Sustainable Water Resources Research Articles

“From Waste to Wonder”: Comparative Evaluation of Chinese Cabbage Waste and Banana Peel Derived Hydrogels on Soil Water Retention Performance

Under the increasing severity of drought issues and the urgent need for the resourceful utilization of agricultural waste, this study aimed to compare the soil water retention properties of hydrogels prepared from Chinese cabbage waste (CW) and banana peel (BP) using grafting techniques with acrylic acid (AA) and acrylamide (AAm). Free radical polymerization was initiated with ammonium persulfate (APS), and N, N′-methylene bisacrylamide (MBA) served as the crosslinking agent to fabricate the grafted polymer hydrogels. The hydrogels were subjected to detailed evaluations of their water absorption, reusability, and water retention capabilities through indoor experiments. The optimal hydrogel was identified and its applicability in wheat seedling growth was assessed. The findings revealed that the CW-gel, with an equilibrium swelling ratio of 551.8 g/g in ultrapure water, demonstrated remarkable performance and sustained a high water retention of 57.6% even after drying, which was markedly superior to that of the BP-gel. The CW-gel with the best comprehensive properties significantly improved water retention in sandy soil by 78.2% and prolonged the retention time by five days, indicating its potential for long-term irrigation management. In contrast, the BP-gel showed better performance in clay soil, with an increased water-holding capacity of 43.3%. The application of a 1.5% CW-gel concentration under drought stress significantly improved wheat seedling growth, highlighting the role of hydrogels in agriculture and providing a new path for sustainable water resource management in dryland farming.

Spatiotemporal Dynamic Assessment of Water Resources Carrying Capacity and Identification of Obstacle Factors in Yunnan Province Based on Grey Water Footprint Theory

The water resources carrying capacity (WRCC) is a crucial indicator for assessing the sustainability of regional development. This study integrates the gray water footprint (GWF) into the WRCC evaluation, constructing a comprehensive framework that encompasses five subsystems: water resources, society, economy, ecology, and climate. Using the CRITIC-TOPSIS model, the WRCC of Yunnan Province from 2012 to 2022 is analyzed, and a dynamic assessment is conducted through spatiotemporal hotspot and obstacle factor coupling analyses. The results show that the comprehensive WRCC of Yunnan decreased from 0.489 in 2012 to 0.477 in 2022, displaying an overall fluctuating downward trend with uneven spatial distribution. The per capita GWF and GWF load significantly impacted the WRCC within the social and ecological subsystems, respectively, highlighting the importance of water quality in the WRCC evaluation. The results reveal differing development trends in the dynamic changes of WRCC cold- and hotspots across various regions in Yunnan. Through coupling the obstacle factors of each regional subsystem, the main challenges and key measures for sustainable water resource development in each area are identified. This study optimizes the traditional evaluation framework by addressing shortcomings in water quality considerations, enriching the WRCC assessment, and providing a more comprehensive and accurate decision-support tool for regional development.

Water footprint and virtual water trade of apples: Insights from India

India is a prominent producer and exporter of apples globally. However, apple cultivation requires significant water resources, and the water foot- print associated with apple production and trade in India has not been thor- oughly quantified. This study quantified the water footprint associated with apple production in India from 2000 to 2023, as well as the virtual water trade between 2018 and 2023. State-wise data on Indian apple production was collected and analyzed to assess the domestic water footprint, while trade data was compiled to estimate the virtual water flow associated with apple imports and exports. The results showed that the water footprint of Indian apple production averaged 2,430 million cubic meters (Mm3 ) annual- ly. This substantial footprint was primarily composed of green water (69.9%), along with blue water (23.9%) and grey water (6.2%). In terms of virtual water trade, India was a net importer with 27.8 Mm3 of virtual water embodied in apple imports from major exporters such as Turkey, Iran and Italy. This analysis underscores the considerable water footprint of Indian apple production and the nation's significant net inflow of virtual water re- sources through the apple trade. Additionally, the study highlights the im- portance of considering virtual water flow in agricultural trade policies to achieve sustainable and equitable water resource management.

Sustainability and groundwater in the context of Water-Energy-Food Nexus: a review of the literature

The sustainability of groundwater is contingent upon the Water-Energy-Food Nexus. In this context, the article aimed to analyze the state of the art in this field by using the Scopus database and the following keywords: “Sustainability”, “Nexus”, and “Groundwater”. The analysis was based on articles published over the last 79 years, from 1945 to August 2024. The results indicated that the production of articles on this topic started in 2008 and increased significantly from 2015 to 2023, with the USA having the highest number of publications. The publications encompass a multitude of disciplines, including environmental sciences, energy, engineering, social sciences, agricultural and biological sciences, earth and planetary sciences, business, management and accounting, biochemistry, genetics and molecular biology, chemical engineering, economics, econometrics, and finance. This demonstrates that the topic is inherently multidisciplinary, a conclusion supported by the variety of keywords identified. The keyword analysis yielded three clusters. The first area of focus is the nexus between climate change, agriculture (particularly crops and irrigation), energy, and sustainable water resources management. The second area of focus addresses the interrelationship between agriculture, ecosystems, food security, and the quality and availability of water resources. Moreover, the third area is related to hydrogeology and management of underground water resources. The identified gaps in the nexus include the lack of a comprehensive understanding of the nexus as a system, the absence of policy development to analyze synergies among all factors, the need for multi-sector integration, the dearth of socioeconomic impacts, the scarcity of local and specific data availability, and limited mention of the role of artificial intelligence and the Internet of Things in integrated water resource management. The identified trends highlight the convergence of climate change, agriculture, and water resource management, emphasizing food security and ecosystem protection. Technologies are becoming more energy-intensive, increasing the interdependence between water and energy. Mathematical models and machine learning are employed to predict the quality and quantity of groundwater.

Spatiotemporal Assessment of Water Quality and Quantity of the Kaptai Lake at Rangamati, Bangladesh - An Approach of Remote Sensing, Field Investigation and Laboratory Analysis

Monitoring water quality and quantity is essential for sustainable water resource management. This study investigates changes in the extent and water quality of Kaptai Lake using remote sensing, field measurements, and laboratory analysis. Analysis of Landsat TM/OLI images from 1989, 2000, 2010, and 2021 shows that the lake's water extent ranges from 380 km² (in 2010) to 435 km² (in 2021), with an average of 407.5 km². The extent of water decreased by approximately 3% from 1989 to 2010 and increased by about 5% from 2010 to 2021 due to changing rainfall patterns, dam operations, sedimentation, and land use changes. Seasonal variations in chlorophyll-a concentration and turbidity, analyzed using Sentinel 2B images from 2022 and 2023, indicate mesotrophic to eutrophic conditions and higher turbidity in post-monsoon. The study found that nutrient enrichment from untreated sewage, agricultural runoff, and algal growth affect chlorophyll-a levels, while development activities, excessive rainfall, and sedimentation influence turbidity. Linear regression analyses show strong positive correlation between field obtained and image derived values both for chlorophyll-a (R2 0.621) and turbidity (R2 0.698). Physico-chemical parameters such as pH, EC and temperature have been measured in the field and hydrochemical parameters including, cations and anions have been measured by laboratory analysis to assess the contemporary water quality status. The average values for pH, EC and temperature are 7.55, 119.85 µS/cm and 22.17 °C respectively. The cationic dominance in the studied segment of the Lake is in the order of Ca2+ > Na2+ > Mg2+>K+ > Fe2+ >Mn2+. On the other hand, the anions are in the order of HCO3- > SO42- > Cl- > NO3-. All the physico-chemical parameters of the lake water fall within the Bangladesh Drinking Water Limit (BDWL) and are not linked to chlorophyll-a and turbidity variations. The findings of this study can help mitigate the deterioration of Kaptai Lake by addressing water quality and extent issues, promoting effective and sustainable lake management strategies. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 13(1), 2024, P 121-139

Optimized Evaluations of Irrigation Profits and Balance of Irrigation Water Demand and Supply Under Climate Change

Optimizing irrigation profit is essential for enhancing agricultural productivity and ensuring sustainable water resource management, especially under the uncertainties caused by climate variability. It signifies that maximizing irrigation profits has become the primary consideration of current agricultural irrigation systems. By discussing the change in irrigation profits with irrigation fraction , which represents the proportion of irrigated farmland per unit area of cultivated land, a new method of qualitative diagnosis of irrigation supply and demand balance was proposed by means of the optimal irrigation fraction corresponding to the objective function and the correlation coefficient between irrigation water demand anomalies and irrigation water withdrawal anomalies (). It will serve as a new attempt to optimize irrigation profits. We argue that the optimal objective function represents the state of equilibrium of irrigation supply and demand. This study proposes a reverse optimization idea, which includes two comparison methods, to estimate the comprehensively optimal irrigation fraction that maximizes irrigation profits and irrigation profit per unit area while minimizing risks associated with climatic anomalies. By demonstrating that performs exceptionally well in meeting the objectives of maximizing irrigation profits and minimizing risks across various climatic scenarios, we suggest a robust method for optimizing irrigation profits, which simply calculates because is the function of . Since could capture the optimal solution to the greatest extent. It can serve as a simple and effective solution to determine the optimal objective function and diagnose the state of balance between irrigation water demand and supply. This method offers practical implications for water resource management and agricultural planning in the face of climate change.

Groundwater potential zones delineation in Oued Zdin basin using GIS, RS and hierarchical analysis process

Water scarcity poses a significant challenge, particularly in regions with limited rainfall such as Algeria, where groundwater plays a crucial role in supporting both daily life and economic activities. This research aims to evaluate the groundwater potential in the Oued Zdin basin in northern Algeria by utilizing advanced geomatics methods, particularly the Analytic Hierarchy Process (AHP). Through the integration of Remote Sensing (RS) and Geographic Information Systems (GIS), the study incorporates multiple datasets, including rainfall patterns, topography, geology, drainage networks, land use, and hydrological data to assess areas with high groundwater potential. By applying AHP, the study assigns relative importance to these factors, creating a groundwater potential map that classifies the region into very high, high, low, and poor potential zones. The results indicate that 7% of the basin has very high potential for groundwater recharge, 33% has high potential, while 56% is categorized as low potential, and 4% falls under poor potential. The accuracy of the results is validated through comparison with existing well data, which aligns with the identified high-potential zones. The research demonstrates that combining GIS, RS, and AHP is an effective approach for mapping groundwater potential, offering valuable insights for sustainable water resource management in areas experiencing water scarcity. This methodology presents a scalable model that can be applied to similar regions facing groundwater challenges.

Evaluating Students’ Literacy on Safe Pesticide Use and Sustainable Resource Management: A Case Study in Alentejo, Portugal

The intensive use of pesticides contaminates soil and water, raising the risk of diseases like cancer and hormonal/neurological disorders. The continuous exposure to pesticides through water and food is concerning. Therefore, raising awareness about biological pest control is essential to reduce the harmful impact of pesticides on food and the environment. This study evaluates students’ literacy on pesticide use and its implications, focusing on three topics, pesticide use, disease prevention, and sustainability and health promotion. Thus, a questionnaire was drawn up and distributed to students of both genders, aged between 12 and 16 years old, from Alentejo (Portugal). The students were asked to indicate their agreement grade with statements related to key themes, such as pesticide use and consumer attitudes, healthy practices and disease prevention, and sustainability and health promotion. The cohort includes 1051 students, and the results suggest that environmental education and student awareness are crucial for promoting sustainable water resources and minimizing exposure to environmental and food pesticides. This study presents an Artificial Neural Network model, with its accuracy surpassing 90%, to assess students’ literacy on pesticide use and its implications. It also proposes a new approach to evaluate their potential for improvement, which is essential for developing educational strategies on health and the environmental impacts.

Use of the SWAT Model to Simulate the Hydrological Response to LULC in a Binational Basin between Ecuador and Peru

Land use change has played a crucial role in altering the hydrological behavior, making detailed assessments essential to ensure sustainable water resource management and the conservation of natural ecosystems. This study focuses on simulating the impact of different Land Use and Land Cover (LULC) scenarios for the years 1985, 1995, 2005, and 2015 on the water balance in the Puyango-Tumbes River basin, which spans across Ecuador and Peru, during the period 1981-2015. The results indicated an 18.3% increase in the grassland areas and a significant 38.2% reduction in the savanna zones, contributing to an annual 2.1% increase in the Evapotranspiration (PET) rates. These land use changes led to a 29.2% decrease in the Percolation (PERC), a 20.7% decrease in the Surface Runoff (SURQ), a 33% reduction in the Groundwater Flow (GW_Q), and a 26.6% decrease in the Annual Water Yield (WYLD), as well as a slight reduction of 0.9% in the Lateral flow (LAT_Q). These findings highlight the importance of considering land use changes to ascertain the sustainable management of natural resources, particularly in a transboundary basin.

Economic irrigation water productivity of wheat and potato: An earth observation perspective on policy implications in the Litani Basin, Lebanon

Efficient water management is critical in addressing the challenges posed by water scarcity and resource sustainability in agriculture. However, the utilization of remote sensing technology to monitor and enhance water productivity in data-scarce environments remains an open question. This study underscores the importance of integrating earth observation systems into agricultural water management policies, elucidating their potential to shape crucial policy decisions and investment strategies, particularly in regions facing data limitations. To address this issue, we provide a comprehensive framework that blends remote sensing data with field-based economic information, to develop the concept of economic productivity of irrigation water. Leveraging FAO’s Water Productivity Open-access portal (WaPOR) data, we spatially assess yields, water use, crop water productivity, economic water productivity, and economic irrigation water productivity (EIWP) for wheat and potatoes in the Upper Litani Basin of Lebanon's Bekaa Valley. Early season potatoes outperform irrigated wheat significantly, providing up to ten times higher returns on irrigation water ($6/m3 vs. $0.6/m3). Spatial analysis shows that southern areas have 30 % lower potato EIWP than northern areas of the valley but 55 % higher wheat EIWP, mainly due to higher rainfall. Our findings reveal that merely considering crop water productivity is insufficient when deciding what to plant, as it fails to account for profitability. While transitioning to crops or practices with greater EIWP can enhance economic productivity on the short-term, it may simultaneously lead to increased water consumption. As a result, the shift towards highly water-productive systems may require measures such as controlling irrigated areas or implementing restrictions on water withdrawals to maintain stable water consumption levels. This study offers valuable insights for water resource management, agricultural policy, and sustainable water utilization, especially in semi-arid regions like the Litani Basin, providing a foundation for informed decision-making in these resource-constrained environments.

Groundwater Potential Mapping Using Random Forest and Extreme Gradient Boosting Algorithms

Abstract The availability of groundwater is a crucial solution to ensure the sustainability of water resources, including providing clean water. Therefore, efforts to map groundwater potential are required to enhance the efficiency of groundwater utilization and support achieving one of the Sustainable Development Goals (SDGs), particularly clean water and sanitation. This research aims to identify the distribution of the groundwater potential in Kediri Regency using the random forest (RF) and extreme gradient boosting (XGB) algorithms. This research utilizes 13 parameters, including elevation, slope, aspect, drainage density, river density, distance from rivers, lineament density, Topographic Wetness Index (TWI), Normalized Difference Vegetation Index (NDVI), land cover, soil type, lithology, and band 3 from Sentinel-2A satellite imagery. The coordinates of groundwater wells are used as training and testing data with ratios of 80:20, 70:30, and 60:40. Through the evaluation of each model’s performance using a confusion matrix, it is revealed that the best model is the RF 70:30 ratio model with Accuracy (Acc), Specificity (Spe), Sensitivity (Sen), Positive Predictive Value (PPV) values of 0.978, Cohen’s Kappa (CK) and Matthew’s Correlation Coefficient (MCC) of 0.956, and Area Under Curve (AUC) of 0.994. In this model, the elevation has the highest influence on the model, with a significance level equal to 100.

Contribution to the sustainable management of water and soil resources in North-West Benin: characterization of the watershed heads of the Ouémé and Pendjari rivers in the commune of Copargo

Watershed heads, which are the upstream areas where rivers originate, are crucial zones for water resource management. Defined by first- and second-order streams according to Strahler’s classification, watershed heads are often overlooked in water resource planning due to limited information and knowledge about these areas. This oversight leads to anthropogenic pressures and negative impacts on water quality, soils, and biodiversity. The objective of the present study is to characterize the watershed heads of the Ouémé and Pendjari rivers within the Copargo municipality, with the aim of improving understanding of sustainable water and soil resource management in this region. For this purpose, mapping techniques and geographic information systems were employed to identify and delineate the watershed heads. Criteria related to morphometry, land use, and land cover were utilized to characterize the areas of the watershed heads. Exploratory and principal component analyses based on various characteristics of the watershed heads were conducted using the R software, which highlighted the different challenges associated with these areas. The study delineated 25 watershed heads: 14 in the Pendjari watershed and 11 in the Ouémé watershed, revealing their surface area and occupancy within the respective watersheds. The average unit area of the watershed heads is 23.6 km² in the Ouémé watershed and 21 km² in the Pendjari watershed. Across all watershed heads, the Gravelius compactness index ranges from 1.2 to 1.5, while slopes vary from 1.5% to 4.5%. Most watershed heads in Copargo are characterized by high proportions of agricultural land, moderate forest cover, and low levels of urbanized area. The high proportion of agricultural land has significant implications for water and soil resources. The results of this study provide valuable data for decision-makers and reveal the vulnerability of watershed heads to anthropogenic pressures. With a view to assessing the impact of anthropogenic pressure on the water resources of the study area, it would be beneficial in the future to proceed with the physicochemical and bacteriological characterization of these resources.

Identifying TSM dynamics in arid inland lakes combining satellite imagery and wind speed

The Chah Nimeh Reservoirs (CNRs), located in Iran’s Sistan region, are critical arid inland lakes that support agriculture and supply drinking water to the region. A major concern regarding water quality in these reservoirs is the concentration of Total Suspended Matter (TSM), which has significant implications for both the local communities and the aquatic ecosystem. This study demonstrates the complicated connection between wind speed and TSM values, indicating that wind speed is an essential variable influencing TSM concentrations. By combining in-situ wind measurements with satellite imagery, we mapped TSM distributions using empirically derived models. Our investigation identified the Long Short-Term Memory (LSTM) and Attention-Mechanism-Based Dynamic Inner Partial Least Squares Long Short-Term Memory (ADiPLS-LSTM) models as effective predictors of TSM levels. Specifically, two distinct machine learning models were utilized: Rrs2TSM, which relies solely on Remote Sensing Reflectance (Rrs(λ)), and the more advanced Rrs&Wind2TSM, which incorporates both Rrs(λ) and wind data. The ADiPLS-LSTM model generated results with minimal variance, showing exceptional consistency. The Root Mean Square Error (RMSE) remains low at 0.617, while the R2 value maintained continually elevated at 0.997. It’s interesting to note that modest variations in TSM concentrations occurred when wind speed data was incorporated into the algorithm, especially during times of greater wind speeds. This study emphasizes the significant impact of wind speed on TSM dynamics in arid inland lakes, showcasing the value of satellite imagery in conducting such analyses. The findings provide essential insights for developing strategies that promote sustainable water resource management.

A novel comprehensive approach to soil and water conservation: integrating morphometric analysis, WSA, PCA, and CoDA-PCA in the Naama sub-basins case study, Southwest of Algeria.

This research paper presents a detailed investigation into the morphometric characteristics of sub-basins within the Naama region of Algeria, aiming to prioritize areas vulnerable to soil erosion and runoff risks. Focusing on five key sub-basins that collectively represent 75% of the Wilaya of Naama, the study employs a comprehensive methodological framework, integrating morphometric analysis (MA), weighted sum analysis (WSA), principal component analysis (PCA), and the novel approach of compositional data analysis (CoDA). Through the rigorous evaluation of sixteen distinct morphometric parameters selected based on their relevance to hydrological and geomorphological processes that influence erosion and runoff, this research provides a nuanced understanding of the factors influencing erosion susceptibility within each sub-basin. The analysis reveals a clear hierarchy of sub-basins based on their calculated compound parameters, effectively classifying them into high, moderate, and low priority categories for targeted intervention and resource allocation. The results highlight the Ain Sefra and Wadi Er Rosafa sub-basins as the highest priority areas, collectively encompassing 31.51% of the wilaya and posing the most significant threats of runoff and soil erosion. This identification allows for the prioritization of conservation efforts and the implementation of tailored management strategies in these critical areas. Furthermore, the integration of multiple prioritization approaches, including the innovative application of CoDA, ensures a robust and comprehensive assessment of the sub-basin landscapes. This multi-faceted approach provides a more nuanced understanding of the complex interplay between various morphometric parameters and their influence on erosion and runoff potential. The findings of this research have significant implications for sustainable land and water resource management within the Naama region. By identifying and prioritizing vulnerable sub-basins, the study provides a crucial foundation for informed decision-making, enabling stakeholders to implement targeted interventions and mitigate the detrimental impacts of soil erosion and excessive runoff. Moreover, the methodological framework presented in this research paper offers a valuable blueprint for similar studies in other regions facing comparable challenges. The cost-effective and time-efficient nature of the approach makes it a practical tool for prioritizing erosion and runoff risks in arid and semi-arid environments worldwide, contributing to the broader goals of environmental sustainability and land degradation neutrality.

Can 3D-printed flow electrode gaskets replace CNC-milled graphite current collectors in flow capacitive deionization?

As billions of people suffer from water scarcity, finding sustainable water resources is imperative. Flow capacitive deionization (FCDI) is a highly promising desalination process that can produce clean water from saline streams such as brackish and seawater. Conventional FCDI systems employ Computerised Numerical Control (CNC)-milled graphite plates that serve as current collectors and flow electrode channels. However, they have drawbacks such as high manufacturing costs, waste generation, and the difficulty of producing complex geometries required for efficient flow electrode mixing. Here, we successfully demonstrate that 3D-printed flow electrode gaskets, made of non-conductive polyethylene terephthalate glycol (PET-G) or a carbon black-infused conductive polylactic acid (PLA), are viable alternatives to traditional graphite plates. In specific cases, the desalination and energy efficiency in FCDI cells with 3D-printed conductive gaskets were even 25 % and 10 % higher, respectively, compared to traditional CNC-milled current collectors. The transition to 3D printing offers notable benefits, such as the competence to fabricate complex designs that enhance internal mixing and charge percolation. This innovation represents a change of paradigm in the way FCDI cells should be designed and manufactured, using additive manufacturing, which represents an efficient, scalable, and cost-effective substitute for the conventional approach, contributing therefore for the advancement of FCDI desalination technology.

Morphometric analysis and environmental planning: an educational approach in science and mathematics for understanding geomorphological processes in the Água das Araras watershed, Cornélio Procópio and Santa Mariana, Paraná, Brazil

The article develops a detailed morphometric analysis of the Água das Araras Stream Watershed, located in the regions of Cornélio Procópio and Santa Mariana, Paraná. The investigation focuses on the geomorphological characterization and the dynamics of processes shaping the basin's relief and drainage network. Using quantitative methods such as areal, linear, hypsometric, and fluvial planning analysis, the research aims to clarify the structural factors and environmental conditions shaping the basin.The study seeks not only to identify the natural potential and aspects of environmental vulnerability but also to suggest management actions that enable more effective and sustainable territorial planning. This work presents an important resource for future disciplines in favor of water resource preservation, besides strengthening interdisciplinary understanding of geomorphological processes and their relevance for sustainable development. Additionally, it highlights the application of these concepts in environmental education, especially in the teaching of Geography, Science, and Mathematics. Moreover, morphometric analysis proves to be a powerful tool for interdisciplinary teaching in Geography, Sciences, and Mathematics, promoting a practical understanding of natural processes and their impacts. The study concludes by emphasizing the relevance of the basin for environmental education and the necessity of conservation policies to ensure the sustainability of local water resources. The study also highlights the need for preservation policies and the importance of the watershed as an educational resource to foster environmental awareness.

An Integrated Model for Pollution Prevention, Ecological Integration and Sustainability of Surface Water: Case of Awetu River, Jimma City, South-Western Ethiopia

There are complex relationships among water quality, ecological integration and sustainability of surface water resource. Several factors are interacting in these three things, making them complex for understanding and managing, while the integration of these three is very important for sustainable development, environmental sustainability and public health. To increase the understanding of this complex relationship, appropriate tool is needed. Modeling is considered as an appropriate tool to simplify the understanding of this concept. The objective of this study is developing an integrated conceptual model for pollution prevention, ecological integration and sustainability of Awetu River basin. To develop this model, a preliminary study was conducted in the study area, which includes water quality status, its ecological condition, settlement in the river area, identifying pollution sources, and an on-going project in the river basin. Based on this information, and general environmental scientific knowledge, a conceptual model was developed. This conceptual modeling was passed through the four broad steps; each step involved several key activities that support developing an integrated model. Three correlated sub-models were developed first; finally, one integrated conceptual model was developed. Developing and application of an integrated model for Awetu river basin is very important to improve the current situation of the river. Achieving this needs an integrated work of all stakeholders and concerned bodies. Stakeholders recommended applying this model, whereas researchers recommended evaluation and modifying the model more. The model is also applicable for most rivers and surface water, particularly for waters with similar situations.

