risks to children (Hazard Index (HI) > 1). RF outperformed other models in predicting GPI (R² = 0.76) and NPI (R² = 0.95). Spatial prediction maps visualized contamination hotspots aligned with intensive horticultural activity. This integrated methodology offers a robust framework to diagnose groundwater pollution sources and predict future risks. 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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38 pages, 8869 KB

Open AccessArticle

Hydrogeologic and Agricultural Drivers of Groundwater Salinity, Boron, Selenium, and Nitrate in Wister Unit, Eastern Salton Sea, California

by Barry J. Hibbs, Mackenzie Schilling, Andrew Sunda and Jerusalem Miramontes

Hydrology 2026, 13(2), 58; https://doi.org/10.3390/hydrology13020058 - 3 Feb 2026

Viewed by 842

Abstract

Selenium contamination in arid agricultural basins remains a key ecological concern, yet the Wister Unit of the Imperial Wildlife Area has received comparatively little hydrochemical study. This investigation provides the most integrated assessment to date of selenium, salinity, nitrate, stable water isotopes (δ [...] Read more.

Selenium contamination in arid agricultural basins remains a key ecological concern, yet the Wister Unit of the Imperial Wildlife Area has received comparatively little hydrochemical study. This investigation provides the most integrated assessment to date of selenium, salinity, nitrate, stable water isotopes (δ²H and δ¹⁸O), and selected redox-sensitive trace elements within the Wister Unit and its contributing open agricultural drains, with the goal of identifying controls on selenium concentrations and mobility. Water samples from open agricultural drains, shallow groundwater tile drains, canal project water, and tailwater return flow were analyzed for Total Dissolved Solids (TDS), major ions, nutrients, selenium, and stable water isotopes. A subset of samples was anlayzed for iron, manganese, and vanadium. Overall, 71% of open drain and tile drain samples collected in this study exceeded the U.S. Environmental Protection Agency aquatic-life criterion of 5 µg/L, indicating persistent ecological risk. All waters plotted along an evaporation trajectory originating from imported Colorado River irrigation water; however, isotopic enrichment did not scale directly with salinity. Pure evaporation models predicted much lower TDS values than observed, and the most evaporated samples were not the most saline or selenium-rich. These results demonstrate that simple soil water evaporation alone cannot explain the data. Instead, the broad isotopic range at similar salinities reflects a secondary process in which salts that accumulated in soils during dry or average years are later mobilized and flushed during periods of surplus water and heavy irrigation. Low dissolved iron, manganese, and vanadium concentrations in a subset of water samples indicate predominantly oxidizing conditions, under which selenium behaves conservatively during salt leaching, producing a strong correlation with TDS. Selenium levels measured in Wister Unit are generally lower than those reported in nearby areas during the 1990s–2000s, implying changes in salt accumulation, hydrologic routing, or agricultural practices. These results refine the conceptual model for the Wister Unit and motivate future work on selenium speciation, nitrate isotope tracing, time series monitoring, and soil-salt interactions. Full article

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19 pages, 5086 KB

Open AccessArticle

Online Monitoring of Heavy Metals in Groundwater: A Case Study of Dynamic Behavior, Monitoring Optimization and Early Warning Performance

by Shuping Yi, Yi Deng, Pizhu Huang, Yi Liu, Xuerong Zhang and Yi Shen

Hydrology 2026, 13(2), 57; https://doi.org/10.3390/hydrology13020057 - 2 Feb 2026

Viewed by 538

Abstract

Groundwater heavy metal contamination (GHMC) has drawn significant attention in China over recent decades due to industrialization. However, effective monitoring and early warning remain global challenges because of the limited understanding of heavy metal behavior in groundwater. This study conducts a detailed comparative [...] Read more.

