Hydrology

19 pages, 13983 KB

Open AccessArticle

The Role of Toposequence and Underground Drainage in Variation of Groundwater and Salinity Levels in Irrigated Areas

by Laercia da Rocha Fernandes Lima, Ceres Duarte Guedes Cabral de Almeida, Gabriel Rivas de Melo, Manassés Mesquita da Silva, Keila Jeronimo Jimenez, Valdiney Bizerra de Amorim, Andrey Thyago Cardoso S. G. da Silva, Magnus Dall Igna Deon, Rebeca Neves Barbosa, José Fernandes Ferreira Júnior, Tarcísio Ferreira de Oliveira and José Amilton Santos Júnior

Hydrology 2026, 13(3), 99; https://doi.org/10.3390/hydrology13030099 - 18 Mar 2026

Viewed by 425

Abstract

In irrigated areas around the world, the recommendation for the use of subsurface drainage is also associated with controlling salinity problems. Due to the high implementation cost, the search for solutions that make this requirement more flexible is necessary. Among the options to [...] Read more.

In irrigated areas around the world, the recommendation for the use of subsurface drainage is also associated with controlling salinity problems. Due to the high implementation cost, the search for solutions that make this requirement more flexible is necessary. Among the options to be investigated is the hypothesis that the height and salinity of the water table in plots located at the highest points of a toposequence are lower and do not compromise plant development, even without underground drainage systems. In this context, the present work was developed to monitor and evaluate the variation in water level or mottling over twelve months, as well as to measure and analyze the electrical conductivity and average pH of the water table during this period and its possible impact on plants. For this purpose, three lots in toposequence were selected in the Senador Nilo Coelho Public Irrigation Project, Petrolina—PE, with previously defined characteristics: soil classification (Plinthic Yellow—Ultisol), crop planted (Mangifera indica L.) and irrigation system used (micro-sprinkler). Precipitation, reference evapotranspiration and volume of water applied via irrigation were monitored by an automatic weather station and hydrometers in each lot. In each plot, nine observation wells were installed, distributed in a grid, with the aim of make monthly measurements of the water table level or mottling. The electrical conductivity and pH of the groundwater were also measured to obtain the average monthly value for each lot. Illustrative 3D maps of the water table level in relation to the ground surface were created using the simple kriging method, in the UTM SIRGAS 2000 24S projection system. The absence and presence of groundwater in the upper and lower hillslope lots, respectively, were favored by the toposequence. The decision to install underground drainage or not can be made on a case-by-case basis; this must take into account, among other aspects, changes in physical characteristics along the soil profile, possible occurrence of mottling, the quality of water for irrigation, the irrigation management adopted and the position of the lot in the toposequence. Full article

(This article belongs to the Section Soil and Hydrology)

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23 pages, 9997 KB

Open AccessArticle

Hybrid Deep Learning Architectures for Multi-Horizon Precipitation Forecasting in Mountainous Regions: Systematic Comparison of Component-Combination Models in the Colombian Andes

by Manuel Ricardo Pérez Reyes, Marco Javier Suárez Barón and Óscar Javier García Cabrejo

Hydrology 2026, 13(3), 98; https://doi.org/10.3390/hydrology13030098 - 18 Mar 2026

Viewed by 422

Abstract

Forecasting monthly precipitation in mountainous terrain poses challenges that push conventional deep learning approaches to their limits: convective processes operate locally while orographic effects span entire drainage basins. We compare three architecture families on precipitation prediction across the Colombian Andes: ConvLSTM (convolutional recurrent), [...] Read more.

Forecasting monthly precipitation in mountainous terrain poses challenges that push conventional deep learning approaches to their limits: convective processes operate locally while orographic effects span entire drainage basins. We compare three architecture families on precipitation prediction across the Colombian Andes: ConvLSTM (convolutional recurrent), FNO-ConvLSTM (spectral–temporal), and GNN-TAT (graph attention LSTM). Using CHIRPS v2.0 and SRTM topography for Boyacá department (61 × 65 grid, 3965 nodes), we evaluate 39 configurations across feature bundles (BASIC, KCE elevation clusters, and PAFC autocorrelation lags) and horizons from 1 to 12 months. GNN-TAT matches ConvLSTM accuracy (

R^{2}

: 0.628 vs. 0.642; RMSE: 82.29 vs. 79.40 mm) with 95% fewer parameters (∼98K vs. 2.1M). Across configurations, GNN-TAT produces a lower mean RMSE (92.12 vs. 112.02 mm;

p = 0.015

) and a 74.7% lower variance. The explicit graph structure, with edges weighted by elevation similarity, appears to reduce sensitivity to hyperparameter choices. Pure FNO struggles with precipitation’s spatial discontinuities (

R^{2} = 0.206

), though adding a ConvLSTM decoder recovers much of the lost skill (

R^{2} = 0.582

). Elevation clustering improves GNN-TAT significantly (

p = 0.036

) but not ConvLSTM, suggesting that feature design should match the spatial encoding paradigm. ConvLSTM achieves peak accuracy on local patterns; GNN-TAT provides robust predictions with interpretable spatial reasoning. These complementary strengths motivate stacking ensembles that combine grid-based and graph-based representations. Full article

(This article belongs to the Special Issue Advancing Hydrological Science Through Artificial Intelligence: Innovations and Applications)

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17 pages, 6263 KB

Open AccessArticle

Beyond One-Dimension: How Transient Groundwater Flow Amplifies Groundwater Evapotranspiration and Extinction Depth

by Jia-Xin Shi, Linpeng Chen, Zhi-Yuan Zhang, Peng-Fei Han, Hongjuan Dong and Zhenbin Zhang

Hydrology 2026, 13(3), 97; https://doi.org/10.3390/hydrology13030097 - 16 Mar 2026

Viewed by 439

Abstract

Accurate quantification of groundwater evapotranspiration (ET_g) is essential for reliable water resource assessment. Existing methods for estimating ET_g from water table fluctuation largely rely on one-dimensional simplifications that neglect transient groundwater flow. However, in areas with shallow water table and [...] Read more.

