Every fall season, Sudan experiences devastating floods that result in significant fatalities, displacement of populations, and severe disruptions to agricultural and economic activities. The 2020 floods were particularly catastrophic, reaching the highest Nile River levels in over a century and affecting more than 800,000 people. To the best of the authors' knowledge, this study represents one of the first large-scale, data-driven flood susceptibility assessments for Sudan using deep Convolutional Neural Network (CNN) model. Twelve conditioning factors spanning topographical, hydrological, geological, and anthropogenic parameters were systematically analyzed. The flood inventory dataset was obtained from the Humanitarian Data Exchange (HDX), comprising geospatially verified flood polygons compiled from remote sensing and field observations. A five-fold cross-validation strategy was implemented to ensure model robustness, yielding a classification accuracy of 97% and demonstrating reliable generalizability across spatial partitions. The analysis generated probability maps with susceptibility values ranging from zero to 1, delineating three discrete risk zones: High, Medium, and Low susceptibility. Results reveal that very high susceptibility zones are concentrated along immediate river corridors, the Khartoum metropolitan confluence area, and low-lying Quaternary alluvial plains in Jazirah and Sennar states, where Sudan's most critical agricultural production occurs. The susceptibility maps provide essential decision-support tools for evidence-based urban planning, agricultural management, and water resources development, enabling targeted risk reduction strategies that can protect lives, livelihoods, and development investments.

Saline-alkaline stress, particularly sodium bicarbonate-induced alkaline stress, can cause tissue damage and oxidative stress in aquatic animals, thereby inhibiting their growth and even threatening their survival. This has become a key factor limiting the utilization of saline-alkaline water resources. This study for the first time systematically established acute and chronic time-series gradient NaHCO₃ stress treatments, and integrated histological observation, ultrastructural examination, enzyme activity determination as well as transcriptomic and metabolomic profiling to reveal the adaptive response mechanism of M. rosenbergii. In this study, M. rosenbergii were selected as the research object to evaluate the physiological responses under acute (96h) and chronic (56 d) alkaline stress at NaHCO₃ concentrations of control (0.0 mmol/L), low (3.2 mmol/L, 30% LC₅₀), and high (6.4 mmol/L, 60% LC₅₀). The results indicated that during acute NaHCO₃ stress, the oxidative stress and energy metabolism-related enzyme activities fluctuated over time, reflecting adaptive response to the stress-induced damage. Chronic exposure results showed activation of a coordinated energy network-evidenced by upregulated glycolysis, accompanied by increased expression of hk2 and glut2, as well as elevated activities of HK, PFK and LDH, increased TCA intermediates (succinate, fumarate), and elevated oxidative phosphorylation metabolites, enhancing ATP production. Fatty acid metabolism exhibited a dose-dependent response: synthesis was upregulated under low stress (elevated fas, acsbgl2, and palmitic acid) likely for membrane remodeling, but suppressed under high stress. Prolonged exposure induced significant oxidative damage, evidenced by increased MDA, accumulated LysoPCs, and decreased SOD activity. Concurrently, a marked increase in autolysosomes indicated autophagy activation. Notably, these physiological disruptions were accompanied by a significant, dose-dependent decline in growth performance (FAW, WGR, SGR). These findings indicate that NaHCO₃ stress induces integrated physiological responses in M. rosenbergii, including enhanced energy metabolism, oxidative injury, and autophagic activation, providing a reference for the development and utilization of saline-alkaline water resources.

Groundwater exploration in arid regions of the Eastern Desert of Egypt requires an integrated understanding of the structural, geomorphic, and subsurface controls governing recharge and storage. This study presents a GIS-based groundwater potentiality model for a structurally complex rift-related zone along the southern Esh El Mellaha Block, between the Gulf of Suez and northern Red Sea. Sixteen topographical, meteorological, hydrological, and surface geological factors were systematically integrated with particular magnetic basement-depth modeling and subsurface fault architecture, which were weighted using the Analytical Hierarchy Process (AHP). Results demonstrate that regional tectonic configuration and structural geometry, rather than surface geomorphic factors alone, exert the primary control on groundwater distribution. High-potential zones are concentrated within major structural lows, including the Tarboul syncline, West Hurghada trough, and El Gouna fan system, where thick Quaternary deposits and enhanced infiltration prevail. The ENE-trending Bali Shear Zone acts as a key conduit for focused recharge by enhancing fracture permeability and linking the Gulf of Suez and Red Sea structural domains. Model validation yielded an AUC of 0.80, with balanced sensitivity and specificity (0.74), indicating reliable predictive performance. Single parameter sensitivity analysis confirms the robustness of the model and indicates that structural and geological factors exert the strongest control on groundwater potential distribution. The study emphasizes the role of structural architecture in groundwater assessment and supports future sustainable water-resource development in arid extensional tectonic settings.

