Hydrology

17 pages, 649 KB

Open AccessReview

Advances and Challenges in Dew Research on Land Surface: A Review

by Hongyuan Li, Chuntan Han, Yong Yang and Rensheng Chen

Hydrology 2025, 12(12), 320; https://doi.org/10.3390/hydrology12120320 - 5 Dec 2025

Dew, a key component of Non-Rainfall Water Inputs (NRWIs), plays a disproportionately significant role in land–atmosphere interactions. This review synthesizes advances in understanding its ecological, hydrological, and environmental effects, quantification methods, and spatiotemporal variations. A key finding is the regional dichotomy of dew [...] Read more.

Dew, a key component of Non-Rainfall Water Inputs (NRWIs), plays a disproportionately significant role in land–atmosphere interactions. This review synthesizes advances in understanding its ecological, hydrological, and environmental effects, quantification methods, and spatiotemporal variations. A key finding is the regional dichotomy of dew effects: in arid regions, it is a crucial hydrological source, whereas in humid/alpine regions, its energy-balance regulation via latent heat release often outweighs its hydrological contribution. Significant challenges persist, including methodological inconsistencies, an overreliance on point-scale data from arid zones, and an underappreciation of dew’s energy impacts, particularly in cold regions. Recent studies suggest a general declining trend in dew frequency and amount in many arid regions, which could exacerbate water stress for dependent ecosystems. However, regional heterogeneities and interactions with other NRWIs remain poorly constrained. Future research must overcome observational bottlenecks, deepen energy–water coupling studies, quantify climate change impacts, expand research to underrepresented regions, and integrate multi-method approaches to improve model predictability, thereby supporting ecosystem resilience and water security under global change. Full article

(This article belongs to the Section Ecohydrology)

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23 pages, 3017 KB

Open AccessArticle

Water Resource Allocation Considering the Effects of Emergency Supply Augmentation Costs and Water Use Compression Losses Under Extreme Drought Conditions

by Chentao He, Xi Guo and Zening Wu

Hydrology 2025, 12(12), 319; https://doi.org/10.3390/hydrology12120319 - 4 Dec 2025

Abstract

Extreme drought intensifies the complexity of the water resource allocation system, and unreasonable water distribution exacerbates drought losses. Drought mitigation measures such as emergency water supply augmentation and water use compression incur additional costs or losses, thereby compromising the accuracy of water allocation [...] Read more.

Extreme drought intensifies the complexity of the water resource allocation system, and unreasonable water distribution exacerbates drought losses. Drought mitigation measures such as emergency water supply augmentation and water use compression incur additional costs or losses, thereby compromising the accuracy of water allocation outcomes. To address the insufficient consideration of the impacts of emergency water supply augmentation and water use compression measures under extreme drought conditions in current research, this study employs emergy theory to systematically identify and quantify the emergency water supply augmentation costs and water use compression losses. A dual-objective water resource allocation model was constructed under extreme drought conditions by taking the minimization of the sum of the emergency water supply augmentation costs and water use compression losses as the comprehensive loss objective, and the minimization of the total water scarcity as the water use guarantee objective. The model was subsequently transformed into a single-objective optimization problem for solution. The allocation model was applied to the typical severe drought scenario in Chuxiong Prefecture of Yunnan Province in 2011. The results demonstrate that the scheme implementing both measures reduced comprehensive losses by 4.97 × 10¹⁹ sej and total water shortage by 7.02 × 10⁶ m³ compared to the scheme excluding these measures. The water resource allocation model considering emergency water supply augmentation costs and water use compression losses can effectively mitigate the drought impact in the study area. Full article

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

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Graphical abstract

17 pages, 3294 KB

Open AccessArticle

Detecting 3D Anomalies in Soil Water from Saline-Alkali Land of Yellow River Delta Using Sampling Data

by Zhoushun Han, Xin Fu, Haoran Zhang, Yang Li, Lehang Tang, Hengcai Zhang and Zhenghe Xu

Hydrology 2025, 12(12), 318; https://doi.org/10.3390/hydrology12120318 - 1 Dec 2025

Abstract

Understanding soil water in the saline-alkali lands is crucial for sustainable agriculture and ecological restoration. Existing studies have largely focused on macroscopic distribution and associated interpolation techniques, which complicates the precise identification of localized anomalous regions. To address this limitation, this study proposes [...] Read more.