Accurate quantification of groundwater evapotranspiration (ET_g) is essential for reliable water resource assessment. Existing methods for estimating ET_g from water table fluctuation largely rely on one-dimensional simplifications that neglect transient groundwater flow. However, in areas with shallow water table and topographic relief, where transient groundwater flow often occurs, the validity and accuracy of this simplification remain inadequately evaluated. In this study, we used HYDRUS-2D to construct a 50 m-long sandy hillslope with a 0.05 gradient to investigate ET_g based on the water table fluctuation (WTF) method under transient groundwater flow conditions. The results indicate that periodic evapotranspiration generates water table fluctuations along the hillslope that exhibit amplitude attenuation and temporal phase lag, features not captured by 1D models. Ignoring transient groundwater flow leads to a systematic underestimation of ET_g by up to 85% in sandy soil near the topographic lows. Furthermore, we found that both the decoupling depth and the extinction depth are significantly amplified by lateral groundwater flow, by up to 66% and 51%, respectively, compared with 1D estimates derived from the Shah method. These findings highlight the importance of incorporating transient flow processes into ET_g estimation to improve the accuracy of water balance assessments and ecohydrological predictions, particularly in areas with shallow water tables and topographic relief. Full article

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

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41 pages, 8144 KB

Open AccessArticle

Statistical Development of Rainfall IDF Curves and Machine Learning-Based Bias Assessment: A Case Study of Wadi Al-Rummah, Saudi Arabia

by Ibrahim T. Alhbib, Ibrahim H. Elsebaie and Saleh H. Alhathloul

Hydrology 2026, 13(3), 96; https://doi.org/10.3390/hydrology13030096 - 16 Mar 2026

Viewed by 646

Abstract

Reliable estimation of extreme rainfall is essential for hydraulic design and flood risk mitigation, particularly in arid regions where rainfall exhibits strong temporal and spatial variability. This study presents a statistical framework for developing rainfall intensity-duration-frequency (IDF) curves, complemented by a machine learning-based [...] Read more.

Reliable estimation of extreme rainfall is essential for hydraulic design and flood risk mitigation, particularly in arid regions where rainfall exhibits strong temporal and spatial variability. This study presents a statistical framework for developing rainfall intensity-duration-frequency (IDF) curves, complemented by a machine learning-based assessment of model bias and performance. The analysis was conducted using data from ten rainfall stations located within or near the Wadi Al-Rummah Basin. Annual maximum series (AMS) from 1969 to 2024 were first reconstructed to address missing years using a modified normal ratio method (NRM) combined with nearest-station selection, ensuring spatial consistency while preserving station-specific rainfall characteristics. Six probability distributions (Weibull, Gumbel, gamma, lognormal, generalized extreme value (GEV), and generalized Pareto) were fitted to each station, and the best-fit distribution was identified using multiple goodness-of-fit (GOF) criteria, including the Kolmogorov–Smirnov (K-S) test, Anderson–Darling (A-D) test, root mean square error (RMSE), chi-square (χ²) statistic, Akaike information criterion (AIC), Bayesian information criterion (BIC), and the coefficient of determination (R²). Statistical IDF curves were then developed for durations ranging from 5 to 1440 min and return periods from 2 to 1000 years. To evaluate the robustness of the statistically derived IDF curves, three machine learning (ML) models, multiple linear regression (MLR), regression random forest (RRF), and multilayer feed-forward neural network (MFFNN), were trained as surrogate models using duration, return period, and station geographic attributes as predictor variables. Model performance was evaluated using RMSE, MAE, and mean bias metrics across stations and return periods. The lognormal distribution emerged as the best-fit model for four stations, while the Gumbel and gamma distributions were selected for two stations each. Overall, no single probability distribution consistently outperformed others, indicating station-dependent behavior. Among the machine learning models, the MFFNN achieved the closest agreement with statistical IDF estimates (

R M S E \approx 0.97

,

M A E \approx 0.65

,

b i a s \approx - 0.02

), followed by RRF and MLR based on global average performance across all stations and return periods. The proposed framework offers a reliable approach for rainfall IDF development and evaluation in arid region watersheds. Full article

(This article belongs to the Section Statistical Hydrology)

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29 pages, 5427 KB

Open AccessArticle

Integrated Multi-Evidence Modeling of River–Groundwater Interactions and Sustainable Water Use in the Arid Aksu River Basin, Northwest China

by Jingya Ban, Shukun Ni, Zhilin Bao, Bin Wu and Chuanhong Ye

Hydrology 2026, 13(3), 95; https://doi.org/10.3390/hydrology13030095 - 16 Mar 2026

Viewed by 502

Abstract

The Aksu River Basin, the main headwater of the Tarim River, contributes more than 70% of the main stream’s runoff and is therefore critical in maintaining hydrological stability in this arid river system. In recent decades, rapid oasis expansion and growing agricultural water [...] Read more.

The Aksu River Basin, the main headwater of the Tarim River, contributes more than 70% of the main stream’s runoff and is therefore critical in maintaining hydrological stability in this arid river system. In recent decades, rapid oasis expansion and growing agricultural water withdrawals have intensified competition for surface and groundwater, posing increasing ecological risks to the downstream Tarim River Basin. To quantitatively characterize river–groundwater hydrological responses under intensive water use, we combined statistical analysis, field observations, and distributed hydrological modeling within a basin-scale conceptual framework. Multiple lines of evidence—water level monitoring, hydrochemical tracers, stable isotopes, and the integrated surface–groundwater model MIKE SHE—were used to identify river–groundwater interaction mechanisms in the Aksu alluvial plain. Results reveal a typical three-stage spatial exchange pattern: river recharge to groundwater in the upstream reach, groundwater discharge to the river in the midstream, and renewed river infiltration to groundwater downstream. The patterns inferred from water levels, hydrochemistry, and isotopes are broadly consistent, while water-level data better resolve left–right bank asymmetry. The MIKE SHE model supports the seasonal bidirectional exchange dynamics and reproduces runoff behavior with acceptable performance (RMSE and residual standard deviation within 20% of observed means and R² > 0.7 during both calibration (2010–2017) and validation (2018–2021)). The proposed multi-evidence framework captures the spatio-temporal variability of river–groundwater interactions in arid regions and provides spatially differentiated guidance for conjunctive surface–groundwater regulation and integrated water resources management in the Tarim River Basin. Full article

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

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32 pages, 6655 KB

Open AccessArticle

Hydrogeochemical Assessment of Groundwater Quality in Basaltic and Alluvial Aquifers, Al Madinah Al-Munawwarah, Saudi Arabia

by Hamdy Hamed Abd El-Naby, Yehia Hassan Dawood and Abduallah Abdel Aziz Sabtan

Hydrology 2026, 13(3), 94; https://doi.org/10.3390/hydrology13030094 - 15 Mar 2026

Viewed by 555

Abstract

Groundwater in Al-Madinah Al-Munawwarah faces considerable challenges from high salinity, elevated TDS, and nitrate contamination, primarily due to urbanization and industrial activities, making ongoing monitoring and management essential for its sustainable use in both drinking water and agriculture. The assessment of groundwater quality [...] Read more.

