Hydrology

10168 KiB

Open AccessArticle

Weathering Records from an Early Cretaceous Syn-Rift Lake

by Yaohua Li, Qianyou Wang and Richard H. Worden

Hydrology 2025, 12(7), 179; https://doi.org/10.3390/hydrology12070179 - 3 Jul 2025

The Aptian–Albian interval represents a significant cooling phase within the Cretaceous “hothouse” climate, marked by dynamic climatic fluctuations. High‑resolution continental records are essential for reconstructing terrestrial climate and ecosystem evolution during this period. This study examines a lacustrine‑dominated succession of the Shahezi Formation [...] Read more.

The Aptian–Albian interval represents a significant cooling phase within the Cretaceous “hothouse” climate, marked by dynamic climatic fluctuations. High‑resolution continental records are essential for reconstructing terrestrial climate and ecosystem evolution during this period. This study examines a lacustrine‑dominated succession of the Shahezi Formation (Lishu Rift Depression, Songliao Basin, NE Asia) to access paleo‑weathering intensity and paleoclimate variability between the Middle Aptian and Early Albian (c. 118.2–112.3 Ma). Multiple geochemical proxies, including the Chemical Index of Alteration (CIA), were applied within a sequence stratigraphic framework covering four stages of lake evolution. Our results indicate that a hot and humid subtropical climate predominated in the Lishu paleo‑lake, punctuated by transient cooling and drying events. Periods of lake expansion corresponded to episodes of intense chemical weathering, while two distinct intervals of aridity and cooling coincided with phases of a reduced lake level and fan delta progradation. To address the impact of potassium enrichment on CIA values, we introduced a rectangular coordinate system on A(Al₂O₃)‑CN(CaO* + Na₂O)‑K(K₂O) ternary diagrams, enabling more accurate weathering trends and CIA corrections (CIA_corr). Uncertainties in CIA correction were evaluated by integrating geochemical and petrographic evidence from deposits affected by hydrothermal fluids and external potassium addition. Importantly, our results show that metasomatic potassium addition cannot be reliably inferred solely from deviations in A‑CN‑K diagrams or the presence of authigenic illite and altered plagioclase. Calculations of “excess K₂O” and CIA_corr values should only be made when supported by robust geochemical and petrographic evidence for external potassium enrichment. This work advances lacustrine paleoclimate reconstruction methodology and highlights the need for careful interpretation of weathering proxies in complex sedimentary systems. Full article

(This article belongs to the Special Issue Lakes as Sensitive Indicators of Hydrology, Environment, and Climate)

10218 KiB

Open AccessArticle

Rainfall Organization and Storm Tracking in Urban Barcelona, NE Spain, Using a High-Resolution Rain Gauge Network

by María del Carmen Casas-Castillo, Xavier Navarro and Raül Rodríguez-Solà

Hydrology 2025, 12(7), 178; https://doi.org/10.3390/hydrology12070178 - 3 Jul 2025

Abstract

Extreme rainfall in urban areas can cause major economic damage, a problem expected to intensify with climate change. Despite this, high-resolution studies at the city scale remain limited. This study analyzes rainfall organization and storm dynamics over Barcelona using data from a dense [...] Read more.

Extreme rainfall in urban areas can cause major economic damage, a problem expected to intensify with climate change. Despite this, high-resolution studies at the city scale remain limited. This study analyzes rainfall organization and storm dynamics over Barcelona using data from a dense rain gauge network (1994–2019). The aim is to identify dominant spatial patterns and understand how storms evolve in relation to local urban and topographic features. Principal component analysis and simple scaling analysis revealed signs of a rainfall island effect, possibly linked to the urban heat island and modulated by orographic and coastal influences. Tailored rainfall indices highlighted a division between inland areas shaped by orography and coastal zones influenced by the sea. These spatial structures evolved with rainfall duration, shifting from localized contrasts at a 10 min resolution to more homogeneous distributions at daily scales. Storm tracking showed that 90% of speeds ranged from 5 to 60 km/h and intense rainfall events typically moved east–southeast toward the sea and north–northeast. Faster storms tended to follow preferred directions reflecting mesoscale circulations and possible modulations by local terrain. These findings underscore how urban morphology, local relief, and a coastal setting may shape rainfall at the city scale, in interaction with broader Mediterranean synoptic dynamics. Full article

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

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25 pages, 1568 KiB

Open AccessArticle

Analysis of the Potential Impacts of Climate Change on the Mean Annual Water Balance and Precipitation Deficits for a Catchment in Southern Ecuador

by Luis-Felipe Duque, Greg O’Donnell, Jimmy Cordero, Jorge Jaramillo and Enda O’Connell

Hydrology 2025, 12(7), 177; https://doi.org/10.3390/hydrology12070177 - 2 Jul 2025

Abstract

The mean annual water balance is essential for evaluating water availability in a catchment and planning water resources. Climate change alters this balance by affecting precipitation, evapotranspiration, and overall water availability. This study analyses the impact of climate change on the mean annual [...] Read more.