Understanding soil water in the saline-alkali lands is crucial for sustainable agriculture and ecological restoration. Existing studies have largely focused on macroscopic distribution and associated interpolation techniques, which complicates the precise identification of localized anomalous regions. To address this limitation, this study proposes a novel three-dimensional detection method for localized soil water anomalies (3D-SWLA). Utilizing soil water sampling data, a comprehensive three-dimensional soil water cube is constructed through 3D Empirical Bayesian Kriging (3D EBK). We introduce the Soil Water Local Anomaly Index (SWLAI) and apply a second-order difference method to effectively identify and filter anomalous voxels. Then, the 3D Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is utilized to cluster Soil Water Anomalous Voxels (SWAVs), thereby delineating three-dimensional Local Anomalous Soil Water Areas (LASWAs) with precision and robustness. A series of experiments were conducted in Kenli to validate the proposed methodology. The results reveal that 3D-SWLA successfully identified a total of 8 Local Anomalous Soil Water Areas (LASWAs), four of which—classified as large-scale anomalies (area > 1.0 km²)—are predominantly concentrated in the northeastern coastal zone and the southern salt fields. The largest among them, LASWA-1, spans 1.8 km² with a vertical depth ranging from 0 to 35 cm and an average soil water content of 0.36. Another significant anomaly, LASWA-8, covers 1.5 km², extends to a depth of 0–60 cm, and exhibits a higher average water content of 0.42, reflecting distinct hydrological dynamics in these regions. Additionally, 4 smaller LASWAs (area < 1.0 km²) are spatially distributed along the northeastern irrigation channels, indicating localized moisture accumulation likely influenced by agricultural water management. Full article

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24 pages, 16248 KB

Open AccessArticle

Drivers and Future Risks of Groundwater Projection in Tangshan, China: Integrating SHAP, Geographically Weighted Regression, and Climate–Land-Use Scenarios

by Arifullah, Yicheng Wang, Hejia Wang and Jia Liu

Hydrology 2025, 12(12), 317; https://doi.org/10.3390/hydrology12120317 - 30 Nov 2025

Abstract

Groundwater depletion causes a critical risk for the sustainability of urban and agricultural resilience in semi-arid regions such as Tangshan city. This study deployed an integrated framework that combines understandable machine learning (Shapley Additive exPlanations (SHAP), Geographically Weighted Regression (GWR), spatial autocorrelation (Local [...] Read more.

Groundwater depletion causes a critical risk for the sustainability of urban and agricultural resilience in semi-arid regions such as Tangshan city. This study deployed an integrated framework that combines understandable machine learning (Shapley Additive exPlanations (SHAP), Geographically Weighted Regression (GWR), spatial autocorrelation (Local Indicators of Spatial Association or LISA), and scenario-based recharge forecasting to evaluate the spatial drivers and patterns of groundwater stress and project potential future risks. Using spatial groundwater table data from 2022 and key environmental and anthropogenic variables such as evapotranspiration (ET), population, temperature, precipitation, and land use and land cover changes, an XGBoost (Extreme Gradient Boosting) regression model was trained to capture nonlinear spatial patterns. SHAP analysis found that ET and population density are prominent contributors to groundwater depletion in agricultural and urban zones. To capture spatial heterogeneity, GWR was utilized to estimate localized coefficients and construct a Vulnerability and Resilience Index (VRI) from normalized coefficients and residuals. LISA validated vulnerability zones and revealed transitional stress regions. Future risks are also projected using Coupled Model Intercomparison Project Phase 6 (CMIP6) climate data and land-use data to run recharge modeling from 2023 to 2049 for both representative concentration pathway (RCP) 4.5 and RCP 8.5. Results show that RCP 8.5 demonstrates highly unstable recharge with frequent negative episodes (ET > P), while RCP 4.5 shows relatively stable patterns of groundwater table. Furthermore, coupled with urban and agricultural expansion, RCP 8.5 intensifies depletion risks. This combined framework provides analytical understandings of spatial driver patterns and scenario-based risk assessments under climate and land use change. The findings of the study recommend priority zones for intervention and underline the importance of adaptive, scenario-sensitive groundwater governance in semi-arid, urbanizing regions. Full article

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20 pages, 12557 KB

Open AccessArticle

The Atmospheric Water Cycle over South America as Seen in the New Generation of Global Reanalyses

by Mário Francisco Leal de Quadro, Dirceu Luís Herdies, Ernesto Hugo Berbery, Caroline Bresciani, Fabrício Daniel dos Santos Silva, Helber Barros Gomes, Michel Nobre Muza, Cássio Aurélio Suski and Diego Portalanza

Hydrology 2025, 12(12), 316; https://doi.org/10.3390/hydrology12120316 - 29 Nov 2025

Abstract

We assess precipitation and key atmospheric water-cycle terms over South America (SA) in three modern reanalyses—MERRA-2, ERA5, and CFSR/CFSv2—during 1980–2021. Two observation-based datasets (CPC Unified Gauge and MSWEP-V2) serve as references to bracket observational uncertainty. Diagnostics include regional means for the Tropical and [...] Read more.

We assess precipitation and key atmospheric water-cycle terms over South America (SA) in three modern reanalyses—MERRA-2, ERA5, and CFSR/CFSv2—during 1980–2021. Two observation-based datasets (CPC Unified Gauge and MSWEP-V2) serve as references to bracket observational uncertainty. Diagnostics include regional means for the Tropical and Subtropical South Atlantic Convergence Zone (TSACZ, SSACZ) and southeastern South America (SESA), Taylor-diagram skill metrics, and a vertically integrated moisture-budget residual as a proxy for closure. All products reproduce the large-scale spatial and seasonal patterns, but disagreements persist over the Andes and parts of the central/northern Amazon. Relative to CPC/MSWEP-V2, MERRA-2 exhibits the smallest precipitation biases and the highest correlations, followed by ERA5; CFSR/CFSv2 shows a warm-season wet bias. Moisture-budget residuals are smallest in MERRA-2, moderate in ERA5, and largest in CFSR/CFSv2, with clear regional and seasonal dependence. These results document improvements in the new generation of reanalyses while highlighting persistent challenges in gauge-sparse and complex-orography regions. For hydroclimate applications that depend on internally consistent P, E, moisture-flux convergence, and runoff, MERRA-2 provides the most coherent depiction among the three, whereas ERA5 is a strong alternative when higher spatial/temporal resolution or dynamical fields are needed and CFSR/CFSv2 should be applied with caution for warm-season precipitation and closure-sensitive analyses. Full article

