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A comprehensive modeling framework utilizing hydrodynamic and sediment transport models (MIKE Hydro River, MIKE 21 FM, MIKE 21C) was applied to the 33.57 km stretch of the Banshadhara River from Banshadhara bridge, Gunupur to Kashinagar town. Daily discharge, water levels, and sediment data from 2013 to 2022 of Gunupur and Kashinagar gauge stations was used as model input, and calibration–validation of models. Additionally, satellite remote sensing data used for determined Manning's roughness (n) values as well compared the model outputs. Calibration procedures ensured high accuracy, with MIKE Hydro River achieving 98.3% agreement between observed and simulated water levels. 1D sediment transport model showing significant variability in total bed load values ranging from 0.3 to 3.83 m^3/s. The Wilcock & Crowe gravel bed load formula accurately predicted bed load transport within the expected magnitude, albeit tending to overestimate transport, indicative of supply-limited conditions. 2D MIKE 21 FM simulations highlighted flow dynamics, with rapid flood arrival at Kashinagar and varying current speeds along the river, especially at bends. MIKE 21C, focused on the central portion, indicated erosion processes at river bends with high discharge. Sediment transport model accuracy was approximately 86.7%, capturing general trends despite occasional discrepancies. Over a 10-year simulation, erosion trends and potential river course shifting were observed, particularly near bends. The analysis provides valuable insights for river management, flood risk mitigation, water resource management, infrastructure planning, and environmental preservation in the Banshadhara River basin and similar environments. Article Highlights: Accurate modeling predicts river erosion and possible course shifts, vital for flood risk planning. Sediment transport varies widely, indicating complex riverbed dynamics impacting river management. Study offers insights into managing river ecosystems, infrastructure, and environmental preservation. [ABSTRACT FROM AUTHOR]

Examining the chemical properties of river water and the controlling factors is crucial for devising efficacious strategies in water resources management and ecological conservation. This study investigates the hydrochemical characteristics and driving factors of the Beichuan River in the arid region of Northwest China. Surface water samples were collected during wet and dry seasons, and analyzed using hydrochemical diagrams, mathematical statistics, and principal component analysis (PCA). The results show that the pH value of Beichuan River is generally weakly alkaline, the main hydrochemical types are HCO3-Ca, and the average TDS are 224 mg/L and 236 mg/L respectively, which are higher than the world average level (115 mg/L). The seasonal variation of hydrochemical components is mainly controlled by rainfall, showing that the concentrations of Na+, Cl− and NO3 − in the wet season are higher than those in the dry season, while the concentrations of other chemical components show an opposite trend, while the spatial variation is mainly controlled by human activities, and the concentrations of hydrochemical components show a gradual increasing trend from upstream to downstream, especially Na+, Mg2+, Cl− and NO3 − . Rock weathering is the key natural factor controlling the Hydrochemical Composition of Beichuan River. Na+ and Cl− are mainly from the dissolution of silicate, Ca2+ and Mg2+ are mainly from the weathering of carbonate rocks and silicate, and SO4 2- is mainly from the dissolution of evaporite. It is noted that human activities, especially domestic sewage and agricultural runoff, contribute significantly to NO3 − in the water body. PCA identified rock weathering and agricultural runoff as major wet-season factors, while domestic sewage predominantly affects the dry season. This study can provide a scientific basis for the rational development of water resources and ecological environment protection in arid areas. [ABSTRACT FROM AUTHOR]

Efficient monitoring of crop water requirements is crucial for assessing the impacts of major irrigation projects, such as the Kaleshwaram lift irrigation project, both before and after their implementation. These projects can significantly change agricultural practices and water usage patterns, necessitating thorough evaluations to ensure sustainable water management and agricultural resilience. The main aim of this study is to evaluate and compare crop water needs during the winter (rabi) seasons of 2018-2019 and 2022-2023 across the command area of the project. This is achieved by mapping major crops and their respective length of growing periods across the study area using sentinel-2 satellite data and ground data, and quantifying crop water requirements using reference evapotranspiration and FAO crop coefficients. Results reveal a significant shift towards rice cultivation, with an over 80% increase in the winter season of 2022-2023 compared to 2018-2019, indicating substantial escalations in crop water requirements. These findings provide valuable insights into agricultural transformations induced by largescale irrigation interventions, emphasizing the need for sustainable water management practices to ensure agricultural resilience and resource conservation in similar contexts. [ABSTRACT FROM AUTHOR]

Rivers are cradles of human civilisations and continual innovations in water technologies are the key to sustainable human development. Yet, limited research has explored the interactive dynamics among different technologies, hindering our ability to effectively manage technological transition. This paper presents a framework that conceptualizes water technology as a complex adaptive system containing three interrelated sub-systems: water demand, water supply, and water management. The interactions among these subsystems were measured using three network-based metrics: intensity, brokerage, and efficiency. Patents registered in the World Intellectual Property Organization from 1863 to 2020 were used as the data source. It was found that 40,304 patents from 44 countries were registered, with 40% of them belonging to the water management sub-system, followed by water supply (35%), and water demand (25%). Technological development in the three sub-systems presented linear growth over the past 160 years, focusing on water treatment, hydroelectric power, hydraulic engineering and water monitoring. The water-demand subsystem was identified as the structural "bottleneck" with the highest brokerage value, which was considered crucial for knowledge transfer between the other two sub-systems. Overall, the water technology system is characterized by slow development, skewed spatial coverage, categorical homogeneity, and structural imbalances, limiting our ability to address the escalating global water threats. [ABSTRACT FROM AUTHOR]

Introduction: Improving the level of intensive and economical utilization of water resources is an important step towards water and food security. Methods: Based on China's provincial panel data from 2015 to 2021, this study uses a difference-in-differences (DID) model to examine the effect of agricultural water rights trading on intensive and economical utilization of water resources. Results: The results show that agricultural water rights trading can significantly promote an intensive and economical utilization of water resources at the 1% level, and the results remain valid even after a series of robustness tests. Further analysis indicates that agricultural water rights trading can promote better utilization of water resources by significantly reducing agricultural water consumption at the 1% level and reducing the proportion of agricultural water consumption at the 5% level to optimize water use structure. Moreover, in regions with scarce water resources, strong water resource constraints, more farmland water conservancy projects, and greater economic development, the promoting effect of agricultural water rights trading on the intensive and economical use of water resources is more significant. Discussion: This study provides evidence of the impact of China's agricultural water rights trading policy and offers new ideas and experiences to improve China's water resource utilization efficiency. The contributions of this work are mainly threefold. First, this paper clearly distinguishes the intensive conservation of water resources, presents an evaluation index system, and complements the existing literature on measuring the intensive and economical utilization of water resources. Second, the path of agricultural water rights trading is analyzed to improve the level of intensive and economical utilization of water resources, thus enriching related research on transmission mechanisms. Third, the heterogeneity of the influence of different regional conditions on the level of intensive and economical utilization of water resources is discussed to improve relevant policies. [ABSTRACT FROM AUTHOR]

