Abstract Global climate change and growing water demand exacerbate the imbalances in reservoir resource allocation, necessitating advanced frameworks that move beyond static valuation methods. Traditional valuation methods, constrained by static or homogenized assumptions, fail to capture the spatiotemporal heterogeneity and dynamic trade‐offs inherent in cascade reservoir operations. To address this gap, this study develops a novel marginal value framework based on shadow pricing to assess the marginal values of multidimensional resources—water, storage capacity, and turbine capacity—in weekly hydropower scheduling. The key methodological contribution is overcoming the duality gap challenge in mixed‐integer linear programming (MILP) models by proposing two practical methods: Method‐I fixes integer variables to derive dual multipliers via linear programming, while Method‐II computes shadow prices through perturbation analysis. Validated on 26 cascaded reservoirs in Yunnan, China, both methods yield consistent results, with Method‐I demonstrating superior computational efficiency. Key findings reveal that: (a) irrigation water values in dry seasons and upstream regions exceed wet seasons and downstream by 1.11–7.34 times; (b) Nuozhadu Reservoir's storage capacity shadow price peaks in week 44, signaling flood control‐power generation trade‐offs; (c) Wunonglong and Dachaoshan exhibit the highest marginal turbine capacity values for spillage reduction; and (d) reserve capacity costs surge by 32%–45% in weeks 36–37. This work bridges the fields of resource economics and hydraulic engineering, providing actionable insights for dynamic water pricing, infrastructure investment prioritization, and seasonal ancillary service markets.

Europe ranks second in global broccoli production and first in exports, with Spain leading the sector. In Spain, cultivation is concentrated in the southeast, especially the Region of Murcia, one of the main producing areas. The study has three objectives: (1) to establish the characteristic cultivation model of the region, (2) to perform an analysis of the cost structure, and (3) to carry out a sensitivity analysis considering variability in irrigation water prices and the use of organic fertilizers to assess their cost impact. The base information was obtained from surveys conducted with representative farmers of the production sector during the year 2025. The cost structure analysis highlights the dominance of labor-related tasks. Preparation and planting, along with harvesting, are especially significant, accounting for over 34% and 18% of total costs, respectively. Despite this, broccoli generates only 0.22 AWU·ha−1, lower than other horticultural crops. Irrigation is another key cost factor, due to the high price of water. Sensitivity analysis shows that sharp increases in water costs significantly raise overall expenses. Likewise, the high cost of liquid organic fertilizers results in the crop being unfeasible, in contrast to the results obtained with solid organic and synthetic inorganic fertilizers, or the combination of solid and liquid organic fertilizers.

ABSTRACT This study presents an integrated NSGA‐II–AHP–TOPSIS framework to optimize cropping patterns and assess water conservation strategies in Iran's water‐scarce Dasht‐e‐Azadegan plain. Eight conflicting objectives—maximizing profit, labour, energy and manure use, while minimizing water, pesticide, fertiliser and machinery inputs—are addressed simultaneously. Ther following five scenarios are evaluated: (1) improved irrigation efficiency, (2) deficit irrigation, (3) increased water pricing, (4) reduced rice cultivation and (5) expanded sesame cultivation. Scenario 1 delivers the most favourable trade‐off, boosting profit by 15.7% and cutting water use by 24.4%. Scenarios 2 and 3 reduce profitability (−16.5%, −8%), while Scenario 5 yields only a 4.8% gain. AHP‐weighted TOPSIS ranks Scenario 1 highest, followed by Scenarios 2, 4, 3 and 5. The framework proves effective in balancing competing goals and offers a robust decision‐support tool. Results highlight that modernising irrigation systems is the most sustainable strategy for agricultural water management in arid environments.

Objective: Analyze the impact of various levels of drought and increase in groundwater use on agricultural income in Irrigation District 023 of San Juan del Río, Qro., and determine water productivity as drought increases. Design/methodology/approach: Linear programming was used; Four scenarios were built: a typical year with surface and groundwater, two with moderate drought levels and one, only with groundwater for irrigation. In addition to four others with the same characteristics, in addition to considering the cultivation of 60% of alfalfa to serve the dairy sector due to its importance Results: There are reductions ranging from 8.6% to 19.1% in agricultural income for the first set of models and from 9.7% to 23.1% in income when alfalfa planting is forced. The most water-demanding crops cause a significant reduction in agricultural income. Shadow water prices range from $800 per thousand m3 to $5,819 per thousand m3 for the W-I cycle as drought increases. Limitations on study/implications: The research included the most representative crops in the district and limited the area of ​​crops with high profitability due to market aspects. Findings/conclusions: It is concluded that droughts significantly affect agricultural income and that the shadow price of water increases significantly as the drought increases, so groundwater should be allocated to the most productive agricultural activities and less demanding of water.