Groundwater in Al-Madinah Al-Munawwarah faces considerable challenges from high salinity, elevated TDS, and nitrate contamination, primarily due to urbanization and industrial activities, making ongoing monitoring and management essential for its sustainable use in both drinking water and agriculture. The assessment of groundwater quality was conducted on 44 wells tapping two major aquifers (basaltic and alluvial) in the region, utilizing various geochemical techniques, including ICP-MS, FAAS, and XRF, to evaluate hydrochemical characteristics and identify the primary controlling factors. Key physicochemical parameters, including total dissolved solids (TDSs), electrical conductivity (EC), pH, total hardness (TH), and major ion concentrations, were evaluated. The results indicate that several parameters exceed permissible limits established by Gulf and international standards, reflecting highly saline conditions that could adversely affect drinking water safety and agricultural practices. Elevated nitrate levels and other contaminants indicate a combination of geological processes, including mineral leaching, and anthropogenic activities, such as agricultural runoff. Correlations among various ions reveal complex interactions driven by both natural and human factors. High nitrate and potassium concentrations, particularly in the alluvial aquifer, combined with weak correlations with geogenic ions, indicate anthropogenic inputs. Heavy metals in groundwater were classified into two groups: those within permissible limits (Ag, Ba, Be, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Sb, and U) and those exceeding recommended limits (Zn, Al, As, Se, and Tl). Elevated metal concentrations are primarily attributed to water–rock interactions and the fertilizer use in surrounding agricultural areas. These findings highlight the urgent need for continuous monitoring and proactive groundwater to ensure sustainable and safe use of water resources. Full article

(This article belongs to the Topic Geological Processes: A Key to Understand Water Quality Issues)

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26 pages, 7601 KB

Open AccessArticle

Hydrological Modeling of Reservoir Sedimentation and Evolution of Elevation–Capacity Curve of the Dam Reservoir

by Baradin Adisu Arebu, Nassir Alamri and Amro Elfeki

Hydrology 2026, 13(3), 93; https://doi.org/10.3390/hydrology13030093 - 13 Mar 2026

Viewed by 581

Abstract

Accurate modeling of dam reservoir sedimentation is crucial for effective reservoir management. Traditional approaches for estimating sedimentation include the Hydraulic Approach (HA) and the Empirical Approach (EA). HA involves complex computations and requires substantial data, while the EA relies on equations like the [...] Read more.

Accurate modeling of dam reservoir sedimentation is crucial for effective reservoir management. Traditional approaches for estimating sedimentation include the Hydraulic Approach (HA) and the Empirical Approach (EA). HA involves complex computations and requires substantial data, while the EA relies on equations like the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE), which use subjective parameters and lead to inaccurate estimations. This study introduces a novel approach called the hydrological approach, which integrates the sediment rating curve (SRC) and the dam reservoir elevation-capacity curve (ECC) to estimate reservoir sedimentation and evolution of the ECC. This HA leads to a newly developed equation for the estimation of the sediment rise and the corresponding sediment volume. The approach is applied to the Wadi Fatimah Dam in Saudi Arabia. By combining rainfall data from 1985 to 2022 and performing rainfall–runoff hydrological modeling combined with the proposed HA, sediment accumulation trends and reservoir capacity reductions are estimated from past to present. Validation through ground survey and geophysical investigations in 2008 confirms model accuracy. Findings reveal significant sediment buildup, with an estimated average of 7.5 m rise from 1985 to 2008. The study’s main findings highlighted the urgent need for effective sediment management strategies in arid regions, where sedimentation rates are notably higher than in other regions. Full article

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16 pages, 14806 KB

Open AccessArticle

A Paleo Perspective of Future Precipitation Drought in the Tennessee Valley

by Kane Thurman, Julianne Webb, Grace Peart, Glenn Tootle, Zhixu Sun and Joshua S. Fu

Hydrology 2026, 13(3), 92; https://doi.org/10.3390/hydrology13030092 - 13 Mar 2026

Viewed by 466

Abstract

Hydrologic assessment within the Southeast United States is challenging, particularly in upstream basins, necessitating improved approaches to drought forecasting and water management. Within the Tennessee Valley, dense populations intensify the need for robust hydrologic management and predictive capabilities. This study integrates dendrochronological proxy [...] Read more.

Hydrologic assessment within the Southeast United States is challenging, particularly in upstream basins, necessitating improved approaches to drought forecasting and water management. Within the Tennessee Valley, dense populations intensify the need for robust hydrologic management and predictive capabilities. This study integrates dendrochronological proxy data, hindcast information, and future climate projections from the Oak Ridge National Laboratory (ORNL) to evaluate May–June–July drought regimes. Holistic hydrologic conditions were attained by integrating self-calibrating Palmer Drought Severity Index data from the North American Drought Atlas, basin-scale precipitation data from ORNL hindcasts and future predictions, and streamflow data from United States Geological Survey. Development of precipitation and streamflow reconstructions were completed using Stepwise Linear Regression, then bias-corrected and temporally smoothed using five- and ten-year moving windows. The reconstructions demonstrated strong statistical skill across all three basins (Little Tennessee River, Nantahala River, South Fork Holston River). When compared only to the hindcast, future drought is predicted to be the most severe on record, but within the context of the paleo record, while still severe, these future droughts remain inside the natural variability envelope. Findings highlight the importance of novel approaches to long-term drought monitoring, specifically integrating basins where instrumental periods are limited, and water management demands are high. 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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17 pages, 7243 KB

Open AccessArticle

Assessment of Haditha Dam’s Operation Under Historical Hydrological Conditions: Comparison Between Actual and Simplified Operation Using the HEC-HMS Model in Different Scenarios

by Ghasaq Saadoon Mutar, Lariyah Mohd Sidek, Hidayah Basri and Mahmoud Saleh Al-Khafaji

Hydrology 2026, 13(3), 91; https://doi.org/10.3390/hydrology13030091 - 11 Mar 2026

Viewed by 476

Abstract

Water resources management in arid and semi-arid regions has become increasingly challenging due to climate change impacts and upstream water policies, particularly for strategic reservoirs. This study evaluates the applicability of the HEC-HMS model for simulating inflow hydrographs and supporting reservoir operation in [...] Read more.

