Water

21 pages, 1713 KB

Open AccessArticle

Hydrochemical Characteristics of Shallow Groundwater and Analysis of Vegetation Water Sources in the Ulan Buh Desert

by Xiaomeng Li, Jie Zhou, Wenhui Zhou, Lei Mao, Changyu Wang, Yi Hao and Peng Bian

Water 2025, 17(21), 3058; https://doi.org/10.3390/w17213058 (registering DOI) - 24 Oct 2025

The Ulan Buh Desert represents a quintessential desert ecosystem in the arid northwest of China. As the key factor to maintain the stability of ecosystem, the chemical characteristics of groundwater and its water relationship with vegetation need to be further studied. Through field [...] Read more.

The Ulan Buh Desert represents a quintessential desert ecosystem in the arid northwest of China. As the key factor to maintain the stability of ecosystem, the chemical characteristics of groundwater and its water relationship with vegetation need to be further studied. Through field sampling, hydrochemical analysis, hydrogen and oxygen isotope testing and the Bayesian mixing model (MixSIAR), this study systematically analyzed the chemical characteristics of groundwater, spatial distribution and vegetation water sources in the study area. The results show that the groundwater is predominantly of the Cl⁻–SO₄²⁻ type, with total dissolved solids (TDS) ranging from 0.34 to 9.56 g/L (mean: 2.03 g/L), indicating medium to high salinity and significant spatial heterogeneity. These characteristics are jointly controlled by rock weathering, evaporative concentration, and ion exchange. Soil water isotopes exhibited vertical differentiation: the surface layer (0–20 cm) was significantly affected by evaporative fractionation (δD: −72‰ to −45‰; δ¹⁸O: −9.3‰ to −6.2‰), while deep soil water (60–80 cm) showed isotopic enrichment (δD: −29‰ to −58‰; δ¹⁸O: −6.8‰ to 0.9‰), closely matching groundwater isotopic signatures. Vegetation water use strategies demonstrated depth stratification: shallow-rooted plants such as Reaumuria soongorica and Kalidium foliatum relied primarily on shallow soil water (0–20 cm, >30% contribution), whereas deep-rooted plants such as Nitraria tangutorum and Ammopiptanthus mongolicus predominantly extracted water from the 40–80 cm soil layer (>30% contribution), with no direct dependence on groundwater. Full article

(This article belongs to the Special Issue Advances in Groundwater Resource Development: Innovative Methods and Technologies)

24 pages, 2070 KB

Open AccessArticle

Enhanced Time Series–Physics Model Approach for Dam Discharge Impacts on River Levels: Seomjin River, South Korea

by Chunggil Jung, Darae Kim, Gayeong Lee and Jongyoon Park

Water 2025, 17(21), 3057; https://doi.org/10.3390/w17213057 (registering DOI) - 24 Oct 2025

Abstract

In dam operations, sudden discharges during extreme rainfall events can pose severe flood risks to downstream communities. This study developed a dam discharge-based river water level forecasting model using a data-driven deep learning approach, long short-term memory (LSTM). To enhance predictive performance, physics-based [...] Read more.

In dam operations, sudden discharges during extreme rainfall events can pose severe flood risks to downstream communities. This study developed a dam discharge-based river water level forecasting model using a data-driven deep learning approach, long short-term memory (LSTM). To enhance predictive performance, physics-based HEC-RAS simulation outputs, including extreme events, were incorporated as additional inputs. The Seomjin River Basin in South Korea, which recently experienced severe flooding, was selected as the study area. Hydrological data from 2010 to 2023 were utilized, with 2023 reserved for model testing. Forecasts were generated for four lead times (3, 6, 12, and 24 h), consistent with the operational flood forecasting system of the Ministry of Environment, South Korea. Using only observed data, the model achieved high accuracy at upstream sites, such as Imsil-gun (Iljung-ri, R² = 0.92, RMSE = 0.27 m) and Gokseong (Geumgok Bridge, R² = 0.91, RMSE = 0.35 m), for a 6-h lead time. However, performance was lower at Gurye-gun (Songjeong-ri, R² = 0.72, RMSE = 1.48 m) due to the complex influence of two dams. Incorporating enhanced inputs significantly improved predictions at Gurye-gun (R² = 0.91, RMSE = 1.17 m at 3 h). Overall, models using only observed data performed better at upstream sites, while enhanced inputs were more effective in downstream or multi-dam regions. The 6-h lead time yielded the highest overall accuracy, highlighting the potential of this approach to improve real-time dam operations and flood risk management. Full article

(This article belongs to the Special Issue Advances in Machine Learning and Artificial Intelligence Technologies for Hydrological Processes and Hydrologic Disasters)

19 pages, 8637 KB

Open AccessArticle

The Shrinkage of Lakes on the Semi-Arid Inner Mongolian Plateau Is Still Serious

by Juan Bai, Yue Zhuo, Naichen Xing, Fuping Gan, Yi Guo, Baikun Yan, Yichi Zhang and Ruoyi Li

Water 2025, 17(21), 3056; https://doi.org/10.3390/w17213056 (registering DOI) - 24 Oct 2025

Abstract

In the Inner Mongolia Plateau Lake Zone (IMP), situated in China’s semi-arid region, its lake water storage change plays a critical role in wetland ecosystem conservation and regional water security through its lake water storage dynamics. To investigate long-term lake water storage (LWS) [...] Read more.

In the Inner Mongolia Plateau Lake Zone (IMP), situated in China’s semi-arid region, its lake water storage change plays a critical role in wetland ecosystem conservation and regional water security through its lake water storage dynamics. To investigate long-term lake water storage (LWS) changes, this study proposes a novel lake monitoring framework that reconstructs historical lake level time series and estimates water level variations in lakes without altimetry data. Using multi-source satellite data, we quantified LWS variations (2000–2021) across 109 lakes (≥5 km²) on the IMP and examined their spatiotemporal patterns. Our results reveal a net decline of 1.21 Gt in total LWS over the past two decades, averaging 0.06 Gt/yr. A distinct shift occurred around 2012: LWS decreased by 10.82 Gt from 2000 to 2012 but increased by 9.61 Gt from 2013 to 2021. Spatially, significant LWS reductions were concentrated in the central and eastern IMP, resulting from intensive water diversion and groundwater exploitation. In contrast, increases were observed mainly in the western and southern regions, driven by enhanced precipitation and reduced aridity. The findings improve understanding of lake dynamics in semi-arid China over the last two decades and offer technical guidance for sustainable water resource management. Full article

(This article belongs to the Special Issue Remote Sensing of Spatial-Temporal Variation in Surface Water)

► Show Figures

Figure 1

20 pages, 8623 KB

Open AccessArticle

Revitalization of Trakošćan Lake—Preliminary Analyses of the Sediment with the Possibility of Its Reuse in the Environment

by Saša Zavrtnik, Dijana Oskoruš, Sanja Kapelj and Jelena Loborec

Water 2025, 17(21), 3055; https://doi.org/10.3390/w17213055 (registering DOI) - 24 Oct 2025

Abstract

Trakošćan Lake is an artificial lake created in the mid-19th century for aesthetic and economic purposes. The area around the lake has been protected as park forest. Recently, the lake has become the most famous example of eutrophication in Croatia, as by 2022, [...] Read more.

Trakošćan Lake is an artificial lake created in the mid-19th century for aesthetic and economic purposes. The area around the lake has been protected as park forest. Recently, the lake has become the most famous example of eutrophication in Croatia, as by 2022, a significant amount of sediment had accumulated in it. Therefore, the lake was drained that same year, followed by mechanical removal of the sediment. The total amount of sediment removed was 204,000 m³. After the removal work, a particularly important question arose of what to do with such a large amount of sediment. The objective of this research was to gain specific insight into the chemical composition of the sediment with the aim of its possible use in agricultural production for increasing the quality of arable land. A comprehensive qualitative geochemical and agrochemical analysis of the sediment composition was carried out for the first time, including indicators of the pH value, amount of organic matter and carbon, total nitrogen, available phosphorus and potassium, amount of carbonates, and the presence of metals, metalloids, and non-metals, of which As, Cd, Hg, and Pb are toxic. Electrochemical, spectrophotometric, and titration methods were used, along with three atomic absorption spectrometry techniques. The results of the analyses were interpreted in comparison with the natural substrate, as well as with the current regulations for agricultural land in the Republic of Croatia. According to this, sediment is not harmful for the environment. Full article

(This article belongs to the Section Water Erosion and Sediment Transport)

► Show Figures

Figure 1

18 pages, 1891 KB

Open AccessArticle

Plants Decrease Network Complexity and Increase Environmental Stability of Microbial Communities, Shifting the Dominant Environmental Controls from Carbon-Related Factors to pH in Newly Formed Wetlands

by Yijing Wang, Junyu Dong, Xiaoke Liu, Changchao Li, Yongkang Zhao, Yan Wang and Jian Liu

Water 2025, 17(21), 3054; https://doi.org/10.3390/w17213054 (registering DOI) - 24 Oct 2025

Abstract

Soil microorganisms are crucial regulators of wetland ecological functions and are significantly influenced by plants. However, the ecological patterns underlying soil microbial responses to plants during wetland restoration remain poorly understood. Soil samples from sections with and without plants in each wetland were [...] Read more.