Rapid urbanization and climate change necessitate the adoption of innovative technologies to enhance resource efficiency and environmental sustainability in smart cities. Artificial Intelligence (AI)-driven optimization has emerged as a transformative solution for improving water usage and waste management by leveraging real-time data analytics, predictive modeling, and automation. This study explores the integration of AI into urban water and waste systems to enhance efficiency, reduce resource wastage, and minimize environmental impact. AI-powered water management utilizes machine learning algorithms and Internet of Things (IoT) sensors to monitor consumption patterns, detect leaks, and optimize distribution networks. By analyzing vast datasets, AI enables predictive maintenance, demand forecasting, and adaptive water pricing strategies, reducing water losses and ensuring sustainable usage. Smart irrigation systems employ AI to assess weather conditions, soil moisture, and plant requirements, leading to optimized water allocation and conservation. In waste management, AI enhances collection logistics, sorting efficiency, and recycling processes. AI-driven route optimization for waste collection reduces fuel consumption and operational costs by dynamically adjusting pickup schedules based on waste levels. Computer vision and robotic automation improve waste segregation, increasing recycling rates and minimizing landfill dependency. Predictive analytics further supports waste reduction initiatives by identifying consumption trends and promoting circular economy practices. Integrating AI with cloud computing and blockchain enhances data security and interoperability, facilitating seamless collaboration among urban stakeholders. AI-driven decision support systems empower policymakers with actionable insights for formulating sustainable urban strategies. However, challenges such as data privacy concerns, infrastructure costs, and public acceptance must be addressed for successful implementation. This paper underscores the potential of AI-driven optimization in transforming urban water and waste systems to achieve environmental sustainability. By leveraging AI's predictive capabilities and automation, smart cities can significantly reduce resource wastage, lower carbon footprints, and enhance resilience against climate challenges. Future research should focus on enhancing AI algorithms, fostering interdisciplinary collaborations, and developing regulatory frameworks to ensure ethical and equitable AI deployment in smart cities

ABSTRACT Water pricing, often pursued under the goal of getting the prices right, is widely promoted as a pathway to efficiency and sustainability in agricultural water use. However, this long-standing and often polarized debate frequently overlooks the complexities of real-world implementation, where pricing decisions intersect with deep-rooted social, economic, and environmental concerns. Reform advocates argue that subsidies encourage inefficiency, strain public finances, and limit investment in critical infrastructure. Conversely, opponents view such subsidies as necessary welfare mechanisms that support vulnerable communities and safeguard national food security. This analytical review paper critically examines the validity of both perspectives, offering a new conceptual framing that situates the subsidy pricing debate within the emerging context of desalinated water use and broader water governance reform. It investigates whether pricing reforms alone can meaningfully alter water use behavior among agricultural users and what contextual factors shape their success or failure. The analysis suggests that pro- and anti-reform arguments are not mutually exclusive. Artificially low prices are increasingly unsustainable; yet abrupt or poorly designed reforms may be equally harmful. A transitional, context-sensitive approach, combining targeted support mechanisms with gradual reform, offers a more viable path, particularly in settings where full cost recovery may be unrealistic.

In the current operational landscape, there are no commercial-off-the-shelf (COTS) solutions capable of turning wave power into clean water on a small scale and expedited timeline. Available wave-powered installations and desalination plants are mostly large infrastructure projects that leverage economies of scale. This is typically the result of economic drivers – the availability and price of electrical power and clean water. However, natural disasters often strike where clean water is scarce and local infrastructure is unable to respond quickly, which drives an urgent need for clean water in locations far from these installations. Here, we present the design, modelling, and initial performance of a compact Wave-Energy-Converter (WEC) powering a reverse osmosis desalination system; a simple technical solution that provides clean water on a small scale (~1,000 Liters per day) and is quickly deployable in disaster zones.