Water resources management in arid and semi-arid regions has become increasingly challenging due to climate change impacts and upstream water policies, particularly for strategic reservoirs. This study evaluates the applicability of the HEC-HMS model for simulating inflow hydrographs and supporting reservoir operation in data-scarce arid environments, focusing on Haditha Reservoir, the only major dam on the Euphrates River within Iraqi territory. An integrated hydro-meteorological and GIS-based framework was developed using 20 years of data (2004–2024), incorporating basin characteristics and reservoir operation records into the HEC-HMS model. Rainfall–runoff processes were simulated using SCS-based methods and routing techniques, followed by calibration and validation against observed inflows. The results demonstrated satisfactory model performance, with an accurate reproduction of inflow hydrographs during both calibration and validation periods. Subsequently, three reservoir operation scenarios were developed and compared with the actual operating policy (outflow curve operation, outflow structure routing operation and rule-based operation scenarios). The rule-based operation scenario showed superior performance by maintaining higher reservoir storage and water levels during dry periods compared to the existing operation, despite higher supply deficits. Overall, the findings confirm that the HEC-HMS model can be reliably applied as a decision-support tool for evaluating reservoir operation in arid and semi-arid regions under water scarcity conditions. Full article

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

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21 pages, 8264 KB

Open AccessArticle

Climate Change Projections: Application of the Statistical Downscaling Model in the Souss-Massa Watershed

by Maryame El-Yazidi, Mohammed Benabdelhadi, Brahim Benzougagh, Yasmine Boukhlouf, Manal El Garouani, Malika El-Hamdouny, Hassan Tabyaoui, Zineb El Attar Soufi, Abderrahim Lahrach and Khaled Mohamed Khedher

Hydrology 2026, 13(3), 90; https://doi.org/10.3390/hydrology13030090 - 10 Mar 2026

Viewed by 330

Abstract

The research focuses on analyzing historical climate variability over the period 1982–2022, as well as future projections of climate change over the period 2025–2099, with regard to the Souss-Massa watershed, a semi-arid region with high dependency on agricultural activities. Precipitation and temperature data [...] Read more.

The research focuses on analyzing historical climate variability over the period 1982–2022, as well as future projections of climate change over the period 2025–2099, with regard to the Souss-Massa watershed, a semi-arid region with high dependency on agricultural activities. Precipitation and temperature data were collected annually from five meteorological stations, Agadir, Amaghouz, Amsoul, Aoulouz, and Taroudant, in order to analyze long-term climatic trends and predict possible scenarios of climate change. A trend analysis was carried out using a combination of the Mann–Kendall test and Sen’s slope estimator. The findings of this study indicate that there is an increase in mean annual temperature that is statistically significant (p < 0.05) across all stations, ranging from +0.28 °C per decade at Agadir, which is located along the coastal region of Morocco, to as high as +0.45 °C per decade at Taroudant, which is located inland. Conversely, the precipitation trend is decreasing and not statistically significant (p > 0.05). For projecting future climatic conditions, we used the Statistical Down-Scaling Model (SDSM v4.2.9) with global climate models using outputs from CanESM2 under two emission scenarios, namely RCP 4.5 and RCP8.5. The calibration period (1982–2001) and the validation period (2002–2022) were satisfactory, as indicated by the high values of the coefficients of determination (R² > 0.6) for temperature and moderate values (R² = 0.5–0.6) for precipitation. Projections indicate an increase in temperature, with the mean temperature change ranging from +4.8 °C and +8.7 °C by 2099 depending on the station’s location. Projected precipitation decreases are found under both scenarios, but with stronger decreases under RCP8.5, especially along the coastal regions, with decreases as large as −53.8% at Agadir. However, the precipitation projections have to be used with caution due to the limitations associated with the downscaling methods and the use of a single global climate model. All the projections indicate a trend towards arid conditions, emphasizing the need for adaptive water resources management and improving the ensemble models for climate projections. Full article

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32 pages, 3447 KB

Open AccessArticle

Spatial Downscaling of the CHIRPS Rainfall Product Using Machine Learning Methods: The Catamayo–Chira Transboundary Basin (Ecuador-Peru) Case

by Jessica K. Gaona, Luis-Felipe Duque, Raúl F. Vázquez and Candy L. Ocaña

Hydrology 2026, 13(3), 89; https://doi.org/10.3390/hydrology13030089 - 10 Mar 2026

Viewed by 754

Abstract

Precipitation modeling is vital for water resource management in basins with limited gauged data. In this study, the 5 km Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) product was downscaled to 1 km at the annual and mean monthly scales for the [...] Read more.

Precipitation modeling is vital for water resource management in basins with limited gauged data. In this study, the 5 km Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) product was downscaled to 1 km at the annual and mean monthly scales for the Catamayo–Chira catchment, a key water source for Ecuador and Peru. Single-variable and multivariable machine learning (ML) methods were applied to data from 10 gauged stations from 2001 to 2023. Predictors included longitude (Long), latitude (Lat), altitude, Normalized Difference Vegetation Index, and Land Surface Temperature. Performance metrics were utilized to assess the methods. The results demonstrated a notable improvement after downscaling compared to the original CHIRPS estimates. The most effective single-variable methods were simple linear regression (LR) for Long and Lat, and non-linear ML methods such as support vector machine with linear kernel (SVM-lin) and with radial basis function kernel (SVM-rbf), and artificial neural networks (ANN), employing all predictors. Surprisingly, single-variable linear methods yield better results than multivariable non-linear ones. These models provided acceptable fits to annual and mean monthly observations, and their performance tended to be better during the drier months. Downscaled annual precipitation distributions successfully captured differences between “El Niño” and non-“El Niño” years. The current study could be replicated in basins with limited gauging data, thereby enhancing water resource management. Full article

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

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27 pages, 8625 KB

Open AccessArticle

Assessment of Hybrid Grey-Green Infrastructure for Waterlogging Control and Environmental Preservation in Historic Urban Districts: A Model-Based Approach

by Haiyan Yang, Han Wang and Zhe Wang

Hydrology 2026, 13(3), 88; https://doi.org/10.3390/hydrology13030088 - 9 Mar 2026

Viewed by 399

Abstract

Historic cities face a dual challenge of managing waterlogging risks while adhering to strict preservation constraints. Traditional drainage upgrades often require extensive excavation, threatening cultural heritage. This study establishes a quantitative assessment framework for the historic urban district of City B using a [...] Read more.