A nonporous metal-organic material (MOM) captures water from the atmosphere under ambient conditions upon exposure to light. The water capture is achieved via a single-crystal-to-single-crystal [2 + 2] photocycloaddition. The MOM adopts an unusual condensed version of the primitive cubic (pcu) topology. The light generates isolated cavities within the crystal lattice that capture the water with overall retention of the pcu topology. The work underscores how MOMs can be advanced for controlled water capture with implications for sustainable water resource development, exemplifying how nonporous crystalline materials can be developed to capture small molecules from the atmosphere in the presence of light.

Sustainable development of regional water resources requires objective classification of lake systems according to dominant hydrochemical processes. The aim of the study was to develop a data-driven hydrochemical typology of natural lakes in Polissya based on the Self-Organizing Map (SOM) method to identify functionally distinct water quality regimes and justify management decisions within the basin approach. The study covered nine lakes of different genesis and trophic status. Key water quality indicators were analyzed: total nitrogen (TN), biochemical and chemical oxygen demand (BOD5, COD), suspended solids (TSS), iron (Fe), and total dissolved solids (TDS). Descriptive statistics, correlation analysis, and neural network SOM modeling with subsequent clustering were applied. The results revealed strong positive correlations between TN, BOD5, COD, and TSS, indicating joint control by biogenic and organic processes, while TDS showed negative correlations with organic indicators, reflecting mineralization control. SOM classification allowed us to identify three hydrochemical clusters: background systems with low anthropogenic load; organically enriched lakes with intense biogeochemical cycling; and mineralization-controlled water bodies dominated by geogenic factors. It has been established that spatial features of land use and morphometric characteristics (depth, type of feeding, hydrological connectivity) determine the sensitivity of lakes to external loads and their location.

Water resources in the mining area are an important foundation for maintaining the normal operation of mining activities and supporting the production and life of the surrounding residents， and the rational utilization and protection of water resources are of great significance to the ecological safety and sustainable development of the mining area. Surface water and groundwater in the centralized coal mining area of the Yellow River's Jizi Bend were selected as the research objects. Based on the results of hydrochemical testing of 37 sets of water samples collected in September 2023 （24 sets for groundwater and 13 sets for surface water）， mathematical statistics， Piper's trilinear diagram， Gibbs' diagram， ion ratio， mixing simulation， and PCA-APCS-MLR source analysis were utilized to investigate the chemical characteristics and controlling factors of groundwater and surface water in the centralized coal mining area of the Yellow River at several bends and to quantitatively analyze the sources of the hydrochemical components. The results showed that： the overall water environment in the study area was weakly alkaline， groundwater was dominated by freshwater， and surface water was dominated by brackish water and freshwater. Groundwater in the study area was dominated by HCO3-Ca type and HCO3-Na type， while surface water was dominated by Cl·SO4-Na and HCO3·Cl-Na type. The hydrochemical formation process of surface water and groundwater was dominated by water-rock action and cation-exchange action， in which the weathering and dissolution of silicate rocks dominated. The water chemistry of groundwater in the mixing simulation was lower than that of surface water， and the mixing had a diluting effect on the water chemistry of surface water. PCA-APCS-MLR source analysis identified three main controlling factors， namely， the dissolution-filtration-enrichment factor， primary geologic factor， and human activity factor， among which， the dissolution-filtration-enrichment factor was the first controlling factor for the formation of water chemistry. The results of the analysis can provide a scientific basis for the rational development and utilization of water resources in the mining area.

Application of hydro-economic modelling to river basin development planning and management in Nepal

FATA Water Resources Development Project (FWRDP) operates in many regions of the erstwhile FATA, including Bajaur, and one of its primary components is on-farm water management (OFWM). This study investigates how agricultural production of wheat in district Bajaur is transformed by on-farm water management practices. This study is based on household data from 120 farmers that were gathered using a pre-tested questionnaire. A binary logit model was used to identify determinants of OFWM on agricultural productivity of wheat. The study found that the age of respondents, farming experience, working members, water availability and community organization membership were statistically significant and positively related to OFWM effects on agricultural productivity of wheat. On the other side, variables such as education level, access to agriculture extension, credit and land tenancy were statistically non-significant and had an inverse effect on the agricultural productivity of wheat. The overall model was significant as shown by p<0.05 which depicts that the socio-economic characteristics of the population are the main factors contributing to the effects on OFWM on agricultural productivity of wheat crop. It is important to consider these factors when designing policies and programs aimed at improving water management practices in agriculture to promote sustainable economic development and increase crop yields.