Groundwater heavy metal contamination (GHMC) has drawn significant attention in China over recent decades due to industrialization. However, effective monitoring and early warning remain global challenges because of the limited understanding of heavy metal behavior in groundwater. This study conducts a detailed comparative analysis of heavy metals and conventional indicators using a long-term, high-frequency online monitoring program. Groundwater online monitoring is an automated system for real-time, continuous collection, and transmission of indicators via sensors and IoT platforms. Conventional indicators refer to the priority parameters used to assess basic water quality, hydrological characteristics and health risks in routine monitoring. Nineteen heavy metals and ten conventional indicators were monitored simultaneously, generating approximately 1.6 million data points over three years. The time series data show that online monitoring effectively captures abnormal changes in heavy metal levels. Abnormal heavy metal fluctuations appear as sharp, isolated spikes lasting at least several hours, while conventional indicators exhibit high-amplitude variations lasting over 30 h—indicating that heavy metal changes are harder to detect in a timely manner. Long-term comparisons also reveal low consistency between heavy metals and conventional indicators, supporting the need for independent heavy metal monitoring. In contrast, strong consistency among heavy metals suggests opportunities to streamline monitoring by selecting representative elements. Monitoring frequency optimization shows that daily measurement is sufficient for heavy metals, which is slightly more frequent than the typical three-day interval for most conventional indicators. Long-term data enable reliable early warnings for both indicator types, with predictions closely matching field observations. However, heavy metal alerts are shorter and less frequent than those for conventional indicators. Integrating both types into a unified early warning system enhances its comprehensiveness, accuracy and timeliness. This study provides a solid scientific foundation for efficient GHMC monitoring and early warning in groundwater in areas under the influence of industrial activities. Full article

(This article belongs to the Topic Critical Issues in Groundwater Pollution Monitoring and Risk Warning)

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29 pages, 15995 KB

Open AccessEditor’s ChoiceArticle

Investigating the Influence of Geological Uncertainty on Urban Hydrogeological Modeling

by Charalampos Ntigkakis, Stephen Birkinshaw and Ross Stirling

Hydrology 2026, 13(2), 56; https://doi.org/10.3390/hydrology13020056 - 2 Feb 2026

Viewed by 824

Abstract

Groundwater models form the basis for investigating subsurface processes that relate to groundwater flow. Urban cover, however, usually inhibits the collection of new subsurface or geological data. Therefore, models usually depend on existing, poor-quality, or scarce datasets. The geological domain is an integral [...] Read more.

Groundwater models form the basis for investigating subsurface processes that relate to groundwater flow. Urban cover, however, usually inhibits the collection of new subsurface or geological data. Therefore, models usually depend on existing, poor-quality, or scarce datasets. The geological domain is an integral part of any groundwater model, and as such, understanding the model’s sensitivity to the geological interpretation is key to constraining uncertainty. This research uses a recent advancement in mitigating uncertainty in geological modeling to investigate how different geological interpretations affect groundwater model uncertainty. Using the Ouseburn catchment, Newcastle upon Tyne, UK, as a case study, it estimates baseflows and uses them to develop an ensemble of coupled distributed groundwater recharge and groundwater flow models using SWAc and MODFLOW, and performs a Monte Carlo analysis on the different model formulations. Results indicate that even though river baseflows are not highly affected, there is a connection between simulated groundwater level sensitivity and areas of high geological uncertainty. As the interest in the urban subsurface grows, constraining uncertainty in groundwater models is especially important for urban planning, policy making, water resources, and groundwater flooding protection. Therefore, constraining uncertainty from geological datasets is key to robust groundwater modeling. Full article

(This article belongs to the Topic Advances in Hydrogeological Research)

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18 pages, 3225 KB

Open AccessEditor’s ChoiceArticle

Using High-Resolution Hydrodynamic Models to Assess the Environmental Status of Highly Modified Transitional Waters in Salt Marshes

by Cira Buonocore, Juan J. Gomiz-Pascual, Ander López Puertas, Óscar Álvarez Esteban, Rafael Mañanes, María L. Pérez Cayeiro, Alfredo Izquierdo González, Antonio Gómez Ferrer, Noelia P. Sobrino González and Miguel Bruno

Hydrology 2026, 13(2), 55; https://doi.org/10.3390/hydrology13020055 - 2 Feb 2026

Viewed by 552

Abstract

Effective management of transitional waters requires collaboration between administrative and scientific institutions, in line with the sustainable water management principles established by the Water Framework Directive (WFD, 2000/60/EC). The Cadiz and San Fernando salt marshes, classified as wetlands of international importance, currently exhibit [...] Read more.