The mean annual water balance is essential for evaluating water availability in a catchment and planning water resources. Climate change alters this balance by affecting precipitation, evapotranspiration, and overall water availability. This study analyses the impact of climate change on the mean annual water balance in the Catamayo catchment, a key water source for irrigation and hydropower in southern Ecuador and northern Peru. A Budyko-based approach was employed due to its conceptual simplicity and proven robustness for estimating long-term water balances under changing climatic conditions. Using outputs from 23 Global Circulation Models (GCMs) under CMIP6’s SSP2-4.5 and SSP8.5 scenarios, the results indicate increasing aridity, particularly in the lower and middle parts of the catchment, which correspond to arid and semi-arid zones. Water availability may decrease by 26.3 ± 12.3% to 33.3 ± 17% until 2080 due to negligible changes (statistically speaking) in average precipitation but rising evapotranspiration. However, historical precipitation analysis (1961–2020) reveals an increasing trend over this historical period which can be attributed to natural climatic variability associated to the El Nino-Southern Oscillation (ENSO), possibly enhanced by anthropogenic climate change. A novel hybrid method combining the statistics of historical precipitation deficits with GCM mean projections provides estimates of future precipitation deficits. These findings suggest potential reductions in crop yields and hydropower capacity, which (although not quantitatively assessed in this study) are inferred based on the projected decline in water availability. Such impacts could lead to higher energy costs, increased reliance on fossil fuels, and intensified competition for water. Mitigation measures, including water-saving strategies, energy diversification, and integrated water resource management, are recommended to address these challenges. Full article

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23 pages, 2289 KiB

Open AccessArticle

Experimental Study on Influence of Height of Full-Width Plate Weirs on Flow Behavior, Discharge, and Energy Dissipation

by Ali Mahdian Khalili, Hossein Sohrabzadeh Anzani, Mehdi Hamidi and Sameh Ahmed Kantoush

Hydrology 2025, 12(7), 176; https://doi.org/10.3390/hydrology12070176 - 1 Jul 2025

Abstract

The role of weirs in flow regulation in water resources infrastructure and flood control is well known. In the meantime, the study of full-width plate weirs (FWPW), due to their wide application and lacking findings, is of great importance. In this study, experimental [...] Read more.

The role of weirs in flow regulation in water resources infrastructure and flood control is well known. In the meantime, the study of full-width plate weirs (FWPW), due to their wide application and lacking findings, is of great importance. In this study, experimental models were conducted at Babol Noshirvani University of Technology to investigate flow passing through FWPWs with five different heights (p = 0.07, 0.09, 0.11, and 0.15 m) under eight discharge conditions (Q = 1.4 to 6.3 L/s). The experiments were carried out in a flume measuring 4 m in length, 0.6 m in width, and 0.2 m in height. The discharges were measured with a calibrated flowmeter, and the water depths upstream of the weir (h) and the tailwater depths (h₁) were measured with a point gauge with an accuracy of 0.1 mm. For each test, the discharge coefficient (C_d), relative residual energy (E₁/E₀), and relative energy dissipation ((E₀ − E₁)/E₀) were computed. The proposed equation for calculating discharge achieved good accuracy with RMSE = 0.0002, MAE=0.0002, and R² = 0.997. Results show a reducing trend of C_d by increasing h/P, which is compatible with previous results. It was observed that at a constant discharge, relative residual energy reduces by an average of 47% by increasing weir height, and at a constant P, increasing flow discharge increases it a little. A novel accurate equation for relative energy dissipation in FWPW was proposed based on h/P that provided specific constant coefficients for each p value. Full article

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

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27 pages, 5041 KiB

Open AccessArticle

Differential Evolution in Hydrochemical Characteristics Amongst Porous, Fissured and Karst Aquifers in China

by Chengsong Li, Jie Fang, Feisheng Feng, Tingting Yao, Yongping Shan and Wanli Su

Hydrology 2025, 12(7), 175; https://doi.org/10.3390/hydrology12070175 - 1 Jul 2025

Abstract

The efficacy of water resource management and protection hinges on a profound understanding of the controlling factors and regulatory mechanisms that shape groundwater chemistry within aquifers. Despite this, our comprehension of how groundwater chemistry and ion sources vary across diverse aquifer types remained [...] Read more.