(This article belongs to the Special Issue Advances in the Measurement, Utility and Evaluation of Precipitation Observations: 2nd Edition)

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20 pages, 2522 KB

Open AccessArticle

The Estimation of Evapotranspiration Rates from Urban Green Infrastructure Using the Three-Temperatures Method

by Bruce Wickham, Simon De-Ville and Virginia Stovin

Hydrology 2025, 12(12), 315; https://doi.org/10.3390/hydrology12120315 - 27 Nov 2025

Abstract

The three-temperatures (3T) method is a robust approach to estimating evapotranspiration (ET), requiring relatively few measurable, physical parameters and an imitation surface, making it potentially suited for estimating ET from sustainable drainage systems (SuDS) and green infrastructure (GI) in urban environments. However, limited [...] Read more.

The three-temperatures (3T) method is a robust approach to estimating evapotranspiration (ET), requiring relatively few measurable, physical parameters and an imitation surface, making it potentially suited for estimating ET from sustainable drainage systems (SuDS) and green infrastructure (GI) in urban environments. However, limited 3T-ET data from SuDS and/or GI makes it difficult to assess the conditions that affect its accuracy. The purpose of this study was to determine whether reasonable ET estimates could be achieved using the 3T method with a plastic imitation surface for a small, homogenous vegetated surface. The 3T-ET estimates were produced at an hourly timestep and compared to reference ET (

E T_{o}

) derived using the Penman–Monteith equation. The 3T-ET estimates were consistently higher than

E T_{o}

(mean absolute error of 0.05 to 0.15 mm·h⁻¹), which may indicate systematic overestimation of ET or that the actual ET was greater than

E T_{o}

. Unrealistic 3T-ET estimates are produced when the air temperature and the imitation surface temperature converge, limiting the method’s application to between mid-morning and late afternoon. Further work to validate and refine the 3T method is required before it can be recommended for deployment in the field for spot-sampling ET rates from urban SuDS/GI. Full article

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29 pages, 48540 KB

Open AccessArticle

Morphostructural Controls Reflected in Drainage Patterns

by Raissa Eduarda da Silva Archanjo, Pablo César Serafim, Bruno César dos Santos, Vandoir Bourscheidt, Rodrigo Martins Moreira, Nelson Ferreira Fernandes, Paulo Henrique Souza, Ronaldo Luiz Mincato and Felipe Gomes Rubira

Hydrology 2025, 12(12), 314; https://doi.org/10.3390/hydrology12120314 - 26 Nov 2025

Abstract

The drainage network of the Upper Araguari River, Brazil, developed within an intraplate setting characterized by the Brasiliano structural inheritance, Mesozoic magmatism, and marked lithological contrasts. Although these factors strongly influence fluvial organization, gaps remain in how litho-structural controls modulate fluvial transience and [...] Read more.

The drainage network of the Upper Araguari River, Brazil, developed within an intraplate setting characterized by the Brasiliano structural inheritance, Mesozoic magmatism, and marked lithological contrasts. Although these factors strongly influence fluvial organization, gaps remain in how litho-structural controls modulate fluvial transience and divide stability in intraplate regions. We hypothesize that drainage systems constrained by structural controls and resistant lithologies exhibit higher k_sn values, larger χ offsets, greater knickpoint frequency, and less stable divides than systems developed on friable substrates. To test this hypothesis, we applied integrated morphometric metrics (χ parameter, normalized channel steepness index—k_sn, knickpoints, roughness concentration index—Rci, stream frequency—Sf, drainage density—Dd, and lineaments) across 23 sub-basins to assess how the litho-structural conditions influence the drainage patterns, the fluvial gradients, the equilibrium states, and the divide stability. We identified 57 knickpoints and high k_sn values concentrated in quartzitic and basaltic terrains and along fault zones. χ-plot offsets near quartzite–phyllite/schist contacts indicate transient fronts slowed by differential erodibility, whereas catchments developed on friable substrates respond more rapidly to perturbations. Trellis, rectangular, parallel, and radial drainage patterns exhibit greater instability, underscoring the integrated role of lithological contrasts and tectonic reactivations in modulating intraplate fluvial transience. Full article

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

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19 pages, 2459 KB

Open AccessArticle

Multivariate RVA Assessment of Hydrological Alterations: Huangshui River, Xining

by Wanqi Wang, Hao Wang, Feng Wang, Xiaohui Lei, Xiaoyan Wei and Kang Li

Hydrology 2025, 12(12), 313; https://doi.org/10.3390/hydrology12120313 - 26 Nov 2025

Abstract

Indicators of Hydrologic Alteration (IHA) are commonly screened with the Range of Variability Approach (RVA), which captures frequency shifts but can miss changes in central tendency, dispersion, distributional shape, and trend. We propose a Comprehensive Degree (CD) index that integrates RVA with these [...] Read more.