Effective management of transitional waters requires collaboration between administrative and scientific institutions, in line with the sustainable water management principles established by the Water Framework Directive (WFD, 2000/60/EC). The Cadiz and San Fernando salt marshes, classified as wetlands of international importance, currently exhibit an ecological and chemical status that is “worse than good.” However, there is still a lack of high-resolution, spatially explicit tools to identify where contaminants are most likely to accumulate in highly modified transitional waters, which limits effective monitoring and management strategies. This study aims to fill this gap by combining a high-resolution hydrodynamic model with a Lagrangian-particle-tracking approach to determine areas most vulnerable to contaminant accumulation from wastewater discharges. Simulations across multiple tidal cycles revealed that contamination is concentrated near discharge points and in low-flow channels, with tidal dynamics strongly influencing transport patterns. Key findings indicate that certain marsh sectors consistently experience higher contaminant exposure, highlighting priority areas for monitoring and management. The study provides novel insights by integrating modeling tools to produce a vulnerability classification of high-, medium-, and low-risk zones. These results contribute to the broader scientific understanding of contaminant dynamics in transitional waters and offer a transferable framework for improving wetland management in other heavily modified coastal systems. 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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31 pages, 5823 KB

Open AccessEditor’s ChoiceArticle

Integrated Hydrological and Water Allocation Modelling for Drought Management and Restriction Planning in a Regulated River Basin: Application to the Olt River Basin (Romania)

by Maria Ilinca Chevereșan, Cristian Ștefan Dumitriu, Mihai Valentin Stancu and Alina Bărbulescu

Hydrology 2026, 13(2), 54; https://doi.org/10.3390/hydrology13020054 - 1 Feb 2026

Viewed by 564

Abstract

Effective Water Resource Management (WRM) requires the integration of physical hydrological processes with institutional drought response plans. In Romania, the Olt River Basin represents one of the most highly regulated catchments, where water security is maintained through a series of staged restriction measures [...] Read more.

Effective Water Resource Management (WRM) requires the integration of physical hydrological processes with institutional drought response plans. In Romania, the Olt River Basin represents one of the most highly regulated catchments, where water security is maintained through a series of staged restriction measures (TR1–TR3). However, the efficacy of these measures under the shifting baselines of the SSP2-4.5 climate scenario remains poorly understood. This study addresses this gap by coupling rainfall–runoff dynamics with a priority-based allocation model to evaluate the reliability of current drought protocols in a climate-perturbed future. Rainfall–runoff modelling, reservoir operation, priority-based allocation, environmental flow constraints, and officially applied drought restriction plans were combined within a single modelling environment. Under the SSP2-4.5 climate scenario, total basin runoff decreased by approximately 13.3%, leading to more frequent activation of restriction stages and reduced allocation reliability. Full article

(This article belongs to the Special Issue Sustainable Water Management in the Face of Drastic Climate Change)

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24 pages, 3870 KB

Open AccessArticle

Hybrid Ensemble Learning for TWSA Prediction in Water-Stressed Regions: A Case Study from Casablanca–Settat Region, Morocco

by Youssef Laalaoui, Naïma El Assaoui, Oumaima Ouahine, Thanh Thi Nguyen and Ahmed M. Saqr

Hydrology 2026, 13(2), 53; https://doi.org/10.3390/hydrology13020053 - 1 Feb 2026

Cited by 1 | Viewed by 1595

Abstract

A hybrid machine learning framework has been developed in this study to estimate Terrestrial Water Storage Anomalies (TWSA) in Morocco’s Casablanca–Settat region, which faces serious groundwater stress due to rapid urbanization, intensive agriculture, and climate variability. In this study, TWSA is used as [...] Read more.