Historic cities face a dual challenge of managing waterlogging risks while adhering to strict preservation constraints. Traditional drainage upgrades often require extensive excavation, threatening cultural heritage. This study establishes a quantitative assessment framework for the historic urban district of City B using a 1D-2D-coupled hydrodynamic model (InfoWorks ICM). The model was calibrated using continuous monitoring data, achieving a Nash–Sutcliffe Efficiency (NSE) of 0.91. Its spatial accuracy was subsequently validated against historical waterlogging records, showing a strong consistency between simulated flood-prone areas and observed flood locations. We simulated waterlogging distribution under rainfall events with return periods of 0.5 to 5 years. Results reveal two key deficiencies in the current drainage system under a 0.5-year return period storm event. Firstly, 75.3% of the pipe segments are hydraulically overloaded, failing to meet the design standard. Secondly, this widespread network overload contributes to surface waterlogging, with 9.58 ha (1.80% of the total area) being waterlogged. We evaluated three strategies: Low Impact Development (LID), underground storage tanks, and intercepting sewers. A hybrid grey-green infrastructure (HGGI) system was proposed, integrating source reduction and terminal storage. The HGGI system reduced waterlogged areas by 83.58% (0.5-year event) and 64.87% (5-year event), outperforming single measures. Crucially, this hybrid system achieves minimal intervention in historic street patterns through trenchless construction for intercepting sewers, decentralized LID layout and underground storage tanks, avoiding large-scale road excavation while enhancing flood resilience. This study demonstrates that hybrid strategies can effectively balance flood resilience with environmental and cultural preservation in high-density historic districts. Full article

(This article belongs to the Special Issue Advances in Urban Hydrological Modeling and Stormwater Management for Hydrological Hazard Mitigation)

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26 pages, 4149 KB

Open AccessReview

Water Resources in South of Iraq: Current State, Future Evolutions, Challenges, and Potential Solutions

by Saleem Ethaib, Marwan Fahs, Hussein Mishbak, Mohammad N. Fares, Jamal S. Makki, Abdulzahra Alhello, Hayder Abbood, Sarah N. Abdel Hassan, Abdulsattar A. Alrijabo, Mohamed Azaroual, Husam Musa Baalousha, Nicolas Baghdadi, Pierre Blanc, Juliette Duclos, Laurent Drapeau, Nizar Hariri, Hayfaa Hussein, Waleed Jebir Hassan, Talib E. Hussien, François Lehmann, Florence Le Ber, Mahdi S. Mizel, Raghdan Mohsin, Amera Nasser, Tarek Nasser, Ali Farouq Al-Ma’athedi, Ali Raeisi, Renaud Toussaint, Adrien Wanko Ngnien, Anis Younes, Kevin Del Vecchio and Ahmad Al Bitar Show full author list Hide full author list

Hydrology 2026, 13(3), 87; https://doi.org/10.3390/hydrology13030087 - 9 Mar 2026

Viewed by 1070

Abstract

Southern Iraq or lower Mesopotamia has a crucial role in Iraq’s economy due to its agricultural resources and unique wetland areas. Today southern Iraq, which is historically considered the birthplace of the development of early farming communities and the domestication of plants, is [...] Read more.

Southern Iraq or lower Mesopotamia has a crucial role in Iraq’s economy due to its agricultural resources and unique wetland areas. Today southern Iraq, which is historically considered the birthplace of the development of early farming communities and the domestication of plants, is experiencing a drastic water resources crisis which is driven by both natural and human-induced reasons such as climate change, long periodical drought and water resources mismanagement practices. Despite the severity of the crisis, there is a lack of integrated and comprehensive assessments addressing the current state of water resources in southern Iraq. This paper aims to fill this gap by providing an in-depth review of the factors affecting water resources in the region. The current situation of water resources is analyzed using different indicators such as water availability in marshes, salinity variation along Shatt al-Arab river and surface of cultivated areas. This paper reviews previous studies, summarizes the current situation, analyzes the key challenges, and explores a range of potential solutions for further investigation. This study analysis is essential for guiding advanced research efforts that offer deeper insight into the challenges and propose practical solutions. This paper identifies key topics for future research to address the water crisis. Full article

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21 pages, 7632 KB

Open AccessArticle

Study on Characteristics of Floating Ice Accumulation and Entrainment Safety Thresholds Upstream of Sluice Gates Based on Model Tests and Logistic Regression

by Suming Li, Chao Li, Huiping Hou, Shiang Zhang and Xizhi Lv

Hydrology 2026, 13(3), 86; https://doi.org/10.3390/hydrology13030086 - 6 Mar 2026

Viewed by 328

Abstract

In the complex flow fields of channels affected by sluice gates and bridge piers, winter ice transport, accumulation characteristics upstream of the gate, and the determination of entrainment thresholds are crucial for the safe operation of hydraulic projects. In this study, ice transport [...] Read more.

In the complex flow fields of channels affected by sluice gates and bridge piers, winter ice transport, accumulation characteristics upstream of the gate, and the determination of entrainment thresholds are crucial for the safe operation of hydraulic projects. In this study, ice transport experiments were conducted with and without bridge piers upstream of the gate to analyze the key factors governing the transport process and accumulation morphology of floating ice. Four machine learning models were evaluated and compared to identify the optimal model for predicting the motion state of floating ice. Based on this optimal model, the discriminant conditions for ice entrainment under both pier configurations were proposed. The results indicate that, driven by incoming hydraulic parameters, gate boundary conditions, and ice discharge, the upstream floating ice undergoes a progressive evolution: “flat accumulation

\to

“

\nabla

”-shaped accumulation

\to

wedge-shaped accumulation

\to

passing through the gate (entrainment)”. Compared to the GBDT, RF, and SVM models, the LR model achieves higher and more stable accuracy, precision, recall, and F1 scores under configurations without and with bridge piers. With AUC values reaching 0.993 and 0.997, respectively, this model demonstrates optimal comprehensive performance in classifying whether floating ice passes through the gate. Furthermore, based on the LR model, explicit algebraic formulas for the critical entrainment thresholds were constructed. Under the experimental conditions, the critical threshold intervals for the relative gate opening (e/H) are [0.170, 0.182] without piers and [0.142, 0.155] with piers. This study provides a solid theoretical foundation and technical support for ice-prevention operations and gate dispatching in cold-region hydraulic engineering under submerged outflow conditions. Full article

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

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23 pages, 1478 KB

Open AccessArticle

A Hybrid Index-Flood and Non-Stationary Bivariate Logistic Extreme-Value Framework for Flood Quantile Estimation in Data-Scarce Mexican Catchments

by Laura Berbesi-Prieto and Carlos Escalante-Sandoval

Hydrology 2026, 13(3), 85; https://doi.org/10.3390/hydrology13030085 - 5 Mar 2026

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Abstract

Regional flood frequency analysis (RFFA) is a cornerstone for estimating design floods at ungauged or data-scarce sites by pooling information within hydrologically homogeneous regions. This study proposes and evaluates a hybrid RFFA framework that integrates the Index-Flood (IF) technique with a bivariate logistic [...] Read more.