Indicators of Hydrologic Alteration (IHA) are commonly screened with the Range of Variability Approach (RVA), which captures frequency shifts but can miss changes in central tendency, dispersion, distributional shape, and trend. We propose a Comprehensive Degree (CD) index that integrates RVA with these four statistical dimensions and apply it to daily discharge at the Xining station on the Huangshui River (1954–2022). Using conventional RVA, the overall alteration was 61.16% (moderate). After integration, alteration increased by 7.59% to 68.75%, reclassifying the regime as high. Across 32 Indicators, 15 showed larger alteration and 12 moved up one class, whereas 17 decreased and 2 moved down. Distributional shape and trend dominated the signal, revealing strongly altered ecohydrological indicators—most notably low-pulse frequency/duration and 3-day minimum—and, additionally, flagging indicators that RVA downplays (e.g., April–August monthly flows) via high trend and distributional shape shifts. The framework addresses RVA’s frequency-only blind spots, is more robust to short-term or episodic fluctuations, and improves diagnostic precision and ecological interpretability. These results provide a decision-ready basis for adaptive environmental flow management in climatically sensitive, topographically complex plateau basins. Full article

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20 pages, 4437 KB

Open AccessArticle

Watershed Runoff Simulation and Prediction Based on BMA Coupled SWAT-LSTM Model

by Wenju Zhao, Yongwei Hao, Yongming Zhang, Haiying Yu and Xing Li

Hydrology 2025, 12(12), 312; https://doi.org/10.3390/hydrology12120312 - 24 Nov 2025

Abstract

In response to the issues of low runoff prediction accuracy and difficulty in parameter determination in regions frequently experiencing extreme hydrological events, this study is based on data such as digital elevation, land use, soil type, and meteorology. The SWAT-LSTM (Long Short-Term Memory) [...] Read more.

In response to the issues of low runoff prediction accuracy and difficulty in parameter determination in regions frequently experiencing extreme hydrological events, this study is based on data such as digital elevation, land use, soil type, and meteorology. The SWAT-LSTM (Long Short-Term Memory) model is coupled based on the Bayesian Model Averaging (BMA) method. The simulation accuracies of the optimized model are, respectively, compared with those of the SWAT (Soil and Water Assessment Tool) model and the SWAT-LSTM model. Taking the Zuli River Basin as an example, the optimal runoff prediction model for this basin is determined. Combining with future meteorological data, runoff predictions for the period from 2025 to 2030 are carried out. The findings indicate that the SWAT-LSTM-BMA coupled model is the optimal runoff prediction model for the Zuli River Basin. Compared with the SWAT model and the SWAT-LSTM model used alone, its simulation accuracy has been systematically improved. During the calibration period, R² increased by 8–12%, NSE increased by 9–13%, and MSE decreased by 14–30%. During the validation period, R² increased by 10–12%, NSE increased by 10–14%, and MSE decreased by 16–31%. Based on the model and the prediction of future climate data under multiple scenarios, the annual runoff of the basin will show a decreasing trend compared with the historical period between 2025 and 2030, with a decrease of 12–15%. The coupling framework proposed in this study effectively improves the accuracy of runoff prediction and provides a reliable theoretical foundation and technological assistance for revealing the evolution law of extreme hydrological events and the management of water resources in the basin. Full article

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

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16 pages, 2253 KB

Open AccessArticle

Coupled Impacts of Bed Erosion and Roughness Variation on Stage-Discharge Relationships: A 1D Hydrodynamic Modeling Analysis of the Regulated Jingjiang Reach

by Yanqing Li, Minglong Dai, Dongdong Zhang and Yingqi Chen

Hydrology 2025, 12(12), 311; https://doi.org/10.3390/hydrology12120311 - 22 Nov 2025

Abstract

The stage-discharge relationship in the Jingjiang Reach of the Yangtze River has undergone significant alterations due to post-Three Gorges Reservoir (TGR) operation effects, notably bed erosion and roughness variation. This study employs a calibrated 1D hydrodynamic model based on Saint-Venant equations. The model [...] Read more.