The efficacy of water resource management and protection hinges on a profound understanding of the controlling factors and regulatory mechanisms that shape groundwater chemistry within aquifers. Despite this, our comprehension of how groundwater chemistry and ion sources vary across diverse aquifer types remained limited. To bridge this gap, our study conducted a detailed hydrochemical and statistical investigation of porous, fissured, and karst aquifers. By applying multivariate statistical techniques, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), the hydrochemical characteristics and main ion sources of each aquifer type, as well as distinct controlling factors and regulation patterns, were determined. Notably, evaporation predominantly affected the hydrochemistry of porous aquifers, whereas mineral dissolution and rock weathering processes played a pivotal role in shaping the groundwater evolution of fissured and karst aquifers. HCO₃⁻ and SO₄²⁻ are the most common anions of all types, while Na⁺ is dominant in porous and fissured aquifers and Ca²⁺ is dominant in karst aquifers. The most common hydrochemical types identified were HCO₃-Ca·Mg (accounting for approximately 56.84%) and SO₄·Cl-Na (constituting approximately 21.75%). PCA results revealed that lateral recharge from fissured aquifers in hilly regions into the groundwater of porous aquifer, and wastewater discharge and agricultural fertilizer application, significantly impact the groundwater chemistry across all three aquifer types. It is worth noting that the dissolution of carbonate minerals, often influenced by human activities, had a profound effect on the hydrochemistry of each aquifer. Conversely, the dissolution of evaporitic minerals affected groundwater chemistry primarily through cation exchange processes. In summary, the hydrochemical characteristics of these aquifer types were predominantly shaped by a complex interplay of mineral dissolution, cation exchange, evaporation, and anthropogenic activities, with notable contributions from fissured aquifer recharge and pollution. These insights were critical for informing national-level strategies for groundwater resource protection and management. Full article

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24 pages, 5443 KiB

Open AccessArticle

The Characteristics and Trend Prediction of Water and Sediment Evolution at the Toudaoguai Station on the Yellow River from 1960 to 2019

by Chao Li, Jing Guo, Xinlei Guo and Hui Fu

Hydrology 2025, 12(7), 174; https://doi.org/10.3390/hydrology12070174 - 30 Jun 2025

Abstract

The Yellow River is a renowned sediment-laden river and analyzing its water–sediment evolution characteristics and trends is critical for rational water resource utilization and water security. Using annual runoff and sediment transport data from Toudaoguai Hydrological Station (1960–2019), Mann–Kendall tests, cumulative anomalies analysis, [...] Read more.

The Yellow River is a renowned sediment-laden river and analyzing its water–sediment evolution characteristics and trends is critical for rational water resource utilization and water security. Using annual runoff and sediment transport data from Toudaoguai Hydrological Station (1960–2019), Mann–Kendall tests, cumulative anomalies analysis, and wavelet analysis were used to investigate the decadal variations. A coupled ARIMA-BP model was developed to improve simulation accuracy over standalone ARIMA/BP models for trend prediction. The results showed significant decreasing trends in both runoff (Z = −3.22) and sediment transport (Z = −4.73) during 1960–2019, with change points in 1986 (runoff) and 1984 (sediment). The primary periodicities were 12 years for runoff and 31 years for sediment transport. The coupled model achieved good consistency (R² = 0.9142 for runoff, 0.8637 for sediment), outperforming individual models. Projections indicate continued declines in both variables from 2020 to 2029. Natural factors are the main cause affecting the changes in runoff, while human activities are the primary influencing factor for the changes in sediment load. This study introduces a novel approach for water–sediment analysis in the Yellow River Basin, providing technical support for sustainable water resource management. Full article

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20 pages, 4438 KiB

Open AccessArticle

Impacts of Urbanization and Climate Variability on Groundwater Environment in a Basin Scale

by Olawale Joshua Abidakun, Mitsuyo Saito, Shin-ichi Onodera and Kunyang Wang

Hydrology 2025, 12(7), 173; https://doi.org/10.3390/hydrology12070173 - 30 Jun 2025

Abstract

Globally, groundwater resources are experiencing a decline in hydraulic heads resulting from the dual effects of urbanization and climate change, highlighting the need for integrated and sustainable water resources management. Urban development in the cities of Kansai region, western Japan, presents a significant [...] Read more.

Globally, groundwater resources are experiencing a decline in hydraulic heads resulting from the dual effects of urbanization and climate change, highlighting the need for integrated and sustainable water resources management. Urban development in the cities of Kansai region, western Japan, presents a significant challenge to the sustainability of groundwater resources. This study aims to assess the combined influence of urbanization and climate change on the groundwater resources of the Nara Basin using MODFLOW 6 for two distinct periods: The Pre-Urbanization Period (PreUP: 1980–1988), and the Post-Urbanization Period (PostUP, 2000–2008) with an emphasis on spatiotemporal distribution of recharge in a multi-layer aquifer system. Simulated hydraulic heads were evaluated under three different recharge scenarios: uniformly, spatiotemporally and spatially distributed. The uniform recharge scenario both overestimates and underestimates hydraulic heads, while the spatially distributed scenario produced a simulated heads distribution similar to the spatiotemporally distributed recharge scenario, underscoring the importance of incorporating spatiotemporal variability in recharge input for accurate groundwater flow simulation. Moreover, our results highlight the relevance of spatial distribution of recharge input than temporal distribution. Our findings indicate a significant decrease in hydraulic heads of approximately 5 m from the PreUP to PostUP in the unconfined aquifer, primarily driven by changes in land use and climate. In contrast, the average head decline in deep confined aquifers is about 4 m and is mainly influenced by long-term climatic variations. The impervious land use types experienced more decline in hydraulic heads than the permeable areas under changing climate because of the impedance to infiltration and percolation exacerbating the climate variability effect. These changes in hydraulic heads were particularly evident in the interactions between surface and groundwater. The cumulative volume of groundwater discharge to the river decreased by 27%, while the river seepage into the aquifer increased by 16%. Sustainable groundwater resources management under conditions of urbanization and climate change necessitates a holistic and integrated approach. Full article