ABSTRACT In the North China Plain (NCP), the assessment of water surplus or deficit (WSD), which is calculated as precipitation minus reference evapotranspiration (ET0), holds significant implications for water resource management and agricultural irrigation decision‐making, given the region's long‐standing severe shortage of water resources. However, the magnitude, trend and climatic drivers of WSD remain poorly understood in the NCP. This study analysed the spatial and temporal characteristics of WSD, and quantified the contribution of climatic factors to WSD based on the sensitivity and contribution rate analysis methods with climatic data from 75 meteorological stations. The result showed that: (1) Annual WSD decreased mainly in northeastern NCP and increased significantly in southern NCP during 1961–2022. Annual WSD increased slightly from 1961 to 2022 at a rate of 1.63 mm a−2 mainly due to the more significant decrease (−1.88 mm a−2) in ET0 compared to precipitation (−0.25 mm a−2). (2) In terms of the sensitivity of WSD to climatic factors, relative humidity had the highest sensitivity, followed by net radiation, wind speed, precipitation and average air temperature. (3) Significant declines of wind speed were the most dominant factor affecting WSD variation in most part of NCP during most of a year, and net radiation of four stations in the western high‐elevation regions played the most important role. This study enhances comprehension of the impact of climate change on WSD in the NCP and provides a reference for improving management of agricultural water resources under NCP's evolving climatic conditions. [ABSTRACT FROM AUTHOR]

This paper explores the concept of meaningful participation in river basin management, using the case study of the Hennops River in Gauteng Province, South Africa. Experiences of different stakeholders and communities regarding their involvement in the management of the Hennops River basin are analysed following engagement through interviews, workshops and clean-up initiatives. Several barriers and enablers for meaningful participation, such as lack of awareness, capacity, coordination, trust and incentives, are identified. Some recommendations are proposed for improving stakeholder and community participation, based on the lessons learned from the case study. This includes the formulation of a social fund to support small community-based projects such as clean-up campaigns. Projects should be reflective, keeping the community engaged and active. The paper argues that meaningful participation requires not only formal mechanisms of engagement and decision-making but also informal and practical actions that empower stakeholders and communities to take ownership and responsibility for their water resources and environment. For meaningful participation to take place, more needs to be done to shift communities away from a ‘bystander’ position to a more active role. A new approach to community engagement is therefore necessary to support stakeholder-driven initiatives and the raising of awareness in poorer communities. [ABSTRACT FROM AUTHOR]

Biological assessment of rivers is critical for evaluating ecosystem health, detecting ecological changes, validating physicochemical monitoring data, assessing the effectiveness of water treatment systems, conserving biodiversity, and guiding water resource management. In this study, the surface water quality of the Karkheh River basin was evaluated using the National Sanitation Foundation Water Quality Index (NSFWQI) and the Iranian Surface Water Quality Index (IRWQIsc) for qualitative analysis. For biological monitoring, the Biological Monitoring Working Party (BMWP) index, along with the Average Score per Taxon (ASPT) and the Hilsenhoff Biotic Index (HFBI), was employed to provide a comprehensive assessment. Water quality was analyzed across 18 sampling stations, revealing significant spatial variation. Upstream areas exhibited relatively good conditions, with NSFWQI and IRWQIsc values of 59 and 68, respectively. In contrast, downstream locations near urban and agricultural areas demonstrated poor water quality, with values of 27 and 33, respectively.Overall, approximately 70% of the river's length has been severely impacted, highlighting the need for targeted planning and management to mitigate pollution. The biological indices corroborated the physicochemical results, revealing severe ecological stress in polluted regions. The close alignment between the NSFWQI and biological indicators emphasizes the importance of a multifaceted approach in assessing aquatic health. Key factors contributing to the river's degradation include excessive water extraction, untreated wastewater discharge, and diminished self-purification capacity, particularly in downstream areas. [ABSTRACT FROM AUTHOR]

Central Sahel is affected by a reinforcement of rainfall since the beginning of 1990s. This increase in rainfall is affected by high inter-annual variability and is characterized by extreme rain events causing floods of unprecedented magnitude. However, few studies have been carried out on these extreme events. Moreover, with current climate change expected to strengthen the hydrological cycle, we don't know if these events could become more frequent. Here, we report the hydrological changes that currently occur in the Lake Chad basin. Based on ground observations and satellite data, we focused on the 2022 flood event, demonstrating that it was the most important event from the last 60 years, comparable to what occurred during the last wet period between the 1950s and the 1960s. We showed that under this precipitation regime and if warming is not regulated at a global scale, the return period of the 2022 major riverine flood is expected to be between 2 and 5 years. By using modelling experiments, our study also suggested that in the next decade, future flow rates of the main rivers draining the Lake Chad basin could reach the values observed in the 1950s. These results strongly suggest anticipating water management in a context of poor infrastructural development. [ABSTRACT FROM AUTHOR]

In the development of smart cities, accurate liquid flow monitoring is essential for the efficient operation of water supply systems. Current flow sensors often face limitations in sensitivity and environmental adaptability, affecting measurement accuracy, and restricting their application in smart city infrastructure. To address these challenges, this study proposes a high‐accuracy flow monitoring method. Specifically, by combining the bionic design with advanced signal processing techniques, the sensitivity and anti‐interference ability are improved, respectively, to enhance the measurement accuracy. Based on this method, a self‐powered flow sensor (SPFS) is developed using noncontact triboelectric nanogenerators (NC‐TENGs) as the sensing unit. The SPFS achieves a sensitivity of 2.07 Hz L−1 min−1 and improves the signal‐to‐noise ratio by more than 13 times over the initial sensing signal. In addition, an intelligent system is developed to accurately measure water resources. The maximum flow rate error rate is less than 0.97% compared to commercial flow sensors. The SPFS demonstrates higher sensitivity and accuracy compared to the existing TENG flow sensors. This study addresses the limitations of existing flow sensors and pioneers a novel solution for enhanced water resource management in smart cities. [ABSTRACT FROM AUTHOR]

In urban areas with dense populations and high water demands, effective management of water resources is crucial for sustainable development. It includes optimizing water usage and recycling wastewater to balance supply and demand. Urban rivers, which now carry sewage year-round due to increased urban water consumption, are increasingly used for irrigation in peri-urban regions. This study aims to assess the suitability of an urban stream for irrigation compared to catchment groundwater, using hydrochemical parameters to evaluate water quality indices. Analysis of major ion distribution from upstream to downstream reveals a significant increase of TDS (r2 = 0.65; p < 0.001) in the surface water and a decrease (r2 = 0.93; p < 0.001) in groundwater samples. The calculated Weighted Arithmetic-Water Quality Index (WA-WQI) indicates that around 85% and 75% of surface water and groundwater samples from the Musi river are classified as very poor to unsuitable for any use, highlighting critical pollution levels. Based on irrigation suitability indices, only 16% of the surface water samples and 60% of the groundwater samples are suitable for irrigation. The nitrate concentration increased from less than 10 mg l−1 in the upstream region to over 100 mg l−1 in the urban stretch. Nitrogen-Phosphate-Potassium (NPK) ratios across the basin are exceptionally higher, representing crops irrigated using the Musi river water might not require fertilizer applications. The adoption of fertilizer application concerning supplied water hydrochemistry, particularly the NPK ratio, might limit the excess usage of fertilizer and benefit farmers. Additionally, this practice may also limits the excess input of nitrate to the groundwater in the Musi river basin. [ABSTRACT FROM AUTHOR]