A hybrid machine learning framework has been developed in this study to estimate Terrestrial Water Storage Anomalies (TWSA) in Morocco’s Casablanca–Settat region, which faces serious groundwater stress due to rapid urbanization, intensive agriculture, and climate variability. In this study, TWSA is used as an integrated proxy for groundwater-related storage changes, while acknowledging that it also includes contributions from soil moisture and surface water. The approach combines satellite-based observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) with key environmental indicators such as rainfall, evapotranspiration, and land use data to track changes in groundwater availability with improved spatial detail. After preprocessing the data through feature selection, normalization, and outlier handling, the model applies six base learners, i.e., Huber regressor, automatic relevance determination regression, kernel ridge, long short-term memory, k-nearest neighbors, and gradient boosting. Their predictions are aggregated using a random forest meta-learner to improve accuracy and stability. The ensemble achieved strong results, with a root mean square error of 0.13, a mean absolute error of 0.108, and a determination coefficient of 0.97—far better than single-model baselines—based on a temporally independent train-test split. Spatial analysis highlighted clear patterns of groundwater depletion linked to land cover and usage. These results can guide targeted aquifer recharge efforts, drought response planning, and smarter irrigation management. The model also aligns with national goals under Morocco’s water sustainability initiatives and can be adapted for use in other regions with similar environmental challenges. Full article

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

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16 pages, 2412 KB

Open AccessArticle

Daily and Monthly Scale Comparisons of Three Gridded Precipitation Datasets over the British Columbia Province, Canada

by Riki Ogawa, Yoshihiko Iseri, M. Levent Kavvas and Angela M. Duren

Hydrology 2026, 13(2), 52; https://doi.org/10.3390/hydrology13020052 - 1 Feb 2026

Viewed by 686

Abstract

Understanding the characteristics of precipitation datasets in a given region is crucial for hydrological studies. This study focuses on the British Columbia (BC) Province in Canada and evaluates the statistical characteristics of precipitation data from three gridded precipitation datasets: the Pacific Climate Impacts [...] Read more.

Understanding the characteristics of precipitation datasets in a given region is crucial for hydrological studies. This study focuses on the British Columbia (BC) Province in Canada and evaluates the statistical characteristics of precipitation data from three gridded precipitation datasets: the Pacific Climate Impacts Consortium’s northwestern North America meteorological dataset (PNWNAmet), Global Precipitation Measurement (GPM), and Global Precipitation Climatology Centre (GPCC). These precipitation datasets at both daily and monthly scales were compared with point observation data from the Global Historical Climatology Network (GHCN). For the daily-scale comparison of three precipitation datasets, seven indices of extreme precipitation were computed at ten observation points. Out of eleven locations for the monthly analysis, GPCC showed the lowest RMSE at six locations (five of them were in the northern to central BC), and PNWNAmet showed the lowest RMSE at four locations (three of them were in the southern BC), suggesting GPCC’s superior agreements with GHCN at the northern and central part of BC and PNWNAmet’s better agreements with GHCN at the southern part of BC. The comparison of monthly precipitation averaged over BC showed that PNWNAmet offers higher monthly precipitation than GPCC and GPM, while the variability of annual precipitation among the three datasets is similar. Spatial analysis of precipitation–elevation relationships revealed the value of considering both elevation and distance from the coast in evaluating the precipitation–elevation relationships. Full article

(This article belongs to the Special Issue Hydrological Modeling and Sustainable Water Resources Management, 2nd Edition)

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29 pages, 3650 KB

Open AccessArticle

Decoding LSTM to Reveal Baseflow Contributions in Fractured and Sedimentary Mountain Basins: A Case Study in the Sangre de Cristo Mountains, Southwestern United States

by Michael Rosati, Yeo H. Lim, Katie Zemlick and Kamran Syed

Hydrology 2026, 13(2), 51; https://doi.org/10.3390/hydrology13020051 - 1 Feb 2026

Viewed by 502

Abstract

This study investigates how a Long Short-Term Memory (LSTM) model internally represents baseflow contributions in snowmelt-driven, semi-arid mountain basins with heterogeneous geologic characteristics. Five basins in the Sangre de Cristo Mountains of northern New Mexico, spanning fractured Precambrian bedrock and sedimentary-volcanic terrain, were [...] Read more.