Socio-hydrological lock-in; an emergent phenomenon in the face of anthropogenic drought

This study investigates the drought of three major terminal lakes: Great Salt Lake, Salton Sea, and Lake Urmia, driven by socio-hydrological lock-in—a phenomenon characterized by feedback loops between human activities and environmental processes. Previous research has linked this drying to socio-hydrological lock-in, where rational actions by individuals collectively lead to suboptimal outcomes, exacerbating water scarcity and ecological degradation. Despite existing studies, a critical knowledge gap remains in understanding how these feedback mechanisms operate across different socio-economic and ecological contexts. This research seeks to address this gap through an integrative analysis of historical data and case studies, highlighting the interplay between increased water demand for agriculture, population growth, and governance challenges. The resultant shrinkage of these lakes exposes saline playas, generating salt-rich dust with severe ecological and health impacts, including soil salinization and respiratory illnesses. By comparing the socio-hydrological lock-in across diverse regions, this study provides insights into preventing and mitigating these cycles. It emphasizes the necessity for holistic water management strategies that integrate both supply and demand-side measures. The key contribution of this research lies in its systematic exploration of the feedback mechanisms driving socio-hydrological lock-ins, offering a foundation for developing sustainable water resource management policies globally. This work aims to influence policy and practice by highlighting the need for integrated, long-term strategies that balance economic pursuits with environmental sustainability, ensuring resilience in water management amidst mounting environmental challenges.

Climate shapes baseflows, influencing drought severity

Abstract Baseflow, the sustained flow from groundwater, lakes, and snowmelt, is essential for maintaining surface water flow, particularly during droughts. Amid rising global water demands and climate change impacts, understanding baseflow dynamics is crucial for water resource management. This study offers new insights by assessing baseflow controls at finer temporal scales and examining their relationship with hydrological drought flows. We investigate how climatic factors influence seasonal baseflow in 7138 global catchments across five major climate regions. Our analysis identifies precipitation as the primary driver, affecting 58.3% of catchments, though its impact varies significantly across different climates. In temperate regions, precipitation dominates (61.9% of catchments), while in tropical regions, evaporative demand is the leading factor (47.3%). Snow fraction is particularly crucial in both snow-dominated (20.8%) and polar regions (48.5%). Negative baseflow trends generally emerge where the effects of evaporative demand or snow fraction outweigh those of precipitation. Specifically, in northern regions and the Rocky Mountains, where snow fraction predominantly controls baseflow changes, a negative trend is evident. Similarly, in tropical catchments, where evaporative demand drives baseflow changes, this also leads to a negative trend. Additionally, our findings indicate that baseflow changes are closely linked to hydrologic drought severity, with concurrent trends observed in 69% of catchments. These findings highlight the relationship between baseflow changes, the severity of hydrologic drought and shifts in precipitation, evaporative demand, and snow dynamics. This study provides crucial insights for sustainable water resource planning and climate change adaptation, emphasizing the importance of managing groundwater-fed river flows to mitigate drought impacts.

A mindset toward greening the blue economy: Analyzing social environmental awareness of aquatic ecosystem protection

To help address global water pollution challenges, this article explores the interconnections between public awareness, education, social engagement, and knowledge transfer in promoting sustainable water resource management. The socialization, externalization, combination, and internalization (SECI) model and the transtheoretical model of change (TMC) are used to examine how education and awareness can influence citizens' behavior. The article also assesses the contribution of the entrepreneurial sector to aquatic biodiversity conservation and pollution reduction. The analysis is based on Kruskal-Wallis and Mann-Whitney U tests, as well as several machine learning regression and classification algorithms. This analysis sheds light on the complex relationships between awareness, education, engagement, and knowledge transfer. A key aspect of this study is the analysis of demographic data. This analysis reveals varying perceptions and levels of engagement with aquatic ecosystem protection across different demographic groups. The results indicate variations by age, gender, occupation, and education level, highlighting the importance of tailored educational and social engagement strategies. Additionally, the results underscore the pivotal role of entrepreneurs in developing and implementing innovative, sustainable solutions. This research reveals the need for integrated strategies that combine educational and entrepreneurial efforts to ensure more efficient and responsible management and thus protect aquatic ecosystems while reducing pollution.