Soil microorganisms are crucial regulators of wetland ecological functions and are significantly influenced by plants. However, the ecological patterns underlying soil microbial responses to plants during wetland restoration remain poorly understood. Soil samples from sections with and without plants in each wetland were collected to investigate the impact of plants on soil microbial communities using high-throughput absolute quantification sequencing and analysis of soil physicochemical properties. Results showed that environmental drivers exerted stronger effects on microbial communities in areas without plants. Soil microbial networks in areas without plants were more complex and stable, while plants enhanced the contribution of stochastic processes to microbial community assembly. In areas with plants, pH was the most important environmental driver of soil microbial community variations, while organic carbon was the primary driver in areas without plants. Moreover, bacteria exhibited higher sensitivity than fungi to the same environmental variation in both areas with and without plants. In summary, our findings elucidate the responses of soil microbial ecological patterns to plants in newly formed wetlands, while emphasizing that the major environmental drivers of soil microbial communities are influenced by plants. This study provides important implications for enhancing wetland restoration efficiency. Full article

(This article belongs to the Section Soil and Water)

► Show Figures

Figure 1

15 pages, 913 KB

Open AccessArticle

The Impact of China’s Targeted Poverty Alleviation Policy on Water Resource Utilization Pressure and Allocation in Arid Regions: A Case Study of Hotan Prefecture, Xinjiang

by Jin-Wei Huo, Fu-Qiang Xia, Rong-Qian Lu, Dan-Ni Lu, De-Gang Yang and Yang Chen

Water 2025, 17(21), 3053; https://doi.org/10.3390/w17213053 (registering DOI) - 24 Oct 2025

Abstract

Targeted poverty alleviation is a major national initiative in China. The Hotan region, located within the four prefectures of Southern Xinjiang, is one of the 14 contiguous poverty-stricken areas in China as well as a quintessential inland arid zone. Water scarcity is the [...] Read more.

Targeted poverty alleviation is a major national initiative in China. The Hotan region, located within the four prefectures of Southern Xinjiang, is one of the 14 contiguous poverty-stricken areas in China as well as a quintessential inland arid zone. Water scarcity is the primary constraint on development in the Hotan region and a major bottleneck for Northwest China as a whole. However, previous assessments of the effectiveness of poverty alleviation measures have primarily focused on industrial growth itself, lacking an analysis of the adaptability between key regional resource elements and industrial poverty alleviation measures. The core of promoting targeted poverty alleviation in arid regions is properly managing the relationships within the “industry–water resources” system and achieving a balance between resource use, environmental capacity, and economic development. Focusing on the coordinated development of industry and water resources, this study evaluates the spatio-temporal evolution of the industry–water resource relationships in the Hotan region after the implementation of the targeted poverty alleviation policy with the aim of measuring the sustainability of industrial poverty alleviation outcomes in this arid region. The results indicate the following: (1) The targeted poverty alleviation policy has reduced industrial water consumption. Following the policy’s implementation, industrial water consumption decreased by 541 million m³, driven by improvements in water use intensity and shifts in the industrial structure. The primary contributor to this reduction was enhanced water use efficiency within the primary sector. (2) The policy exacerbated the misallocation of water resources relative to industrial output across the region. The Gini coefficient for water resources versus GDP across Hotan’s eight counties and cities rose from 0.26 to 0.32, indicating a shift from a ‘relatively balanced’ to a ‘moderately imbalanced’ allocation. Therefore, achieving sustainable poverty alleviation in this arid region necessitates enhanced coordination between industrial development and water resources. Full article

(This article belongs to the Section Water Resources Management, Policy and Governance)

► Show Figures

Figure 1

25 pages, 1582 KB

Open AccessReview

A Review on Climate Change Impacts on Freshwater Systems and Ecosystem Resilience

by Dewasis Dahal, Nishan Bhattarai, Abinash Silwal, Sujan Shrestha, Binisha Shrestha, Bishal Poudel and Ajay Kalra

Water 2025, 17(21), 3052; https://doi.org/10.3390/w17213052 (registering DOI) - 24 Oct 2025

Abstract

Climate change is fundamentally transforming global water systems, affecting the availability, quality, and ecological dynamics of water resources. This review synthesizes current scientific understanding of climate change impacts on hydrological systems, with a focus on freshwater ecosystems, and regional water availability. Rising global [...] Read more.

Climate change is fundamentally transforming global water systems, affecting the availability, quality, and ecological dynamics of water resources. This review synthesizes current scientific understanding of climate change impacts on hydrological systems, with a focus on freshwater ecosystems, and regional water availability. Rising global temperatures are disrupting thermal regimes in rivers, lakes, and ponds; intensifying the frequency and severity of extreme weather events; and altering precipitation and snowmelt patterns. These changes place mounting stress on aquatic ecosystems, threaten water security, and challenge conventional water management practices. The paper also identifies key vulnerabilities across diverse geographic regions and evaluates adaptation strategies such as integrated water resource management (IWRM), the water, energy and food (WEF) nexus, ecosystem-based approaches (EbA), the role of advanced technology and infrastructure enhancements. By adopting these strategies, stakeholders can strengthen the resilience of water systems and safeguard critical resources for both ecosystems and human well-being. Full article

(This article belongs to the Special Issue Water Management and Geohazard Mitigation in a Changing Climate)

► Show Figures

Figure 1

19 pages, 5541 KB

Open AccessArticle

Hybrid LSTM-ARIMA Model for Improving Multi-Step Inflow Forecasting in a Reservoir

by Angela Neagoe, Eliza-Isabela Tică, Liana-Ioana Vuță, Otilia Nedelcu, Gabriela-Elena Dumitran and Bogdan Popa

Water 2025, 17(21), 3051; https://doi.org/10.3390/w17213051 (registering DOI) - 24 Oct 2025

Abstract

In the hydropower sector, accurate estimation of short-term reservoir inflows is an essential element to ensure efficient and safe management of water resources. Short-term forecasting supports the optimization of energy production, prevention of uncontrolled water discharges, planning of equipment maintenance, and adaption of [...] Read more.

In the hydropower sector, accurate estimation of short-term reservoir inflows is an essential element to ensure efficient and safe management of water resources. Short-term forecasting supports the optimization of energy production, prevention of uncontrolled water discharges, planning of equipment maintenance, and adaption of operational strategies. In the absence of data on topography, vegetation, and basin characteristics (required in distributed or semi-distributed models), data-driven approaches can serve as effective alternatives for inflow prediction. This study proposes a novel hybrid approach that reverses the conventional LSTM (Long Short-Term Memory)—ARIMA (Autoregressive Integrated Moving Average) sequence: LSTM is first used to capture nonlinear hydrological patterns, followed by ARIMA to model residual linear trends.The model was calibrated using daily inflow data in the Izvorul Muntelui–Bicaz reservoir in Romania from 2012 to 2020, tested for prediction on the day ahead in a repetitive loop of 365 days corresponding to 2021 and further evaluated through multiple seven-day forecasts randomly selected to cover all 12 months of 2021. For the tested period, the proposed model significantly outperforms the standalone LSTM, increasing the R² from 0.93 to 0.96 and reducing RMSE from 9.74 m³/s to 6.94 m³/s for one-day-ahead forecasting. For multistep forecasting (84 values, randomly selected, 7 per month), the model improves R² from 0.75 to 0.89 and lowers RMSE from 18.56 m³/s to 12.74 m³/s. Thus, the hybrid model offers notable improvements in multi-step forecasting by capturing both seasonal patterns and nonlinear variations in hydrological data. The approach offers a replicable data-driven solution for inflow prediction in reservoirs with limited physical data. Full article

(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)

► Show Figures

Figure 1

24 pages, 2539 KB

Open AccessArticle

From Indices to Algorithms: A Hybrid Framework of Water Quality Assessment Using WQI and Machine Learning Under WHO and FAO Standards

by Senem Güneş Şen

Water 2025, 17(21), 3050; https://doi.org/10.3390/w17213050 (registering DOI) - 24 Oct 2025

Abstract

Assessing water quality is essential for the sustainable use of freshwater resources, especially under increasing climatic and agricultural pressures. Small irrigation ponds are particularly sensitive to pollution due to their limited buffering capacity. This study evaluates the water quality of the Taşçılar and [...] Read more.