Regional flood frequency analysis (RFFA) is a cornerstone for estimating design floods at ungauged or data-scarce sites by pooling information within hydrologically homogeneous regions. This study proposes and evaluates a hybrid RFFA framework that integrates the Index-Flood (IF) technique with a bivariate logistic extreme-value model whose marginal distributions are formulated under both stationary and non-stationary assumptions. Non-stationarity is incorporated through a covariate-dependent location parameter, using time and large-scale climate indices—the Pacific Decadal Oscillation (PDO) and the Southern Oscillation Index (SOI)—as explanatory variables. The proposed approach is applied to two contrasting hydrological regions in Mexico—RH10 (Sinaloa) and RH23 (Chiapas Coast)—to assess its performance under differing climatic and hydrological regimes. Model adequacy and stability are evaluated using likelihood-based goodness-of-fit criteria (log-likelihood and Akaike Information Criterion) and a leave-one-out (jackknife) cross-validation scheme embedded within the IF regionalization workflow. Results indicate that non-stationary bivariate formulations dominate model selection at most stations and yield stable regional growth curves, providing robust and engineering-relevant performance under cross-validation. Overall, the proposed framework offers a conservative and operational pathway for regional flood quantile estimation that bridges local data scarcity and regional hydrological characterization in environments influenced by climate variability and long-term change. Full article

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16 pages, 2593 KB

Open AccessArticle

Using Hydrochemistry, Multi-Isotope, and MixSIAR Model to Analyze Nitrate Sources of Groundwater: A Case Study of the Yongning River Banks

by Zhaofei Yang, Yuesuo Yang, Yujuan Wen, Cuiping Gao, Changhong Zheng, Xueyan Teng and Yuhan La

Hydrology 2026, 13(3), 84; https://doi.org/10.3390/hydrology13030084 - 4 Mar 2026

Viewed by 350

Abstract

Groundwater nitrate (NO₃⁻) pollution, caused by anthropogenic activities, poses a global threat to water security. The mixing of multiple nitrate pollution sources and the associated biogeochemical reactions may create a complex chemical background, which renders traditional hydrochemical methods and single [...] Read more.

Groundwater nitrate (NO₃⁻) pollution, caused by anthropogenic activities, poses a global threat to water security. The mixing of multiple nitrate pollution sources and the associated biogeochemical reactions may create a complex chemical background, which renders traditional hydrochemical methods and single δ¹⁵N isotope analysis approaches limited in accurately identifying pollution sources and quantifying their contribution ratios. Accordingly, we adopted an integrated framework incorporating hydrochemistry, isotopes, and the MixSIAR model. Within this framework, results from different components mutually validate each other, helping to achieve more accurate source identification and contribution quantification. Results revealed severe nitrate contamination with striking spatial heterogeneity: concentrations were significantly higher in the eastern region (9.3–1890.7 mg·L⁻¹, Mean: 472.8 mg·L⁻¹) than in the western region (8.5–204.1 mg·L⁻¹, Mean: 52.0 mg·L⁻¹). Hydrochemical and δ¹⁸O-NO₃⁻ evidence identified nitrification as the dominant nitrogen transformation process. Critically, the MixSIAR model quantified drastically different source contributions between the two regions. In the eastern industrial zone, industrial wastewater was the predominant source (61.3%), followed by manure and sewage (18.5%). In contrast, in the western agricultural area, natural and agricultural sources dominated, with soil nitrogen contributing 43.9% and chemical fertilizer 31.7%. The findings pinpoint specific pollution drivers for each region, offering a robust scientific basis for formulating differentiated and effective nitrate pollution control strategies. Full article

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21 pages, 17583 KB

Open AccessArticle

Numerical Simulation of Rainfall-Induced Debris Flows Triggered by Cyclone Yaku 2023 in Chasquitambo, Peru

by Hildebrandt Flores, Katy Medina, Francisco Castillo-Vergara, Pablo Iribarren, Guillermo Azócar, Cesar Salazar and Edwin Loarte

Hydrology 2026, 13(3), 83; https://doi.org/10.3390/hydrology13030083 - 4 Mar 2026

Viewed by 714

Abstract

Debris flows are rapid downslope movements of soil and rock (a type of external geodynamic process) typically triggered by extreme rainfall, posing significant threats to infrastructure and human lives. The objective of this study is to assess the relationship between rainfall intensity and [...] Read more.

Debris flows are rapid downslope movements of soil and rock (a type of external geodynamic process) typically triggered by extreme rainfall, posing significant threats to infrastructure and human lives. The objective of this study is to assess the relationship between rainfall intensity and debris flow magnitude for different return periods (5, 10, 50, and 100 years) and, ultimately, to establish rainfall thresholds in Chasquitambo (Perú). This work presents numerical simulation results for extreme rainfall scenarios using the open-source software HEC-RAS v6.4.1 (Mud/Debris Flow mode), calibrated with flood marks from the recent extreme Cyclone Yaku event that occurred on 12 March 2023 (considered an approximately 100-year event). The simulations reveal a non-linear relationship between rainfall intensity and hazard, with the most extensive impacts reaching velocities of 4.5 m/s, depths of up to 7.0 m, and affecting an area of ~130,000 m². The study indicates an operational rainfall threshold of 20 mm in 24 h, which is proposed to trigger monitoring protocols, early warning systems, and effective mitigation strategies. The proposed workflow provides a transferable and data-efficient foundation for deriving operational rainfall thresholds and scenario-based hazard metrics, which are useful for early warning systems and land-use planning in similar mountain catchments. Full article

(This article belongs to the Special Issue Advances in Flood Studies: Enhancing Data Collection, Rating Curves, and Hydrological Analyses)

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25 pages, 2849 KB

Open AccessArticle

Short-Term Streamflow Forecasting for River Management, Using ARIMA Models and Recurrent Neural Networks

by Nicolai Sîrbu and Andrei-Mihai Rugină

Hydrology 2026, 13(3), 82; https://doi.org/10.3390/hydrology13030082 - 4 Mar 2026

Viewed by 503

Abstract

Short-term river water-level forecasting is essential for operational hydrology, supporting flood warning and water management. Although deep learning models such as Long Short-Term Memory (LSTM) networks have gained attention, classical statistical approaches including Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving [...] Read more.