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

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25 pages, 4553 KiB

Open AccessArticle

Predictive Modeling of Flood Frequency Utilizing an Analysis of the Casimcea River in Romania

by Carmen Maftei, Constantin Cerneaga and Ashok Vaseashta

Hydrology 2025, 12(7), 172; https://doi.org/10.3390/hydrology12070172 - 30 Jun 2025

Abstract

Flooding is a recurrent natural hazard in Romania, causing significant socio-economic impacts. Historical data highlights the severity of floods, particularly the unprecedented flood of 1926. Between 1960 and 2010, Romania experienced over 400 major floods, which significantly impacted its infrastructure and population. Particularly, [...] Read more.

Flooding is a recurrent natural hazard in Romania, causing significant socio-economic impacts. Historical data highlights the severity of floods, particularly the unprecedented flood of 1926. Between 1960 and 2010, Romania experienced over 400 major floods, which significantly impacted its infrastructure and population. Particularly, the floods in 2005 and 2006 affected over 1.5 million people, resulting in 93 deaths and causing damages exceeding EUR 2 billion. In compliance with the Floods Directive, EU member states must assess and map flood hazards and risks. This study aims to develop a frequency analysis to determine discharges as a predictive indicator for different hazard levels: frequent events (10-year return period), medium probability events (100-year return period), and extreme events. The Casimcea catchment in central Dobrogea, drained by the Casimcea River into Lake Tasaul, serves as the study area. The annual maximum discharge data analysis, conducted through frequency analysis and the ELECTRE method, indicates that EV3-Min-Weibull, L-moments, and GEV-Min (L-moments) are the most effective probability density functions (PDFs). To conclude, although a single PDF model cannot be determined for the Casimcea River and its tributaries, it contributes to predictive modeling efforts. Full article

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32 pages, 4407 KiB

Open AccessArticle

A Comparative Analysis of Remotely Sensed and High-Fidelity ArcSWAT Evapotranspiration Estimates Across Various Timescales in the Upper Anthemountas Basin, Greece

by Stefanos Sevastas, Ilias Siarkos and Zisis Mallios

Hydrology 2025, 12(7), 171; https://doi.org/10.3390/hydrology12070171 - 29 Jun 2025

Abstract

In data-scarce regions and ungauged basins, remotely sensed evapotranspiration (ET) products are increasingly employed to support hydrological model calibration. In this study, a high-resolution hydrological model was developed for the Upper Anthemountas Basin using ArcSWAT, with a focus on comparing simulated ET outputs [...] Read more.

In data-scarce regions and ungauged basins, remotely sensed evapotranspiration (ET) products are increasingly employed to support hydrological model calibration. In this study, a high-resolution hydrological model was developed for the Upper Anthemountas Basin using ArcSWAT, with a focus on comparing simulated ET outputs to three freely available remote sensing-based ET products: the MODIS MOD16 Collection 5, the updated MODIS MOD16A2GF Collection 6.1, and the SSEBop Version 5 dataset. ET estimates derived from the calibrated SWAT model were compared to all remote sensing products at the basin scale, across various temporal scales over the 2002–2014 simulation period. Results indicate that the MOD16 Collection 5 product achieved the closest correspondence with SWAT-simulated ET across all temporal scales. The MOD16A2GF Collection 6.1 product exhibited moderate overall agreement, with improved performance during early summer. The SSEBop Version 5 dataset generally displayed weaker correlation, but demonstrated enhanced alignment during the driest years of the record. Strong correspondence is observed when averaging the ET values from all satellite products. These findings underscore the importance of exercising caution when utilizing remotely sensed ET products as the sole basis for hydrological model calibration, particularly given the variability in performance among different datasets. Full article

(This article belongs to the Special Issue Hydrological Modelling for the Sustainable Management of Water Resources in River Basins)

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19 pages, 1630 KiB

Open AccessArticle

Just a Single-Layer CNN for Stochastic Modeling: A Discriminator-Free Approach

by Evangelos Rozos

Hydrology 2025, 12(7), 170; https://doi.org/10.3390/hydrology12070170 - 29 Jun 2025

Abstract

The advent of machine learning (ML) has significantly transformed hydrology, particularly in the simulation of hydrological flows. However, ML techniques have not been employed to the same extent in stochastic hydrology. In applied sciences, the most common ML-based approach for developing stochastic simulation [...] Read more.