The stage-discharge relationship in the Jingjiang Reach of the Yangtze River has undergone significant alterations due to post-Three Gorges Reservoir (TGR) operation effects, notably bed erosion and roughness variation. This study employs a calibrated 1D hydrodynamic model based on Saint-Venant equations. The model was validated with high accuracy (Nash-Sutcliffe efficiency >0.94 at key stations) using long-term hydrological data (1996–2022). Four scenarios were simulated: pre-dam conditions, post-dam topography with pre-dam roughness, pre-dam topography with increased roughness, and coupled post-dam changes. A novel scenario-based decomposition framework was developed to isolate individual and coupled factor contributions, advancing beyond traditional descriptive approaches. The results indicate that upstream water level changes are mainly controlled by riverbed erosion (e.g., at the Zhicheng Station: the topographic contribution rate exceeds 80% at a flow rate of 5000 m³/s, resulting in a water level drop of approximately 1.7 m), while downstream, an increase in roughness becomes the dominant factor (e.g., at the Jianli Station: causing a water level rise of about 1.0 m at a flow rate of 13,000 m³/s, with such changes being particularly pronounced under low-flow conditions). Spatially, topographic influence attenuates downstream, whereas roughness sensitivity amplifies in high-sinuosity reaches (bend coefficient: 3.0). Seasonally, the topographic contribution rate remains stable overall during the low-flow period, e.g., within a narrow range of 0.88–0.98 at Zhicheng Station, while roughness effects exhibit negative values in dry periods (November) due to fine sediment deposition. The coupling effect in mid-discharge ranges (15,000–20,000 m³/s) at Jianli partially offsets stage reductions. These findings not only provide critical insights for flood forecasting and navigation management in the Jingjiang Reach but also offer a transferable methodology for quantifying hydro-morphodynamic interactions in global regulated rivers, highlighting the model’s utility in predictive water resource management. Full article

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25 pages, 6426 KB

Open AccessArticle

Dissolved Ion Distribution in a Watershed: A Study Utilizing Ion Chromatography and Non-Parametric Analysis

by Selline Okechi, Keisuke Nakayama and Katsuaki Komai

Hydrology 2025, 12(12), 310; https://doi.org/10.3390/hydrology12120310 - 22 Nov 2025

Abstract

This study presents a unique approach for characterizing ion distribution within the Kushiro River catchment basin, which is characterized by exceptionally high dissolved ion concentrations. principal component analysis, Mann–Whitney U test, and neural network modeling were employed to analyze data from 11 distinct [...] Read more.

This study presents a unique approach for characterizing ion distribution within the Kushiro River catchment basin, which is characterized by exceptionally high dissolved ion concentrations. principal component analysis, Mann–Whitney U test, and neural network modeling were employed to analyze data from 11 distinct locations in two different seasons. The 11 sampling locations were subsequently classified into five distinct groups to facilitate precise analysis of the ion distribution using neural networks. Two principal components were also employed to visualize and interpret our dataset. Compositional similarities and seasonal variations in ion distribution were identified, as well as the key variability patterns, thereby revealing underlying correlations among the dissolved ions. Our findings highlighted that Group 1, encompassing a caldera lake, exhibits the highest dissolved ion concentrations. This observation may be attributed to the geological characteristics of the underlying rock formation. Furthermore, a significant correlation was observed between the major dissolved ions present in the catchment basin, as evidenced by positive correlation coefficients. Conversely, nitrate ions exhibited a negative correlation with F⁻, Cl⁻, and Na⁺ ions. This comprehensive analytical framework offers a robust and insightful tool for determining ion distribution within catchment basins with significant implications for environmental monitoring and sustainable resource management. Full article

(This article belongs to the Section Soil and Hydrology)

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26 pages, 6770 KB

Open AccessFeature PaperArticle

TopEros: An Integrated Hydrology and Multi-Process Erosion Model—A Comparison with MUSLE

by Emmanuel Okiria, Noda Keigo, Shin-ichi Nishimura and Yukimitsu Kobayashi

Hydrology 2025, 12(11), 309; https://doi.org/10.3390/hydrology12110309 - 20 Nov 2025

Abstract

Hydro-erosion is a primary driver of soil degradation worldwide, yet accurate catchment-scale prediction remains challenging because sheet, gully, and raindrop-impact detachment processes operate simultaneously at sub-grid scales. We introduce TopEros, a hydro-erosion model that integrates the hydrological framework of TOPMODEL with three distinct [...] Read more.

Hydro-erosion is a primary driver of soil degradation worldwide, yet accurate catchment-scale prediction remains challenging because sheet, gully, and raindrop-impact detachment processes operate simultaneously at sub-grid scales. We introduce TopEros, a hydro-erosion model that integrates the hydrological framework of TOPMODEL with three distinct erosion modules: sheet erosion, gully erosion, and raindrop-impact detachment. TopEros employs a sub-grid zoning strategy in which each grid cell is partitioned into diffuse-flow (sheet erosion) and concentrated-flow (gully erosion) domains using threshold values of two topographic indices: the topographic index (TI) and the contributing area–slope index (a_itanβ). Applied to the Namatala River catchment in eastern Uganda and calibrated with TI = 15 and a_itanβ = 35, TopEros identified sheet-dominated and gully-prone areas. The simulated specific sediment yields ranged from 95 to 155 Mgha⁻¹yr⁻¹—classified as “high” to “very high”—with gully zones contributing disproportionately large erosion volumes. These results demonstrate the importance of capturing intra-cell heterogeneity: conventional catchment-average approaches can obscure critical erosion hotspots. By explicitly representing multiple soil detachment and transport mechanisms within a unified process-based framework, TopEros has the potential to enhance the realism of catchment-scale erosion estimates and support the precise targeting of soil and water conservation measures. Full article

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28 pages, 7124 KB

Open AccessArticle

Flash Drought Assessment: Insights from a Selection of Mediterranean Islands, Greece

by Chrysoula Katsora, Evangelos Leivadiotis, Nektaria Papadopoulou, Isavela Monioudi, Efthymia Kostopoulou, Petros Gaganis, Aris Psilovikos and Ourania Tzoraki

Hydrology 2025, 12(11), 308; https://doi.org/10.3390/hydrology12110308 - 18 Nov 2025

Abstract

Flash droughts are a significant natural hazard, characterized by rapid onset and potential to cause substantial economic and environmental impacts. This study utilizes ERA5 soil moisture data to identify and define historical flash drought (FD) events in the Northeastern Aegean islands (specifically Chios, [...] Read more.