In conflict-laden international river basins, collaborative governance has often relied on third-party involvement in conflict resolution. In recent years, increasing attention has been paid to the role of non-state actors—such as NGOs, research institutions, and private-sector actors—that differ in character from traditional international organizations. It has also been argued that such non-state actors may function as Track 1.5 diplomacy, bridging formal multilateral negotiations among state actors by facilitating dialogue and trust-building. However, empirical cases in which non-state actors have effectively played such roles remain limited. Against this backdrop, Global Infrastructure Fund Research Foundation Japan (GIF) and its support for water resource development in the eastern Himalayan region during the 1990s constitute a notable example. This study represents the first systematic attempt to document and analyze the evolution of GIF’s activities in this context. GIF engaged high-level stakeholders from India, Nepal, and Bangladesh by organizing international conferences and workshops aimed at promoting dialogue. It also facilitated the prioritization of transboundary river development projects, which had previously been pursued separately by each country. Nevertheless, amid political instability in the region—where governmental counterparts and project priorities shifted frequently—GIF faced organizational constraints inherent to non-state actors, limiting its ability to respond effectively to these changes. Furthermore, insufficient funding and a lack of engagement with local communities ultimately prevented the projects from being realized. Drawing on the GIF case, this study examines the conditions necessary for non-state actors to elicit sustained commitment from state actors in conflict-prone transboundary river basins.

Abstract The provision of water for various needs remains a top priority in Indonesia’s water resources development. To meet increasing water demands, the government has implemented several initiatives, including the construction of large-scale dams. One of the National Strategic Projects (NSP) is the Manikin Dam in East Nusa Tenggara Province. While its construction contributes significantly to water availability and regional development, it also presents several risks throughout the planning, construction, and operational phases. Each of these risks must be properly managed to ensure that potential issues can be anticipated, controlled, and mitigated effectively. At the Ministry of Public Works and Housing, Risk Management serves as the principal instrument for managing and controlling risks. Based on Ministerial Circular Letter No. 12 of 2024, risk management is defined as a coordinated activity to direct and control risks to protect organizational value. This study develops a risk profile using the Lost Event Database (LED) integrated with expert opinions to establish a practical and applicable model for identifying, analyzing, and mitigating risks during the Manikin Dam project. The integration of LED data and expert validation has been shown to increase the accuracy of risk identification and enhance mitigation effectiveness by 43% compared to conventional approaches. The findings highlight that a systematic and evidence-based risk management framework can significantly improve project performance, reduce uncertainty, and strengthen decision-making. This model also offers potential for replication in other National Strategic Projects, providing a foundation for more sustainable and accountable infrastructure development in Indonesia.

The 6 th International Conference on Water Resources Development and Environmental Protection 2025 (ICWRDEP 2025) was successfully conducted using a hybrid approach on 27-28 September 2025, at Universitas Brawijaya in Malang, East Java, Indonesia. ICWRDEP has maintained its biennial schedule, an ongoing tradition since 2015. The Water Resources Engineering Department - Faculty of Engineering - Universitas Brawijaya (Indonesia) organized the ICWRDEP 2025 in cooperation with universities across Asia Pacific, i.e. University of Auckland (New Zealand), Curtin University (Australia), King Mongkut’s University of Technology (Thailand), and the University of Tokyo (Japan). The conference topics are River Engineering and Management, Coastal Engineering and Management, Environmental Engineering and Sanitation, Water-Related Disaster Risk Reduction, Water Resources Engineering and Management, and Water-related to Civil, Architectural Engineering. Through the presentation of papers and discussion, the conference provides a platform for researchers, engineers, and academicians to meet and share ideas, achievements, and experiences. This international event is essential in promoting and encouraging practitioners to apply the new concept of water resource development and techniques and enhancing knowledge and understanding with the required specifications of analysis, design, and construction of any engineering concept. We want to convey our deepest gratitude to the Rector of Universitas Brawijaya, the Dean of Engineering Faculty, Keynote Speakers Dr. Sebrian Beselly from Universitas Brawijaya (Indonesia), Prof. Karin Bryan, PhD from University of Auckland (New Zealand), Ranjan Sarukkalige, PhD from Curtin University (Australia), Yoshinao Matsuba, PhD from the University of Tokyo (Japan), and Chaiwat Ekkawatpanit, PhD from King Mongkut’s University of Technology (Thailand), International Advisory Board members, organizing committee, and all participants. List of Committees and Documentation are available in this PDF.

Nitrate source identification and health risk assessment of surface waters in southwestern China.

This study assesses the influence of climate change on the projected water requirements (WR) for wheat cultivation in Egypt's New Delta region. Climate projections from five CMIP6 (Coupled Model Intercomparison Project Phase 6) regional climate models under three socio-economic scenarios (SSP2.6, SSP4.5, SSP8.5) were employed to estimate WR utilizing a Deep Learning Artificial Intelligence (DLAI) model. Thirteen meteorological stations throughout the New Delta were examined to evaluate drought indicators, such as the Reconnaissance Drought Index (RDI/eRDI) and the Standardized Precipitation Index (SPI/aSPI). Results indicate a consistent rise in annual RDI and eRDI across most stations, with the most pronounced trends observed in AlFrafrah and Borg Elarab. Conversely, SPI and aSPI values demonstrated declining trends, indicating increasing dryness; approximately 16 % of SPI observations corresponded to moderately dry conditions, with certain stations such as Baharia and Siwa exhibiting severe dryness. WR exhibits a consistent upward trajectory across all scenarios, attaining its peak levels by 2100 under SSP8.5. WR increases by 9–12 % under SSP2.6, 15–18 % under SSP4.5, and 24–36 % under SSP8.5. These findings indicate that climate-induced increases in WR will significantly raise irrigation requirements, highlighting the necessity for ongoing evaluation of water resource development and allocation strategies.

ABSTRACT The Great Ruaha River Catchment (GRRC) in Tanzania faces water stress from competing demands, necessitating equitable and sustainable allocation strategies. Previous analyses on water allocation often overlooked unlicensed abstractions, leading to unrealistic estimations. This study used the WEAP model for comprehensive hydrological and water allocation modelling, incorporating both licensed and unlicensed abstractions for realistic demand estimates, which includes the incorporation of future sectoral development plans. Six scenarios: Baseline (SC1), Lugoda dam construction (SC2), Madibira irrigation expansion (SC3), N’Giriama Weir construction (SC4), irrigation efficiency improvements (SC5), and combined interventions (SC6) were evaluated. Results indicate that the catchment has an unmet demand of ∼1.16 Bm3/year, representing ∼30.91% of total annual demand (∼3.75 Bm3/year). The trade-offs were observed in scenarios SC2, SC3, and SC4, where localized benefits come at the cost of downstream ecological impacts, and hydropower shortages. SC5 was found to reduce the overall unmet demand from ∼31% to ∼20%, benefiting both the RNP ecosystem and hydropower production. SC6 shows the same benefits as SC5 but with increased average dry seasonal flows in the Ruaha National Park by ∼5.12%. These findings emphasize the need for integrated water management to evaluate trade-offs, ensuring equitable allocation and addressing ecological, water quality, food, and energy sector complexities.

The detection of arsenic in shallow groundwater threatens groundwater based water supply in Bangladesh. Seawater encroachment in coastal aquifers is another major problem for the availability of fresh water. On the other hand, surface water source is not suitable in many parts of the country. In addition, vu1nerable climatic conditions and anticipated impact of climate change arc putting more stress on the sustainable development of safe water resources. Therefore, one technology is not suitable for all areas due to different hydro meteorological conditions. The aim of this paper is to determine sustainable context-specific water supply technologies considering the climatic hazard and other vu1nerabilities in 5 different hard to reach (HtR) areas, which are (a) drought prone, (b) flood prone, (c) char (sand bar), (d) coastal and (e) haor (swamp) areas. It is found from the study that more activities and effort is needed to ensure the water supply facilities for all, mainly in the HtR areas. Still expansion and improvement of the water supply services is required to satisfy the basic needs in these areas. Proper maintenance and monitoring of existing appropriate technologies arc also important for sustainable use. Guidelines and user manuals need to be prepared as a tool to standardized procedures for installation and easy maintenance of technologies.

ABSTRACT The reservoirs are long‐lived infrastructures interrelated to the well‐being of the local community. This study focuses on a comprehensive analysis of the well‐being factors of the local people surrounding the reservoirs. The study aims to find and understand the relationship of variables influencing well‐being and develop a causal loop diagram (CLD) to illustrate the complex relationship by applying correlation and regression analysis data from households. However, it is acknowledged that statistical associations alone do not imply causation. Additional validation is required to ensure that these connections reflect actual causal mechanisms rather than coincidental statistical patterns. Participation in water management and appropriate discrimination handling in obtaining water were the most correlated variables. Meanwhile, a family's net income had the highest level correlation with crime in residential areas and a confidence of livelihoods. These data were used to develop the CLD by representing the amount, level, direction and characteristic of correlations with connection line, line colour, arrowhead and the polarity symbol, respectively. The CLD serves as a decision‐making tool to understand the complex interrelation of variables and improve well‐being factors impacting sustainable water resources development projects.

ABSTRACT Water resources development and the intensification of water uses have profoundly altered water circulation in the arid river basins of southeast Morocco, leading to water reallocation and scarcity. Four case studies show how the State and farmers are adapting, often unsustainably, to the created water scarcity, including by promoting local water circularity. This paper argues that incorporating the principles of the circular economy ‘Reduce’ and ‘Replenish’ might be helpful to reconnect surface and groundwater at the explicit condition to reduce anthropogenic pressure on water resources and consider water circulation at the basin level.

Climate change and human activities are intensifying the water cycle processes, exerting a certain degree of impact on the spatiotemporal distribution characteristics of water resources, thereby increasing the uncertainty in water resource development and utilization. This has led to situations where in some regions, the degree of water resources development and utilization has approached or even exceeded the carrying capacity of water resources, creating a mismatch between the spatial layout of water resource carrying capacity and the economic and social structure. This study focuses on the Yishusi River Basin, constructing a system dynamics coupled orthogonal experimental optimization method for predicting and regulating water resources carrying capacity. By setting various scenarios combining climate change and human activities, and applying the constructed model for predicting and regulating water resources carrying capacity under climate change, the study conducted analysis on predicting and regulating water resources carrying capacity during different future development periods in the region. The results include predictions of water resources carrying capacity and regulatory measures for this basin. The results indicate that: (1) Under different scenarios, the natural runoff in the Yishusi River Basin is expected to increase in the future. (2) By 2030, 2035, and 2050, under current water supply conditions, the water quantity and quality in the Yishusi River Basin will be all in a state of overload for each climate scenario.(3) By selecting regulatory indicators and formulating control measures, the predicted results for different scenarios in the Yishusi River basin were regulated. After regulation, all scenarios are in a critically overloaded state.

Given the characteristics of water resources in Northeast Sichuan, a systematic evaluation system for water resources utilization was developed based on the water resources ecological footprint model and calculation methods. This system was applied to analyze the ecological footprint of water resources and the sustainable development capacity of Northeast Sichuan from 2013 to 2022. The results showed the following: (1) The ecological footprint of water resources in Northeast Sichuan increased by a total of 1.35 × 10 6 ha(hectare) from 2013 to 2022, with the largest per capita ecological footprint of water resources in each city being Guangyuan and the smallest being Bazhong. (2) The ecological carrying capacity of water resources in the region varies greatly from year to year, mainly affected by the total amount of water resources and the amount of precipitation in that year, with large spatial differences between districts and counties, and a general downward trend. (3) The ecological footprint of water quality shows a trend of first increasing and then continuously decreasing, indicating that the treatment rate of wastewater is continuously improving. The value of water resources’ ecological footprint of 10,000 yuan GDP (Gross Domestic Product) in each district and county basically stays around 0.10 ha, and the utilization efficiency of water resources is improving. (4) Water resource utilization and economic growth in Northeast Sichuan are in a weakly decoupled state, and economic growth is still dependent on water resource consumption, and benign development is not stable enough. In the future, attention will be paid to the ecological protection of water resources to avoid possible ecological risks and water scarcity. This will ensure the sustainable development of water resources.

Water resource monitoring can provide beneficial information supporting water management; however, present operational systems are small and provide only a subset of the information needed. Primary advancements consist of the clear explanation of water redistribution and water use from groundwater and river schemes, achieving better spatial detail and increased precision as evaluated against hydrometric observation. In such cases, Earth Observation (EO) satellite systems are persistently creating extensive data, which is now essential for applications in different fields. With readily available open-source satellite imagery, aerial remote sensing is progressively becoming a quick and efficient tool for monitoring land and water resource development actions, demonstrating time and cost savings. At present, the deep learning (DL) model will be beneficial for monitoring water resources and EO utilizing remote sensing. In this paper, a Deep Neural Network-Based Object Detection for Water Resource Monitoring and Earth Observation (DNNOD-WRMEO) model is introduced. The main intention is to develop an effective monitoring and analysis framework for water resources and Earth surface observations using aerial remote sensing images. Initially, the Wiener filter (WF) model was used for image pre-processing. For object detection, the Yolov12 method was used for identifying, locating, and classifying objects within an image, followed by the DNNOD-WRMEO methodology, which implements the ResNet-CapsNet model for the backbone feature extraction method. Finally, the temporal convolutional network (TCN) model was implemented for the classification of water resources. The comparison analysis of the DNNOD-WRMEO methodology exhibited a superior accuracy value of 98.61% compared with existing models under the AIWR dataset.