Assessing water quality is essential for the sustainable use of freshwater resources, especially under increasing climatic and agricultural pressures. Small irrigation ponds are particularly sensitive to pollution due to their limited buffering capacity. This study evaluates the water quality of the Taşçılar and Yumurtacılar ponds in Kastamonu, Türkiye, by combining conventional Water Quality Indices (WQI) with machine-learning-based interpretation. Physicochemical parameters were measured monthly for one year, and water quality was classified according to WHO and FAO thresholds using the CCME-WQI and weighted arithmetic methods. The integrated approach identified significant differences among standards and highlighted the parameters most responsible for water quality degradation. Machine-learning models improved the interpretation of these indices and supported consistent classification across datasets. The findings emphasize that coupling index-based and data-driven methods can enhance routine monitoring and provide actionable insights for sustainable irrigation-water management, thereby contributing to achieving the SDGs 6, 13, and 15. Full article

(This article belongs to the Special Issue Water Modeling Using Combined Machine Learning and Fieldwork Investigation)

► Show Figures

Figure 1

22 pages, 4399 KB

Open AccessArticle

Coupled Model Validation and Characterization on Rainfall-Driven Runoff and Non-Point Source Pollution Processes in an Urban Watershed System

by Hantao Wang, Genyu Yuan, Yang Ping, Peng Wei, Fangze Shang, Wei Luo, Zhiqiang Hou, Kairong Lin, Zhenzhou Zhang and Cuijie Feng

Water 2025, 17(21), 3049; https://doi.org/10.3390/w17213049 - 24 Oct 2025

Abstract

Rainfall-driven non-point source (NPS) pollution has become a critical issue for water environment management in urban watershed systems. However, single-model use is limited to fully represent the intricate processes of rainfall-correlated NPS pollution generation and dispersion for effective decision-making. This study develops a [...] Read more.

Rainfall-driven non-point source (NPS) pollution has become a critical issue for water environment management in urban watershed systems. However, single-model use is limited to fully represent the intricate processes of rainfall-correlated NPS pollution generation and dispersion for effective decision-making. This study develops a novel cross-scale, multi-factor coupled model framework to characterize hydrologic and NPS pollution responses to different rainfall events in Shenzhen, China, a representative worldwide metropolis facing challenges from rapid urbanization. The calibrated and validated coupled model achieved remarkable agreements with observed hydrologic (Nash–Sutcliffe efficiency, NSE > 0.81) and water quality (NSE > 0.85) data in different rainfall events and demonstrated high-resolution dynamic changes in flow and pollutant transfer within the studied watershed. In an individual rainfall event, heterogeneous spatial distributions of discharge and pollutant loads were found, highly correlated with land use types. The temporal change pattern and risk of flooding and NPS pollution differed significantly with rainfall intensity, and the increase in the pollutants (mean 322% and 596%, respectively) was much larger than the discharge (207% and 302%, respectively) under intense rainfall conditions. Based on these findings, a decision-support framework was established, featuring land-use-driven spatial prioritization of industrial hotspots, rainfall-intensity-stratified management protocols with event-triggered operational rules, and integrated source-pathway-receiving end intervention strategies. The validated model framework provides quantitative guidance for optimizing infrastructure design parameters, establishing performance-based regulatory standards, and enabling real-time operational decision-making in urban watershed management. Full article

(This article belongs to the Special Issue Urban Water Pollution Control: Theory and Technology, 2nd Edition)

► Show Figures

Figure 1

26 pages, 652 KB

Open AccessReview

Coagulation–Sedimentation in Water and Wastewater Treatment: Removal of Pesticides, Pharmaceuticals, PFAS, Microplastics, and Natural Organic Matter

by Ewelina Łukasiewicz

Water 2025, 17(21), 3048; https://doi.org/10.3390/w17213048 - 24 Oct 2025

Abstract

Coagulation–sedimentation remains a widely used process in drinking and wastewater treatment, yet its performance for emerging contaminants requires further evaluation. This review summarizes recent advances in conventional and novel coagulant systems for the removal of pesticides, pharmaceuticals, per- and polyfluoroalkyl substances (PFAS), natural [...] Read more.

Coagulation–sedimentation remains a widely used process in drinking and wastewater treatment, yet its performance for emerging contaminants requires further evaluation. This review summarizes recent advances in conventional and novel coagulant systems for the removal of pesticides, pharmaceuticals, per- and polyfluoroalkyl substances (PFAS), natural organic matter (NOM), and micro- and nanoplastics (MNPs). The efficiency of conventional aluminum- and iron-based coagulants typically ranges from 30–90% for NOM and pesticides, 10–60% for pharmaceuticals, <20% for PFAS, and up to 95% for microplastics. Modified and hybrid materials, including titanium-based and bio-derived coagulants, demonstrate superior performance through combined mechanisms of charge neutralization, adsorption, and complexation. The zeta potential of particles was identified as a key factor in optimizing MNP removal. The ability of iron and titanium to form complexes with organic ligands significantly influences the removal of organic pollutants and metal–organic interactions in water matrices. While most research remains at the laboratory scale, promising developments in hybrid and electrocoagulation systems indicate potential for field-scale application. The review highlights that coagulation is best applied as a pretreatment step in integrated systems, enhancing subsequent adsorption, oxidation, or membrane processes. Future studies should focus on large-scale validation, energy efficiency, and the recovery of metal oxides (e.g., TiO₂) from residual sludge to improve sustainability. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

► Show Figures

Figure 1

25 pages, 2395 KB

Open AccessArticle

Eco-Tourism and Biodiversity Conservation in Aquaculture Lagoons: The Role of Operator Philosophy and Low-Vibration Pontoon Boats

by Po-Jen Chen, Chun-Han Shih, Yu-Chi Sung and Tang-Chung Kan

Water 2025, 17(21), 3047; https://doi.org/10.3390/w17213047 - 23 Oct 2025

Abstract

Aquaculture lagoons must reconcile visitor access with biodiversity protection. This study integrates results of a large survey of the attitudes of tour operators with field observations of fish populations to test whether operator choices can align tourism and conservation. Using data from 801 [...] Read more.

Aquaculture lagoons must reconcile visitor access with biodiversity protection. This study integrates results of a large survey of the attitudes of tour operators with field observations of fish populations to test whether operator choices can align tourism and conservation. Using data from 801 guided-tour participants in Taiwan’s Cigu Lagoon, a sequential experience hierarchy was validated whereby environmental knowledge enhanced attitudes, strengthened perceived guide professionalism, induced flow, and ultimately increased conservation intention (R² = 0.523). Experiential service quality exerted stronger effects than functional quality (β = 0.287 vs. 0.156; both p < 0.001). Parallel underwater monitoring indicated that electric, low-vibration motors were associated with richer fish assemblages and larger fish body sizes; fish abundance is 61% higher and mean body length 38% greater, with community composition differing significantly by motor type (PERMANOVA, p < 0.001). Together, these results link training and technology adoption to measurable ecological gains and pro-conservation motivation, indicating that electrified propulsion and interpretive practice are mutually reinforcing levers for biodiversity-positive tourism. The framework offers directly actionable criteria—motor choice, guide development, and safety/facility context—for transitioning small-scale fisheries and recreation toward low-impact marine experiences. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

► Show Figures

Figure 1

18 pages, 2705 KB

Open AccessArticle

Real-Time Risk Rate Quantification Model and Early Warning Method for Earth–Rock Dams Under Sudden Changes in Reservoir Water Levels

by Xiang Luo, Fuheng Ma, Wei Ye, Benxing Lou, Qiang Li and Hanman Li

Water 2025, 17(21), 3046; https://doi.org/10.3390/w17213046 - 23 Oct 2025

Abstract

Under the influence of global climate change, extreme weather events have become more frequent, and earth and rockfill dams often encounter unconventional working conditions such as sudden changes in reservoir water levels during operation. These abrupt changes are characterized by their strong suddenness [...] Read more.