Flash droughts are a significant natural hazard, characterized by rapid onset and potential to cause substantial economic and environmental impacts. This study utilizes ERA5 soil moisture data to identify and define historical flash drought (FD) events in the Northeastern Aegean islands (specifically Chios, Lemnos, Lesvos and Samos). Hourly soil moisture data, spanning from 1990 to the present, covering three soil layers (0–7 cm, 7–28 cm and 28–100 cm), were analyzed and mapped onto a 0.1° × 0.1° grid with a native resolution of approximately 9 km. Additionally, the Standardized Precipitation Evapotranspiration Index (SPEI) was applied to the island of Lesvos, using precipitation and average temperature data from the local meteorological stations. The number and characteristics of these events—including frequency, duration, decline rate, magnitude, intensity, recovery rate and recovery duration—were produced to construct a regional overview of FD risk across the Northeastern Aegean Islands. These results reveal a considerable variability in the spatial, seasonal and temporal distribution of past FD events. Furthermore, this study highlights the value of using satellite-derived soil moisture data for identifying FD events and demonstrates that analyzing this data with field temperature and precipitation measurements enables a more localized and accurate interpretation of past events. This approach facilitates the definition of FD “hotspot” areas, which, when combined with further investigation, can lead to the development of a predictive FD model. Full article

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

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21 pages, 4290 KB

Open AccessArticle

Robust and Fast Sensing of Urban Flood Depth with Social Media Images Using Pre-Trained Large Models and Simple Edge Training

by Lin Lin, Zhenli Zeng, Chaoqing Tang, Yilin Xie and Qiuhua Liang

Hydrology 2025, 12(11), 307; https://doi.org/10.3390/hydrology12110307 - 17 Nov 2025

Abstract

Accurately estimating urban floodwater depth is a critical step in enhancing urban resilience and strengthening disaster prevention and mitigation capabilities. Traditional methods relying on hydrological monitoring stations and numerical simulations suffer from limitations such as sparse spatial coverage, insufficient validation data, limited accuracy, [...] Read more.

Accurately estimating urban floodwater depth is a critical step in enhancing urban resilience and strengthening disaster prevention and mitigation capabilities. Traditional methods relying on hydrological monitoring stations and numerical simulations suffer from limitations such as sparse spatial coverage, insufficient validation data, limited accuracy, and delayed fast performance. In contrast, social media data—characterized by its vast volume and fast availability, can effectively compensate for these shortcomings. When processed using artificial intelligence (AI) algorithms, such data can significantly improve credibility, disaster perception speed, and water depth estimation accuracy. To address these challenges, this paper proposes a robust and widely applicable method for rapid urban flood depth perception. The approach integrates AI technology and social media data to construct an AI framework capable of perceiving urban physical parameters through multimodal big data fusion without costly model training. By leveraging the near real-time and widespread nature of social media, an automated web crawler collects flood images and their textual descriptions (including reference objects), eliminating the need for additional hardware investments. The framework uses predefined prompts and pre-trained models to automatically perform relevance verification, duplicate filtering, object detection, and feature extraction, requiring no manual data annotation or model training. With only a minimal amount of water depth annotated data and compressed cross-modal feature vectors as training input, a lightweight Multilayer Perceptron (MLP) achieves high-precision depth estimation based on reference objects. This method avoids the need for large-scale model fine-tuning, allowing rapid training even on devices without GPUs. Experiments demonstrate that the proposed method reduces the Mean Square Error (MSE) by over 80%, processes each image in less than 0.5 s (more than 20 times faster than existing large-model approaches), and exhibits strong robustness to changes in perspective and image quality. The solution is fully compatible with existing infrastructure such as surveillance cameras, offering an efficient and reliable approach for fast flood monitoring in urban hydrology and water engineering applications. Full article

(This article belongs to the Special Issue Advances in Urban Hydrology and Stormwater Management)

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21 pages, 7782 KB

Open AccessArticle

Groundwater Recharge Estimation Based on Environmental Isotopes, Chloride Mass Balance and SWAT Model in Arid Lands, Southwestern Saudi Arabia

by Milad Masoud, Maged El Osta, Jalal Basahi, Burhan Niyazi, Nassir Al-Amri, Michael Schneider, Abdulaziz Alqarawy and Riyadh Halawani

Hydrology 2025, 12(11), 306; https://doi.org/10.3390/hydrology12110306 - 16 Nov 2025

Abstract

Estimated groundwater recharge is considered the essential factor for groundwater management and sustainability, especially in arid lands such as the Kingdom of Saudi Arabia (KSA). Consequently, assessing groundwater recharge is a key process for forecasting groundwater accessibility to sustain safe withdrawal. So, this [...] Read more.