This study investigates how a Long Short-Term Memory (LSTM) model internally represents baseflow contributions in snowmelt-driven, semi-arid mountain basins with heterogeneous geologic characteristics. Five basins in the Sangre de Cristo Mountains of northern New Mexico, spanning fractured Precambrian bedrock and sedimentary-volcanic terrain, were used to evaluate both model performance and interpretability. Baseflow dynamics were inferred post hoc using the Baseflow Index (BFI) and a two-reservoir HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System) model. Although baseflow components were not explicitly included in model training, internal cell state activations exhibited strong correlations with both shallow and deep baseflow components derived from the HEC-HMS model. To better understand how these relationships may change under climatic stress, BFI-based baseflow patterns were further analyzed under pre-drought and drought conditions. Results indicate that the internal LSTM states differentiated patterns consistent with short- and long-residence flow paths, reflecting physically interpretable hydrologic behavior. This work demonstrates the potential of LSTM models to provide valuable insights into baseflow generation and groundwater–surface water interactions, which is especially critical in water-scarce regions facing increasing drought frequency. Full article

(This article belongs to the Special Issue Machine Learning Applications in Soil Water and Groundwater Assessment)

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20 pages, 5161 KB

Open AccessArticle

Copula-Based Bayesian Inference Approaches for Uncertainty Quantification for Hydrological Simulation

by Feng Wang, Ruixin Duan, Jiannan Zhang, Mengyu Zhai, Yanfeng Li, Yurui Fan and Yulei Xie

Hydrology 2026, 13(2), 50; https://doi.org/10.3390/hydrology13020050 - 29 Jan 2026

Viewed by 751

Abstract

In this study, an advanced copula-based Bayesian inference framework is proposed to characterize probabilistic features in hydrological simulations. Specifically, a Copula–Metropolis–Hastings (CopMH) algorithm is developed through integrating copula functions into the conventional Metropolis–Hastings (MH) algorithm within an interdependence-sampling framework. In CopMH, the interdependence [...] Read more.

In this study, an advanced copula-based Bayesian inference framework is proposed to characterize probabilistic features in hydrological simulations. Specifically, a Copula–Metropolis–Hastings (CopMH) algorithm is developed through integrating copula functions into the conventional Metropolis–Hastings (MH) algorithm within an interdependence-sampling framework. In CopMH, the interdependence structure among model parameters is quantified using copula functions, which are subsequently employed to generate proposal candidates. The proposed approach is then applied to uncertainty analysis in hydrological simulations of the Ruihe River watershed in Northwest China. The results indicate that, compared with the traditional MH, incorporating copula-based proposal distributions significantly improves convergence efficiency and simulation accuracy, as inter-parameter dependence is more effectively captured. All algorithms are independently repeated 15 times, and CopMH exhibits more robust and stable performance than MH. Furthermore, the intercorrelation analysis of hydrological model parameters reveals that interactive effects among parameters are ubiquitous. These findings highlight that consideration of the interrelationship among the parameters in hydrologic models is meaningful and necessary for uncertainty quantification of hydrological simulation. This study demonstrates the strong potential of the proposed CopMH approach for effectively quantifying and reducing parameter uncertainty in hydrological simulations. Full article

(This article belongs to the Special Issue Hydrological Modeling and Sustainable Water Resources Management, 2nd Edition)

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26 pages, 6002 KB

Open AccessArticle

Analyzing Multisource Hydrological Variability for Precise Water Allocation in an Arid Terminal Lake: A Case Study of Taitema Lake, Northwest China

by Shuo Zhang, Guang Yang, Yun Zhang and Hongbo Ling

Hydrology 2026, 13(2), 49; https://doi.org/10.3390/hydrology13020049 - 28 Jan 2026

Viewed by 436

Abstract

Terminal lakes in arid regions are highly vulnerable to climate variability and human water management, yet their long-term hydrological responses under multi-river regulation remain insufficiently quantified. Using Taitema Lake at the terminus of the Tarim Basin as a case study, this research integrates [...] Read more.