Urban water utilities in rapidly developing regions face growing challenges in ensuring continuous supply. Intermittent public water supply leads to unreliable and inequitable access, compelling households to adopt energy-intensive coping strategies. This creates a nexus between water and energy demand at the household level. Few econometric analyses of household water demand have explicitly addressed this demand-side nexus in developing regions. Using survey data from the city of Pimpri-Chinchwad, India, where intermittent water supply is prevalent, we analyze household expenditures related to water access and estimate a piped water demand function with a Discrete-Continuous Choice model. We find that electricity expenditures for accessing water exceed water bills for approximately one-third of households. Including these costs in affordability calculations reveals hidden financial burdens, particularly for middle-income households. Water and electricity prices, income, and household size significantly influence water demand, with an income elasticity of 0.177 and water price elasticities ranging from 0 to −0.876. The cross-price elasticity of −0.097 indicates weak complementarity between electricity and piped water, suggesting electricity price changes do affect water use but are insufficient to drive substantial behavioral shifts. Targeted price increases in high-consumption blocks are more effective at curbing overuse, while simultaneous increases in water and electricity prices may heighten household vulnerability. These findings highlight the need for integrated, nexus-aware demand management strategies, particularly in regions with intermittent supply.

Climate change is increasing the frequency and intensity of disasters that disrupt supply chains and threaten urban food supplies. Urban agriculture can make urban food systems resilient to such threats by localizing food production and recycling urban waste as food production inputs. The urban environment, however, brings unique water access and management challenges that can threaten the viability of urban agriculture, particularly in water-scarce regions. This case study of the San Francisco East Bay, a region vulnerable to water scarcity, examines (1) how stakeholders manage water resources for urban agriculture under water-scarce conditions and (2) the potential for urban agriculture to be both water resilient and a contributor to overall urban resilience. We employed a mixed-methods approach consisting of identifying and mapping 91 urban agriculture sites, interviewing 34 stakeholders, and analyzing the region's general and climate action plans. Urban growers were the main actors in water management, and they maximized water conservation regardless of drought conditions. Municipalities and water utilities were minimally involved in water management for urban agriculture, but provided access to land and water. Land access played a significant role in water access by dictating the available infrastructure and water pricing. We found a large gap between the actual practice of urban agriculture and the idealized systems modeled in academic literature. Although urban agriculture sites withstood previous droughts, they had not implemented water resilience strategies, such as urban greywater and reclaimed water use, that are often modeled in studies on urban agriculture and resilience. Sites were dependent on municipal water sources. Institutional support is necessary to stabilize long-term access to land and water at urban agriculture sites. With greater stability, urban agriculture can further pursue infrastructural improvements that enhance water resilience and overall food system resilience.

Optimization of agricultural water price setting strategy and government subsidy mechanisms based on game analysis

ABSTRACT In cities in the Global North, economic crises (such as the bursting of the property bubble in 2008 and the impact of COVID-19 in 2020) and the increase in water rates have exacerbated structural inequalities, leading to situations of water poverty. In this context, households may be forced to reduce their water consumption or temporarily or permanently stop paying for the service, risking disconnection. This study analyses quantitative and qualitative data at the neighbourhood scale related to the number of contracts with debts considered uncollectible and requests for subsidies and social tariffs provided by municipal water managers in the cities of Murcia and Alicante (Spain), two cities with high water prices and areas with the lowest income on a national level. These data measure one dimension of water poverty, affordability, and evaluate its relationship with the socioeconomic, demographic, and housing characteristics of the neighbourhoods analysed. The study of these relationships, along with interviews with water management companies, allows us to identify the strengths and limitations of the developed subsidy systems in terms of their scope and effectiveness. It also highlights the barriers and specific needs of vulnerable groups to guarantee the human right to water.

Study of the game mechanism of agricultural water price sharing in irrigation areas

ABSTRACT The Netherlands is known as a water-rich country with high-quality drinking water services. However, under the current conditions, it is expected that there will be insufficient drinking water supply by 2030. In this study, we developed a qualitative dynamic system to identify the drivers and barriers of the dynamic processes that explain household drinking water consumption. A causal loop diagram was constructed as a working theory on how household drinking water consumption could develop over time. System archetypes were used to explain the potential dynamic behavior of sub-models. Motivation to save water, hedonic motivation, security of supply and water price are the linking variables between the sub-models. Sub-model analysis reveals that hedonic motivation and drought response are the main barriers to reducing drinking water consumption. Social norms and water-saving experience are the drivers of reducing drinking water consumption by households. We discuss how smart meters and setting legal requirements can provide promising interventions with the potential to facilitate these drivers. We recommend future research to develop a simulation model to test the dynamic structure and to further investigate the impact of hedonic motivation as a barrier to saving drinking water.

As China confronts intensifying water scarcity, pollution and regional disparities, it has implemented a series of advanced and often experimental water-related policies. This article provides a comprehensive review and critical synthesis of these policies by drawing upon an extensive body of existing empirical literature. Anchored in the triadic evaluative framework of effectiveness, efficiency and welfare distribution, the paper assesses major national strategies — including the Strictest Water Resources Management Policy, water pricing and rights reforms, agricultural water-saving initiatives, groundwater overdraft control, the South–North Water Diversion Project and pollution mitigation mechanisms such as the River Chief System and interprovincial ecological compensation. By systematically compiling and analyzing empirical findings from both quantitative and qualitative studies, the review highlights policy impacts, regional variations in implementation and emerging trade-offs such as rebound effects and equity concerns. The study further situates China’s experience within broader theoretical frameworks in water economics and public policy, revealing a distinct hybrid governance model that integrates command-and-control regulation with market-based instruments. This review not only consolidates existing knowledge but also identifies gaps for future inquiry, offering conceptual and practical insights for other countries navigating the complexities of integrated and equitable water resource governance.

Abstract Water demand in the United States is projected to increase by up to 140% by 2050 and 220% by 2070 while climate change will reduce the availability of freshwater in large parts of the country. Here we quantify the magnitude of this challenge and define pathways of sustainable water desalination that can satisfy projected deficits between supply and demand on a US county-level. Simulations using verified models and databases on water, solar and wind resources and prices show the potential of desalination technologies with zero liquid discharge (ZLD), mainly powered by solar and wind energies, sustainably meeting the needs of the municipal, thermoelectric and industrial sectors. This analysis offers a new reference point for supplemental social studies addressing issues and perceptions regarding the sustainability of producing fresh water via desalination.

ABSTRACTGlobal land issues are becoming increasingly critical, with challenges such as land pollution and land degradation threatening food security and ecological balance. In the context of land degradation, this study utilized panel data from 27 prefecture‐level cities in the Yangtze River Delta (YRD) urban agglomeration from 2008 to 2020. This research adopted a comprehensive methodology, first constructing three subsystem indicator systems for water, energy, and economy; second, applying a comprehensive evaluation model to assess the overall system index; and third, using a coupling coordination degree (CCD) model to evaluate the interaction among these subsystems. Additionally, exploratory spatial data analysis was employed to examine the spatial and temporal dynamics of the region's synergistic development. Results indicated that the overall evaluation index of the “water‐energy‐economy” system in YRD from 2008 to 2020 showed an overall downward trend, with the comprehensive evaluation index of each subsystem, except the energy subsystem, remaining below 0.6. In addition, the system's CCD level showed a gradual upward trend, with overall stability and medium‐level coordination. Hefei and Hangzhou improved faster, both surpassing 0.6. The CCD of the “water‐energy‐economy” system exhibited urban agglomeration, mainly high and low value agglomeration, and the system coordination between neighboring areas gradually strengthened. To address land degradation and promote sustainable development, policymakers should develop tiered water pricing mechanisms for industrial sectors and incentivize water recycling in high‐consumption cities. Additionally, fostering intercity collaboration to enhance resource efficiency and drive economic growth should be prioritized. The findings offer a foundation for government strategies aimed at achieving sustainable development goals and mitigating land degradation in the YRD.