Short-term river water-level forecasting is essential for operational hydrology, supporting flood warning and water management. Although deep learning models such as Long Short-Term Memory (LSTM) networks have gained attention, classical statistical approaches including Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) remain attractive due to their interpretability and efficiency. This study presents a controlled comparison between ARIMA/SARIMA and stacked LSTM models for 7-day-ahead water-depth forecasting using synthetic daily hydrographs representing normal, drought, and flood regimes. Model performance is assessed using a rolling-origin forecasting strategy that generates multiple overlapping predictions, reducing bias from short validation windows. Forecast skill is evaluated through standard error metrics and hydrology-oriented indicators, including the Global Forecast Skill Index (GFSI). Results show comparable median performance between SARIMA and LSTM across regimes, with no statistically significant differences detected by nonparametric tests. Apparent differences in flood conditions should be interpreted cautiously due to limited sample representation. Overall, increased model complexity does not inherently guarantee superior predictive skill in this univariate short-term setting, highlighting the importance of rigorous evaluation design in comparative forecasting studies. Full article

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

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22 pages, 8365 KB

Open AccessArticle

Numerical Simulation of Karst Groundwater Systems Under Construction of Xiushan Tunnel in Pingyanggai Syncline, Chongqing, China

by Xingyu Zhu, Qiang Xia, Mo Xu, Yinghe Wang, Yixiong Huang, Yayi Li and Boru Ding

Hydrology 2026, 13(3), 81; https://doi.org/10.3390/hydrology13030081 - 4 Mar 2026

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Abstract

Tunnel construction in karst aquifers can substantially alter groundwater flow systems. In this study, a three-dimensional groundwater flow model based on MODFLOW-CFP was developed to simulate the Pingyanggai synclinal karst system in Chongqing, China, incorporating dynamic tunnel excavation and lining processes. Under natural [...] Read more.

Tunnel construction in karst aquifers can substantially alter groundwater flow systems. In this study, a three-dimensional groundwater flow model based on MODFLOW-CFP was developed to simulate the Pingyanggai synclinal karst system in Chongqing, China, incorporating dynamic tunnel excavation and lining processes. Under natural conditions, groundwater recharge is approximately 4.8 × 10⁴ m³/d and is primarily balanced by discharge to the Yanmenkou and Miaolongtang underground rivers. Tunnel excavation introduced a new drainage outlet, generating an inflow of about 5.6 × 10⁴ m³/d. The two underground rivers exhibited contrasting responses to excavation. Discharge from the Yanmenkou underground river decreased by approximately 6 × 10³ m³/d (about 30%), indicating strong hydraulic connectivity with the tunnel, whereas the Miaolongtang underground river showed only minor changes. The simulated responses were qualitatively consistent with field observations during key excavation stages. These results demonstrate that tunnel excavation modifies not only the overall groundwater balance but also the internal redistribution of discharge pathways within the karst system, providing a quantitative basis for evaluating tunnel-induced hydrogeological impacts in complex karst environments. Full article

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

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36 pages, 67306 KB

Open AccessReview

Fluvial Characteristics of the Magdalena River (Colombia) and a Nature-Based Solution for Navigation Conditions

by Allen Bateman Pinzón and Raúl Sosa Pérez

Hydrology 2026, 13(3), 80; https://doi.org/10.3390/hydrology13030080 - 3 Mar 2026

Viewed by 469

Abstract

This study analyzes the hydro-morphological dynamics of the lower 40 km of the Magdalena River (Colombia), with particular emphasis on the reach between Malambo and the river mouth at Bocas de Ceniza. Bathymetric profiles obtained from three field campaigns conducted between 2017 and [...] Read more.

This study analyzes the hydro-morphological dynamics of the lower 40 km of the Magdalena River (Colombia), with particular emphasis on the reach between Malambo and the river mouth at Bocas de Ceniza. Bathymetric profiles obtained from three field campaigns conducted between 2017 and 2018 were used to characterize riverbed morphology and to quantify the evolution of subaqueous bedforms (dunes) under different flow conditions. The results reveal a systematic increase in dune height and wavelength with increasing discharge. The dominant discharge during the observation period was approximately 7400 m³/s, associated with a total measured sediment load of about 2000 kton/day, corresponding to a volumetric concentration of 0.12%. Variations in the Manning roughness coefficient were identified, ranging from 0.020 to 0.037, primarily driven by changes in discharge and, to a lesser extent, by spatial variability in hydraulic roughness, particularly in port areas. Bedforms exhibit significant growth during high-flow periods, consistent with findings reported in the literature. Analysis of mean velocity profiles indicates that the von Kármán coefficient varies with sediment concentration and turbulence intensity. Finally, a nature-based solution is proposed for the river mouth, consisting of reconfiguring the Thalweg in the final kilometers of the channel to replicate the meandering pattern of the adjacent bend. This intervention aims to enhance Thalweg stability, reduce saline wedge intrusion, promote sediment and flow dispersion toward the natural submarine canyon, and improve navigability at the river mouth. Full article

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

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19 pages, 5093 KB

Open AccessArticle

Extreme Hydrological Events and Land Cover Impacts on Water Resources in Haiti: Remote Sensing and Modeling Tools Can Improve Adaptation Planning

by Jeldane Joseph, Suranjana Chatterjee, Joseph J. Molnar and Frances O’Donnell

Hydrology 2026, 13(3), 79; https://doi.org/10.3390/hydrology13030079 - 3 Mar 2026

Viewed by 334

Abstract

Populations in areas with limited hydrological data face ongoing challenges related to water supply and management, with climate change increasing the risks of floods and droughts. New remote sensing and modeling tools can improve land and water management in these regions, especially when [...] Read more.

