Search Results (317)

As the impacts of climate change intensify, water resource conflicts are escalating globally, particularly in regions with uneven water distribution, such as Central Asia. Long-standing disputes over water allocation persist between Kyrgyzstan and Uzbekistan. This paper aims to examine the conflicts and challenges in water allocation between the two countries and explore the potential of Decision Support Systems (DSSs) as a viable solution. The paper begins by reviewing the historical evolution of water allocation in Central Asia, analyzing upstream–downstream disputes and notable cooperation efforts, with a focus on key water agreements. It then outlines the definitions, development, and classifications of DSSs in the context of water allocation and presents two illustrative case studies—the Tarim River Basin in Xinjiang, China, and the Nile River Basin in Africa. These cases demonstrate the applicability of DSSs in water-scarce regions with similar socio-ecological dynamics and complex multi-country, cross-sectoral water demands. Building on these insights, the paper analyzes the key challenges to implementing DSSs for transboundary water allocation in Central Asia, including limited data availability and sharing, insufficient technical capacity, chronic funding shortages, socio-political complexities, climate change impacts, and the inherent difficulty of modeling complex systems. In response, a set of targeted pragmatic recommendations is proposed. While acknowledging its limitations, the paper argues that establishing a structured, system-based decision-making framework—namely DSSs—can help stakeholders enhance climate-informed strategic planning and foster cooperation, ultimately contributing to more equitable and sustainable water resource allocation in the region. Full article

The Nile River Basin—shared by eleven countries and supporting over 300 million people—exemplifies the complexity of managing shared waters amid asymmetrical power relations, historical legacies, and competing development priorities. To advance the understanding of transboundary water governance and guide future cooperative strategies in the Nile Basin, a synthesis linking historical governance regimes with current contemporary frameworks is essential, as the existing literature is largely episodic, and its scope rarely includes recent governance developments. This review traces over a century of governance evolution, from pre-colonial and colonial allocation treaties through post-independence bilateral agreements to current institutional innovations and basin-wide initiatives. Historical and contemporary arrangements are assessed against principles of equitable and reasonable utilization, revealing persistent gaps in fairness, enforceability, and adaptive capacity. The analysis concludes by exploring emerging cooperation mechanisms and opportunities to transform the Nile from a locus of geopolitical tension into a model of equity-driven, cooperative governance. Full article

Predicting dam inflow is critical for human life safety, water resource management, and hydroelectric power generation. While machine learning (ML) models address complex, nonlinear hydrological problems, quantum machine learning (QML) offers greater potential to overcome classical computational limits. This study compares a hybrid quantum neural network (HQNN) with the following two classical models: bidirectional CNN-LSTM and support vector regression (SVR). These models were evaluated to predict monthly inflow to the Mile Mughan Dam, a transboundary hydroelectric and irrigation dam located on the Aras River between Azerbaijan and Iran, using a 14-year dataset (2010–2023) under two scenarios. In total, 70% of data was used for training and 30% for testing. The first scenario encompassed meteorological variables plus three months of inflow lags, and the second included inflow lags only. Model performance was assessed using Coefficient of Determination (R²), Root Mean Squared Error (RMSE), Nash–Sutcliffe efficiency (NSE), Mean Absolute Percentage Error (MAPE), and graphical plots. HQNN showed superior performance across all metrics. In Scenario 1, HQNN achieved R² = 0.915, RMSE = 37.318 MCM, NSE = 0.908, MAPE = 8.343%; CNN-BiLSTM had R² = 0.867, RMSE = 46.506 MCM, NSE = 0.858, MAPE = 10.795%; SVR had R² = 0.846, RMSE = 52.372 MCM, NSE = 0.821, MAPE = 12.772%. In Scenario 2, HQNN maintained strong performance (R² = 0.855, RMSE = 48.56 MCM, NSE = 0.845, MAPE = 9.979%) and outperformed CNN-BiLSTM (R² = 0.810, RMSE = 56.126 MCM, NSE = 0.793, MAPE = 11.456%) and SVR (R² = 0.801, RMSE = 60.336 MCM, NSE = 0.761, MAPE = 12.901%). In Scenario 1 and Scenario 2, HQNN increased the prediction accuracy by 19.76% and 13.47%, respectively, compared to the CNN-BiLSTM model. These results confirm HQNN’s reliability in both multivariate and univariate modeling. Full article