The Citarum River revitalization program through the "Citarum Harum" program, focuses on integrated cooperation between multi-sector actors in managing the Citarum Watershed sustainably and improving the quality of life around the river. Such as ministries (central government) acting as policy and regulation providers and as the leading sector, local governments acting as program supervisors and monitors, academics/universities acting as knowledge creators and program management innovations, the private sector acting as important partners, communities acting as program supporters and participants, and the Indonesian National Army (Tentara National Indonesia, TNI) acting as initiators, law enforcers, and field supervisors. This article outlines some of the challenges faced by Citarum Watershed, as well as important findings regarding collaborative sustainable and resilient watershed management, particularly in the context of the Citarum River, Indonesia. In this commentary, we underscore the importance of collaborative efforts, effective policy frameworks, and adaptive management strategies in addressing the environmental challenges faced by the Citarum River, while highlighting the need for ongoing commitment from all stakeholders during program implementation and post-program. The implications of these findings suggest a holistic, inclusive, and adaptive approach to sustainable management of watersheds and the environment that can be applied to other regions facing similar challenges such as Pollution; Environmental Degradation; Critical Land and Sedimentation; Inadequate Infrastructure; Population Growth and Urbanization; Climate Change, Weak Law Enforcement, and Lack of Coordination Among Stakeholders. Article highlights: Management of the Citarum River Basin (Daerah Aliran Sungai, DAS) is a mainstay of household life, urban communities, the environment, and supports industrial activities in the western region of Java Island, where no other river has a role and function as large as the Citarum River Basin. Challenges in the complexity of Citarum River Basin management highlight the need for an integrated and multi-stakeholder approach to ensure sustainable water resources management and environmental protection. The emphasis on Indonesian policy regulation and interactive collaboration model of various mutually beneficial helixes are the keys to success in sustainable and resilient management of the Citarum River Basin. Significant barriers that need to be considered in the Quintuple Helix Model framework are related to power dynamics, operational clarity, resource allocation, community involvement, and stakeholder integration to achieve its goals effectively. [ABSTRACT FROM AUTHOR]

Agroecology, as a holistic approach to sustainable food systems, is gaining momentum globally as a key approach to addressing current challenges in agricultural and food production. In sub-Saharan Africa, despite numerous efforts to address declining soil productivity, water scarcity, and increasing pest pressure through agroecological soil, water, and integrated pest management (IPM) practices, the adoption of such practices remains low. As part of the CGIAR Agroecology Initiative, we conducted a collaborative rapid innovation assessment of existing soil, water, and pest management practices in two Agroecological Living Landscapes (ALLs) in Makueni and Kiambu counties, Kenya. The assessment also included an evaluation of the performance of these practices and identified farmer preferences. Using a multi-stage approach, we applied stratified random sampling to identify 80 farmers for farm assessments and in-depth interviews. A total of 31 practices were identified, of which 26 were further evaluated. The evaluation revealed a heterogeneous set of socio-economic and biophysical contextual factors influencing practice performance. Respondents identified 19 strengths, and 13 challenges associated with the practices, highlighting opportunities for innovation to improve or adapt performance. Farmers also expressed preferences for future adoption of 31 practices, 77% of which were listed in one of the three focus areas, namely soil management, water management, or IPM. The other 33% were associated with multiple functions and were listed under two or three of the focus areas. The results of the collaborative assessment informed a broader co-design cycle that included participatory prioritization and selection of innovative practices, experimental design, and monitoring protocols. This collaborative and systematic approach was taken because innovative practices often fail to be adopted due to a lack of co-design and inclusion of local perspectives in innovation design, and a disconnect between science and practice. Our study highlights the importance of integrating stakeholder input and transdisciplinary technical expertise in the co-design and implementation of agroecological innovations. It also emphasizes the importance of using a structured methodology to understand farmers' options, context, and preferences while co-designing locally relevant agroecological practices, which promotes holistic and inclusive adoption, successful implementation and long-term sustainability of agroecological practices. [ABSTRACT FROM AUTHOR]

An accurate estimation of leakages in water distribution networks is of primary importance for the definition of strategies aimed at ensuring an efficient management of water resources and avoiding water waste. However, in the case of methods based on water balance—such as the Minimum Night Flow method—inaccurate assessment of the minimum night consumption (MNC), e.g. the assumption of fixed MNC values from the literature, can heavily mislead the quantification of leakage level. This study aims at providing insights into the variability of MNC and the related drivers. In greater detail, hourly water consumption data of approximately 200 users are collected over a period of two years and subjected to a multi-phase methodology to obtain a detailed characterization of MNC, with and without considering the users affected by post-meter leakages. The study demonstrates that factors such as seasonality or the presence of post-meter leakages may strongly impact the MNC—the values of which can significantly deviate from the literature references—and thus lead to significant misestimation of network leakages in water systems. Highlights: A methodology for the statistical analysis of minimum night consumption (MNC) based on the daily water-consumption profiles at the user level is proposed. The methodology is applied to hourly-resolution water-consumption data collected over two years in a sample of over 200 users. Occupancy rate, seasonality, and presence of post-meter leakages affect MNC statistics. [ABSTRACT FROM AUTHOR]

Evapotranspiration is one of the crucial elements in water balance equations and plays a pivotal role in the water and energy cycle of an area. An accurate and precise estimation and prediction of reference evapotranspiration (ETo) is necessary for regional management of water resources and irrigation scheduling. The challenge of predicting daily evapotranspiration with limited meteorological data in Bangladesh. This study aims to predict daily evapotranspiration using limited meteorological data of Bangladesh by three deep learning (CNN, GRU, LSTM) and one hybrid (CNN-GRU) model. The novel method of hybrid CNN-GRU models, which have not been commonly used for this purpose. The performance of models was evaluated by five accuracy matrices R2, RMSE, MAE, MAPE, and CE and comparison is visualized by radar graphs. The study's novelty lies in the use of hybrid CNN-GRU models to estimate reference evapotranspiration, as this algorithm has not been commonly used for this purpose. In the case of the Rangpur station, the hybrid CNN-GRU algorithm outperformed other models, achieving the best values across various statistical metrics during both the training and testing phases. The highest correlation coefficient values of approximately 0.994 and 0.995. Moreover, during training and testing stages, the hybrid model had the lowest MAE (0.076, 0.068) and RMSE (0.138, 0.106) at the Rangpur station. Additionally, in the Sreemangal station, it can be notable that the statistical parameter RSME found superior results in the hybrid model around 0.225 and 0.174, respectively. In addition, the highest R2 and CE values were noted as 0.986, 0.987 and 0.985, 0.986 during the training and testing phases, respectively. The comparison suggests that the hybrid model will be best suited for prediction with the limited meteorological data. The outcome of the present research signifies the ability of deep learning methods in the prediction of evapotranspiration and the dominant variables affecting the changes the in context of Bangladesh. [ABSTRACT FROM AUTHOR]

Introduction: Moral Intelligence (MI) as a concept has gained importance Increasing water scarcity as a result of climate change and its coincidence with population growth, economic development, and the resulting rising demand has become an important challenge in most parts of the world. In numerous nations, such as Iran, frequent occurrences of droughts, combined with the extensive utilization of surface and groundwater resources, have resulted in numerous environmental detriments, including a decrease in groundwater levels, land subsidence, deterioration of water quality, and, more recently, the emergence of dust storms due to soil erosion and desertification. In this situation, stakeholders can play an efficient role in water management and the alleviation of water scarcity and its negative environmental externalities in the context of good water governance. Method: This investigation endeavored to examine the functions and importance of individuals or groups with a vested interest in groundwater resources within the Hamedan-Bahar Plain. Additionally, it aimed to evaluate their influence and motivations through the utilization of the power-interest matrix (PIM) and important-performance matrix techniques. A total of 86 people were identified who could and were allowed to be interviewed through the snowball method. Then a 10-point scale questionnaire was used to rate the questions. To examine the power and interest of the stakeholders, the IPM test was carried out using the smart pls.3 software, and the results were classified based on the average values and the overall impact. The results reveal that 20 institutions and agencies have an effective role in the governance of groundwater resources in the Hamedan- Bahar plain. Furthermore, the analysis of the PIM revealed that the most powerful organizations that play the most important role in the management of the groundwater resources of the studied area are the regional water organization, the representatives of the parliament, and the governor, respectively. Results and discussion: Based on the research findings, the governance "power" index of organizations and institutions with power (39.77%) and total impact (0.516) is higher and more effective than the value of benefits with power (36.13%) and total impact (0.48). Accordingly, paying attention to the role and influence of the power of stakeholders will be an important and effective point in the plans and strategies for groundwater resources in the Hamadan-Bahar plain. In the end, strategies are suggested to each stakeholder for better implementation of the programs and strategies. [ABSTRACT FROM AUTHOR]