The advent of machine learning (ML) has significantly transformed hydrology, particularly in the simulation of hydrological flows. However, ML techniques have not been employed to the same extent in stochastic hydrology. In applied sciences, the most common ML-based approach for developing stochastic simulation schemes is the use of generative adversarial networks (GANs), which consist of two sub-models, that is, a generator and a discriminator. Despite their potential, GANs have notable limitations, including high architectural complexity and the requirement to divide observed time series into shorter segments to generate sufficient training examples. This segmentation reduces the effective length of the series, limiting the model’s ability to capture and reproduce long-term dependencies. In this study, we propose a simpler stochastic scheme based on a single convolutional neural network (CNN) used as a generator, replacing the discriminator component of the GAN with a specifically designed cost function. The model is applied to a case study involving measured flow velocity time series and evaluated against traditional stochastic schemes designed for both Markovian and Hurst–Kolmogorov processes. Results show that the CNN-based approach not only offers computational simplicity but also outperforms conventional methods in preserving key statistical characteristics of the observed data. Full article

(This article belongs to the Section Statistical Hydrology)

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14 pages, 7591 KiB

Open AccessArticle

A Paleo-Perspective of 21st Century Drought in the Hron River (Slovakia)

by Igor Leščešen, Abel Andrés Ramírez Molina and Glenn Tootle

Hydrology 2025, 12(7), 169; https://doi.org/10.3390/hydrology12070169 - 28 Jun 2025

Abstract

The Hron River is a vital waterway in central Slovakia. In evaluating observed streamflow records for the past ~90 years, the Hron River displayed historically low hydrologic summer (April–May–June–July–August–September (AMJJAS)) streamflow for the 10-, 20-, and 30-year periods ending in 2020. When using [...] Read more.

The Hron River is a vital waterway in central Slovakia. In evaluating observed streamflow records for the past ~90 years, the Hron River displayed historically low hydrologic summer (April–May–June–July–August–September (AMJJAS)) streamflow for the 10-, 20-, and 30-year periods ending in 2020. When using self-calibrated Palmer Drought Severity Index (scPDSI) proxies developed from tree-ring records, skillful regression-based reconstructions of AMJJAS streamflow were developed for two gauges (Banská Bystrica and Brehy) on the Hron River. The recent observed droughts were compared to these reconstructions and revealed the Hron River experienced extreme drought in the 21st century. A further comparison of observed wet (pluvial) periods revealed that the most extreme robust streamflow periods in the observed record were frequently exceeded in the reconstructed (paleo) record. The Hron River has recently been experiencing decline, and we hypothesize that this decline may be associated with anthropogenic influences, the natural climatic cycle, or the changing climate. Full article

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19 pages, 4916 KiB

Open AccessArticle

Deep Learning-Based Daily Streamflow Prediction Model for the Hanjiang River Basin

by Jianze Huang, Jialang Chen, Haijun Huang and Xitian Cai

Hydrology 2025, 12(7), 168; https://doi.org/10.3390/hydrology12070168 - 27 Jun 2025

Abstract

The sharp decline in streamflow prediction accuracy with increasing lead times remains a persistent challenge for effective water resources management and flood mitigation. In this study, we developed a coupled deep learning model for daily streamflow prediction in the Hanjiang River Basin, China. [...] Read more.

The sharp decline in streamflow prediction accuracy with increasing lead times remains a persistent challenge for effective water resources management and flood mitigation. In this study, we developed a coupled deep learning model for daily streamflow prediction in the Hanjiang River Basin, China. The proposed model integrates self-attention (SA), a one-dimensional convolutional neural network (1D-CNN), and bidirectional long short-term memory (BiLSTM). The model’s effectiveness was assessed during flood events, and its predictive uncertainty was quantified using kernel density estimation (KDE). The results demonstrate that the proposed model consistently outperforms baseline models across all lead times. It achieved Nash-Sutcliffe Efficiency (NSE) scores of 0.92, 0.86, and 0.79 for 1-, 3-, and 5-days, respectively, showing particular strength at these extended lead time predictions. During major flood events, the model demonstrated an enhanced capacity to capture peak magnitudes and timings. It achieved the highest NSE values of 0.924, 0.862, and 0.797 for the 1-, 3-, and 5-day forecasting horizons, respectively, thereby showcasing the strengths of integrating CNN and SA mechanisms for recognizing local hydrological patterns. Furthermore, KDE-based uncertainty analysis identified a high prediction interval coverage in different forecast periods and a relatively narrow prediction interval width, indicating the strong robustness of the proposed model. Overall, the proposed SA-CNN-BiLSTM model demonstrates significantly improved accuracy, especially for extended lead times and flood events, and provides robust uncertainty quantification, thereby offering a more reliable tool for reservoir operation and flood risk management. Full article

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22 pages, 9661 KiB

Open AccessArticle

Regional Groundwater Flow and Advective Contaminant Transport Modeling in a Typical Hydrogeological Environment of Northern New Jersey

by Toritseju Oyen and Duke Ophori

Hydrology 2025, 12(7), 167; https://doi.org/10.3390/hydrology12070167 - 27 Jun 2025

Abstract

This study develops a numerical model to simulate groundwater flow and contaminant transport in a “typical hydrogeological environment” of northern New Jersey, addressing freshwater decline. Focusing on the Lower Passaic water management area (WMA), we model chloride transport in a fractured-rock aquifer, where [...] Read more.

This study develops a numerical model to simulate groundwater flow and contaminant transport in a “typical hydrogeological environment” of northern New Jersey, addressing freshwater decline. Focusing on the Lower Passaic water management area (WMA), we model chloride transport in a fractured-rock aquifer, where fracture networks control hydraulic conductivity and porosity. The urbanized setting—encompassing Montclair State University (MSU) and municipal wells—features heterogeneous groundwater systems and critical water resources, providing an ideal case study for worst-case contaminant transport scenarios. Using MODFLOW and MODPATH, we simulated flow and tracked particles over 20 years. Results show that chloride from MSU reached the Third River in 4 years and the Passaic River in 10 years in low-porosity fractures (0.2), with longer times (8 and 20 years) in high-porosity zones (0.4). The First Watchung Mountains were identified as the primary recharge area. Chloride was retained in immobile pores but transported rapidly through fractures, with local flow systems (MSU to Third River) faster than regional systems (MSU to Passaic River). These findings confirm chloride in groundwater, which may originate from road salt application, can reach discharge points in 4–20 years, emphasizing the need for recharge-area monitoring, salt-reduction policies, and site-specific assessments to protect fractured-rock aquifers. Full article

(This article belongs to the Special Issue Hydrological Modelling for the Sustainable Management of Water Resources in River Basins)

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25 pages, 8903 KiB

Open AccessArticle

Comparative Analysis of Satellite-Based Rainfall Products for Drought Assessment in a Data-Poor Region

by Hansini Gayanthika, Dimuthu Lakshitha, Manthika Chathuranga, Gouri De Silva and Jeewanthi Sirisena

Hydrology 2025, 12(7), 166; https://doi.org/10.3390/hydrology12070166 - 27 Jun 2025

Abstract

Drought is one of the most impactful natural disasters, and it significantly impacts three main sectors of a country: the environment, society, and the economy. Therefore, drought assessment and monitoring are essential for reducing vulnerability and risk. However, insufficient and sparse long-term in [...] Read more.

Drought is one of the most impactful natural disasters, and it significantly impacts three main sectors of a country: the environment, society, and the economy. Therefore, drought assessment and monitoring are essential for reducing vulnerability and risk. However, insufficient and sparse long-term in situ rainfall data limit drought assessment in developing countries. Recently developed satellite-based rainfall products, available at different temporal and spatial resolutions, offer a valuable alternative in data-poor regions like Sri Lanka, where rain gauge networks are sparse and maintenance issues are prevalent. This study evaluates the accuracy of satellite-based rainfall estimates compared to in situ observations for drought assessment within the Mi Oya River Basin, Sri Lanka. We assessed the performance of various satellite-based rainfall products, including IMERG, GSMaP, CHIRPS, PERSIANN, and PERSIANN-CDR, by comparing them with ground-based observations over 20 years, from 2003 to 2022. Our methodology involved checking detection accuracy using the False Alarm Ratio (FAR), Probability of Detection (POD), and Critical Success Index (CSI), and assessing accuracy through metrics such as Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC), Percentage Bias (PBias), and Nash–Sutcliffe Efficiency (NSE). The two best-performing satellite-based rainfall products were used for meteorological and hydrological drought assessment. In the accuracy detection metrics, the results indicate that while products like IMERG and GSMaP generally provide reliable rainfall estimates, others like PERSIANN and PERSIANN-CDR tend to overestimate rainfall. For instance, IMERG shows a CSI range of 0.04–0.25 for moderate and heavy rainfall and 0.10–0.30 for light rainfall. On a monthly scale, IMERG and CHIRPS showed the highest performance, with CC (NSE) values of 0.81–0.94 (0.53–0.83) and 0.79–0.86 (0.54–0.74), respectively. However, GSMaP showed the lowest bias, with a range of −17.1–13.2%. Recorded drought periods over 1981–2022 (1998–2022) were reasonably well captured by CHIRPS (IMERG) products in the Mi Oya River Basin. Our results highlighted uncertainties and discrepancies in the capability of different rainfall products to assess drought conditions. This research provides valuable insights for optimizing the use of satellite rainfall products in hydrological modeling and disaster preparedness in the Mi Oya River Basin. Full article

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17 pages, 6551 KiB

Open AccessArticle

Monitoring the Impacts of Human Activities on Groundwater Storage Changes Using an Integrated Approach of Remote Sensing and Google Earth Engine

by Sepide Aghaei Chaleshtori, Omid Ghaffari Aliabad, Ahmad Fallatah, Kamil Faisal, Masoud Shirali, Mousa Saei and Teodosio Lacava

Hydrology 2025, 12(7), 165; https://doi.org/10.3390/hydrology12070165 - 26 Jun 2025

Abstract

Groundwater storage refers to the water stored in the pore spaces of underground aquifers, which has been increasingly affected by both climate change and anthropogenic activities in recent decades. Therefore, monitoring their changes and the factors that affect it is of great importance. [...] Read more.