Under the influence of global climate change, extreme weather events have become more frequent, and earth and rockfill dams often encounter unconventional working conditions such as sudden changes in reservoir water levels during operation. These abrupt changes are characterized by their strong suddenness and rapid rate of change, which can be challenging for traditional numerical analysis methods due to slow modeling and time-consuming calculations, presenting certain limitations. Therefore, an approach has been developed that integrates seepage monitoring data into the failure probability analysis and early warning methods for earth and rockfill dams. Based on the model’s prediction results, dynamic safety warning indicators for the effect of single measurement points on earth and rockfill dams under sudden reservoir water level changes have been quantitatively designed. A risk probability function reflecting the relationship between the residuals of seepage monitoring effects and the risk rate has been constructed to calculate the risk rate of single measurement points for dam seepage effects. By employing the Copula function, which considers the differences and correlations in monitoring effect amounts across different parts of the dam, the single-point seepage risk rates are elevated to a multi-point seepage risk rate analysis. This enables the quantification of the overall seepage risk rate of dams under sudden reservoir water level changes. Case study results show that the safety model has high prediction accuracy. The joint risk rate of the dam based on the Copula function can simultaneously consider spatial correlations and individual differences among multiple measurement points, effectively reducing the interference of randomness in the calculation of single-point risk rates. This method successfully achieves the dynamic transformation of actual seepage effect measurements into risk rates, providing a theoretical basis and technical support for the operational management and safety monitoring of earth and rockfill dams during emergency events. Full article

(This article belongs to the Special Issue Intelligent Safety Diagnosis and Reinforcement of Water-Related Buildings)

► Show Figures

Figure 1

23 pages, 2997 KB

Open AccessArticle

Improving a Prediction Model for Tunnel Water Inflow Estimation Using LSTM and Bayesian Optimization

by Zhen Huang, Zishuai Yang, Yun Wu, Lijian Ma, Tao Sun, Zhenpeng Wang, Kui Zhao, Xiaojun Zhang, Haigang Li and Yu Zheng

Water 2025, 17(21), 3045; https://doi.org/10.3390/w17213045 - 23 Oct 2025

Abstract

Water inrush and mud burst disasters pose severe challenges to the safe and efficient construction of underground engineering. Water inflow prediction is closely related to drainage design, disaster prevention and control, and the safety of the surrounding ecological environment. Thus, assessing the water [...] Read more.

Water inrush and mud burst disasters pose severe challenges to the safe and efficient construction of underground engineering. Water inflow prediction is closely related to drainage design, disaster prevention and control, and the safety of the surrounding ecological environment. Thus, assessing the water inflow accurately is of importance. This study proposes a Bayesian Optimization-Long Short-Term Memory (BOA-LSTM) recurrent neural network for predicting tunnel water inflow. The model is based on four input parameters, namely tunnel depth (H), groundwater level (h), rock quality designation (RQD), and water-richness (W), with water inflow (WI) as the single-output variable. The model first processes and analyzes the data, quantitatively characterizing the correlations between input parameters. The tunnel water inflow is predicted using the long short-term memory (LSTM) recurrent neural network, and the Bayesian optimization algorithm (BOA) is employed to select the hyperparameters of the LSTM, primarily including the number of hidden layer units, initial learning rate, and L2 regularization coefficient. The modeling process incorporates a five-fold cross-validation strategy for dataset partitioning, which effectively mitigates overfitting risks and enhances the model’s generalization capability. After a comprehensive comparison among a series of machine learning models, including a long short-term memory recurrent neural network (LSTM), random forest (RF), back propagation neural network (BP), extreme learning machine (ELM), radial basis function neural network (RBFNN), least squares support vector machine (LIBSVM), and convolutional neural network (CNN), BOA-LSTM performed excellently. The proposed BOA-LSTM model substantially surpasses the standard LSTM and other comparative models in tunnel water inflow prediction, demonstrating superior performance in both accuracy and generalization. Hence, it provides a reference basis for tunnel engineering water inflow prediction. Full article

(This article belongs to the Special Issue Advances in Hydro-Thermal–Mechanical Coupling Geotechnical Engineering)

► Show Figures

Figure 1

18 pages, 650 KB

Open AccessArticle

The Influence of Sewage on the Quantitative and Functional Diversity of Nematode Communities in Constructed Wetlands (VFCW): Analysis of Trophic Relationships Using Canonical Methods

by Magdalena Bagińska, Tomasz Warężak, Wacław Romaniuk, Dawid Kozacki, Zbigniew Skibko, Andrzej Borusiewcz and Jarosław Dąbrowski

Water 2025, 17(21), 3044; https://doi.org/10.3390/w17213044 - 23 Oct 2025

Abstract

Given the increasing demand for water and the need to reduce energy consumption, modern wastewater treatment systems should be characterised by high pollutant removal efficiency while consuming low resources. Hydrophytic wastewater treatment plants with vertical flow through a soil-plant bed (VFCW) are one [...] Read more.

Given the increasing demand for water and the need to reduce energy consumption, modern wastewater treatment systems should be characterised by high pollutant removal efficiency while consuming low resources. Hydrophytic wastewater treatment plants with vertical flow through a soil-plant bed (VFCW) are one solution that meets these requirements. The efficiency of these systems largely depends on the biological activity of the bed, of which free-living soil nematodes are an important component. The study presented in this paper aimed to assess the relationship between the quality of domestic wastewater flowing into VFCW beds and the abundance and trophic structure of soil nematode communities. The analysis was carried out on two real-world sites, where VFCW beds were the third stage of the plant bed system. Both treatment plants received only domestic wastewater. Statistical analysis showed no significant differences (p > 0.05) in the physicochemical composition of the wastewater flowing into the two treatment plants, indicating homogeneous system feed conditions. Nevertheless, canonical correspondence analysis (CCA) showed that the relationships between effluent parameters and the abundance of individual nematode trophic groups differed in each bed, suggesting the influence of local environmental and biocenotic conditions. In particular, bacterivorous nematodes—key to bed function—were shown to be sensitive to different sets of variables at the two sites despite similar effluent composition. These results confirm that the rhizosphere—a zone of intense interactions between plant roots, microorganisms, and soil microfauna—plays a critical role in shaping the biological activity of the bed. Nematodes, particularly bacterivorous nematodes, support the mineralisation of organic matter and nutrient cycling, resulting in increased efficiency of treatment processes. The stability of the total nematode abundance, irrespective of inflow conditions, demonstrates the bed biocenosis high ecological resilience to external disturbances. The study’s results highlight the importance of an ecosystem approach in designing and managing nature-based solutions (NBS) treatment plants, which can be a sustainable component of sustainable water and wastewater management. Full article

(This article belongs to the Special Issue Rural Wastewater Treatment by Nature-Based Solutions)

► Show Figures

Figure 1

34 pages, 23946 KB

Open AccessArticle

Estimation of Groundwater Recharge in the Volcanic Aquifers in a Tropical Climate, Southwestern Ethiopia: Insights from Water Table Fluctuation and Chloride Mass Balance Methods

by Adisu Befekadu Kebede, Fayera Gudu Tufa, Wagari Mosisa Kitessa, Beekan Gurmessa Gudeta, Seifu Kebede Debela, Alemu Yenehun, Fekadu Fufa Feyessa, Thomas Hermans and Kristine Walraevens

Water 2025, 17(21), 3043; https://doi.org/10.3390/w17213043 - 23 Oct 2025

Abstract

The sustainable use and management of groundwater resources is a challenging issue due to population growth and climate change. Accurate quantification of groundwater recharge is a basic requirement for effective groundwater resource management, yet it is still lacking in many areas around the [...] Read more.