With climate change, population growth and the resulting escalating water shortage, humanity is increasingly turning to non-renewable and even fossil groundwater resources, which poses a major challenge to sustainable water management. In this study, 2D basin-scale numerical simulations were carried out on the COMSOL Multiphysics® finite element numerical platform to identify non-renewable water resources in the Central Pannonian Basin (Central Europe, Hungary) based on the lack of hydraulic connection to recharge areas. The concept and boundary conditions (fixed water table configuration at the top, pressure-elevation profiles on the lateral sides, and constant pressure on the bottom) were derived from a previous basin-scale hydraulic data evaluation study, while the hydrostratigraphic subdivision was based on seismic and well log interpretations. As a result, topography-driven groundwater flow systems fed by meteoric water infiltration were separated from a transition zone, which contains non-renewable groundwater resources and covers 85% area of the simulated 110 km long and roughly 1600 m deep cross-section what was previously thought to be fully renewable. Such complex flow pattern and re-interpretation of the renewable and non-renewable groundwater resources can be expected in any terrestrial sedimentary basin with over-pressured flow domains. [ABSTRACT FROM AUTHOR]

Advancements in Artificial Intelligence (AI) technology allow for development of new tools for analytics and management which present new opportunities in field of environmental protection. The following study showcases usage of Machine Learning (ML) techniques as a complementary method for water status assessment of water bodies. Since the main goal of Water Framework Directive (WFD) is to improve the quality of water and reach good status in all the water bodies across Europe intensive monitoring program was launched together with water status assessment procedure. Based on requirements of the European Union's WFD concerning ecological status assessment it is presented how ML can be used for assessment of Polish unmonitored river water bodies. Due to the absence of monitoring data, the foremost challenge lay in securing relevant alternative data which was set to be anthropogenic pressures. The pivotal solution was implementation of ML techniques which enable processing of seemingly unrelated information concerning pressures in the catchment. Decision Tree, Random Forest, KNN, Support Vector Machine, Multinomial Naive Bayes, XGBoost models have been tested and the results indicated most suitable techniques. Study shows highest efficiency of XGBoost and Random Forest algorithms for classification of unmonitored water bodies. The models were compared by their overall accuracy (OA) reaching approximately 93% for binary classification and 72% for comprehensive classification as well as partial class accuracies and the Probability of Misclassification (PoM) parameter. The analyses demonstrates a practical application of AI in assessment of unmonitored water bodies in case of binary classification used for reporting water status objectives of WFD as well as possible usage of full classification for planning and operational uses. OA and PoM are postulated as the best measures of goodness of classification. [ABSTRACT FROM AUTHOR]

Analysing non-stationarity in runoff and sediment load is crucial for effective water resource management in the Dongting Lake basin amid climate change and human impacts. Using the Mann-Kendall test, Generalized Additive Models for Location, Scale, and Shape framework, and Random Forest models, we evaluated non-stationarity and its drivers in the annual runoff and annual sediment load series at eight hydrological stations from 1961 to 2021. These stations include three inflow sites at the Jingjiang Three Outlets (Ouchi, Songzi, and Hudu Rivers), four inflow sites in the Four Rivers basin (Xiang, Zi, Yuan, and Li Rivers), and one outflow site at Chenglingji. Results revealed a significant decrease in annual runoff at the Three Outlets and Chenglingji, while the Four Rivers basin showed no significant trend. The non-stationary models with multiple physically-based covariates better captured non-stationarity compared to single covariate models. Annual rainfall was a key contributor to annual runoff in the Four Rivers basin, while reservoir storage capacity played a more dominant role in the Three Outlets. At Chenglingji station, both factors significantly influenced annual runoff. For annual sediment load, reservoir storage capacity emerged as the most critical factor across all regions. These findings provide a basis for improving runoff and sediment regulation in the Dongting Lake basin. [ABSTRACT FROM AUTHOR]

Nearshore seagrass, kelp, and other macroalgae beds (submerged aquatic vegetation [SAV]) are productive and important ecosystems. Mitigating anthropogenic impacts on these habitats requires tools to quantify their ecological value and the debits and credits of impact and mitigation. To summarize and clarify the state of SAV habitat quantification and available tools, we searched peer‐reviewed literature and other agency documents for methods that either assigned ecological value to or calculated equivalencies between impact and mitigation in SAV. Out of 47 tools, there were 11 equivalency methods, 7 of which included a valuation component. The remaining valuation methods were most commonly designed for seagrasses and rocky intertidal macroalgae rather than canopy‐forming kelps. Tools were often designed to address specific resource policies and associated habitat evaluation. Frequent categories of tools and methods included those associated with habitat equivalency analyses and those that scored habitats relative to reference or ideal conditions, including models designed for habitat suitability indices and the European Union's Water and Marine Framework Directives. Over 29 tool input metrics spanned 3 spatial scales of SAV: individual shoots or stipes, bed or site, and landscape or region. The most common metric used for both seagrasses and macroalgae was cover. Seagrass tools also often employed density measures, and some categories used measures of tissue content (e.g., carbon, nitrogen). Macroalgal tools for rocky intertidal habitats frequently included species richness or incorporated indicator species to assess habitat. We provide a flowchart for decision‐makers to identify representative tools that may apply to their specific management needs. [ABSTRACT FROM AUTHOR]

An electrochemical hydrogen compressor (EHC) system capable of producing dry compressed hydrogen up to 10 MPa has been developed in this study. The drying system, located downstream of the compressor, consists of a passive countercurrent membrane water exchanger which dries the produced hydrogen flow while simultaneously humidifying the low-pressure hydrogen fed to the compressor. This highly flexible drying system can achieve a dew point temperature of less than −30 °C. A dryer structured in this way avoids conventional drying methods such as temperature and pressure swing adsorption cycles, which are very demanding in terms of power and heat rejection. Four proton exchange membranes of different thicknesses were investigated in this study. Hydrogen flows at 10 MPa in the range 0.1–1 mg s−1 have been obtained using a single EHC. The best performance was obtained with the thinnest membrane, Gore 18 μm, which allowed reaching a current density of 4 A cm−2 at 0.4 V and 35 °C, with pumped hydrogen flows greater than 0.8 mg s−1. The efficiency achieved with this system was around 60% at low voltages and current densities, at pressures between 7.5 and 10 MPa. The efficiency was found to decrease with the pumped flow, but the flexibility of this compressor, with its wide range of flow rates and total absence of vibration, should be highlighted. [Display omitted] • An electrochemical compressor of hydrogen up to 10 MPa has been developed • Dry high-pressure hydrogen has been produced (dew point < - 30 °C) • A current density of 4 A cm−2 at 0.4 V and 35 °C has been achieved • Efficiencies of around 60% have been achieved [ABSTRACT FROM AUTHOR]

Given the distinct water management requirements in anion-exchange membrane fuel cells (AEMFCs) and proton-exchange membrane fuel cells (PEMFCs), the necessity for tailored flow field redesign and analysis in AEMFCs becomes paramount. In this study, a three-dimensional, two-phase, non-isothermal AEMFC model is constructed to explore the impact of the channel shape of a parallel flow field on the cell performance. The results demonstrate that the channel shape notably influences cell performance at low voltages, and the cell performance follows: inverted trapezoidal > square > triangular > rectangular > trapezoidal > semicircular. A cell with inverted trapezoidal channels achieves a 12.9% increase in peak power density and an 83.4% reduction in current density non-uniformity compared to that with semicircular channels. Analysis of the evaluation criteria indicates that excellent heat transfer performance, superior mass transfer performance, and sufficient water content in the membrane are critical for improving AEMFC performance. • Effect of six channel geometries on the AEMFC performance is investigated. • EMTC, EEC, and inhomogeneity index are used to evaluate the whole performance. • Inverted trapezoidal channels yield the best overall performance. • Triangular channels result in the lowest EEC. [ABSTRACT FROM AUTHOR]