Populations in areas with limited hydrological data face ongoing challenges related to water supply and management, with climate change increasing the risks of floods and droughts. New remote sensing and modeling tools can improve land and water management in these regions, especially when combined with limited ground measurements and local knowledge of extreme events. This study examined hydrological extremes and land cover change impacts in the Grande Rivière du Nord watershed, Haiti, using satellite and model-based data. Precipitation extremes were obtained from the Global Precipitation Measurement Integrated Multi-satellite Retrievals for GPM (GPM IMERG; 2000–2025), and streamflow data were sourced from the Group on Earth Observation Global Water Sustainability (GEOGLOWS) system and bias-corrected with a small historical hydrologic database. Annual maximum series were created and fitted with Gumbel, Lognormal, and Generalized Extreme Value (GEV) distributions using the L-moment method. Goodness-of-fit tests identified the best models, and precipitation amounts for return periods of 2–100 years were estimated. The precipitation maxima aligned with locally reported extreme events, and GEV provided the best overall fit. Using the bias-corrected streamflow, a hydrologic model was calibrated and validated and then applied to land cover change scenarios. Simulations suggest that moderate land-use change can increase peak flows beyond channel capacity, raising flood risk and informing adaptation planning in northern Haiti, which has limited data. Full article

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

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30 pages, 19883 KB

Open AccessArticle

A Spatial Approach for Vadose Zone Monitoring During a Zonal Artificial Infiltration Experiment Using Custom Flexible and Rigid Time Domain Reflectometry Sensors

by Alexandros Papadopoulos, Franz Königer and Andreas Kallioras

Hydrology 2026, 13(3), 78; https://doi.org/10.3390/hydrology13030078 - 28 Feb 2026

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Abstract

This study aims at developing an integrated system comprising TDR technologies for continuous and 3D monitoring of the vadose zone with special focus on the aerial distribution of water during an artificial sprinkling experiment. The system was tested during field artificial infiltration experiments. [...] Read more.

This study aims at developing an integrated system comprising TDR technologies for continuous and 3D monitoring of the vadose zone with special focus on the aerial distribution of water during an artificial sprinkling experiment. The system was tested during field artificial infiltration experiments. The objective of this study is to evaluate a flexible long TDR sensor in the field during a sprinkling and infiltration experiment that mimics rainfall and irrigation events through zonal wetting, monitor the resulting water flows and compare the findings with those from custom rigid spatial TDR sensors. This study exclusively used the TDR technique to measure soil moisture changes during the infiltration experiment, utilizing both custom rigid spatial sensors and a flexible sensor. The results indicate that the flexible sensor, which can be installed in the soil in arrays that rigid sensors cannot, achieved logical and coherent soil moisture estimations, proving that it could also be used as a standalone sensor for soil volumetric water content measurements. The use of long flexible sensors, along with long rigid sensors, facilitates continuous, precise, and 3D monitoring of moisture changes across larger soil volumes, transcending traditional point measurements and 1D soil moisture profiles typically associated with the TDR technique. Full article

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27 pages, 14919 KB

Open AccessArticle

Sustainable Water Management in a Complex Watershed: A Case Study in Tulancingo Valley, Mexico

by Georgina Itandehui Ávila-Castañeda, Elena María Otazo-Sánchez, Silvia Chamizo-Checa, Gabriela Marisol Vázquez-Cuevas and Alma Delia Román-Gutiérrez

Hydrology 2026, 13(3), 77; https://doi.org/10.3390/hydrology13030077 - 28 Feb 2026

Viewed by 312

Abstract

This research analyzes water availability in the Tulancingo Valley (Hidalgo State, Mexico), a representative region with notable industrial and agricultural activities, over the period from 2013 to 2050. A conceptual model was developed and calculated with the Water Evaluation and Planning System (WEAP) [...] Read more.

This research analyzes water availability in the Tulancingo Valley (Hidalgo State, Mexico), a representative region with notable industrial and agricultural activities, over the period from 2013 to 2050. A conceptual model was developed and calculated with the Water Evaluation and Planning System (WEAP) simulation platform, calibrated with 2014 data, to estimate future water demand under mitigation scenarios that incorporate inertial population and industrial growth, as well as projected climate change trends. The simulation identifies the key actions that support sustainable water-resource management. Results show that agricultural groundwater demand is the dominant pressure on the aquifer, which is projected to become overexploited by 2050 (−185.65 hm³). The most effective mitigation strategies involve increasing the use of available surface water in both industrial and agricultural sectors; under these measures, the aquifer could recover and reach an annual availability of 231.7 hm³, ensuring long-term water sustainability of the valley. The modeling approach applied here offers a useful framework for similar assessments in other complex areas. Full article

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

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26 pages, 12927 KB

Open AccessArticle

Impacts of Sea-Level Rise and Recharge Fluctuations on Cutoff Wall Effectiveness for Freshwater Lens Development and Seawater Intrusion Mitigation in Unconfined Island Aquifers

by Weijiang Yu and Yipeng Zhang

Hydrology 2026, 13(3), 76; https://doi.org/10.3390/hydrology13030076 - 28 Feb 2026

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Abstract

Sea-level rise (SLR) and regional precipitation pattern change cause island subsurface freshwater, typically shaped like a thin lens, to be at higher risk of contamination from seawater intrusion (SWI). Installing a cutoff wall is considered a feasible strategy for protecting coastal fresh groundwater [...] Read more.

Sea-level rise (SLR) and regional precipitation pattern change cause island subsurface freshwater, typically shaped like a thin lens, to be at higher risk of contamination from seawater intrusion (SWI). Installing a cutoff wall is considered a feasible strategy for protecting coastal fresh groundwater from SWI. However, the performance of the cutoff wall in managing freshwater lens (FWL) development and mitigating SWI into island aquifers under SLR and aquifer recharge (RCH) fluctuations remains inadequately quantified. This study investigates how water table elevation (WTE), FWL depth, thickness, and SWI extent, measured by aquifer salt mass and freshwater volume, in an island aquifer equipped with cutoff walls, respond to SLR and RCH fluctuations. It focuses on a two-dimensional, variable-density island groundwater simulation model based on hydrogeological conditions of San Salvador Island, Bahamas. The results demonstrate that RCH critically influences cutoff wall effectiveness for FWL development and SWI mitigation, with higher RCH amplifying gains in WTE, FWL metrics, freshwater storage, and aquifer salt removal, but this influence diminishes with wall depth increasing. SLR elevates WTE in a stable manner associated with its magnitude but negligibly affects the cutoff wall performance in FWL enhancement and SWI mitigation. Under simultaneous SLR and RCH fluctuations, SLR can offset the WTE reduction caused by reduced RCH, but the joint effects of SLR and RCH on FWL metrics, freshwater storage and aquifer salt removal align with their individual impacts. Moreover, cutoff walls are more efficient in low-RCH settings, yielding greater relative improvements in FWL development and SWI mitigation per unit wall depth increase. Full article

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

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Hydrology, Volume 13, Issue 3 (March 2026) – 24 articles

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