This study employs k-means clustering to analyze local organizations responsible for land improvement in Greece, identifying four distinct groups with consistent geographic patterns but divergent financial and operational characteristics. By integrating unsupervised machine learning with spatial analysis, the research offers a novel perspective on irrigation water pricing and cost recovery. The findings reveal that organizations located on islands, despite high water costs due to limited rainfall and geographic isolation, tend to achieve relatively strong financial performance, indicating the presence of adaptive mechanisms that could inform broader policy strategies. In contrast, organizations managing extensive irrigable land or large volumes of water frequently show poor cost recovery, challenging assumptions about economies of scale and revealing inefficiencies in pricing or governance structures. The spatial coherence of the clusters underscores the importance of geography in shaping institutional outcomes, reaffirming that environmental and locational factors can offer greater explanatory power than algorithmic models alone. This highlights the need for water management policies that move beyond uniform national strategies and instead reflect regional climatic, infrastructural, and economic variability. The study suggests several policy directions, including targeted infrastructure investment, locally calibrated water pricing models, and performance benchmarking based on successful organizational practices. Although grounded in the Greek context, the methodology and insights are transferable to other European and Mediterranean regions facing similar water governance challenges. Recognizing the limitations of the current analysis—including gaps in data consistency and the exclusion of socio-environmental indicators—the study advocates for future research incorporating broader variables and international comparative approaches. Ultimately, it supports a hybrid policy framework that combines data-driven analysis with spatial intelligence to promote sustainability, equity, and financial viability in agricultural water management.

ABSTRACTThis paper incorporates water demand decisions by households and firms into an urban spatial model. Using both land‐use and water demand data from the Denver Water service area, I calibrate the model to focus on four policy options to reduce urban water demand: (1) a “cash‐for‐grass” proposal to reduce irrigated lawn area, (2) relaxing development regulations to increase housing supply, (3) lowering the price of recycled water, and (4) raising the marginal price of potable water. The “cash‐for‐grass” policy reduces water demand, yet the policy is both costly and leads to an increase in the average household yard size. Loosening development regulations may lead to either a rise or fall in aggregate water demand. Lowering the price of recycled water increases demand by firms but lowers revenue for the water district. Numerical simulations suggest that raising marginal water rates are the most effective means of reducing aggregate water demand.

Abstract What about Water Markets in Senegal’s Ferlo Region? The Case of the Communes of Barkedji and Dodji Numerous reforms, in a context of incomplete decentralisation, have succeeded in introducing the rule of selling water to users. From colonial times to the present day, efforts have been made in the rural water sub-sector in the Ferlo. This paper explores a new aspect of access to services in rural areas, namely the disparity between water markets for different boreholes. We hypothesise that user pricing of water is more reasonable than a single imposed tariff. The article is based on several research studies carried out in Senegal and abroad, and on the results of surveys conducted in 2023 in two communes, Barkédji and Dodji. In short, this article provides a spatial analysis of water trading infrastructures, uses and the interplay of players in the water market.

Coronavirus disease 2019 (COVID-19) pandemic has posed significant challenges to healthcare systems worldwide, with the risk of nosocomial infections emerging as a critical concern. The level of knowledge and risk perception could prompt individuals to take precautionary measures and reduce the spread. This study aims to determine the knowledge and risk perception of COVID-19 nosocomial infection among attendees at primary healthcare facilities in the Federal Capital Territory (FCT) of Abuja, Nigeria. A descriptive cross-sectional study design was used in the study where an interviewer-administered semi-structured questionnaire was used to obtain information from attendees of the selected healthcare facilities. Multistage sampling methods were used to select respondents from Gwagwa, Gwarimpa and Kabusa wards of Abuja Municipal Area Council (AMAC). The questionnaire was collated and data was analyzed using SPSS Version 23. Chi-square tests was performed on respondents' socio-demographic characteristics, knowledge and risk perception of COVID-19 nosocomial infection. The result of the findings revealed that majority of the participants were female (74%), aged 25-34(57%) mostly civil servants (29.2%) with tertiary education (45%). Many of the respondents had good knowledge of COVID-19 nosocomial infection (87.7%) as all the respondents heard about COVID-19 mostly through mass media (84.8%). The respondents’ risk perception to COVID-19 nosocomial infection was high (91.6%) with high level of adherence to COVID-19 prevention measures (70.44%). Many of the respondents expressed lack of disinfectants, clean water and high prices of items to be the barriers hindering them from fully protecting themselves against COVID-19. The statistical analysis showed that knowledge and risk perception of COVID-19 nosocomial infection is affected by factors such as age, religion, level of education and occupation as they were statistically significant. The study generally showed high level of knowledge and risk perception of COVID-19 nosocomial infection as well as adherence to COVID-19 prevention measures despite the challenges by some social factors like age, education and occupation.