Groundwater storage refers to the water stored in the pore spaces of underground aquifers, which has been increasingly affected by both climate change and anthropogenic activities in recent decades. Therefore, monitoring their changes and the factors that affect it is of great importance. Although the influence of natural factors on groundwater is well-recognized, the impact of human activities, despite being a major contributor to its change, has been less explored due to the challenges in measuring such effects. To address this gap, our study employed an integrated approach using remote sensing and the Google Earth Engine (GEE) cloud-free platform to analyze the effects of various anthropogenic factors such as built-up areas, cropland, and surface water on groundwater storage in the Lake Urmia Basin (LUB), Iran. Key anthropogenic variables and groundwater data were pre-processed and analyzed in GEE for the period from 2000 to 2022. The processes linking these variables to groundwater storage were considered. Built-up area expansion often increases groundwater extraction and reduces recharge due to impervious surfaces. Cropland growth raises irrigation demand, especially in semi-arid areas like the LUB, leading to higher groundwater use. In contrast, surface water bodies can supplement water supply or enhance recharge. The results were then exported to XLSTAT software2019, and statistical analysis was conducted using the Mann–Kendall (MK) non-parametric trend test on the variables to investigate their potential relationships with groundwater storage. In this study, groundwater storage refers to variations in groundwater storage anomalies, estimated using outputs from the Global Land Data Assimilation System (GLDAS) model. Specifically, these anomalies are derived as the residual component of the terrestrial water budget, after accounting for soil moisture, snow water equivalent, and canopy water storage. The results revealed a strong negative correlation between built-up areas and groundwater storage, with a correlation coefficient of −1.00. Similarly, a notable negative correlation was found between the cropland area and groundwater storage (correlation coefficient: −0.85). Conversely, surface water availability showed a strong positive correlation with groundwater storage, with a correlation coefficient of 0.87, highlighting the direct impact of surface water reduction on groundwater storage. Furthermore, our findings demonstrated a reduction of 168.21 mm (millimeters) in groundwater storage from 2003 to 2022. GLDAS represents storage components, including groundwater storage, in units of water depth (mm) over each grid cell, employing a unit-area, mass balance approach. Although storage is conceptually a volumetric quantity, expressing it as depth allows for spatial comparison and enables conversion to volume by multiplying by the corresponding surface area. Full article

(This article belongs to the Topic Natural Hazards Monitoring, Risk Assessment, Modelling and Management in the Artificial Intelligence Era)

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29 pages, 3325 KiB

Open AccessReview

Half-Century Review and Advances in Closed-Form Functions for Estimating Soil Water Retention Curves

by Ali Rasoulzadeh, Javad Bezaatpour, Javanshir Azizi Mobaser and Jesús Fernández-Gálvez

Hydrology 2025, 12(7), 164; https://doi.org/10.3390/hydrology12070164 - 25 Jun 2025

Abstract

This review provides a comprehensive overview of the closed-form expressions developed for estimating the soil water retention curve (SWRC) from 1964 to the present. Since the concept of the SWRC was introduced in 1907, numerous closed-form functions have been proposed to describe the [...] Read more.

This review provides a comprehensive overview of the closed-form expressions developed for estimating the soil water retention curve (SWRC) from 1964 to the present. Since the concept of the SWRC was introduced in 1907, numerous closed-form functions have been proposed to describe the relationship between soil matric suction and volumetric water content, each with distinct strengths and limitations. Given the variability in SWRC shapes influenced by soil texture, structure, and organic matter, models in the form of sigmoidal, multi-exponential, lognormal, hyperbolic, and hybrid functions have been designed to fit experimental SWRC data. Based on the number of adjustable parameters, these models are categorized into three main groups: three-, four-, and five-parameter models. They can also be classified as one-, two-, or three-segment functions depending on their structural complexity. A review of the developed models indicates that most are effective in representing the SWRC between the residual and saturated water content range. To capture the full range of the SWRC, hybrid functions have been proposed by combining traditional models. This review presents and discusses these models in chronological order of publication. Full article

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14 pages, 2407 KiB

Open AccessArticle

Refining Rainfall Derived from Satellite Radar for Estimating Inflows at Lam Pao Dam, Thailand

by Nathaporn Areerachakul, Jaya Kandasamy, Saravanamuthu Vigneswaran and Kittitanapat Bandhonopparat

Hydrology 2025, 12(7), 163; https://doi.org/10.3390/hydrology12070163 - 25 Jun 2025

Abstract

This project aimed to evaluate the use of meteorological satellite-derived rainfall data to estimate water inflows to dams. In this study, the Lam Pao Dam in the Chi Basin, Thailand, was used as a case study. Rainfall data were obtained using the PERSIANN [...] Read more.