Start-up and Shut-down phases for Proton Exchange Membrane Fuel Cell stacks are known to damage the Cathode Catalyst Layer inducing an irreversible loss of performance. An original Accelerated Stress Test has been designed to mimic the Start-up phase in real-life system conditions. The impact of cathode potential on the degradation mechanisms of the Pt/C components within the Cathode Catalyst Layer by local electrochemical and physicochemical analyses provided a deep understanding of the cathode evolution. An unexpected cell performance improvement is observed between 1.0 and 1.2 V cathode potential, especially at high current density. A beneficial modification of the properties occurs suggesting that fresh Cathode Catalyst Layer exhibits non-optimized carbon support properties. However, a significant structure subsidence appears when the cathode potential is above 1.4 V. In this condition, modification/compaction of cathode layer due to carbon corrosion alters mass transport and empathizes water flooding through the electrode. [Display omitted] • Ageing induced by an original test mimicking realistic startup phase • Characterization of cathode catalyst layer degradations with local coupled techniques • More hydrophilic cathode catalyst layer due to carbon support corrosion at high cathode potential • Carbon corrosion alters mass transport and emphasise water flooding [ABSTRACT FROM AUTHOR]

Robust, accurate, and direct measurements of evaporation and related energy fluxes on the Laurentian Great Lakes are necessary to understand the large historical range in water levels, regional climatology, lake hydrodynamics, and lake-effect snowfall, all of which inform water management. Despite the societal and scientific importance of this information, few long-term, full-year, in situ measurements exist due to logistical, financial, and safety-related challenges. We present 15 years (2008–2022) of eddy covariance data from Stannard Rock, a historic lighthouse on Lake Superior located 38 km southeast of Manitou Island and 72 km north of Marquette, Michigan. We provide information about the site and instrumentation, as well as data availability and processing. Analysis of this unique long-term dataset, available through the AmeriFlux network (US-GL1), will improve our ability to understand the drivers and patterns of large-lake surface energy fluxes and will advance predictions of evaporative regimes over Lake Superior. [ABSTRACT FROM AUTHOR]

River discharge information is crucial for various applications, but the measurement process often remains impeded by factors that hinder near real-time (NRT) data availability in India. However, leveraging telemetry-based water surface elevation (WSE) data across the country provides an opportunity to convert it into river discharge. This conversion is made possible by utilizing rating curves (RCs) derived from historical collocated measurements of WSE and discharge. In this study, NRT WSE from the Central Water Commission (CWC) flood portal is obtained via the web-scraping tool. Through the application of RCs, discharge data is extended across 210 gauging stations in India from the year 2020 to the present, encompassing sub-daily discharge during the non-monsoon and hourly discharge series during monsoon (June-September) across the Indian rivers. Annually, the study generated over 800,000 discharge data points for Indian rivers, accounting for more than 4000 discharge measurements per station annually. These comprehensive datasets provide valuable insights for water resource and flood management research, offering NRT access to WSE, and discharge, along with the local RCs. [ABSTRACT FROM AUTHOR]

Studying groundwater renewal time is a valuable tool to deepen the comprehension of sustainable groundwater resources specific to arid regions. Tritium is a radioactive isotope of hydrogen often used as an environmental tracer to study groundwater renewal time. The present work reports groundwater renewal times by the environmental tracer tritium to understand sustainable water resources in arid regions. First, groundwater samples were collected from wells in northeastern arid regions of Saudi Arabia. Then, an electrolysis process was employed to significantly increase the tritium level from twenty-five to thirty times the original concentration. Subsequently, the enriched water was analyzed using a liquid scintillation counter under optimized measurement conditions to determine the tritium concentration precisely. Two internationally recognized tritium laboratories conducted independent assessments to validate the estimated tritium levels. The verified tritium concentration was then used to estimate the groundwater renewal time using the Morgenstern and Pimenta curves. The results suggest that most of the monitored wells in the surveyed areas are more than a century old. Conversely, a few monitoring wells exhibit renewal times of several hundred years and may be considered nonrenewable water sources. These studies help to understand the geochemical characteristics of arid regions to ensure the sustainable management and protection of groundwater resources. [ABSTRACT FROM AUTHOR]

Water scarcity is exacerbated by rising water use and climate change, yet state-of-the-art Earth system models typically do not represent human water demand. Here we present an enhancement to the Community Earth System Model (CESM) and its land (CLM5) and river (MOSART) components by introducing sectoral water abstractions. The new module enables a better understanding of water demand and supply dynamics across various sectors, including domestic, livestock, thermoelectric, manufacturing, mining, and irrigation. The module conserves water by integrating abstractions from the land component with river component flows and dynamically calculates daily water scarcity based on local demand and supply. Through land-only simulations spanning 1971–2010, we verify our model against known water scarcity hotspots, historical global water withdrawal trends, and regional variations in water use. Our findings show that non-irrigative sectoral consumption has an insignificant effect on regional climate, while emphasizing the importance of including all sectors for water scarcity assessment capabilities. Despite its advancements, the model's limitations, such as its exclusive focus on river water abstractions, highlight areas for potential future refinement. This research paves the way for a more holistic representation of human–water interactions in ESMs, aiming to inform sustainable water management decisions in an evolving global landscape. [ABSTRACT FROM AUTHOR]

Understanding the responses of olive trees to drought stress is crucial for improving cultivation and developing drought-tolerant varieties. Water transport and storage within the plant is a key factor in drought-tolerance strategies. Water management can be based on a variety of factors such as stomatal control, osmoprotectant molecules, proteins and wood properties. The aim of the study was to evaluate the water management strategy under drought stress from an anatomical and biochemical point of view in three young Italian olive cultivars (Giarraffa, Leccino and Maurino) previously distinguished for their physiological and metabolomic responses. For each cultivar, 15 individuals in pots were exposed or not to 28 days of water withholding. Every 7 days, the content of sugars (including mannitol), proline, aquaporins, osmotins, and dehydrins, in leaves and stems, as well as the chemical and anatomical characteristics of the wood of the three cultivars, were analyzed. 'Giarraffa' reduced glucose levels and increased mannitol production, while 'Leccino' accumulated more proline. Both 'Leccino' and 'Maurino' increased sucrose and aquaporin levels, possibly due to their ability to remove embolisms. 'Maurino' and 'Leccino' accumulated more dehydrins and osmotins. While neither genotype nor stress affected wood chemistry, 'Maurino' had a higher vessel-to-xylem area ratio and a larger hydraulic diameter, which allows it to maintain a high transpiration rate but may make it more susceptible to cavitation. The results emphasized the need for an integrated approach, highlighting the importance of the relative timing and sequence of each parameter analyzed, allowing, overall, to define a "strategy" rather than a "response" to drought of each cultivar. [ABSTRACT FROM AUTHOR]

This work presents a novel approach to rainfall–runoff modeling. We incorporate GAN-based data compaction into a spatial-attention-enhanced transductive long short-term memory (TLSTM) network. The GAN component reduces data dimensions while retaining essential features. This compaction enables the TLSTM to capture complex temporal dependencies in rainfall–runoff patterns more effectively. When tested on the CAMELS dataset, the model significantly outperforms benchmark LSTM-based models. For 8-day runoff forecasts, our model achieves an NSE of 0.536, compared to 0.326 from the closest competitor. The integration of GAN-based feature extraction with spatial attention mechanisms improves predictive accuracy, particularly for peak-flow events. This method offers a powerful solution for addressing current challenges in water resource management and disaster planning under extreme climate conditions. [ABSTRACT FROM AUTHOR]