The sustainable use and management of groundwater resources is a challenging issue due to population growth and climate change. Accurate quantification of groundwater recharge is a basic requirement for effective groundwater resource management, yet it is still lacking in many areas around the world. The study was designed to estimate recharge to groundwater from natural rainfall in the Gilgel Gibe and Dhidhessa catchments in southwestern Ethiopia, employing the water table fluctuation (WTF) and chloride mass balance (CMB) techniques. These methods are being applied for the first time in the study area and have not previously been used in these catchments. Given the region’s data scarcity, a community-based data collection program was implemented and supplemented with additional field measurements and secondary data sources. Groundwater level, spring discharge, and rainfall were monitored over the 2022/2023 hydrological year. Groundwater level fluctuations were found to be influenced by topography and rainfall patterns, reaching 8.2 m in amplitude in the upstream part of the catchments. Chloride concentrations were determined in groundwater samples collected from hand-dug wells and springs, and rainwater was also collected. Rainwater exhibited a mean chloride concentration of 2.46 mg/L, while groundwater chloride concentrations ranged from 3 mg/L to 36.99 mg/L. The estimated recharge rates varied spatially, ranging from 170 to 850 mm/year using the CMB method (11% to 55% of annual rainfall, mean recharge rate of 454 mm/year) and from 76 to 796 mm/year using the WTF method (4% to 43% of annual rainfall, mean recharge rate of 439 mm/year). Notably, recharge estimates were lowest downstream in the lowland areas and highest upstream in the highland regions. Rainfall amount, local lithology, and topography were identified as major influences on groundwater recharge across the study area. Both CMB and WTF methods were deemed applicable in the volcanic aquifers, provided that all the respective assumptions are followed. This study significantly contributes to the groundwater dataset for the region, in addition to recharge estimation and the research conclusions, emphasizing the importance of long-term monitoring and time series analysis of chloride data to reduce uncertainties. The work serves as a valuable reference for researchers, policymakers, and regional water resource managers. Full article

(This article belongs to the Section Hydrogeology)

► Show Figures

Figure 1

15 pages, 1225 KB

Open AccessArticle

Forms of Element Migration in Natural and Drinking Waters of Krasnoshchelye Village (Kola Peninsula, Russia) and Human Health Risk Assessment

by Svetlana Mazukhina, Svetlana Drogobuzhskaya, Vladimir Masloboev, Aleksandr Safonov, Anna Shirokaya, Sergey Sandimirov and Vladislav Rybachenko

Water 2025, 17(21), 3042; https://doi.org/10.3390/w17213042 - 23 Oct 2025

Abstract

This work is a logical continuation of the study of the chemical composition of the waters of the Lovozersky district (Kola Peninsula, Russia), where an indigenous population resides. The problem statement is caused by the discovery of rare and rare earth elements in [...] Read more.

This work is a logical continuation of the study of the chemical composition of the waters of the Lovozersky district (Kola Peninsula, Russia), where an indigenous population resides. The problem statement is caused by the discovery of rare and rare earth elements in drinking water and the high rate of illness among the residents of the Lovozersky district. The goal of this work is to assess the quality of natural waters in the village of Krasnoshchelye (Kola Peninsula, Russia) and compare it with the composition of other waters in the Kola Peninsula, taking into account sanitary standards (maximum permissible concentrations) and biologically significant concentrations. As a result, the chemical composition of surface and groundwater was studied, their quality was characterized, and the forms of element migration in the “solution–crystalline substance” system in water and the human body (using the stomach as an example) were examined. The results of studies of drinking water in the village of Krasnoshchelye indicate that the macro-(Ca, Mg, Na, K) and microelement (Co, Cu, Mn, Ni, V, Zn, Cr) composition has lower concentrations in terms of biological significance for the elemental balance of humans than the recommended levels for them. The exceptions are the elements U, Th, and Y, whose concentrations are several times higher than their lower limits of biologically significant concentrations. In the human body, within the “water–gastric juice” system, the forms of the migration of elements and newly formed phases depend not only on the acidity of the stomach but also on the amount of gastric juice, which are individual characteristics of a person and their age. It has been established that well water contains rare elements and up to 50 µg L⁻¹ of rare earth elements, and changes in their migration forms can lead to accumulation in the human body and become a cause of diseases of the nervous system and other organs. Full article

(This article belongs to the Special Issue Water Quality Studies: Assessing the Presence of Nutrients and Pollutants)

► Show Figures

Figure 1

30 pages, 11120 KB

Open AccessArticle

Impact of Extreme Droughts on the Water Balance in the Peruvian–Ecuadorian Amazon Basin (2003–2024)

by Daniel Martínez-Castro, Jhan-Carlo Espinoza, Ken Takahashi, Miguel Octavio Andrade, Dimitris A. Herrera, Abel Centella-Artola, James Apaestegui, Elisa Armijos, Ricardo Gutiérrez, Sly Wongchuig and Fey Yamina Silva

Water 2025, 17(21), 3041; https://doi.org/10.3390/w17213041 - 23 Oct 2025

Abstract

This study assesses the impact of extreme droughts on the surface and atmospheric water balance of the Peruvian Amazon basin during 2003–2024. It extends previous work by incorporating multiple datasets for precipitation (CHIRPS, MSWEP, and ERA5) and evapotranspiration (ERA5, GLDAS, Amazon-Paca, and observations [...] Read more.

This study assesses the impact of extreme droughts on the surface and atmospheric water balance of the Peruvian Amazon basin during 2003–2024. It extends previous work by incorporating multiple datasets for precipitation (CHIRPS, MSWEP, and ERA5) and evapotranspiration (ERA5, GLDAS, Amazon-Paca, and observations from the Quistococha flux tower) and comparing three drought indices: Maximum Cumulative Water Deficit (MCWD), Standardized Precipitation Evapotranspiration Index (SPEI), and self-calibrated Palmer Drought Severity Index (scPDSI). The study focuses on the Peruvian–Ecuadorian Amazon basin, particularly on the Amazon and Madre de Dios river basins, closing at Tamshiyacu and Amaru Mayu stations, respectively. The results confirm four extreme drought years (2004–2005, 2009–2010, 2022–2023, and 2023–2024) with major precipitation deficits in dry seasons and significant reductions in runoff and total water storage anomalies (TWSAs), physically manifesting as negative surface balances indicating net terrestrial water depletion and negative atmospheric balances reflecting reduced moisture convergence, with residuals signaling hydrological uncertainties. The study highlights significant imbalances in the water cycle during droughts and underscores the need to use multiple indicators and datasets to accurately assess hydrological responses under extreme climatic conditions in the Amazon basin. Full article

(This article belongs to the Special Issue The Impact of Climate Change and Land Use on Water Resources—an Issue of Environmental Global Safety)

► Show Figures

Figure 1

44 pages, 15150 KB

Open AccessArticle

Impact of Climate Change on Reference Evapotranspiration: Bias Assessment and Climate Models in a Semi-Arid Agricultural Zone

by Osvaldo Galván-Cano, Martín Alejandro Bolaños-González, Jorge Víctor Prado-Hernández, Adolfo Antenor Exebio-García, Adolfo López-Pérez and Gerardo Colín-García

Water 2025, 17(21), 3040; https://doi.org/10.3390/w17213040 - 23 Oct 2025

Abstract

Climate change (CC) is a growing threat to water security in agricultural regions, particularly in semi-arid areas. This study evaluates the impact of CC on reference evapotranspiration (ET₀) in Irrigation District 001 Pabellón de Arteaga, Aguascalientes (DR 001), with the [...] Read more.