This project aimed to evaluate the use of meteorological satellite-derived rainfall data to estimate water inflows to dams. In this study, the Lam Pao Dam in the Chi Basin, Thailand, was used as a case study. Rainfall data were obtained using the PERSIANN technique. To improve accuracy, satellite-derived rainfall estimates were adjusted using ground-based rainfall measurements from stations located near and within the catchment area, applying the 1-DVAR method. The Kriging method was employed to estimate the spatial distribution of rainfall over the catchment area. This approach resulted in a Probability of Detection (POD) of 0.92 and a Threat Score (TS) of 0.72 for rainfall estimates in the Chi Basin. Rainfall data from the Weather Research and Forecasting (WRF) numerical models were used as inputs for the HEC-HMS model to simulate water inflows into the dam. To refine rainfall estimates, various microphysics schemes were tested, including WSM3, WSM5, WSM6, Thompson, and Thompson Aerosol-Aware. Among these, the Thomson Aerosol-Aware scheme demonstrated the highest accuracy, achieving an average POD of 0.96, indicating highly reliable rainfall predictions for the Lam Pao Dam catchment. The findings underscore the potential benefits of using satellite-derived meteorological data for rainfall estimation, particularly where installing and maintaining ground-based measurement stations is difficult, e.g., forests/mountainous areas. This research contributes to a better understanding of satellite-derived rainfall patterns and their influence on catchment hydrology for enhanced water resource analysis. Full article

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

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3 pages, 142 KiB

Open AccessBook Review

Book Review: Water Sustainability; Zhang, H.X., Ed.; Springer: New York, NY, USA, 2023; ISBN: 978-1-0716-2465-4

by Dmitry A. Ruban

Hydrology 2025, 12(7), 162; https://doi.org/10.3390/hydrology12070162 - 23 Jun 2025

Abstract

Water is an essential resource of contemporary civilization and also a factor of its progress [...] Full article

31 pages, 3453 KiB

Open AccessArticle

Addressing Weather Data Gaps in Reference Crop Evapotranspiration Estimation: A Case Study in Guinea-Bissau, West Africa

by Gabriel Garbanzo, Jesus Céspedes, Marina Temudo, Tiago B. Ramos, Maria do Rosário Cameira, Luis Santos Pereira and Paula Paredes

Hydrology 2025, 12(7), 161; https://doi.org/10.3390/hydrology12070161 - 22 Jun 2025

Abstract

Crop water use (ET_c) is typically estimated as the product of crop evapotranspiration (ET_o) and a crop coefficient (K_c). However, the estimation of ET_o requires various meteorological data, which are often unavailable or of poor quality, [...] Read more.

Crop water use (ET_c) is typically estimated as the product of crop evapotranspiration (ET_o) and a crop coefficient (K_c). However, the estimation of ET_o requires various meteorological data, which are often unavailable or of poor quality, particularly in countries such as Guinea-Bissau, where the maintenance of weather stations is frequently inadequate. The present study aimed to assess alternative approaches, as outlined in the revised FAO56 guidelines, for estimating ET_o when only temperature data is available. These included the use of various predictors for the missing climatic variables, referred to as the Penman–Monteith temperature (PMT) approach. New approaches were developed, with a particular focus on optimizing the predictors at the cluster level. Furthermore, different gridded weather datasets (AgERA5 and MERRA-2 reanalysis) were evaluated for ET_o estimation to overcome the lack of ground-truth data and upscale ET_o estimates from point to regional and national levels, thereby supporting water management decision-making. The results demonstrate that the PMT is generally accurate, with RMSE not exceeding 26% of the average daily ET_o. With regard to shortwave radiation, using the temperature difference as a predictor in combination with cluster-focused multiple linear regression equations for estimating the radiation adjustment coefficient (k_Rs) yielded accurate results. ET_o estimates derived using raw (uncorrected) reanalysis data exhibit considerable bias and high RMSE (1.07–1.57 mm d⁻¹), indicating the need for bias correction. Various correction methods were tested, with the simple bias correction delivering the best overall performance, reducing RMSE to 0.99 mm d⁻¹ and 1.05 mm d⁻¹ for AgERA5 and MERRA-2, respectively, and achieving a normalized RMSE of about 22%. After implementing bias correction, the AgERA5 was found to be superior to the MERRA-2 for all the studied sites. Furthermore, the PMT outperformed the bias-corrected reanalysis in estimating ET_o. It was concluded that PMT-ET_o can be recommended for further application in countries with limited access to ground-truth meteorological data, as it requires only basic technical skills. It can also be used alongside reanalysis data, which demands more advanced expertise, particularly for data retrieval and processing. Full article

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