Dryland lakes are indispensable to regional water resource systems. Ebinur Lake, the largest saline lake in Xinjiang Uygur Autonomous Region, is vital for regional biodiversity and environmental stability but has been facing the predicament of gradual shrinkage in recent decades. In this study, we proposed a new dual-index method for Landsat (-5, -7, -8, and -9) data to extract water with the combinations of the normalized difference water index (NDWI) and the modified NDWI for turbid waters (NDWIturbid). The dual-index method showed a high overall accuracy of 96.36% for Ebinur Lake. Landsat series images from 1992 to 2023 were employed to acquire the water areas of Ebinur Lake. The results showed that, over the past three decades, the area of Ebinur Lake exhibited a fluctuating decreasing trend, with an average lake area of 568.74 ± 152.43 km². The northwest intermittent water areas showed significant changes, and there was a close connection between the northwest and core water areas. Seasonally, the lake area decreased from spring to autumn. River inflow, driven by rainfall and human activities, was the primary factor affecting the inter/inner annual changes in Ebinur Lake. Furthermore, due to the valley effects, wind was found to be a critical factor in the diurnal changes in the water areas. This study should deepen the understanding of the variations of Ebinur Lake and benefit local water resource management. [ABSTRACT FROM AUTHOR]

Satellite rainfall estimates are robust alternatives to gauge precipitation, especially in Africa, where several watersheds and regional water basins are poorly gauged or ungauged. In this study, six satellite precipitation products, the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS); Tropical Applications of Meteorology Using Satellite and Ground-based Observations (TAMSAT); TRMM Multi-satellite Precipitation Analysis (TMPA); and the National Aeronautics and Space Administration's new Integrated Multi-SatellitE Retrievals for Global Precipitation Measurement (GPM) early run (IMERG-ER), late run (IMERG-LR), and final run (IMERG-FR), were used to force a gauge-calibrated Soil & Water Assessment Tool (SWAT) model for the Congo River Basin, Central Africa. In this study, the National Centers for Environmental Prediction's Climate Forecast System Reanalysis (CFSR) calibrated version of the SWAT was used as the benchmark/reference, while scenario versions were created as configurations using each satellite product identified above. CFSR was used as an independent sample to prevent bias toward any of the satellite products. The calibrated CFSR model captured and reproduced the hydrology (timing, peak flow, and seasonality) of this basin using the average monthly discharge from January 1984–December 1991. Furthermore, the results show that TMPA, IMERG-FR, and CHIRPS captured the peak flows and correctly reproduced the seasonality and timing of the monthly discharges (January 2007–December 2010). In contrast, TAMSAT, IMERG-ER, and IMERG-LR overestimated the peak flows. These results show that some of these precipitation products must be bias-corrected before being used for practical applications. The results of this study will be significant in integrated water resource management in the Congo River Basin and other regional river basins in Africa. Most importantly, the results obtained from this study have been hosted in a repository for free access to all interested in hydrology and water resource management in Africa. [ABSTRACT FROM AUTHOR]

Accurate and efficient streamflow simulations are necessary for sustainable water management and conservation in arid and semi-arid contexts. Conceptual hydrological models often underperform in these catchments due to the high climatic variability and data scarcity, leading to unstable parameters and biased results. This study evaluates the stability of the HBV model across seven sub-catchments of the Oum Er Rabia river basin (OERB), focusing on the HBV model regionalization process and the effectiveness of Earth Observation data in enhancing predictive capability. Therefore, we developed a nested cross-validation framework for spatiotemporal stability assessment, using optimal parameters from a donor-single-site calibration (DSSC) to inform target-multi-site calibration (TMSC). The results show that the HBV model remains spatially transferable from one basin to another with moderate to high performances (KGE (0.1~0.9 NSE (0.5~0.8)). Furthermore, calibration using KGE improves model stability over NSE. Some parameter sets exhibit spatial instability, but inter-annual parameter behavior remains stable, indicating potential climate change impacts. Model performance declines over time (18–124%) with increasing dryness. As a conclusion, this study presents a framework for analyzing parameter stability in hydrological models and highlights the need for more research on spatial and temporal factors affecting hydrological response variability. [ABSTRACT FROM AUTHOR]

Lake is an important water resources in Mongolia, which has undergone a large variation in past decades. However, it is still challenging to monitor long-term changes in lake water storage (LWS) due to the lack of lake level monitoring and long-term satellite altimetry data for Mongolian lakes. According to the Advanced Land Observing Satellite Digital Elevation Model (ALOS DEM) and the Joint Research Centre (JRC) dataset, we estimated the LWS changes of 55 Mongolian lakes (> 10 km2) from 1991 to 2020. The results showed that the LWS increased by 40.24 km3 from 1991 to 1997, especially for northwestern Mongolia with 31.47 km3. However, the LWS decreased by 32.44 km3 from 1998 to 2010, and the lakes in the northwestern and southern decreased by 20.24 km3 (62%) and 7.38 km3 (23%), respectively, and then the LWS continued to decrease by 10.22 km3 from 2011 to 2020. The precipitation was the primary cause of lake change, which could explain 45.13% of LWS change based on Generalized Linear Model, followed by temperature (26.33%) and irrigated area (16.72%). Analyzing the changing characteristic and driving mechanisms of LWS can provide a scientific basis for local water resources management and planning. [ABSTRACT FROM AUTHOR]

The water ecological security pattern is a core factor. A scientific, accurate, and practical evaluation of water ecological security provides a theoretical basis for regional water ecological management. Using water resource data from five cities in the Hexi Corridor of Gansu Province (Jiuquan (JQ), Jiayuguan (JYG), Zhangye (ZY), Jinchang (JC), and Wuwei (WW)) from 2006 to 2021, a water ecological security evaluation index system based on the PSR (pressure-state-response) framework was constructed, covering 27 factors related to water resources, socio-economics, and the ecological environment. The main obstacle factors of water ecological security were identified using the obstacle degree model, and the grey GM(1,1) model was employed to predict water ecological security. Results indicated that the comprehensive assessment index of water ecology in the Hexi Corridor increased from 2006 to 2021, showing a transition from relatively unsafe (0.319) to basic safety and then to relatively safe (0.672). The pressure and response systems were the main limiting factors affecting water ecological security in the Hexi Corridor. After a slight decline in 2008, the overall spatial distribution continued to rise, with WW City and ZY City leading since 2016. ZY had a higher safety grade proportion (25%) compared to other areas in the Hexi region. The pressure system was the most significant obstacle to water ecological security after 2006. Prediction results indicated that the comprehensive evaluation index of water ecological security would continue to rise annually from 2022 to 2031, reaching a very safe level by 2025. The evaluation results provide a scientific basis for ecological security and risk decision-making in the study area. [ABSTRACT FROM AUTHOR]