Climate change (CC) is a growing threat to water security in agricultural regions, particularly in semi-arid areas. This study evaluates the impact of CC on reference evapotranspiration (ET₀) in Irrigation District 001 Pabellón de Arteaga, Aguascalientes (DR 001), with the aim of strengthening its sustainable management. We used historical data (2002–2023) and future projections (2026–2100) from 22 CMIP6 global climate models, previously corrected for bias under the scenarios SSP2-4.5 and SSP5-8.5. The evaluation of the correction methods showed that PTF-scale performed best in correcting precipitation, solar radiation, relative humidity, and wind speed, although the latter showed a low correlation. The maximum, mean, and minimum temperatures showed a better fit with the RQUANT and QUANT methods. The ACCESS-ESM1-5 model displayed the best performance in six of the nine corrected variables; therefore, it was the most suitable model to estimate ET₀. The uncertainty analysis showed that the FAO-56 method, although characterized by a higher current error, is more robust for future projections. A progressive increase in ET₀ is projected under both CC scenarios, ranging from 13.0 to 15.8% (SSP2-4.5), and between 12.5 and 20.4% (SSP5-8.5). The results highlight the urgent need to implement water adaptation strategies in DR 001 and make informed decisions to achieve resilient water management in the face of CC. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

► Show Figures

Figure 1

26 pages, 3270 KB

Open AccessArticle

GRU-Based Reservoir Operation with Data Integration for Real-Time Flood Control

by Li Li and Kyung Soo Jun

Water 2025, 17(21), 3039; https://doi.org/10.3390/w17213039 - 22 Oct 2025

Abstract

Reservoir operation serves as a critical non-structural measure for real-time flood management, aimed to minimize downstream flood damage while ensuring dam safety. This study develops and evaluates a Gated Recurrent Unit (GRU)-based reservoir operation model with data integration (DI) to enhance flood management [...] Read more.

Reservoir operation serves as a critical non-structural measure for real-time flood management, aimed to minimize downstream flood damage while ensuring dam safety. This study develops and evaluates a Gated Recurrent Unit (GRU)-based reservoir operation model with data integration (DI) to enhance flood management capabilities. Optimal reservoir outflows are first determined for historical flood events using the Interior Point Optimizer (IPOPT), a deterministic optimization model designed to minimize peak outflows. The optimized hydrographs are compared with observed outflows to assess the benefits of improved operational strategies. GRU models are then trained and validated using inflow hydrographs and resulting optimal reservoir storage and release data. Various input configurations are tested, incorporating DI of lagged observations and forecasted values to evaluate their influence on model accuracy. The study also examines multiple hyperparameter settings to identify the optimal configuration. The methodology is applied to the Namgang Dam in South Korea, simulating hourly operations during flood events. Results indicate that historical reservoir inflow and storage are the most influential inputs, while adding precipitation (historical or forecasted) and/or forecasted inflows does not improve model performance. The GRU model with DI successfully replicates optimized reservoir operations, demonstrating its reliability and efficiency in flood management. This framework supports timely and informed decision-making and offers a promising approach for enhancing flood risk mitigation through improved reservoir operations. Full article

(This article belongs to the Special Issue Machine Learning Applications in the Water Domain)

► Show Figures

Figure 1

14 pages, 1321 KB

Open AccessArticle

Adsorption–Desorption of Antimony (V) and Phosphorus (V) in Two Typical Soils: Release Behavior and Environmental Implications

by Xingyu Lu, Yuting Zhao, Kefeng Yao, Fande Meng, Feiyue Li, Zhenyu Wu and Yongbing Cai

Water 2025, 17(21), 3038; https://doi.org/10.3390/w17213038 - 22 Oct 2025

Abstract

The competitive adsorption between phosphorus (V) and antimony (V) may influence the release of antimony from Sb-contaminated soils. The objectives of this study were to evaluate the effect of P(V) on the adsorption–desorption behavior and transport of Sb(V) in two typical soil types. [...] Read more.

The competitive adsorption between phosphorus (V) and antimony (V) may influence the release of antimony from Sb-contaminated soils. The objectives of this study were to evaluate the effect of P(V) on the adsorption–desorption behavior and transport of Sb(V) in two typical soil types. Specifically, the simultaneous adsorption, competitive interactions, and miscible displacement dynamics of P(V) and Sb(V) in these soils were investigated. Results clearly indicated that the competitive effect of P(V) on Sb(V) adsorption is more pronounced in acidic red soil than in alkaline calcareous soil. The adsorption capacity of Sb(V) decreased with increasing solution pH, leading to greater mobility of Sb(V) in both soils. P(V) was preferentially adsorbed over Sb(V) in both soil types. Sb(V) adsorption isotherms fitting by Freundlich model yielded higher coefficients of determination (R²) compared to the Langmuir model, while the Langmuir model provided a good fit to the P(V) adsorption isotherms. The total released amounts of P(V) and Sb(V) accounted for 0% and 0.4%, respectively, in red soil and 2.7% and 48.6%, respectively, in calcareous soil, relative to their adsorption capacities. The red soil exhibited remarkably strong binding affinity, with only minimal amounts of P(V) and Sb(V) released after five consecutive desorption steps. Breakthrough curves (BTCs) revealed that the presence of P(V) can promote significant Sb(V) release from the soils, which persists over an extended duration. This study on the adsorption–desorption behavior of P(V) and Sb(V) in two typical soils enhances our understanding of their mobility, fate, and associated environmental risks. In conclusion, the assessment of environmental risks from antimony-contaminated soils should take into account the competitive adsorption–desorption interactions between Sb(V) and P(V). Full article

(This article belongs to the Special Issue Contaminants in Aquatic Systems: Biogeochemical Processes, Ecological Impacts)

► Show Figures

Figure 1

17 pages, 3442 KB

Open AccessArticle

Optimization of Irrigation Efficiency and Water Retention in Agroecological Systems Through Organic Matter Management

by Charles Cachipuendo, Alison Pacheco, Rocío Contero and Jorge Sandoval

Water 2025, 17(21), 3037; https://doi.org/10.3390/w17213037 - 22 Oct 2025

Abstract

Water scarcity poses a critical constraint to sustainable agriculture, particularly in small-scale systems that rely on traditional irrigation methods. Although organic matter (OM) is known to enhance soil structure and water-holding capacity, quantitative evidence regarding optimal OM levels and their interaction with microbial [...] Read more.

Water scarcity poses a critical constraint to sustainable agriculture, particularly in small-scale systems that rely on traditional irrigation methods. Although organic matter (OM) is known to enhance soil structure and water-holding capacity, quantitative evidence regarding optimal OM levels and their interaction with microbial activity in agroecological contexts remains limited. This study evaluates the effect of different OM contents (2.37%, 3.42%, 5.55%, 7.89%, and 9.43%) on infiltration, moisture retention, and microbiological dynamics in 129 agroecological plots located in the northern highlands of Ecuador. Field and laboratory assessments revealed that intermediate OM levels (between 3.42% and 5.55%) optimize available water retention (up to 14.78%) and stabilize infiltration. In contrast, excessive OM levels (>7.9%) decrease retention efficiency and increase leaching risk. Microbial activity showed a positive correlation with OM up to a certain threshold, beyond which fungal and yeast activity declined under field conditions. The results underscore the importance of managing OM within an optimal functional range to improve irrigation efficiency, enhance microbial resilience, and support water sustainability in agroecological production systems. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

► Show Figures

Graphical abstract

16 pages, 3446 KB

Open AccessArticle

Groundwater Heavy Metal Contamination and Health Risk Assessment: A Case Study of South Dongting Lake, China

by Shun Zhang and Bozhi Ren

Water 2025, 17(21), 3036; https://doi.org/10.3390/w17213036 - 22 Oct 2025

Abstract

To investigate the heavy metal contamination status and associated health risks in the groundwater of South Dongting Lake, China, 88 groundwater samples were collected and analyzed for the contents of heavy metals (Fe, Mn, Cu, Zn, As, Cd, Pb). The heavy metal pollution [...] Read more.