This study evaluates the feasibility of implementing water markets and improving decision-making for irrigated agriculture in transboundary water basins. It analyzes the physical and economic potential of cooperation between institutions and users in the face of recurrent water scarcity. The research’s study case is the Conchos River basin in Chihuahua, Mexico, where agriculture accounts for 96% of the state’s water use. The basin, with its four main irrigation districts: 005 Delicias, 090 Ojinaga, 103 Florido, and 113 Alto Conchos, contributes approximately 80% of the volume committed in the 1944 International Boundary and Water Treaty between Mexico and the United States. The methodology integrates Cooperative Game Theory with Positive Mathematical Programming (PMP) in Python version 3.12 to optimize water allocation. The models consider crop coefficients, yield response to water deficit, and regulatory proposals: water transfer (75% efficiency), fodder production flexibility (10%), and saving 20% of the maximum transferable volume for the treaty. Results show that cooperation between districts allows positive gains to be maintained, even with a 50% reduction in water availability. Full article

The Danube River is one of Europe’s largest transboundary rivers, characterized by substantial spatial heterogeneity in environmental conditions, monitoring practices, and water management frameworks. Developing a harmonized approach for basin-wide surface-water quality assessment is therefore essential. This study presents the development and application of an adapted Water Quality Index (Danube WQI) for assessing and monitoring water quality along the Danube River, one of Europe’s largest and most complex transboundary systems. The Danube WQI is based on established WQI methodologies and integrates two objective weighting approaches—the Entropy Weight Method (EWM) and the CRITIC (Criteria Importance Through Inter-Criteria Correlation) method—to minimize subjectivity and improve the robustness of parameter weighting. Long-term water quality data from the TransNational Monitoring Network (TNMN) of the International Commission for the Protection of the Danube River (ICPDR) were used, covering 42 stations across nine countries (1996–2022). Nine parameters were selected: dissolved oxygen (DO), biochemical oxygen demand (BOD₅), total nitrogen (TN), nitrate (NO₃), ammonium (NH₄), total phosphorus (TP), orthophosphate (PO₄), electrical conductivity (EC), and pH. During the formation of sub-indices and rating curves, national water quality standards from the Danube countries were harmonized to ensure consistent parameter classification. Results indicate that the Danube River generally exhibits very good water quality, with most sections belonging to the first and second quality classes. Comparison with the Canadian Water Quality Index (CWQI) confirmed similar results but demonstrated higher seasonal sensitivity of the Danube WQI. Additionally, rankings obtained using the PROMETHEE II multicriteria method showed strong agreement with the Danube WQI classifications, further confirming the robustness of the proposed index. The proposed index provides a harmonized and transferable framework that can support integrated water management and policy evaluation across the Danube River Basin and within the EU Water Framework Directive context. Full article

Managing hydraulic behaviour and water quality in semi-arid, transboundary rivers such as the Talas River in Kazakhstan requires reliable numerical tools for predicting free-surface flow through porous hydraulic structures. This study develops and verifies a two-dimensional computational fluid dynamics (CFD) framework for simulating free-surface water flow through porous media and demonstrates its applicability to a real river reach of the Talas in the Zhambyl region. The model combines the Volume of Fluid (VOF) method with the Darcy–Forchheimer formulation to represent porous resistance, while turbulence is described by the RNG k–$\epsilon$ model, and pressure–velocity coupling is handled by the PISO algorithm. Model verification is conducted against a classic dam-break experiment involving a rectangular porous barrier across a laboratory channel. The simulations successfully reproduce the main experimental observations, including rapid drawdown after gate opening, formation and attenuation of the free-surface wave, localized depression above the porous insert, and the subsequent approach to a quasi-steady state. Time histories of water levels at control points and the spatial progression of the wet front show close agreement with measurements. Using the validated setup, a site-specific two-dimensional domain for the Talas River is constructed to analyse the hydraulic influence of a porous bar. The model quantifies velocity redistribution and energy dissipation across the porous patch and provides physically consistent flow fields suitable for engineering assessments under various discharge conditions. Full article

