Supply Of Water Resources Research Articles

Transformative change of Jordan’s water system: reconfiguring competitive water users into mutual service providers

ABSTRACT By 2050 and without fundamental policy change, demand for freshwater will exceed renewable supply by a factor of four in Jordan. A water-allocation game was designed to let stakeholders reallocate water and attempt to close the gap between demand and renewable supply, making use of supply augmentation and reutilization options that were defined with stakeholders. Stakeholders who played the game grasped that agriculture will have to completely shift to wastewater reuse in order to preserve precious freshwater resources for the drinking water supply. This paper reflects on the transformation needed to turn competing water users into mutual service providers.

Environmental Risk Study of the Yuanjiang-Lishui River Basin in the Enshi Area

Abstract. The Yuanjiang-Lishui River Basin in the Enshi Prefecture is located in the southwestern part of Hubei Province, China. It is an important tributary of the Qingjiang River Basin and falls within the secondary region of the Qingjiang River Basin. The total area of this basin is approximately 5,320 square kilometers, with most of the region falling under the administrative jurisdiction of Enshi Prefecture. This paper investigates the environmental risks faced by the Yuanjiang-Lishui River Basin in Enshi Prefecture, conducting an in-depth study and discussion of the existing environmental issues in the region and their causes. The study reveals that the Enshi area of the Yuanjiang-Lishui River Basin currently faces significant environmental problems, including severe flood disasters, an increasingly acute conflict between the supply and demand of water resources, and water pollution.

Agricultural Water Conservation Methods: Application, Difficulties, and Innovation

The largest growth in water usage among water-using industries has been in agriculture due to the growing need for agricultural goods to feed the world's expanding population. Presently, agricultural water conservation encompasses a range of technologies that are mostly grounded in human understanding, but also include a number of complex strategies that significantly rely on cutting-edge mechanical and electrical techniques. Modern agronomic practices like precision agriculture may conserve water. Precision agriculture is a modern agronomic strategy that may preserve water.Modern agricultural investments, land transfers, and urbanisation have left these irregular and traditionally built villages with an ambiguous and ever-changing land use pattern. This may hinder water-saving adoption. In addition to taking into account the growth of the agricultural sector, the agricultural water management policy prioritises the long-term ecological economy and the sustainability of the water resource supply network. Water needs are predicted to rise significantly by the end of the twenty-first century, particularly for irrigation. Reducing the amount of water used in agriculture is crucial. With temperatures rising and droughts occurring more frequently in many nations, water is a vital component of agricultural output. Certain technology-based practices coupled with efficient farmers and humans management of water resources will be the key features for improving water conservation.

Assessment of catchment water resources allocation under climate change in Luwombwa sub-catchment, Zambia

The uncertainty in climate change and high water demand pose pressure on the natural water resources supply. Not only does this require better understanding but also a call for immediate interventions, mitigation and adaptive measures. This study evaluates catchment water resources in the Luwombwa sub-catchment in Zambia through statistical analysis in the downscaling of past, present and future climatic variables from the CMIP6 climatic model. These variables are then integrated into WEAP - a semi-distributed hydrological and water evaluation model - to perform water demand and allocation scenario modelling. Mult-site calibration and validation were conducted on five selected micro-catchments within Luwombwa sub-catchment. The model performance was assessed usng the R2, NSE and PBIAS as the objective functions. Satisfactory values of 92 % for R2, 82 % for NSE and 6.9 % for PBIAS were achieved. This allowed for scenario modelling on water demand and allocation among competing users. Three future scenarios (2022–2050) were developed from the historical to baseline (1988–2022) and included state of water resources availability under climate change, expansion of irrigation area and impact of dam construction in the sub-catchment. The study reveals a decrease of 20 % in sub-catchment's water availability resulting from 9.3 % (equivalent to 4oC) rise in maximum temperature and 4.5 % reduction in rainfall within the entire sub-catchment. This is especially under the persistence of SSP370 climate variability scenario projections downscaled from four GCM models by the year 2050. The study further revealed that the change point for anticipated future climate extremes is likely to occur between 2027 and 2030. The results are indicative of downward trends in streamflow under climate change and socioeconomic development leading to increase in water value and water scarcity. The insights from the study are critical to inform formulation of effective catchment water resources management strategies such as the development of management plans and adapation measures in the face of climate change and the needs for different stakeholders involvement.

Crafting Combinations to Govern Groundwater: Knowledge, Motivation, and Agency

Groundwater is a vital common pool resource for water supply, irrigation, and ecosystems, but can be difficult to govern due to invisibility, conflicting interests, and limitations of available institutions. While there are many policy and technical instruments (tools) available, efforts to apply them are often ineffective. This special issue of the International Journal of the Commons presents a set of papers with insights into policy instruments and other methods for groundwater governance. The relevance and effectiveness of tools and combinations of tools (toolboxes) in addressing problems that emerge from groundwater use is related to how they fit with diverse physical and social contexts. Drawing on research and applied experience, including that presented in this issue, we outline a conceptual framework for groundwater governance that emphasizes attention not just to knowledge, but also to motivations, and to agency for effective coordination among key actors. Articles in the special issue analyze groundwater governance in areas of Africa (east, south, and north), Central Asia, India, and the United States. The articles cover a range of scales from small groups playing experiential games to international agreements about transboundary aquifers. Several papers illustrate the crucial role of knowledge about groundwater, and the need for governance instruments and interventions to go beyond only changing knowledge. Three papers focus on groundwater games and their use to understand and change behavior, especially when combined with other tools that facilitate collective deliberation and action. Several papers illustrate how understanding of the ways people care about and practice care for groundwater illuminates examples and capabilities for groundwater governance. Highlights There are many institutional tools for governing groundwater, but no panaceas, and successes are rare Effective groundwater governance requires that key stakeholders have combinations of knowledge, motivation, and agency to act together effectively Groundwater co-management can combine stakeholders’ knowledge, values, and collective action with external science, resources, and authority Participatory processes can craft combinations of tools to fit contexts and pursue shared gains

Specifics of the Availability of Water Resources for Agricultural Water Supply under Changing Climate Conditions in the Ural River Basin

Specifics of the Availability of Water Resources for Agricultural Water Supply under Changing Climate Conditions in the Ural River Basin

Attribution of hydrological droughts in large river-connected lakes: Insights from an explainable machine learning model

Large lakes play an important role in water resource supply, regional climate regulation, and ecosystem support, but they face threats from frequent extreme drought events, necessitating an understanding of the mechanisms behind these events. In this study, we developed an explainable machine learning (ML) model that combines the Bayesian optimized (BO) long short-term memory (LSTM) model and the integrated gradients (IG) interpretation method to simulate and explain lake water level variations. In addition, the hydrological drought trends and extreme drought events in Poyang Lake from 1960 to 2022 were identified using the standardized water level index (SWI) and run theory. The analysis revealed that the frequency of hydrological droughts in Poyang Lake increased from 1960 to 2022, especially in the autumn after 2003. By selecting the flows of the catchment and the Yangtze River as the input features, the BO-LSTM model accurately predicted the water level of Poyang Lake. The IG method was then used to interpret the prediction results from three aspects: the importance ranking of the input features, their roles in the seasonal drought trends, and their roles in extreme drought events. The results indicate that (1) the most influential factor affecting the water level of Poyang Lake was the inflow of the Ganjiang River in the catchment. (2) The increase in the lake outflow caused by the Yangtze River's draining effect was the reason for the intensification of the autumn drought in Poyang Lake. (3) The extreme hydrological drought events were primarily caused by low catchment inflows. Overall, this research provides a new approach that balances prediction accuracy with interpretability for predicting and understanding the hydrological processes in large river-connected lakes. Moreover, this method was also applied to the attribution analysis of hydrological drought in Poyang Lake, providing theoretical support for regional water resource management.

Improved Variable Scale Optimisation Algorithm in Water Saving Landscape Design and Its Application

Abstract With the acceleration of urbanisation, the problem of water resource shortage is becoming increasingly serious. Currently, the water use situation in Chinese cities is severe and the contradiction between the supply and demand of water resources is prominent, which has become one of the main factors restricting sustainable development of cities. Traditional research on water-saving landscape design focuses mainly on the analysis of the efficiency of water resource utilisation within a single area or city. The scope of the research is limited and the research methods are individual, which cannot fully meet the current needs of sustainable urban water-saving landscape design. The improved variable scale optimisation algorithm has become an indispensable tool in modern landscape design and would play a more important role in landscape design and ecological environment protection in the future. In response to the shortcomings of traditional variable-scale optimisation algorithms in solving the optimisation problem of water-saving landscape design for ecological sustainable development, this article would use an improved variable-scale optimisation algorithm to study the water-saving landscape design for ecological sustainable development in Community X, City B, Province A. The research results indicated that there were three experts who rated the effect of the water saving landscape design of the first group of designers as good or above, accounting for 37.5 %. The number of people who rated the effectiveness of water-saving landscape design in the second group as good or higher was 8, representing 100 %. The improved variable-scale optimisation algorithm could effectively improve the application of water-saving landscape design in ecological sustainable development.

A dataset of monthly potential evapotranspiration at ecological stations in arid central Asia from 2005 to 2020

The potential evapotranspiration represents the atmospheric evaporation capacity, which is an important indicator to measure the regional evaporation capacity, and also a key parameter to evaluate drought degree, the balance between supply and demand of water resources, and the water consumption of vegetation. Based on the meteorological data collected by 12 ecological field stations of Central Asia Ecosystem Monitoring Network and 11 ecological field stations of China Ecosystem Research Network in the arid region of Northwest China, and by using Penman-Monteith method recommended by FAO, the potential evapotranspiration was calculated from 2005 to 2020. This dataset has a long time series and covers a variety of ecosystem types. It can be used as basic data, model input data, simulation result verification data for drought research in Central Asia, and also provide data support for the research on the rational development and utilization of water resources, ecological environmental protection and other aspects in this region.

A Study on the Determination and Spatial Flow of Multi-Scale Watershed Water Resource Supply and Benefit Areas

Based on the principle of water supply and demand flow and the natural flow of water, this paper analyzes the flow direction and discharge of water resources in the study area. In order to provide scientific and systematic implementation suggestions for regional water resource protection management and ecological compensation, a SWAT (Soil and Water Assessment Tool) model was constructed to quantify the water resource supply of the upper Hanjiang River basin at three spatial scales: pixel, sub-basin, and administrative unit. The water demand at the three spatial scales was calculated using the LUCC (Land Use and Land Coverage) and water consumption index. The supply and benefit zones under different spatial and temporal scales were obtained. Simultaneously, this study uncovered the spatiotemporal dynamics inherent in water resource supply and demand, alongside elucidating the spatial extent and flow attributes of water supply. The ecological compensation scheme of water resource supply–demand was preliminarily determined. The findings indicate an initial increase followed by a decrease in both the water supply and demand in the upper reaches of the Han River, accompanied by spatial disparities in the water supply distribution. The direction of the water supply generally flows from branch to main stream. The final ecological compensation scheme should be combined with natural conditions and economic development to determine a reasonable financial compensation system.

Real-time water quality monitoring using AI-enabled sensors: Detection of contaminants and UV disinfection analysis in smart urban water systems

This study introduces a novel method for assessing water quality, employing a cutting-edge sensor system integrated with artificial intelligence (AI) technologies. Addressing the global challenge of water scarcity and pollution, the research focuses on the innovative use of spectroscopic analysis for real-time water quality monitoring. The study evaluates the effectiveness of this system in distinguishing between clean, contaminated, and UV-disinfected water samples, highlighting its precision in detecting variations in water quality. Central to the research is the deployment of advanced machine learning algorithms, including Random Forest, Support Vector Machines (SVM), and Neural Networks, to process and classify spectral data. These models demonstrate remarkable accuracy in real-time classification, underscoring the synergy between AI and environmental science in addressing critical public health issues. Significantly, the study showcases the potential of UV disinfection in water treatment, as evidenced by the spectral changes observed in disinfected water samples. This aspect of the research emphasizes the role of spectral analysis in verifying the efficacy of water treatment processes. Overall, this study paves the way for more sophisticated and accessible water quality monitoring systems, offering a promising solution to one of the most pressing environmental challenges. The integration of AI and spectral analysis in this research offers a breakthrough in ensuring a safe water supply and effective water resource management. This study utilizes advanced machine learning algorithms, including Random Forest, Support Vector Machines (SVM), and Neural Networks, for water quality assessment. These models process and classify spectral data with high precision, highlighting variations in water quality.

The Isolation and Identification of Novel Arsenic-Resistant Bacteria from an Arsenic-Contaminated Region—A Study to Understand the Efficiency of Bacteria for Arsenic Removal from Aqueous Media

Drinking water sources with groundwater arsenic (As) contamination face multifaceted challenges in the removal and supply of fresh drinking water resources. To eradicate this problem, bioremediation has evolved to become more effective than other chemical and physical removal processes in its cost-effectiveness, high removal efficiency, and lesser production of secondary by-products or waste. Thus, this study aimed to treat As from aqueous media and to detoxify highly toxic forms of As by the isolated bacteria from As-affected areas. We isolated two new Gram-positive bacteria, which are reported here (Bacillus sp. and Bacillus cereus), with As5+ minimum inhibitory concentrations (MICs) of 4500 mg/L for the Bacillus sp. and 1000 mg/L for Bacillus cereus; meanwhile, for As3+, the MICs are 600 mg/L for both isolates. Bacillus sp. and Bacillus cereus can also effectively convert the highly toxic and easily mobile As3+ to As5+ in aqueous media. This study also demonstrates that these bacteria can remove a significant proportion of As3+ and As5+ (averaging 50% for both) from aqueous media. These As-resistant bacteria from the As-affected area can be used and upscaled for the treatment of As for a safer drinking water supply.

Trade-Off and Synergy Mechanism of Agricultural Water Resource Spatial Allocation in Monsoon Climate Areas Based on Machine Learning: A Case Study of Reservoir Layout Optimization in Shandong Province, China

Influenced by increasing global extreme weather and the uneven spatiotemporal distribution of water resources in monsoon climate areas, the balance of agricultural water resources supply and demand currently faces significant challenges. Conducting research on the spatial allocation trade-offs and synergistic mechanisms of agricultural water resources in monsoon climate areas is extremely important. This study takes the spatial layout of reservoir site selection in water conservancy projects as an example, focusing on Shandong Province as the research area. During the site selection process, the concept of water resource demand is introduced, and the suitability of reservoir siting is integrated. It clarifies ten influencing factors for suitability degree and five influencing factors for demand. A bi-objective optimization model that includes suitability degree and demand degree is established. Utilizing machine learning methods such as the GA_BP neural network model and the GA-bi-objective optimization model to balance and coordinate the supply and demand relationship of agricultural water resources in the monsoon region. The study found that: (1) in the prediction of suitability degree, the influencing factors are most strongly correlated with the regulatory storage capacity (regulatory storage capacity > total storage capacity > regulating storage coefficient); (2) compared with single-objective optimization of suitability degree, the difference between water supply and demand can be reduced by 74.3% after bi-objective optimization; (3) according to the spatial layout optimization analysis, the utilization of water resources in the central and western parts of Shandong Province is not sufficient, and the construction of agricultural reservoirs should be carried out in a targeted manner. This study provides new ideas for promoting the efficient use of water resources in monsoon climate zones and the coordinated development of humans and nature, reflecting the importance of supply and demand balance in the spatial allocation of agricultural water resources, reducing the risk of agricultural production being affected by droughts and floods.

Long-term trends in human-induced water storage changes for China detected from GRACE data

Terrestrial Water Storage (TWS) plays a pivotal role in water resource management by providing a comprehensive measure of both surface water and groundwater availability. This study investigates changes in TWS driven by human activities from 2003 to 2023, and forecasts future TWS trends under various climate change and development scenarios. Our findings reveal a continuous decline in China's TWS since 2003, with an average annual decrease of approximately 1.36 mm. This reduction is primarily attributed to the combined effects of climate change and human activities, including irrigation, industrial water use, and domestic water consumption. Notably, TWS exhibits significant seasonal and annual fluctuations, with variations ranging ±10 mm. For the future period (2024–2030), we project greater disparities between water resource supply and demand in specific years for the Songliao, Southwest, and Yangtze basins. Consequently, future water resource management must prioritize water conservation during wet seasons, particularly in years when supply-demand conflicts for limited water resources intensify. This study is valuable for effective planning and sustainable utilization of water resources.

Utilizing Artificial Intelligence Techniques for a Long–Term Water Resource Assessment in the ShihMen Reservoir for Water Resource Allocation

Accurate long–term water resource supply simulation and demand estimation are crucial for effective water resource allocation. This study proposes advanced artificial intelligence (AI)–based models for both long–term water resource supply simulation and demand estimation, specifically focusing on the ShihMen Reservoir in Taiwan. A Long Short–Term Memory (LSTM) network model was developed to simulate daily reservoir inflow. The climate factors from the Taiwan Central Weather Bureau’s one–tiered atmosphere–ocean coupled climate forecast system (TCWB1T1) were downscaled using the K–Nearest Neighbors (KNN) method and integrated with the reservoir inflow model to forecast inflow six months ahead. Additionally, Multilayer Perceptron (MLP) and Gated Recurrent Unit (GRU) were employed to estimate agricultural and public water demand, integrating both hydrological and socio–economic factors. The models were trained and validated using historical data, with the LSTM model demonstrating a strong ability to capture seasonal variations in inflow patterns and the MLP and GRU models effectively estimating water demand. The results highlight the models’ high accuracy and robustness, offering valuable insights into regional water resource allocation. This research provides a framework for integrating AI–driven models with Decision Support Systems (DSSs) to enhance water resource management, especially in regions vulnerable to climatic variability.

Predictive Functional Profiling Reveals Putative Metabolic Capacities of Bacterial Communities in Drinking Water Resources and Distribution Supply in Mega Manila, Philippines

Assessing bacterial communities across water resources is crucial for understanding ecological dynamics and improving water quality management. This study examines the functional profiles of bacterial communities in drinking water resources in Mega Manila, Philippines, including Laguna Lake tributaries, pre-treatment plant sites, groundwater sources, and post-treatment plant sites. Using eDNA sequencing, flux balance analysis, and taxonomy-to-phenotype mapping, we identified metabolic pathways involved in nutrient metabolism, pollutant degradation, antibio- tic synthesis, and nutrient cycling. Despite site variations, there are shared metabolic pathways, suggesting the influence of common ecological factors. Site-specific differences in pathways like ascorbate, aldarate, and phenylalanine metabolism indicate localized environmental adaptations. Antibiotic synthesis pathways, such as streptomycin and polyketide sugar unit biosynthesis, were detected across sites. Bacterial communities in raw and pre-treatment water showed potential for pollutant degradation such as for endocrine-disrupting chemicals. High levels of ammonia-oxidizing and sulfate-reducing bacteria in pre- and post-treatment water suggest active nitrogen removal and pH neutralization, indicating a need to reassess existing water treatment approaches. This study underscores the adaptability of bacterial communities to environmental factors, as well as the importance of considering their functional profiles in assessing drinking water quality resources in urban areas.

Comparative Physiochemical Appraisal of Groundwater and Drinking Water Quality Assessment in Hisar District

Having access to clean drinking water is crucial, especially in rural areas where groundwater is the main water supply. This study has assessed the physicochemical quality of the groundwater in hisar District, Haryana, India. The following physiochemical parameters were determined on 30 samples samples that were gathered from thirty different locations: pH, total dissolved solids, total hardness, alkalinity, electrical conductivity, calcium, magnesium, sodium, potassium, nitrate, fluoride, and sulfate. These findings were compared to the standards set by the Indian Council of Medical Research, the Bureau of Indian Standards, the World Health Organization, and other regulatory authorities. The majority of the required parameters were found to be within allowable bounds; but, total hardness, calcium, and magnesium were shown to be higher than advised in several locations. According to the Water Quality Index, groundwater in certain regions is becoming unsafe for human consumption due to its diminishing quality. This study emphasizes the need of routine monitoring in addition to providing vital information to support mitigation efforts and guarantee the supply of sustainable and clean water resources for the residents of the hisar district in the state of Haryana

GIS based – GALDIT method for aquifer vulnerability assessment to seawater intrusion: Case of a qp2-3 aquifer of Mekong Delta

Recently, seawater intrusion (SWI) in coastal aquifers is a global issue that is exacerbated by sea-level rise, climate change, and an increasing dependency on coastal fresh groundwater resources for water supply. Vietnam's Mekong Delta has a flat topography, a dense river network, and a 700 kilometer coastline covering the region's west and east. The Mekong Delta is facing increasingly serious saline intrusion. This paper describes the results of the examination using the GALDIT method as a model to evaluate the vulnerability of seawater intrusion. The method is used to determine the trend of groundwater contamination by seawater intrusion in the qp2-3 aquifer of the Mekong Delta, this Upper-middle Pleistocene aquifer (qp2-3) is one of the main productive aquifers in the Mekong Delta. The analysis result in 2015 shows a moderate and high level of vulnerability in which the highly vulnerable area is along the Tien River and at the depression cone area in Ca Mau. The analysis is reconducted for the time of 2030 with the predicted values for the groundwater level through the forecasting tool. By comparing the model of two times of 2015 and 2030, the results indicated that the impact of the continuous decline of groundwater level is greater than the impact of sea level rise. If the rate of drawdown is kept the same, by 2030 the highly vulnerability area will have expanded to two-thirds of the Mekong Delta. The GALDIT method is a good approach for saltwater intrusion research and moreover water management, and environmental management, such as evaluating the most sensitive areas for monitoring or imposing restrictions where necessary.

Trade-off between the future water resource utilization and grain production in a water-deficient region from the perspective of the Water−Land−Grain nexus

The utilization and future evolution of water resources in water-deficient regions will have a significant impact on sustainable agricultural development. The trade-off between water resource utilization and grain production in the Daqing River Basin (DRB) was explored, and the characteristics of the future evolution of the water − land − grain system was analyzed. The main planting patterns of farmland in the DRB are winter wheat, spring maize, summer maize, or a winter wheat − summer maize rotation. The total water consumption and supply are 61.6 × 108 and 54.4 × 108 m3, respectively. The water supply gap is approximately 7.2 × 108 m3, which is mainly supplemented by the overexploitation of groundwater. Under the current land use structure, grain production in the DRB has achieved self-sufficiency, but excessive water consumption in agricultural production has led to severe groundwater overexploitation. Despite the exploration and implementation of a fallow land policy in the DRB, the quantity of water resources conserved currently falls significantly short in comparison to the extent of groundwater overexploitation. From the trade-off between water resource utilization and grain production, if winter wheat areas were left completely fallow, or winter wheat planting regions establish three crops in two years or a single crop in a year, the total amount of irrigation water that could be saved was 18.4 × 108, 7.5 × 108, and 15.2 × 108 m3, although the grain production capacity would be reduced by 31 %, 12 %, and 24 %, respectively. This study proposes prioritizing fallow areas in the winter wheat planting regions with high water demand located in the Diandong Plain, and changing the current system of two crops a year to three crops in two years or a single crop a year. The implementation of this approach is anticipated to alleviate the strain on water resources. To achieve the control of groundwater overexploitation and balance the supply and demand of water resources, it is necessary to continue to expand the fallow area of winter wheat in the eastern and southern plains of Baiyangdian by approximately 25.3 × 104 hm2, or increase the amount of water diverted from outside the basin by approximately 7.20 × 108 m3. By 2030, the DRB will face the dual pressures of both water and grain security, with a water resource gap of 13.8 × 108 m3. It is therefore necessary to increase inter-basin water transfer or continue to expand the fallow area of winter wheat in the future.

Characteristics of intra-annual distribution of precipitation and incoming water and the synchronization analysis of their changes in the lower reaches of the Yangtze river basin

Precipitation and incoming water are the key contributing factors to local flooding events, and analyzing the intra-annual distribution and change characteristics of precipitation and incoming water will be beneficial to the understanding of flooding contributing factors in this region. In this paper, the characteristics of intra-annual distribution of precipitation and incoming water and the synchronization of their changes in the lower reaches of the Yangtze River Basin (LYRB) from 1980 to 2020 are studied using the concentration degree and concentration period as quantitative indicators. The results are as follows: 1) the maximum precipitation occurs earlier in the year, while maximum incoming water occurs with little variation in timing but significant variation in total volume; 2) the concentration degree of both precipitation and incoming water show a slowly decreasing trend. The concentration period of precipitation is slightly advanced, and that of incoming water is significantly delayed; 3) the occurrence time and concentration period of the incoming water peak during 2010–2020 lagged behind that of precipitation, which played a role in suppressing the occurrence of floods in the LYRB. This study can provide a scientific basis for the future supply and demand of water resources in the LYRB for safe use.