Terminal lakes in arid regions are highly vulnerable to climate variability and human water management, yet their long-term hydrological responses under multi-river regulation remain insufficiently quantified. Using Taitema Lake at the terminus of the Tarim Basin as a case study, this research integrates Landsat and Sentinel observations (2005–2025) with meteorological and river-inflow records to examine lake area dynamics and to identify river-specific hydrological controls. The results show pronounced intra- and interannual variability, with the lake expanding to a maximum of 461.52 km² in October 2017 and shrinking to 0.35 km² in October 2008. High-frequency permanent water (~43 km²) is concentrated in the deep central basin and largely influenced by the Qarqan River, whereas seasonal water (~300 km²) is broadly distributed and strongly affected by ecological releases from the Tarim River. Quantified inflow–area relationships indicate that the lake expands by 7–14 km² for each 0.1 × 10⁸ m³ of inflow. Based on frequency-based hydrological analysis, this study develops joint inflow strategies for wet, normal, and dry years, offering a practical hydrological basis for more precise and adaptive water allocation schemes in arid terminal lakes. Full article

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26 pages, 4766 KB

Open AccessArticle

Built-Up Fraction and Residential Expansion Under Hydrologic Constraints: Quantifying Effects of Terrain, Groundwater and Vegetation Root Depth on Urbanization in Kunming, China

by Chunying Shen, Zhenxiang Zang, Shasha Meng, Honglei Tang, Changrui Qin, Dehui Ning, Yuanpeng Wu, Li Zhao and Zheng Lu

Hydrology 2026, 13(2), 48; https://doi.org/10.3390/hydrology13020048 - 28 Jan 2026

Viewed by 447

Abstract

Urbanization in mountainous regions alters hydrologic systems, yet the spatial patterning of residential (RA) and non-residential (NRA) areas in response to hydrologic constraints remains poorly quantified. In this study, we analyzed how such constraints shaped the distinct locational logic of RA and NRA [...] Read more.

Urbanization in mountainous regions alters hydrologic systems, yet the spatial patterning of residential (RA) and non-residential (NRA) areas in response to hydrologic constraints remains poorly quantified. In this study, we analyzed how such constraints shaped the distinct locational logic of RA and NRA expansion in the mountainous Kunming Core Region (KCR), Southwest China, from 1975 to 2020. Using the Global Human Settlement Layer (GHS-BUILT-S) built-up fraction data and its functionally classified RA and NRA layers at 100 m resolution, we quantified multi-decadal urban land changes via regression and centroid migration analyses. Six hydrologic factors, namely altitude, slope, surface roughness, distance to river (DTR), depth to water table (DTWT) and vegetation root depth (VRD), were derived from global terrain, groundwater, and rooting depth datasets, and harmonized to a common grid. Results show a two-phase urbanization pattern: moderate, compact growth before 1995 followed by rapid, near-exponential expansion, dominated by RA. RA consistently clustered in hydrologically favorable zones (low–moderate roughness, mid-altitudes, lower slopes, proximal rivers, shallow–moderate DTWT, moderate VRD), whereas NRA expanded into more hydrologically variable terrain (higher roughness, intermediate DTR, deeper DTWT, higher altitudes, deeper VRD). Contribution-weighting analysis revealed a temporal shift in dominant drivers: for RA, from river proximity and slope in 1975 to terrain roughness in 2020; for NRA, from vegetation root depth and moderate topography to root depth plus altitude. Geographic centroids of both RA and NRA migrated northeastward, indicating coordinated yet functionally distinct peri-urban and corridor-oriented growth. These findings provide a hierarchical, factor-based framework for integrating hydrologic constraints into risk-informed land-use planning in topographically complex basins. Full article

(This article belongs to the Section Hydrology and Economics/Human Health)

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20 pages, 12209 KB

Open AccessArticle

Designing for the Past in a Nonstationary Climate: Evidence from Cyclone Ditwah’s Extreme Rainfall in Sri Lanka

by Chamal Perera, Nadee Peiris, Luminda Gunawardhana, Lalith Rajapakse, Nimal Wijayaratna, Binal Chatura Dissanayake and Kasun De Silva

Hydrology 2026, 13(2), 47; https://doi.org/10.3390/hydrology13020047 - 28 Jan 2026

Viewed by 2600

Abstract

The November 2025 extreme rainfall event associated with Tropical Cyclone Ditwah caused catastrophic flooding and landslides across Sri Lanka. This study presents a national-scale statistical and Intensity–Duration–Frequency (IDF)-based assessment of the event using long-term rain gauge observations, extreme value analysis, and climate scenario-based [...] Read more.