This paper examines the Harirud (Harirod, Tejen) River Basin, a vital transboundary water source shared by Afghanistan, Iran, and Turkmenistan. The basin supports farming, energy production, and home supply in a dry area. Despite its ecological, socio-economic, and geopolitical importance, the basin lacks a cooperative governance framework, leaving it vulnerable to unilateral development, institutional weakness, and climate stress. Addressing an important research gap, this study investigates how unilateral water infrastructure and climate change jointly reshape water security and governance between Afghanistan and Iran. A qualitative case study approach integrates insights from hydropolitics, benefit sharing, and environmental security to analyse ecological and political dynamics. Findings show that climate change has disrupted hydrological regimes—average temperatures have increased by about 1.7 °C and rainfall has declined by roughly 150 mm since 1980. Unilateral dam constructions have altered seasonal flows and intensified hydro-political tensions. The study concludes that implementing Integrated Water Resources Management (IWRM), joint hydrological monitoring, climate adaptation, and equitable benefit-sharing can transform the Harirud from a contested river into a foundation for regional stability and sustainable development. Full article

The Kherlen River Basin is a typical basin in the eastern Mongolian Plateau and is dominated by grassland. This study estimated the grassland yield in the Kherlen River Basin using the Carnegie–Ames–Stanford approach (CASA) model, combined with Theil–Sen median trend analysis and the Geodetector, to explore its spatiotemporal changes and driving factors. This integrated framework links temporal trend detection with spatial interaction analysis to better reveal ecological responses to climatic and anthropogenic influences. The results showed the following: (1) The root mean square error (RMSE) between the estimated grassland yield and the laboratory measurements was 37.88 g/m², with an estimation accuracy (EA) of 73.52%. (2) From 2000 to 2024, the grassland yield increased significantly at a rate of 1.98 g/(m²·a) (p < 0.05), with the fastest growth in the middle reaches. (3) Spatially, 79.78% of the basin exhibited significant increases, mainly in the central and western regions. The proportion of significant increase was highest in the upper reaches (40.36%), followed by the middle (32.89%) and lower reaches (6.53%). (4) Due to limited temporal resolution of socioeconomic data, the driving factor analysis covered the period 2000–2020, during which the overall grassland yield was primarily influenced by the interaction between precipitation and elevation (q = 0.6371). Specifically, the upper, middle, and lower reaches were mainly influenced by the interactions between temperature and precipitation (q = 0.6772), precipitation and elevation (q = 0.6377), and temperature and elevation (q = 0.4255), respectively. The study indicates that grassland yield in the Kherlen River Basin exhibited an overall increasing trend during 2000–2024, with climatic factors (precipitation and temperature) and the geographic factor (elevation) identified as the dominant drivers. The influence of human activities was not significant, although this result may be affected by uncertainties associated with data resolution limitations. Future work should incorporate higher-resolution remote sensing and socioeconomic datasets to better assess the impacts of human activities. Full article

The South-to-North Water Diversion Project (SNWDP), the world’s largest water transfer initiative, is designed to address northern China’s acute water scarcity by diverting approximately 45 km³ of water annually from the south through three major routes, with completion targeted for 2050. This review demonstrates that the SNWDP has already improved water security for over 150 million people, stabilized groundwater, and supported agricultural and urban development, but also presents significant challenges, including escalating costs, large-scale resettlement, and substantial environmental concerns such as ecosystem alteration, salinity intrusion, pollutant transfer, and risks to biodiversity and water quality. While mitigation and adaptive management efforts are ongoing, their long-term effectiveness remains uncertain. Notably, the SNWDP’s influence extends beyond China: by enhancing food production self-sufficiency, it can help stabilize global food markets during concurrent droughts and serves as a model—albeit a debated one—for large-scale water management and governance. The project’s hydropolitical and geopolitical dimensions, especially regarding the planned western route and potential transboundary impacts, underscore the need for international dialog and monitoring. Overall, the SNWDP exemplifies both the opportunities and dilemmas of 21st-century megaprojects, with its legacy dependent on balancing economic, environmental, and social trade-offs and on transparent, participatory governance to ensure sustainable outcomes for China and the global community. Full article

Intensifying urbanization in Central Europe is increasingly pushing flood retention areas onto private farmland, yet the agronomic and socio-economic trade-offs remain poorly quantified. We conducted a narrative review of published field data and post-event assessments from 2014–2023 along the transboundary Sava River. Information was collected from research articles, case studies, and environmental monitoring reports, and synthesized in relation to national and EU regulatory thresholds to evaluate how floods altered soil functions and agricultural viability. Water erosion during floods stripped up to 30 cm of topsoil in torrential reaches, while stagnant inundation deposited 5–50 cm of sediments enriched with potentially toxic elements, occasionally causing food crops to exceed EU contaminant limits due to uptake from the soil. Flood sediments also introduced persistent organic pollutants: 13 modern pesticides were detected post-flood in soils, with several exceeding sediment quality guidelines. Waterlogging reduced maize, pumpkin, and forage yields by half where soil remained submerged for more than three days, with farm income falling by approximately 50% in the most affected areas. These impacts contrast with limited public awareness of long-term soil degradation, raising questions about the appropriateness of placing additional dry retention reservoirs—an example of nature-based solutions—on agricultural land. We argue that equitable flood-risk governance in the Sava River Basin requires: (i) a trans-boundary soil quality monitoring network linking agronomic, hydrological, and contaminant datasets; (ii) compensation schemes for agricultural landowners that account for both immediate crop losses and delayed remediation costs; and (iii) integration of strict farmland protection clauses into spatial planning, favoring compact, greener cities over lateral river expansion. Such measures would balance societal flood-safety gains with the long-term productivity and food security functions of agricultural land. Full article

This study investigates the seasonal variability of water quality in the Yelek River Basin, Western Kazakhstan, using data from 2010 to 2025 that combine remote sensing, GIS, and hydrochemical monitoring data. This research addresses growing pressures on river systems from both natural and anthropogenic factors. Archival records from Kazhydromet and recent field measurements were analysed for dissolved oxygen, total suspended solids (TSSs), and total dissolved solids (TDSs), while satellite indices (NDWI, NDTI) provided spatiotemporal insights into turbidity. The results show clear seasonal contrasts: total suspended solids and turbidity rise sharply during spring floods due to snowmelt and erosion; water quality declines during summer–autumn low-flow periods under intensified human influence; and partial recovery occurs in winter when ice cover stabilises flow. Dissolved oxygen consistently indicates moderate pollution, while total dissolved solids (TDSs) remains within the “clean” range. Integration of satellite data with field observations enabled the development of a turbidity model and highlighted the lower river reaches as most vulnerable, where total suspended solids exceeded permissible limits. The findings confirm the value of combining remote sensing and GIS with traditional monitoring to capture long-term river water dynamics. This approach offers practical tools for sustainable water management, informs regional environmental policies, and provides transferable insights for semi-arid transboundary basins in Central Asia. Full article

Floods are among the most frequent and damaging natural hazards in the Mekong River Basin, where the interplay of monsoon-driven climate variability, complex topography, and rapid socio-economic change creates high exposure and vulnerability. This study presents a comprehensive assessment of flood disaster patterns, loss distribution, and regional disparities across five countries in the Lower Mekong Basin—Cambodia, Laos, Myanmar, Thailand, and Vietnam. Using multivariate spatiotemporal analysis based on EM-DAT, MRC, and national government datasets, the study quantifies flood frequency, casualties, and affected population to reveal cross-country differences in disaster impact and timing. Results show that while Vietnam and Thailand experience high flood frequency and storm-induced events, Laos and Cambodia face riverine flooding under constrained economic and infrastructural conditions. The findings highlight a basin-wide increase in flood frequency over recent decades, driven by climate change, land use transitions, and uneven development. The analysis identifies critical gaps in adaptive governance, particularly the need for dynamic policy frameworks that can adjust to spatial disparities in flood typologies (e.g., Vietnam’s storm floods vs. Cambodia’s riverine floods) and improve transboundary coordination of reservoir operations. Despite the region’s extensive reservoir capacity, most infrastructure prioritizes hydropower over flood mitigation. The study evaluates the role of regional cooperation frameworks such as the Lancang–Mekong Cooperation (LMC), demonstrating how strengthened institutional flexibility and knowledge-sharing mechanisms could enhance progress toward Sustainable Development Goals (SDGs) related to water governance (SDG 6), resilient infrastructure (SDG 9), and disaster risk reduction (SDG 11). By constructing the first integrated national-level flood disaster database for the basin and conducting comparative analysis across countries, this research provides empirical evidence to support differentiated yet coordinated flood risk governance strategies at both national and transboundary levels. Full article

The Erguna River, a Sino-Russian transboundary river, is vital for regional ecology, but land use impacts on its water quality remain unclear. This study aimed to reveal their response relationship. Using ArcGIS/ENVI, it classified land use in 2010 and 2016 into six types, and applied Pearson correlation to 10 monitoring sections’ water quality data. Results showed land use–water quality correlations were temporally and spatially variable: correlations weakened with increasing buffer distance, with the strongest associations within 1000 m. From 2010 to 2016, grassland shifted from a positive (water-purifying) to negative (pollutant-source) impact on water quality (BOD₅ and arsenic), which was driven by area reduction and overuse; forestland transitioned from no significant effect to a positive (pollutant-intercepting) role, attributed to area expansion. Arable and construction land showed no significant correlations with water quality, due to low proportions of construction land in cross-border areas, and arable land is mostly distributed in areas far from the riverbank. This study provides critical scientific support for transboundary water resource cooperation and targeted ecological management of the Erguna River Basin. Full article

Global climate change is expected to alter characteristics of flood events. This study evaluates the rising flood risk and damage potential in the lower Vipava River valley—a transboundary catchment between Slovenia and Italy—under climate scenarios RCP 2.6, 4.5, and 8.5. The area has experienced multiple floods in recent decades, indicating high vulnerability. Using hydraulic modeling for current and future conditions, flood hazard zones were identified and integrated into the KRPAN model to estimate expected annual damage (EAD). The findings show that EAD escalates from €0.97 million under current conditions to €1.97 million under the most extreme scenario. A 20% rise in flood peaks leads to a 1.4-fold increase in damage, while a 40% rise results in losses that are more than double. Buildings show a 2.5-fold increase in EAD, and water infrastructure EAD rises by a factor of 1.9. These results underscore the substantial economic consequences of climate change on flood risk. The study highlights the urgent need to incorporate climate scenarios into flood risk assessments and spatial planning to support adaptive strategies and reduce future damage. These insights are essential for making informed decisions and achieving long-term resilience. Full article

Riverbank height plays a potentially important role in hydrological dynamics and pollutant transport, yet its influence on long-term water quality trends remains insufficiently documented. This study explores possible relationships between riverbank height variations and the Global Pollution Index ($I_{GP}^{*}$) in the Timiș River, Romania, over eleven (11) years (2013–2023). A dataset of 17 physicochemical parameters—including BOD₅, COD-Cr, dissolved oxygen, nutrients (N and P species), heavy metals (As, Cr, Cu, and Zn), detergents, and phenols—was used to tentatively assess ecological status. The results suggest that, despite a maximum riverbank elevation change of ~11 cm between 2020 and 2025, $I_{GP}^{*}$ values remained within a relatively narrow range (1.98–2.56, mean 2.19), pointing to persistent but moderate anthropogenic pressure. The highest index value (2.56, in 2016) coincided with a transient pollution event, whereas subsequent years stabilized around 2.0–2.3, which may reflect chronic diffuse pollution. Correlation analysis revealed strong associations between BOD₅ and conductivity (r = 0.76, linked to organic loads), COD-Cr and heavy metals (r = 0.79, suggestive of industrial influence), and total nitrogen and nitrate (r = 0.97, related to agricultural inputs), appear to outline distinct source-related signatures. This study offers preliminary evidence that even modest riverbank fluctuations may influence hydrodynamics and the fate of pollutants, while basin-scale water quality seems to remain largely governed by diffuse pollution sources. By integrating long-term geomorphological monitoring with multi-parameter water quality data into a composite index ($I_{GP}^{*}$), our work sketches a potentially innovative framework for diagnosing pollution drivers. The findings underscore the importance of incorporating riverbank morphology into EU Water Framework Directive monitoring, alongside GIS, IoT, and machine learning tools, could contribute to more adaptive river basin management. Full article