Estimated groundwater recharge is considered the essential factor for groundwater management and sustainability, especially in arid lands such as the Kingdom of Saudi Arabia (KSA). Consequently, assessing groundwater recharge is a key process for forecasting groundwater accessibility to sustain safe withdrawal. So, this study focused on environmental isotopes, the chloride mass balance (CMB) method, and a SWAT model by integrating GIS with hydrological and hydrochemical techniques to detect the origin of coastal aquifer groundwater and to compute the recharging rate in the study area. This study is based on the results of chemical analysis of 78 groundwater samples and environmentally stable isotopes, including deuterium (²H) and oxygen-¹⁸O, in 29 representative samples. The results revealed that the origin of groundwater recharge comes through precipitation, where the ranges of δ¹⁸O and δ²H isotopes in the analyzed groundwater were from −1.10‰ to +1.03‰ and from −0.63‰ to 11.63‰, respectively. The CMB finding for estimating the average recharge is 3.57% of rainfall, which agrees with a previous study conducted in the wadi Qanunah basin (north of the study area), where the estimated average value of recharge was 4.25% of rainfall. Meanwhile, the estimated annual recharge using a SWAT model ranged between 1 mm and 16.5 mm/year at an average value of approximately 8.75 mm/year. The results obtained by the two techniques are different due to some reasons such as the presence of additional chloride sources, as well as evaporation. Outputs of this study will be valuable for the local community, officials, and decision-makers who are concerned with groundwater resources. Full article

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16 pages, 2077 KB

Open AccessArticle

Snowmelt Volume from Rain-on-Snow Events Under Controlled Temperature and Rainfall: A Laboratory Experimental Study

by Wenjun Liu, Gulimire Hanati, Keke Hu, Sulitan Danierhan and Lei Jin

Hydrology 2025, 12(11), 305; https://doi.org/10.3390/hydrology12110305 - 16 Nov 2025

Abstract

Rain-on-snow (ROS) events profoundly influence mixed rain–snow flooding and the water resource cycle. However, current research regarding ROS events remains predominantly reliant on existing datasets, lacking detailed controlled experiments under variable conditions. This study employed control variables and an orthogonal experimental design to [...] Read more.

Rain-on-snow (ROS) events profoundly influence mixed rain–snow flooding and the water resource cycle. However, current research regarding ROS events remains predominantly reliant on existing datasets, lacking detailed controlled experiments under variable conditions. This study employed control variables and an orthogonal experimental design to conduct laboratory-controlled experiments simulating ROS events with different temperatures, rainfall intensities, and rainfall durations. Observations and analyses were performed on the snowmelt volumes during and after events. The results indicate that ROS events significantly accelerate snowmelt rates and increase total snowmelt volume. Under low-intensity ROS, snowmelt volume exhibits greater sensitivity to temperature changes. A temperature threshold exists between 2 °C and 6 °C; beyond this threshold, the melting rate accelerates and ablation volume increases. Under high-intensity ROS, rainwater becomes the dominant factor driving snowpack ablation. When rainfall intensity exceeds 60 mm·h⁻¹, it triggers a sharp increase in snowmelt volume. Concurrently, following an ROS event, snowpacks subjected to low-intensity rainfall exhibit a stronger rainwater retention capacity, an effect that becomes more pronounced at lower temperatures. Additionally, snowmelt volume increases with prolonged rainfall duration, with the increment in snowmelt volume attributable to extended rainfall time being greater under weaker rainfall intensities. These findings provide a scientific reference for better understanding ROS-related disasters mechanisms. Full article

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16 pages, 13612 KB

Open AccessFeature PaperArticle

Integrated Multi-Scale Hydrogeophysical Characterisation of a Coastal Phreatic Dune Aquifer: The Belvedere–San Marco Case Study (NE Italy)

by Benedetta Surian, Emanuele Forte and Luca Zini

Hydrology 2025, 12(11), 304; https://doi.org/10.3390/hydrology12110304 - 15 Nov 2025

Abstract

Low-lying coastal plains are increasingly threatened by saltwater intrusion, yet the extent of the phenomenon and the role of coastal dune systems remain unevenly assessed. In the northern Adriatic Sea (NE Italy), salinisation has been documented, but systematic, spatially resolved studies are lacking. [...] Read more.

Low-lying coastal plains are increasingly threatened by saltwater intrusion, yet the extent of the phenomenon and the role of coastal dune systems remain unevenly assessed. In the northern Adriatic Sea (NE Italy), salinisation has been documented, but systematic, spatially resolved studies are lacking. This work investigates the Belvedere–San Marco relict dune system to assess its hydrogeological function and vulnerability to seawater intrusion. An integrated methodology combining borehole and core stratigraphy, in situ water electrical conductivity (EC) measurements, and multi-method geophysical surveys (FDEM, ERT, GPR, active seismics) was tested. Results reveal a consistent stratigraphy of permeable aeolian sands overlying clay-rich units, with groundwater EC values in the dune sector always remaining well below thresholds for brackish or saline conditions. Geophysical imaging reveals that the dunes are low-conductive bodies contrasting sharply with the conductive surrounding lowlands, thus indicating the persistence of a freshwater lens sustained by local recharge within the dunes. The Belvedere–San Marco dunes therefore act as both freshwater reservoirs and natural hydraulic barriers, buffering shallow aquifers against salinisation. This study demonstrated the applicability of integrated geophysical methods to extensively investigate shallow phreatic aquifers lying a few metres below the surface, and establishes a baseline for monitoring future changes under rising sea levels, subsidence, and increased groundwater exploitation. Full article

(This article belongs to the Special Issue Characterization and Monitoring of Coastal Hydrological Environment for Assessing the Impact of Seawater Intrusion on Coastal Aquifers)

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15 pages, 5222 KB

Open AccessArticle

Multi-Objective Optimization of the Physical Design of a Horizontal Flow Subsurface Wetland

by Jhonatan Mendez-Valencia, Carlos Sánchez-López, Eneida Reyes-Pérez, Rocío Ochoa-Montiel, Lucila Marquez-Pallares, Juan Aguila-Muñoz, Fredy Montalvo-Galicia, Miguel Angel Carrasco-Aguilar, Jorge Alberto Sánchez-Martínez and Jorge Arellano-Hernández

Hydrology 2025, 12(11), 303; https://doi.org/10.3390/hydrology12110303 - 14 Nov 2025

Abstract

Decontamination of wastewater, industrial effluents, stormwater, and graywater can be carried out through the use of natural or constructed wetlands. In either case, the natural functions of soil, vegetation, and organisms are widely applied for the treatment of contaminated water. In particular, in [...] Read more.

Decontamination of wastewater, industrial effluents, stormwater, and graywater can be carried out through the use of natural or constructed wetlands. In either case, the natural functions of soil, vegetation, and organisms are widely applied for the treatment of contaminated water. In particular, in the physical design of a constructed wetland, several operational factors must be adjusted with the aim of reducing pollution levels. Although various fully customized design methodologies have been developed and reported in the literature, they often fail to meet the required decontamination objectives. In this context, the application of the NSGA-II evolutionary algorithm is adequate to optimize the physical design of a horizontal subsurface flow wetland for graywater treatment, focusing specifically on the removal of biodegradable organic matter (BOD⁵). Four competing objectives are considered: minimizing physical volume and total design cost, while maximizing contaminant removal efficiency and graywater flow rate. Five constraint functions are also incorporated: removal efficiency greater than 95%, physical volume below 1000 m³, flow rate above 10 m³/d, a limit on total construction cost of MXN 1,000,000, and maintaining a length-to-width ratio greater than or equal to 2 but less than or equal to 4. The proposed methodology generates a wide set of non-dominated solutions, visualized through Pareto surfaces, which highlight the trade-offs among different objectives. This approach offers the possibility of selecting optimal designs under specific conditions, which underscores the limitations of conventional single-solution models. The results show that the methodology consistently achieved removal efficiencies above 95%, with construction costs within budget and physical volumes below the established limit, offering a more versatile and cost-effective alternative. This work demonstrates that the integration of NSGA-II into wetland design is an effective and adaptable strategy, capable of providing sustainable alternatives for graywater treatment and constituting a valuable decision-making tool. Full article

(This article belongs to the Special Issue First Papers by Young Investigators in the Hydrological Sciences (2025-2026))

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26 pages, 2546 KB

Open AccessArticle

Characterization of Hyetograms and Rainfall Patterns in Southern Amazonia

by Brenda Buose, Daniela Roberta Borella, Frederico Terra de Almeida and Adilson Pacheco de Souza

Hydrology 2025, 12(11), 302; https://doi.org/10.3390/hydrology12110302 - 14 Nov 2025

Abstract

The variability of rainfall, mainly convective, in the southern Amazon remains poorly understood due to the limited number of studies examining the relationships between the intensities and durations of rainfall events in this region. This study aimed to characterize the intensity patterns—hyetograms (advanced, [...] Read more.

The variability of rainfall, mainly convective, in the southern Amazon remains poorly understood due to the limited number of studies examining the relationships between the intensities and durations of rainfall events in this region. This study aimed to characterize the intensity patterns—hyetograms (advanced, intermediate, delayed, and constant, as well as observations of new patterns)—in the northern state of Mato Grosso (southern Amazon). Generally, most research in Brazil on this topic has focused on other regions of the country or used simulations or data disaggregation processes, limiting the representation of the regional reality. Historical data series from five conventional stations (with pluviograms) and ten automatic stations with data obtained by tipping rain gauges were analyzed. The analysis involved classifying 6187 events into four main patterns: Advanced (53.52%), Intermediate (31.74%), Delayed (14.58%), and Constant (less than 1%), with 93 events unclassified. The hourly distribution of rainfall revealed greater occurrence in the afternoon and evening periods, suggesting a predominance of thermal convection in regional dynamics. The results offer valuable insights for water planning, agricultural security, and adaptive infrastructure, in addition to promoting integration between science, engineering, and public policies aimed at environmental management and risk prevention. Full article

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

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