Accurate and efficient identification of water inrush sources, as one of the three critical elements of mine water hazards, is crucial for mine water management. To identify the sources of mine water inrush effectively, a model named HBA-CatBoost is introduced. This model is established on the hybrid bat algorithm (HBA)-optimized category feature gradient boosting tree (CatBoost), and the shapley additive explanation (SHAP) method is employed to elucidate the model's decision-making process. Given the prevalent occurrence of water hazards in coal seam roofs and floors in the northern Guizhou coalfield, coupled with the challenges in pinpointing water inrush sources in mines, the HBA-CatBoost model is tested at the Longfeng Coal Mine in northern Guizhou to validate its practicality. Comparative analysis with the HBA-RF, HBA-XGBoost, CatBoost, RF, and XGBoost models demonstrates that the hybrid bat algorithm significantly enhances the classification performance of the CatBoost model, resulting in improved convergence speed and classification accuracy. The HBA-CatBoost model outperforms the aforementioned models in terms of classification effectiveness, achieving accuracy, recall, precision, and F1 scores of 96.43%, 97.22%, 96.43%, and 96.61%, respectively. The SHAP method elucidates the decision mechanism of the optimal HBA-CatBoost model, highlighting the significance of sample features and bolstering the model's credibility. These outcomes underscore the superior performance of the HBA-CatBoost model and its potential for effectively identifying water inrush sources in mines. [ABSTRACT FROM AUTHOR]

Cyanophages play a pivotal role in controlling cyanobacterial populations in aquatic environments. These dsDNA viruses harbor auxiliary metabolic genes (AMGs) that modulate the key metabolic processes of their cyanobacterial hosts, such as Photosynthesis, nutrient uptake for the optimization of viral replication. Recently, pan1~pan5 and pam1~pam5 cyanophages have been isolated from the fifth largest water resource in China; Lake Chaohu. Detailed genomic analysis of these phages revealed that these isolated cyanophages especially Pan1, Pam2 and Pam3 possess unique AMGs that significantly enhance the metabolic activities of their hosts, potentially leading to the suppression of bloom formation and stabilization of the ecological dynamics of Lake Chaohu. Our findings provide concrete evidence that cyanophages encoding AMGs could serve as effective biocontrol agents against harmful algal blooms, offering a targeted approach to manage these environmental threats. The integration of cyanophage-based management therapies with traditional methods could advance the efficiency and sustainability of controlling cyanobacterial outbreaks, paving the way for novel applications in water resource management. This review emphasizes the importance and critical need for further exploration of phage-host dynamics to fully harness the potential of cyanophages in ecosystem regulation. [ABSTRACT FROM AUTHOR]

Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management. [ABSTRACT FROM AUTHOR]

The document discusses the importance of water resources management for sustaining ecosystems, economic development, and social well-being. It highlights the significance of reservoir control operations in optimizing water utilization efficiency and supporting various water needs. The document also explores new monitoring technologies, artificial intelligence methods, and integrated water resources management strategies to address challenges such as climate change impacts and increasing water demand. Overall, the document aims to stimulate further research and dialogue on water resources management to achieve global water security and sustainability. [Extracted from the article]

The document discusses the theory and technology for preventing mine water disasters, emphasizing the importance of mine water disaster prevention for safe mining operations. Various studies explore advanced detection methods, disaster prevention technologies, and risk assessment approaches to enhance mine safety and promote sustainable development in the mining industry. The research findings cover topics such as detecting concealed water-conducting faults, monitoring drainage tunnel intrusions, studying landslide initiation mechanisms, analyzing hydrogeochemical characteristics of groundwater, and developing prediction models for water-conducting fracture zones. These studies provide valuable insights for addressing water hazards in coal mines and offer practical engineering applications and methodological guidance. [Extracted from the article]

This paper provides a comprehensive review of the methods and techniques developed for detecting leaks in water distribution systems, with a focus on highlighting their strengths, weaknesses, and areas for future research. Given the substantial economic, social, and environmental impacts of undetected leaks, timely detection and precise location of leaks are critical concerns for water authorities. This review categorizes existing methods into traditional approaches, such as manual sounding, and modern techniques involving smart water management and sensor technologies. A multidimensional bibliometric analysis was employed to systematically identify, select, and evaluate 600 scholarly articles on water leak detection, sourced from the Scopus database over a 23-year period (2000–2023). The paper evaluates each method based on leak sensitivity, burst detection, continuous monitoring, alarm accuracy, and implementation costs. Novel insights include an analysis of emerging smart water technologies and their integration into real-world water distribution networks, offering improved efficiency in leak detection. The paper also identifies key gaps in current research and suggests future directions for advancing the accuracy and cost-effectiveness of these technologies. [ABSTRACT FROM AUTHOR]

The Longmen Shan fold and thrust belt, situated on the eastern margin of the Qinghai–Tibet Plateau, is prone to disasters like earthquakes and debris flows. Thus, applying rapid assessment methods for emergency water sources in disaster-affected areas is crucial for local populations and ensuring an effective response to disasters. In this study, we employed electrical resistivity tomography (ERT) to investigate groundwater resources in post-disaster regions. By integrating the results from ERT profiles with geological and borehole information, we determined the lithology and depth of aquifers. Additionally, we analyzed groundwater recharge and discharge patterns relative to surface water during various precipitation periods and generated a hydrogeological profile for the region. Borehole information confirmed our inferred lithology and aquifer depth, thereby ensuring a reliable water supply during emergencies. This study demonstrates the feasibility of ERT for rapidly identifying water resources in geologically complex environments, providing a scientific foundation for water resource management in disaster-prone regions. [ABSTRACT FROM AUTHOR]

The current study investigated hydroclimatic extremes in Vhembe, Lejweleputswa, and uMgungundlovu District Municipalities based on streamflow data from 21 river gauge stations distributed across the study site for the period spanning 1985–2023. Statistical metrics such as the annual mean and maximum streamflow, as well as trends in annual, maximum, seasonal, and high/low flow, were used to evaluate the historical features of streamflow in each of the three district municipalities. Moreover, the Standardized Streamflow Index (SSI) time series computed from streamflow observations at 3- and 6-month accumulation periods were used to assess hydroclimatic extremes, including drought episodes, proportion of wet/dry years and trends in SSI, drought duration (DD), and drought severity (DS). The results indicate that the three district municipalities have experienced localized and varying degrees of streamflow levels and drought conditions. The uMgungundlovu District Municipality in particular has experienced a significant decline in annual and seasonal streamflow as well as an increase in drought conditions during the 38-year period of analysis. This is supported by the negative trends observed in most of the assessed metrics (e.g., annual, maximum, seasonal, low/high flow, and SSI), whereas DD and DS showed positive trends in all the stations, suggesting an increase in prolonged duration and severity of drought. The Lejweleputswa District Municipality depicted positive trends in most of the assessed metrics, suggesting that streamflow increased, whereas drought decreased in the region over the 38-year period of study. Moreover, the Vhembe District Municipality experienced both negative and positive trends, suggesting localized variations in dry and wet conditions. The results presented in this study contribute towards drought monitoring and management efforts in support of policy- and decision-making that aim to uplift water resources management and planning at local and district municipality levels. [ABSTRACT FROM AUTHOR]

Seasonal changes, sea level rise, and global warming make flood events more frequent, which necessitates watershed management and efficient use of water resources. In this context, understanding the hydrodynamic behavior of basins is critical for the development of flood prevention strategies. The contributions of hydrological and hydraulic modeling techniques in this process are among the key determinants of sustainable water resources management. The Filyos Sub-Basin, located in the Western Black Sea Basin, stands out as one of the regions where flood risk assessment is a priority, as it has two important floodplains. This study aims to analyze the flood risk in the Filyos River Sub-Basin with hydraulic modeling methods, and to determine the Manning roughness coefficient. In the study, the parameters affecting the roughness of the river bed were analyzed using the Cowan method, and the effects of vegetation on river bed resistance were evaluated in the laboratory environment. Flood simulations were carried out for four different flow rates (Q1000, Q500, Q100 and Q50) using the HEC-RAS model, and the performance of flood protection structures were analyzed. The findings show that a significant portion of the existing protection structures are unable to meet the potential flood flows, which can cause serious damage to residential and agricultural areas. In basins with limited historical discharge data, such as the Filyos River, these findings provide important contributions to sustainable water resources management and regional planning processes. The results of the study serve as a reference for flood risk assessment, not only for the Filyos River Basin, but also for other basins with similar hydrodynamic characteristics. It is envisaged that future research, supported by larger data sets, can improve the accuracy of flood simulations. Furthermore, the Cowan method and HEC-RAS model used in this study are expected to contribute to strategic planning and engineering solutions to minimize flood risk in other watershed management projects. In future studies, we plan to further develop methodological approaches for determining the roughness coefficient, and to address applications to increase the effectiveness of flood protection structures. [ABSTRACT FROM AUTHOR]

The document discusses the environmental effects of natural processes and human activities on the water environment in watersheds. It highlights the impact of pollutants from agricultural, urban, and industrial sources on water quality, as well as the accumulation of nutrients and heavy metals. The papers in the special issue focus on topics such as nutrient accumulation, heavy metal contamination, and the origin and transportation of major ions and solutes in river water. Additionally, the document addresses the impact of hydraulic characteristics on water environments in large reservoirs, emphasizing the need for continued research to understand and mitigate the effects of human activities on water quality. [Extracted from the article]

In this study, we explore the potential of assimilating satellite-derived reservoir storage data into the global-scale hydrodynamic model CaMa-Flood, focusing on the Yangtze River basin. We evaluated three data assimilation (DA) methods: direct assimilation (DIR), anomaly based assimilation (ANO), and normalized assimilation (NOM). Our results show that the DIR method achieved the most significant improvements in reservoir storage and downstream discharge simulations. DIR reduced the average relative root mean square error (rRMSE) of reservoir storage estimates by 80.5%, and increased discharge correlation (ΔCC) by 78.6% in the 14 validated discharge stations. ANO, while effective in certain cases, led to mixed results, with 56.4% of the 39 assimilated dams showing improved storage estimates and a modest 7.8% reduction in average RMSE. NOM had minimal impact, with negligible changes in RMSE or discharge correlation (ΔCC). The direct assimilation method (DIR) consistently outperformed the others, improving both reservoir storage and downstream discharge estimates. However, the magnitude of improvement varied across locations, highlighting the need for the further refinement of DA techniques and input data, especially for regions with complex reservoir operations. Our findings enhance reservoir representation in global hydrodynamic models and improve the predictability of river dynamics and water resource management. [ABSTRACT FROM AUTHOR]

Groundwater depletion in Bangladesh's Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 × 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has become an instrument used in all domains with good results. The water resources management field is not an exception. Therefore, in this article, we propose two machine learning (ML) techniques—an echo state network (ESN) and sparrow search algorithm–echo state network (SSA-ESN)—for monthly modeling of the water discharge of one of the biggest rivers in Romania for three periods (S, S1, and S2). In both models, R2 was over 0.989 on the test and training sets and the mean absolute error (MAE) varied between 4.4826 and 7.6038. The performance of the SSA-ESN was similar, but the ESN had the shortest run time. The influence of anomalies on the models' quality was assessed by running the algorithms on a series without the aberrant values, which were detected by the seasonal hybrid extreme studentized deviate (S-H-ESD) test. The results indicate that removing the anomalies significantly improved both models' performance, but the run time was increased. [ABSTRACT FROM AUTHOR]

Water yield, one of the most valuable and important ecological indicators, reflects the renewable capacity of regional water resources. The Taihang Mountains are a natural ecological barrier and an important source of water production for the North China Plain. Two large-scale projects involving returning farmland to forest and grassland have significantly changed the distribution of land use in the Taihang Mountains, and also affect the water production characteristics of the Taihang Mountains. Taking the Hutuo River Basin, a typical river in the Taihang Mountainous region, as the study area, the InVEST model is utilized to calculate the spatial and temporal changes in water yield capacity in the Hutuo River basin, and four scenarios were set to judge the impact of different ecological projects on the water yield of the mountainous watershed of the Hutuo River. The results showed that the water yield in the five study periods was 218.58–376.44 mm. The interannual variations in both precipitation and water yield of the study area in the last decade were large. The water yield is mainly concentrated in the northeast region of the upper reaches of the basin, and the smallest is the northwest and central regions of the upper reaches. The water yield in each year in the study area is mainly less than 400 mm, accounting for more than 60% of the study area, and the water yield has shown a large regional expansion in the past 10 years. Grassland has the largest water yield capacity of all land use types, and climate change has basically no effect on the water yield capacity of different land use types. The ecological project of returning farmland to forestland has a negative impact on the water yield capacity, whereas the water yield capacity increases after returning farmland to grassland. The water conservancy project of river training has a negative impact on the water yield capacity of the Hutuo River mountainous basin. The research results provide theoretical data for judging the relationship between vegetation restoration and water yield in mountainous watersheds, a scientific basis for evaluating the implementation effect of major projects, and strong data support for water resource management in the North China Plain. [ABSTRACT FROM AUTHOR]

The evaluation of sustainable water resources' utilization capacity in the Huangshui Basin is essential for effective management and development in the water-scarce regions of northwest China. This research provides valuable insights into the basin's potential capacity for sustainable water resource use by developing a comprehensive evaluation index that addresses the following three critical aspects: climate factors, water resource systems, and socio-economic conditions. The evaluation is conducted using a dual method, as follows: the fuzzy comprehensive evaluation model and the ELECTRE III evaluation method. The results indicate that the Huangshui Basin's water resources, as a whole, exhibit a medium sustainable utilization capacity. Climatic factors and socio-economic characteristics are the main factors affecting the sustainable utilization of water resources in the Huangshui Basin. Remarkably, both methods yield consistent results, indicating that the overall sustainable utilization capacity of the Huangshui Basin's water resources is medium. Climatic factors and socio-economic characteristics are identified as the primary aspects influencing the sustainable utilization of water resources in the basin. Based on these findings, recommendations such as enhancing the introduction of external water resources, improving water resources' management, and implementing comprehensive remediation efforts can help to elevate the level of sustainable water use. This research not only contributes to a deeper understanding of the basin's water resources' dynamics, but also serves as an important reference for informed decision making regarding sustainable utilization in the Huangshui Basin. [ABSTRACT FROM AUTHOR]

Precise water level forecasting plays a decisive role in improving the efficiency of flood prevention and disaster reduction, optimizing water resource management, enhancing the safety of waterway transportation, reducing flood risks, and promoting ecological and environmental protection, which is crucial for the sustainable development of society. This study proposes a hybrid water level forecasting model based on Time-Varying Filter-based Empirical Mode Decomposition (TVFEMD), Inverse-Free Extreme Learning Machine (IFELM), and error correction. Firstly, historical water level data are decomposed into different modes using TVFEMD; secondly, the Improved Jellyfish Search (IJS) algorithm is employed to optimize the IFELM, and subsequently, the optimized IFELM independently forecasts each sub-sequence and obtains the predictive results of each sub-sequence; thirdly, an Online Sequential Extreme Learning Machine (OSELM) model is used to correct data errors, and the initial predictive results and error prediction results are added together to obtain the final prediction for the sub-sequence; and finally, the final prediction for the sub-sequences are added to obtain the prediction results of the entire water level sequence. Taking the daily water level data from 2006 to 2018 in Taihu, China as the research object, this paper compares the proposed model with the ELM, BP, LSTM, IFELM, TVFEMD-IFELM, and TVFEMD-IFELM-OSELM models. The results show that the TVFEMD-IJS-IFELM-OSELM model established in this study has high prediction accuracy and strong stability and is suitable for water level forecasting. [ABSTRACT FROM AUTHOR]