To investigate the heavy metal contamination status and associated health risks in the groundwater of South Dongting Lake, China, 88 groundwater samples were collected and analyzed for the contents of heavy metals (Fe, Mn, Cu, Zn, As, Cd, Pb). The heavy metal pollution characteristics and human health risks were comprehensively analyzed using a combined approach of the Heavy Metal Pollution Index (HPI), Heavy Metal Evaluation Index (HEI), Water Quality Index (WQI), and by integrating traditional health risk assessment with Monte Carlo simulation. The results indicated that manganese (Mn) and iron (Fe) were the most prominent pollutants in the regional groundwater, with exceedance rates of 35.3% and 25.0%, respectively. Arsenic (As) showed localized exceedances (13.91 μg/L, 1.39 times the standard limit). Spatially, contamination levels were higher in the north and lower in the south, with Fe, Mn, and As enrichment concentrated in the northern region, correlating with geological structures and industrial discharges. Health risk assessment revealed that the total carcinogenic risk (TCR) for children (1.82 × 10⁻⁴) exceeded the safety threshold by 82%, with arsenic being the primary carcinogen (contribution rate: 74.7%). The non-carcinogenic total hazard index (HI) reached 3.59 for adults and 6.54 for children, significantly exceeding the acceptable level of 1.0. Manganese was identified as the core non-carcinogenic risk source (Hazard Quotient (HQ) for children = 3.35). Monte Carlo simulation confirmed that pollutant concentration and exposure time were the most sensitive risk-driving factors. This study provides a scientific basis for prioritizing the control of As and Mn pollution in the northern region and implementing protective measures against children’s exposure. Full article

(This article belongs to the Section Hydrogeology)

► Show Figures

Figure 1

26 pages, 17979 KB

Open AccessArticle

Various Indices of Meteorological and Hydrological Drought in the Warta Basin in Poland

by Joanna Wicher-Dysarz, Tomasz Dysarz, Mariusz Sojka, Joanna Jaskuła, Zbigniew W. Kundzewicz and Supanon Kaiwong

Water 2025, 17(21), 3035; https://doi.org/10.3390/w17213035 - 22 Oct 2025

Abstract

The Warta River basin, Poland’s third-largest basin, is highly vulnerable to drought, which occurs in both cold and warm seasons. This study examined meteorological and hydrological droughts using daily temperature and precipitation data from 211 meteorological stations and discharge data from 15 hydrological [...] Read more.

The Warta River basin, Poland’s third-largest basin, is highly vulnerable to drought, which occurs in both cold and warm seasons. This study examined meteorological and hydrological droughts using daily temperature and precipitation data from 211 meteorological stations and discharge data from 15 hydrological gauges for 2000–2020. Four indicators were applied: SPI and SPEI for meteorological drought, and SRI and ThLM for hydrological drought. The analysis revealed prolonged droughts and a systematic decline in SRI values, especially from March to September. The longest event, a shallow drought, lasted 555 days between 2019 and 2020 at the Sławsk gauge. The period from 2018 to 2020 was particularly severe, with drought intensity increasing and affecting 70–80% of river flows, while events persisted longer than usual. Water withdrawals, especially for municipal use, further reduced river levels. The section between Uniejów and Oborniki, located downstream of one of Poland’s largest reservoirs, proved most vulnerable to hydrological drought. Overall, results indicate a deteriorating water situation in the Warta basin, with the most significant deficits in spring and summer. These trends pose serious challenges for water management and water supply security. An improved understanding of meteorological and hydrological droughts and their impact is essential for managing the water–food–environment–energy nexus, including restrictions on water use for domestic, economic, and agricultural purposes, as well as the functioning of aquatic ecosystems. Full article

(This article belongs to the Special Issue Rainfall Variability, Drought, and Land Degradation)

► Show Figures

Figure 1

29 pages, 2370 KB

Open AccessArticle

Design of Rainwater Harvesting Pond for Runoff Storage and Utilization in Semi-Arid Vertisols

by M. Manikandan, B. Bhakiyathu Saliha, Boini Narsimlu, J. V. N. S. Prasad, K. Baskar, V. Sanjivkumar, S. Manoharan, G. Guru, Gajjala Ravindra Chary, K. V. Rao, R. Rejani and Vinod Kumar Singh

Water 2025, 17(21), 3034; https://doi.org/10.3390/w17213034 - 22 Oct 2025

Abstract

Rainfall deficits and erratic dry spells pose major challenges in rainfed ecosystem. In-situ moisture conservation practices (MCP) like ridge–furrow methods, improve soil moisture but are inadequate during 2–3 week dry spells at critical crop stages (flowering and maturity), leading to yield loss. Supplemental [...] Read more.

Rainfall deficits and erratic dry spells pose major challenges in rainfed ecosystem. In-situ moisture conservation practices (MCP) like ridge–furrow methods, improve soil moisture but are inadequate during 2–3 week dry spells at critical crop stages (flowering and maturity), leading to yield loss. Supplemental irrigation (SI) using an ex-situ rainwater harvesting (RWH) pond can mitigate these effects, but optimizing the pond design is challenging due to limited runoff and storage losses. This study aims to design RWH pond for small farm holders with a 1.0 ha area and evaluate its efficient use for SI during intermittent dry spells and critical crop stages. The design volume was estimated using the SCS-CN method based on daily rainfall data (1974–2010) for the northeast monsoon. A pond with a capacity of 487.5 m³, constructed for a 1 ha micro-watershed, was used to observe the runoff for design validation. The harvested runoff can be used as SI for a cultivable area of 0.4 ha, based on the watershed-to-cultivable area ratio. Statistical analysis of observed and estimated runoff data from 2011 to 2023 revealed a strong correlation (r = 0.87), confirming the pond design. Harvested rainwater, applied through micro-irrigation (rain gun) at a depth of 50 mm during moisture stress periods, significantly improved cotton productivity. The combined use of harvested rainwater and MCP increased yield in the range of 3.8 to 25.3%, improved rainwater use efficiency (1.52 to 3.13 kg ha⁻¹ mm⁻¹), and had a higher benefit-cost ratio (1.15 to 2.43) over a 13-year period. This study concludes that integrating in-situ MCP with ex-situ RWH with micro-irrigation significantly improves rainfed crop productivity in vertisols. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

► Show Figures

Figure 1

30 pages, 11497 KB

Open AccessArticle

Forecasting the Spatio-Temporal Evolution of Groundwater Vulnerability: A Coupled Time-Series and Hydrogeological Modeling Approach

by Yugang Yang and Jingtao Zhao

Water 2025, 17(21), 3033; https://doi.org/10.3390/w17213033 - 22 Oct 2025

Abstract

Proactive management of groundwater resources is hindered by the static nature of conventional vulnerability assessments, which provide only a single temporal snapshot and lack predictive capability. To address this limitation, we developed a coupled dynamic–spatial modeling framework to forecast the spatio-temporal evolution of [...] Read more.

Proactive management of groundwater resources is hindered by the static nature of conventional vulnerability assessments, which provide only a single temporal snapshot and lack predictive capability. To address this limitation, we developed a coupled dynamic–spatial modeling framework to forecast the spatio-temporal evolution of groundwater vulnerability. The framework integrates a βSARMA time-series model for precipitation forecasting with an enhanced M-DRASTIC-LAaRd model, which incorporates Land use, Anthropogenic activity, and River network density, weighted via the Analytical Hierarchy Process (AHP) to better capture hydrogeological complexity. The βSARMA model consistently outperformed conventional SARIMA models across the five subregions of Beijing, achieving the lowest RMSE values (0.0832–0.1617) and MAE values (0.0922–0.1372), with an average RMSE reduction of 15.3% relative to the best SARIMA baseline. These results ensure highly reliable dynamic precipitation inputs for the time-varying Net Recharge (R) parameter. Model validation against historical observations yielded a coefficient of determination (R²) of 0.87, confirming the framework’s robustness and predictive accuracy. Applied to the Beijing metropolitan area (1980–2027), the model projects a marked spatial restructuring of groundwater vulnerability: high-vulnerability zones are expected to expand from 38.65% to 46.18%, while low-vulnerability areas will decline from 42.53% to 34.63%. Emerging “hotspots” are concentrated in the southern urban plains, where urbanization and reduced recharge converge. Overall, 27.9% of the region is predicted to experience intensified vulnerability, whereas only 11.5% will show improvement. This study advances groundwater vulnerability assessment from static mapping toward dynamic forecasting, providing a quantitatively validated and spatially explicit framework that supports more informed groundwater management under future environmental change. Full article

(This article belongs to the Section Hydrogeology)

► Show Figures

Figure 1

19 pages, 570 KB

Open AccessArticle

Adaptive Governance and Policy Evolution of the Yangtze River Fishing Ban: A Quantitative Analysis (2002–2024)

by Liwen Jiang and Tao Ma

Water 2025, 17(21), 3032; https://doi.org/10.3390/w17213032 - 22 Oct 2025

Abstract

The Yangtze River fishing ban policy is a central measure in China’s watershed governance, and the adaptability of its policy tools and collaborative mechanisms directly influences the sustainability and effectiveness of basin management. This study systematically examines the evolution of policy themes, the [...] Read more.