The November 2025 extreme rainfall event associated with Tropical Cyclone Ditwah caused catastrophic flooding and landslides across Sri Lanka. This study presents a national-scale statistical and Intensity–Duration–Frequency (IDF)-based assessment of the event using long-term rain gauge observations, extreme value analysis, and climate scenario-based projections. The 24-h rainfall data from 46 stations were analyzed for 1-, 2-, and 3-day durations. Historical annual maximum series were extracted and compared with the 2025 event to identify record-breaking extremes. Rainfall volumes were also estimated and compared with the island’s Average Annual Rainfall (AAR) and volumes from major flood events in 2010 and 2016. The November 2025 event exceeded historical maxima at 14 stations, with estimated return periods frequently surpassing 1000 years. The cumulative rainfall volume from 26–28 November accounted for 15.8% of Sri Lanka’s AAR. Updated IDF curves incorporating the event showed marked upward shifts, with intensities at some locations matching or exceeding projections under high-emission climate scenarios. The results highlight the inadequacy of existing design standards in capturing emerging extremes and the need for urgent updates to Sri Lanka’s national IDF relationships to support climate-resilient flood risk management and infrastructure planning. Full article

(This article belongs to the Section Statistical Hydrology)

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28 pages, 6966 KB

Open AccessEditor’s ChoiceArticle

Comparing HEC-HMS and HEC-RAS for Continuous, Rain-on-Grid, Urban Watershed Modeling

by Ashmita Poudel and Jose G. Vasconcelos

Hydrology 2026, 13(2), 46; https://doi.org/10.3390/hydrology13020046 - 28 Jan 2026

Viewed by 1748

Abstract

The application of two-dimensional (2D) hydrologic and hydraulic modeling tools is increasing for overland flow simulation, as they represent spatial changes in depth, velocity, and flow conditions more accurately. Recently, the US Army Corps HEC-HMS (Hydrologic Engineering Center Hydrologic Modeling System) added the [...] Read more.

The application of two-dimensional (2D) hydrologic and hydraulic modeling tools is increasing for overland flow simulation, as they represent spatial changes in depth, velocity, and flow conditions more accurately. Recently, the US Army Corps HEC-HMS (Hydrologic Engineering Center Hydrologic Modeling System) added the capability to import an unstructured 2D mesh, which enables the routing of excess precipitation across the mesh, as a fully distributed hydrological model. In HEC-HMS, the 2D diffusion-wave component functions as a hydrologic transform representing overland flow routing. In contrast, HEC-RAS 2D (Hydrologic Engineering Center-River Analysis System), initially applied to river flow simulation, can apply either the 2D shallow-water equations or the 2D diffusion-wave option. Similarly to HEC-HMS, HEC-RAS also includes rain-on-grid (RoG) capability and infiltration algorithms, and in this fashion has some hydrological modeling capabilities. Still, while HEC-HMS is capable of representing extended-period hydrological simulations, HEC-RAS hydrological capabilities are limited to event-based simulations, as there are no provisions to represent abstractions such as evapotranspiration or groundwater/baseflow contributions together. Studies performing a direct comparison between the HEC-HMS RoG and HEC-RAS RoG approaches for representing urban hydrology remain scarce. This study aims to fill that gap by assessing their performance in Moore’s Mill Creek Watershed, in Lee County, Alabama, with a focus on continuous rainfall-runoff modeling. Both models run on the same unstructured mesh and use identical rainfall, terrain, land-use, and soil data. Model simulations are compared over an extended period to evaluate simulated depth, velocity, and flow hydrographs against field observations. The comparison shows HEC-HMS’s superior performance for extended simulation and provides practical guidance on parameter alignment, data needs, and tool selection. Full article

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Hydrology, Volume 13, Issue 2 (February 2026) – 33 articles

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