The Yangtze River fishing ban policy is a central measure in China’s watershed governance, and the adaptability of its policy tools and collaborative mechanisms directly influences the sustainability and effectiveness of basin management. This study systematically examines the evolution of policy themes, the characteristics of policy tool combinations, and their alignment with intergovernmental collaborative governance needs, drawing on 120 central government policy texts issued between 2002 and 2024. Using frequency analysis and policy tool coding, the findings reveal that (1) policy themes have shifted from fishery resource control to comprehensive ecological protection and, more recently, to integrated watershed management, thereby driving progressively higher demands for intergovernmental collaboration. (2) The policy tool structure has long been dominated by environmental tools, supplemented by supply-side tools, while demand-side tools remain underdeveloped. Imbalances persist, such as excessive emphasis on resource inputs over capacity building in supply-side tools, rigid constraints with limited flexibility in environmental tools, and a reliance on publicity while underutilizing market incentives in demand-side tools. (3) Tool combinations have adapted to changing collaboration needs, evolving from rigid constraints and fiscal subsidies to institutional frameworks and cross-regional cooperation, ultimately forming a governance model characterized by systemic guarantees and diversified collaboration. Based on these findings, this study recommends strengthening long-term governance mechanisms, improving cross-regional collaborative structures, authorizing local governments to design context-specific implementation details, enhancing fishermen’s livelihood security and social development, expanding public participation and oversight, and exploring market mechanisms for realizing ecological product value. These measures aim to advance collaborative governance in the Yangtze River Basin and foster a balanced integration of ecological protection and social development. Full article

(This article belongs to the Special Issue Transboundary River Management)

► Show Figures

Figure 1

29 pages, 36263 KB

Open AccessArticle

The Drought Regime in Southern Africa and Recent Climate Change: Long-Term Trends in Climate Elements, Drought Indices and Descriptors

by Fernando Maliti Chivangulula, Malik Amraoui and Mário Gonzalez Pereira

Water 2025, 17(21), 3031; https://doi.org/10.3390/w17213031 - 22 Oct 2025

Abstract

The impacts of climate change are globally evident and cause significant damage to ecosystems and human activities. These impacts intensify social and economic inequality in Southern Africa (SA), where agriculture is vital for livelihoods and economic development. This study aimed to assess long-term [...] Read more.

The impacts of climate change are globally evident and cause significant damage to ecosystems and human activities. These impacts intensify social and economic inequality in Southern Africa (SA), where agriculture is vital for livelihoods and economic development. This study aimed to assess long-term trends in climate elements and parameters relevant to drought regimes in SA to identify drought hotspots and relate them to socioeconomic indicators. The methods include the Theil–Sen slope estimator and the Mann–Kendall statistical significance test. The study analysed ERA5 data for the 1971–2020 to compute the Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI) drought indices and descriptors. Results of the trend analysis reveal (i) the existence in almost the entire SA of statistically significant trends of increasing temperature and potential evapotranspiration and decreasing precipitation; (ii) increasing drought risk hotspots in the SPI and SPEI across all timescales, in the north central rainforest region, south and southeast of SA, while decreasing in the northwest coast, central west region, and in the northeast more recently; and (iii) hotspots in the drought descriptors within the same regions, but of a smaller size. Our findings pinpoint drought hotspots in regions with moderate-to-high population density and agricultural systems that involve species vital for food security and of considerable socioeconomic and commercial importance, emphasising the significance of our results for managers and decision-makers. Full article

(This article belongs to the Section Water and Climate Change)

► Show Figures

Figure 1

21 pages, 6836 KB

Open AccessArticle

Divergent Drought Paradigms and Their Driving Mechanisms in the Yangtze and Yellow River Basins

by Lan Yang, Tingting Wang, He Li, Dejian Wang, Yanfang Wang, Hui Zhang and Xinjia Wu

Water 2025, 17(21), 3030; https://doi.org/10.3390/w17213030 - 22 Oct 2025

Viewed by 22

Abstract

China’s Yangtze and Yellow River Basins exhibit divergent drought patterns, yet the underlying mechanisms driving these differences remain underexplored. This study compares their drought characteristics from 1961 to 2022 using the Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, and Palmer Drought Severity Index, [...] Read more.

China’s Yangtze and Yellow River Basins exhibit divergent drought patterns, yet the underlying mechanisms driving these differences remain underexplored. This study compares their drought characteristics from 1961 to 2022 using the Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, and Palmer Drought Severity Index, and identifies their drivers through attribution models and interpretable machine learning. Our results reveal two distinct paradigms: the Yangtze Basin is characterized by high-frequency, over 14% in all seasons, short-duration droughts, reflecting a rapid hydrological response, while the Yellow River Basin experiences low-frequency, long-duration events indicative of strong soil moisture memory. Quantitative attribution demonstrates that atmospheric evaporative demand (VPD) plays a significantly greater role in the Yellow River Basin, contributing over 20% to soil drought, far exceeding its 14.4% contribution in the Yangtze Basin. Furthermore, their large-scale drivers differ fundamentally: the Yangtze Basin responds primarily to the Atlantic Multidecadal Oscillation (AMO) and Arctic Oscillation (AO), whereas the Yellow River Basin is mainly influenced by solar activity and the El Niño-Southern Oscillation (ENSO). These findings reveal that Yangtze drought is primarily driven by precipitation deficits, while Yellow River drought is a composite phenomenon amplified by evaporative demand. This distinction underscores the need for basin-specific water management strategies. Full article

(This article belongs to the Section Hydrology)

► Show Figures

Figure 1

19 pages, 5585 KB

Open AccessFeature PaperArticle

Stable Isotope Monitoring in a Semi-Arid Olive Orchard Suggest Changes in Ecohydrological Dynamics from Contrasting Drip Irrigation Regimes

by Taha Attou, M. H. Kharrou, S. Kuppel, Y. Ait Brahim, L. Bouchaou, V. Demarez, M. M. Lehmann, F. Raibi, T. Elghali, A. Elazhari, N. Rhoujjati, H. Bouimouass and A. Chehbouni

Water 2025, 17(21), 3029; https://doi.org/10.3390/w17213029 - 22 Oct 2025

Viewed by 100

Abstract

In semi-arid regions of Morocco, where the majority of water withdrawals are devoted to irrigation, optimizing irrigation practices in agriculture is a national priority in the face of recurring droughts and growing pressure on groundwater resources. However, the hydrological impacts of different drip-irrigation [...] Read more.

In semi-arid regions of Morocco, where the majority of water withdrawals are devoted to irrigation, optimizing irrigation practices in agriculture is a national priority in the face of recurring droughts and growing pressure on groundwater resources. However, the hydrological impacts of different drip-irrigation systems in the soil–plant–atmosphere continuum remain insufficiently understood. We monitored the stable isotope composition (δ²H, δ¹⁸O) across the two agricultural plots in Marrakech (Morocco) with surface drip and subsurface drip irrigation treatments for a complete hydrologic year (June 2022 to June 2023). Weekly to daily samples of rainfall, irrigation water, groundwater, and soil at various depths (5–50 cm) were sampled, and water from branch xylem was extracted using the cryogenic vacuum distillation method. We found that the subsurface irrigation treatment, which delivered water directly to the root zone, maintained narrow isotopic ranges in water of soils beyond 30 cm, as well as in branch xylem and leaf water. By contrast, surface irrigation treatment plots showed pronounced evaporative isotopic enrichment: summer topsoil water δ¹⁸O peaked at −1.1‰ (vs. −8.7‰ in subsurface irrigation treatment), and leaf water reached +13‰ (vs. +8‰ in subsurface). Despite this larger isotopic heterogeneity in surface irrigation site, branch xylem water δ¹⁸O remained within −6 to 2.5‰ across all soil depth, similar to subsurface irrigation treatment, which ranged between −5 and 0‰. This suggests that olive roots accessed soil water uniformly from the upper 50 cm under both irrigation treatments. Seasonal xylem isotopic enrichment in spring and midsummer mirrored shifts towards shallow, evaporatively altered soil water under surface irrigation, but not under the subsurface. The results suggest that subsurface drip irrigation can significantly improve drought resilience and water-use efficiency in the expanding olive sector of the Maghreb, while continuous isotope monitoring serves as a practical approach to enhance sustainable and adaptive water management in water-limited regions. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Water, Volume 17, Issue 21 (November-1 2025) – 30 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI