Growing Water Demand Research Articles

Hydrological Parametric Investigation of Water Distribution Network for Sawale Village, Raigad District (Maharashtra): A GIS Approach

The water distribution network (WDN) is considered one of the most important infrastructural requirements for future cities worldwide. In order to meet the growing water demand of the developing population, it is essential to design a sustainable WDN. In recent decades, numerous researches have been conducted in this field considering various parameters, but poor WDN layout design leads to increasing project cost in terms of execution, maintenance, etc. Hence, the objective of this research work was to overcome the above drawbacks by designing a real time network for a rural emerging village near Rasayani, Maharashtra with the help of Geographical Information System (GIS) and hydraulic simulation using Environmental Protection Agency Network (EPANET). The area of Sawale village is surveyed both physically and using the software. The basic objective of this research is to determine the best possible way in which a given WDS can be optimized to meet the current water demand in Sawale village. EPANET is hydraulic simulation software that can be efficiently used for such purposes. The results show that hydraulic simulation together with the application of GIS helps to create a less time consuming, sustainable and optimized WDN.

Regional hydro-climatic characterization for the efficient use and management of water Study case

Objective: To analyze official information to project future groundwater availability and demand scenarios, based on the different consumptive uses of the Alto Atoyac aquifer, in Tlaxcala, Mexico. Design/Methodology/Approach: The methodology used in this study included a bibliographic and documentary research. Likewise, based on the Penman-Monteith equation, quantitative research was used to calculate and estimate crop irrigation requirements. Results: The results of the availability and demand of groundwater showed a surplus of ≈23.34% in 2020. This percentage will gradually decrease in the following years until it reaches a 24.71% deficit by 2070. Consequently, a groundwater deficit in the Alto Atoyac aquifer will take place throughout the whole period (2020-2070). From 2040 to 2050, this deficit will gradually increase. Study Limitations/Implications: Measures for a sustainable use, exploitation, and conservation of the aquifer must be urgently implemented, as a regular and frequent measurements of aquifer depletion, through measures of phreatic and dynamic groundwater levels, also regular and frequent measures of groundwater extraction, water conduction through the conveyance and distribution system, and finally amounts of water applied to all crop pattern. Findings/Conclusions: The integration of the consulted and generated data allowed the development of groundwater availability and demand scenarios in the aquifer. In addition, comparisons between the said scenarios were established and conclusions were drawn. The growing water demand in the region —required to meet the basic needs of the localities and inhabitants and to keep driving the economic activities in the region— would have negative effects on the environment and the inhabitants, due to the overexploitation of the aquifer groundwater.

Water productivity and economic feasibility of drip irrigation system investment in tomato cultivation: Case of northeastern Tunisia

AbstractTunisia is characterized by water scarcity, growing water demand and considerable waste of this resource especially in the agricultural sector. To cope with this situation and enhance water productivity, appropriate utilization of advanced irrigation methods such as drip irrigation is highly needed. Hence, this research aims to evaluate the profitability of drip irrigation systems compared with surface irrigation systems at the perimeter of Echraf, which is located in the northeastern of Tunisia. Primary data were collected from 25 adopters of the Drip Irrigation System and 13 non‐adopters. The results of the partial budget analysis revealed that the average total cost for adopters was higher than that for non‐adopters. However, the net margin was higher for adopters than for non‐adopters. This is due to the greater increase in gross revenue for adopters than for non‐adopters. Additionally, drip irrigation resulted in more efficient water use and water values than did the surface irrigation system. Economic profitability analysis via the benefit cost ratio and net present value tools revealed that the drip irrigation system is profitable. The benefit cost ratio is equal to 1.65, and the net present value is approximately 2938 Tunisian National Dinar. Finally, the sensitivity analysis reveals the extent to which profitability is sensitive to the scenarios of subsidy levels.

Assessing Future Water Scarcity in Texas under Climate Change and Growing Water Demands

Assessing Future Water Scarcity in Texas under Climate Change and Growing Water Demands

Assessing Drought Patterns in Al-Baha: Implications for Water Resources and Climate Adaptation

Due to growing water demands and changing hydro-meteorological variables brought on by climate change, drought is becoming an increasingly serious climate concern. The Al-Baha region of Saudi Arabia is the subject of this study because it is susceptible to both agricultural and meteorological droughts. This study investigates how climate change affects patterns of drought in Al-Baha by analyzing four drought indices (Agricultural Standardized Precipitation Index (aSPI), the Standardized Precipitation Index (SPI), the Rainfall Deficiency Index (RDI), and the Effective Reconnaissance Drought Index (eRDI)) for the years 1991–2022. Analysis of rainfall data was carried out to classify drought events according to their duration, frequency, and severity. Results showed that severe droughts occurred in 2009, 2010, 2012, 2016, and 2022, with 2010 being the worst year. Results also indicated a notable decrease in precipitation, which has resulted in extended dry spells. Several indices indicate that this tendency has significant ramifications for agriculture, particularly in areas where farming is a major economic activity. In addition, the possible occurrence of hydrological drought was also observed based on the negative values for the Reservoir Storage Index (RSI) in Al-Baha. Projections for the future under two Representative Concentration Pathways (RCPs) showed notable variations in temperature and precipitation. Both the RCP4.5 (low emission) and the RCP8.5 (high emission) projection scenarios indicate that drought conditions will likely worsen further. Depending on the emission scenario, it is projected to show a temperature increase of 1–2 °C, whereas the variability in precipitation projections indicates significant uncertainty, with a reduction change in the range of 1.2–27% between 2050 and 2100. The findings highlight the urgent need for proactive adaptation strategies, effective water resource management, and the development of sophisticated drought prediction tools. Addressing these challenges is crucial for sustaining agriculture and managing water scarcity in Saudi Arabia in the face of increasing drought risk.

Revolutionizing the future of hydrological science: Impact of machine learning and deep learning amidst emerging explainable AI and transfer learning

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are revolutionizing hydrology, driving significant advancements in water resource management, modeling, and prediction. This review synthesizes cutting-edge developments, methodologies, and applications of AI-ML-DL across key hydrological processes. By critically evaluating these techniques against traditional models, we highlight their superior ability to capture complex, nonlinear relationships and adapt to diverse environments. We further explore AI applications in precipitation forecasting, evapotranspiration estimation, groundwater dynamics, and extreme event prediction (floods, droughts, and compound events), showcasing their timely potential in addressing critical water-related challenges. A particular emphasis is placed on Explainable AI (XAI) and transfer learning as essential tools for improving model transparency and applicability, enabling broader stakeholder trust and cross-regional adaptability. The review also addresses persistent challenges, including data limitations, computational demands, and model interpretability, proposing solutions that integrate emerging technologies like quantum computing, the Internet of Things (IoT), and interdisciplinary collaboration. This review charts a strategic course for future research and practice by bridging AI advancements with practical hydrological applications. Our findings highlight the importance of embracing AI-driven approaches for next-generation hydrological modeling and provide actionable understandings for researchers, practitioners, and policymakers. As hydrology faces escalating challenges due to human-induced climate change and growing water demands, the continued evolution of AI-integrated models and innovations in data handling and stakeholder engagement will be imperative. In conclusion, the findings emphasize the critical role of AI-driven hydrological modeling in addressing global water challenges, including climate change adaptation, sustainable water resource management, and disaster risk reduction.

LSTM-Autoencoder Based Detection of Time-Series Noise Signals for Water Supply and Sewer Pipe Leakages

The efficient management of urban water distribution networks is crucial for public health and urban development. One of the major challenges is the quick and accurate detection of leaks, which can lead to water loss, infrastructure damage, and environmental hazards. Many existing leak detection methods are ineffective, especially in complex and aging pipeline networks. If these limitations are not overcome, it can result in a chain of infrastructure failures, exacerbating damage, increasing repair costs, and causing water shortages and public health risks. The leak issue is further complicated by increasing urban water demand, climate change, and population growth. Therefore, there is an urgent need for intelligent systems that can overcome the limitations of traditional methodologies and leverage sophisticated data analysis and machine learning technologies. In this study, we propose a reliable and advanced method for detecting leaks in water pipes using a framework based on Long Short-Term Memory (LSTM) networks combined with autoencoders. The framework is designed to manage the temporal dimension of time-series data and is enhanced with ensemble learning techniques, making it sensitive to subtle signals indicating leaks while robustly dealing with noise signals. Through the integration of signal processing and pattern recognition, the machine learning-based model addresses the leak detection problem, providing an intelligent system that enhances environmental protection and resource management. The proposed approach greatly enhances the accuracy and precision of leak detection, making essential contributions in the field and offering promising prospects for the future of sustainable water management strategies.

From single to multi‐purpose reservoir: A framework for optimizing reservoir efficiency

AbstractThe prevailing challenge centers on the limited application of single‐purpose flood control reservoirs transitioning to multi‐purpose reservoirs, which, despite their potential, often fall short in addressing the escalating demands for diverse water resource management. These challenges are compounded by outdated operational rules and changing environmental conditions. This research develops a framework to enhance the dual functionality of reservoirs, initially designed for flood control, to also support water supply through the determination of maximum safe water levels (MSWLs). Utilizing historical inflow data and reservoir simulation models, the study identifies opportunities for optimizing United States Army Corps of Engineers Louisville District reservoirs. It highlights certain reservoirs as ideal for augmenting water supply capabilities without compromising flood control performance. Others remain critical for flood management due to limited water supply potential, underscoring the importance of maintaining a focus on flood control. The findings illuminate the intricate balance required between managing flood risks and enhancing water supply, indicating that precise operational adjustments can significantly improve reservoir sustainability and efficiency. This method offers a viable pathway to convert single purpose reservoirs into multi‐purpose reservoirs, meeting growing water demands while ensuring robust flood mitigation, and making a step toward better water utilization.

Enhancing smallholder agricultural production through sustainable use of shallow groundwater in the Borkena catchment, Awash River Basin, Ethiopia

ABSTRACT With increasing shallow groundwater use for agricultural purposes, understanding the spatiotemporal variability in recharge rates, storage capacity, and its interaction with surface waters becomes crucial for its sustainable management. An integrated SWAT–MODFLOW model is developed to assess shallow groundwater availability in the Borkena catchment. The model is calibrated using streamflow and static groundwater level data. Results show that groundwater recharge in the catchment is 85 mm/a, representing 11% of the mean annual rainfall. Shallow groundwater resources exist across nearly 42% of the Borkena catchment. The percentage of shallow groundwater withdrawal to groundwater recharge is very low (0.1%), signifying the potential for increased shallow groundwater development. However, caution must be taken as its uncontrolled expansion may result in a high risk of depletion. This integrated modeling is one of the few efforts conducted to provide important information regarding shallow groundwater potential in the Borkena catchment, which is essential for the resilience of small-scale producers in the continued growing water demand and climate change.

The Groundwater Management in the Mexico Megacity Peri-Urban Interface

Megacities boost peri-urban socioeconomic development but fulfill their high natural resource demands by overexploitation, yielding irreversible environmental damage in surroundings that turn into sacrifice zones. This study reports the effects on the Cuautitlán-Pachuca Valley, the Mexico City main expansion zone at the northeast of the metropolitan area on the Central Mexico plateau, the trend scenarios from 2020 to 2050, and the actions to mitigate the growing water demand that will worsen its aquifer overexploitation. We designed a conceptual archetype to apply the Water Evaluation and Planning System (W.E.A.P.) mathematical model calibrated with 2013–2014 data to calculate groundwater volume demand in future scenarios. The demand output for the international airport and agriculture was less than 5%. The local climate change effect up to 2050 will slightly reduce the infiltration. The most crucial water demand increase (195% in 2050) is due to the population and industrial growth of the Mexico City northern municipalities (89% of the total groundwater extraction volume), and the aquifer will have a notable −2192.3 hm3 accumulated deficit in 2050, while urban sprawl will decrease water infiltration by 2.3%. Mitigation scenarios such as rainwater harvesting may reduce the urban water supply only by 9%, and a leak cutback will do so by 24%, which is still insufficient to achieve sustainable water management in the future. These outcomes emphasize the need to consider other actions, such as importing water from near aquifers and treating wastewater reuse to meet the future water demand.

Role of endogenous soil microorganisms in controlling antimicrobial resistance after the exposure to treated wastewater

The reuse of treated wastewater (TWW) for irrigation appears to be a relevant solution to the challenges of growing water demand and scarcity. However, TWW contains not only micro-pollutants including pharmaceutical residues but also antibiotic resistant bacteria. The reuse of TWW could contribute to the dissemination of antimicrobial resistance in the environment. The purpose of this study was to assess if exogenous bacteria from irrigation waters (TWW or tap water-TP) affect endogenous soil microbial communities (from 2 soils with distinct irrigation history) and key antibiotic resistance gene sul1 and mobile genetic elements intl1 and IS613. Experiments were conducted in microcosms, irrigated in one-shot, and monitored for three months. Results showed that TP or TWW exposure induced a dynamic response of soil microbial communities but with no significant increase of resistance and mobile gene abundances. However, no significant differences were observed between the two water types in the current experimental design. Despite this, the 16S rDNA analysis of the two soils irrigated for two years either with tap water or TWW resulted in soil microbial community differentiation and the identification of biomarkers from Xanthomonadaceae and Planctomycetes families for soils irrigated with TWW. Low-diversity soils were more sensitive to the addition of TWW. Indeed, TWW exposure stimulated the growth of bacterial genera known to be pathogenic, correlating with a sharp increase in the copy number of selected resistance genes (up to 3 logs). These low-diversity soils could thus enable the establishment of exogenous bacteria from TWW which was not observed with native soils. In particular, the emergence of Planctomyces, previously suggested as a biomarker of soil irrigated by TWW, was here demonstrated. Finally, this study showed that water input frequency, initial soil microbial diversity and soil history drive changes within soil endogenous communities and the antibiotic resistance gene pool.

Temporal and spatial variations of groundwater quantity and quality for drinking and irrigation purposes in the arid and hot weather of Southern Iran

Groundwater provides a reliable water supply of fresh water worldwide for drinking, agricultural, and industrial purposes, especially in areas where surface water is scarce or unreliable, making it an essential resource for human and economic development. Proper management and protection of groundwater resources are crucial to ensure their sustainability and continued contribution to fulfilling the growing water demand worldwide. This study focused on the quantitative and qualitative changes in groundwater in the Kahoorestan Plain, located northwest of the Persian Gulf in southern Iran. The zoning maps produced by Arc GIS revealed a declining trend in the aquifer level and a drop in the groundwater level of 5.24 m over 20 years. The maps of the flow directions also indicated a general trend from the western highlands to the south and southeast regions of the plain. The Piper diagram showed that the predominant hydrochemical facies of the plain area is NaCl. Temporal changes analysis by the Mann-Kendall test revealed that EC, TDS, TH, Na, Mg, Ca, SO4, and Cl parameters have a rising trend in the majority of wells, which attributes to groundwater over-withdrawal, drought, excessive well drilling, and insufficient aquifer recharge. The study’s analysis of the temporal and spatial changes of the water quality index, Schoeller diagram, and Wilcox diagram revealed that the aquifer’s water quality is unsuitable for drinking and irrigation use due to its high salinity and sodium content. The findings underscore the urgency of adopting effective management strategies to ensure the sustainable management of groundwater resources in the region.

The hydromorphological effects of dams in an extreme desert environment - The Fish River Canyon, Namibia

Arid ecohydrology relies on sporadic rainfall and flooding to sustain linear river oases, crucial for supporting flora and fauna during the long dry season and drought years. Growing water demands have led to large reservoir constructions, severely impacting the fragile arid ecosystems. We analyse the hydro-geomorphological impacts of the large Neckartal Dam (completed in 2019) on the Fish River oasis based on existing dams, regional studies, field surveys, hydrological data, and modelling. The Neckartal Dam, along with three smaller dams, impounds 80 % of the desert oasis basin (1235 Mm3, 55,870 km2), exceeding the average annual runoff threefold. A gradient of dam-induced changes was identified, varying with distance from the dam wall. Immediate downstream, hydromorphological impacts include channel narrowing (⁓15 %) and reduce mean annual sediment yield (⁓20 %). Also, water distribution losses create chronic low flows, favour for invasive flora and fauna to spread, significantly disrupting the pristine nature of the desert ecosystem. This phenomenon has been observed over a 70 km stretch below the Hardap Dam. This situation is irreversible, as the invasive flora can withstand even large floods. As the distance increases, the dam suppresses low to moderate annual floods and prolongs droughts from months to years or even decades. Based on our flood routing model, only the largest floods (recurrence interval, RI >25 years) can exceed the dam storage, continue downstream, transport sediment and maintain the pool-bar morphology along 245 km of the oasis. The lack of significant flows between major floods means that sediment from smaller, lower arid basins accumulates in the Fish River valley, filling pools and further reducing water availability during dry periods. The Neckartal Dam's impact assessment demonstrates potential changes in arid river systems globally.

Hydrogeology of the small island: a case study of Pisang island, West Coast Regency, Lampung province

Pisang Island has an area of 1.5 km2. The issue on small islands pertains to the quality and quantity of water. This is related to an increasing population and growing water demand. This research aims to address the sustainability of water resources. Therefore, a hydrogeological concept is required to assess and predict potential water resources to maintain the quality and quantity of water. The methodology used in this research includes geological mapping, measurement of rock resistivity, hydrometeorological analysis, and water quality testing. The research indicates that the lithologies of Pisang Island calcareous gravelly sand, calcareous sandstone, and porous limestone. The aquifer system on Pisang Island is unconfined. The aquifer was spread throughout the island with varying thicknesses. The lithology of calcareous gravelly sand is found in the island’s northern part, with a thickness ranging from 15 to 90 m. Calcareous sandstone is located in fold slopes of 3 to 5 m thickness. Porous limestone is distributed across the island, with a 30–170 m thickness. Pisang Island has an annual rainfall of 3,101.93 mm/year, evapotranspiration of 2,017.91 mm/year, and infiltration of 511.23 mm/year. The groundwater flow pattern moves from high elevations in hilly areas to low elevations in coastal areas.

ASSESSING RAINWATER HARVESTING OPTIONS IN TERESA, RIZAL: INCORPORATING USER PREFERENCES WITH MULTI-CRITERIA DECISION ANALYSIS

Water scarcity has emerged as a critical global challenge, necessitating the exploration of alternative water sources. Rainwater harvesting (RWH) presents a promising solution, given its abundance and ease of collection. Despite the Philippines' ample rainfall, RWH remains underutilized, capturing merely 6% of the annual precipitation. To bolster RWH adoption, this study aims to investigate residents' preferences for alternative water systems, with a specific focus on cost-effectiveness and reliability. By addressing these factors, we aim to identify key strategies for promoting and implementing RWH to mitigate water scarcity and foster sustainable water management practices in the Philippines. Preferences of rural residents (n = 185) in Teresa, Rizal on RWH alternative was then evaluated using a multi-criteria decision analysis. The main criteria assessed were reliability, cost, adoption factors, and benefits. The analysis involved assessing and converting the scores into Yield After Spillage (YAS) to establish rainfall reliability. The study employed Multi-criteria Decision Analysis (MCDA) to compare and evaluate various alternatives based on different factors, which were subsequently ranked under different scenarios. The study found that Alternative P10, a 1,000L plastic tank with a 20L first flush, exhibited the highest utility score among the assessed alternatives, with a score of 0.617. Notably, Alternative F30, featuring a 3,000L ferrocement tank with a 200L first flush, closely followed with a utility score of 0.614. The study employed the Jonckheere-Terpstra test and Kendall's tau with a significance level of 0.05 to determine the significance of these criteria concerning increasing income. The criteria of price, maintenance, and durability were identified as statistically significant (p-values: 0.007, 0.031, and 0.005, respectively) as residents' income increased. Consequently, residents with higher incomes placed greater importance on Alternative F50, a 5,000L ferrocement tank, due to its alignment with these influential criteria. Moreover, given the potential impacts of changing rainfall patterns and growing water demands, implementing larger storage tanks, like Alternative F50, is advisable to enhance future water sustainability in Teresa, Rizal.

Does the South-to-North Water Diversion Project promote the growth of enterprises above designated size in the water-receiving areas?-Evidence from 31 provincial-level administrative regions in China.

The South-to-North Water Diversion Project (SNWDP) is believed to drive the next phase of sustainable productivity growth, meeting growing water demand, so as to address increasing environmental sustainability challenges. The Middle Route of SNWDP is regarded as an extremely large long-distance inter-basin water diversion project, which has benefited Henan, Hebei, Tianjin and Beijing since 2014 with great sustainable changes to the cities, groundwater, ecological environment, industrial structure and social development of the beneficiary areas. Taking the number of industrial enterprises above designated size (IEDS) in the water-receiving areas as the research object, this paper takes the year of policy implementation 2014 as the basic time point, evaluating the change of the number of IEDS in the beneficiary areas of the Middle Route of SNWDP through difference-in-difference model. The results show that: (1) The Middle Route of SNWDP promotes the additional growth of the number of IEDS in the beneficiary areas. (2) When the Middle Route of SNWDP promotes the growth of the number of IEDS in beneficiary areas, there is no regional difference for regions with different development levels. (3) The reasons why the Middle Route of SNWDP contributes to the additional growth of the number of IEDS are composed of promoting mixed ownership reform of enterprises in beneficiary areas, increasing water supply and increasing population. However, the Middle Route of SNWDP has not had a significant impact on the traditional total factor productivity or the components of production factors, technology and capital. From the final outcome, the South-to-North Water Diversion Project has played a facilitating role in the sustainable development of large-scale enterprises in the water-receiving areas.

Projections of Land Use Change and Water Supply–Demand Assessment Based on Climate Change and Socioeconomic Scenarios: A Case Study of Guizhou Province, China

Land use change and water supply–demand assessment are critical to achieving regional sustainable development and improving human wellbeing. In the context of complex climate change and socioeconomic development, there is an urgent need for systematic assessment and forecasting studies on how to combine physical, geographical, and socioeconomic factors to clarify patterns of change in the land use change and water supply–demand, as well as to respond appropriately to different climate and socioeconomic development scenarios in the future. Based on the Shared Socioeconomic Pathways-Representative Concentration Pathway (SSP-RCP) scenarios, a framework for simulating future land use change and assessing water supply–demand in the coupled SD-PLUS-InVEST model was constructed. The land use change in Guizhou Province from 2020 to 2050 was simulated using the SD-PLUS model, and the water supply–demand conditions were projected for 2030, 2040, and 2050 under multiple scenarios (SSP126, SSP245, and SSP585). The research results indicated that (1) The land use change in the study area has significant spatial heterogeneity. It showed similar trends in the land use change in the SSP126 and SSP245 scenarios, with both artificial surfaces and forest showing an expansion trend, but the expansion of forest was most typical in the southwestern region in the SSP126 scenario, and there is a significant increase in the northeastern region in the SSP245 scenario. Additionally, there is a rapid expansion of artificial surfaces in the central region in the SSP585 scenario, and a more rapid expansion of cultivated land in the southeastern region, with a significant increase in the area of water bodies. (2) The changes in water supply from 2020 to 2050 under the three scenarios show a smaller increase (5.22–11.88%), a significant increase in water demand (29.45–58.84%), and an increase in the area of water shortage by about 2708.94–9084.40 km2, with the extent of the shortage increasing by about 23.71–79.50%. (3) According to the results of the SSP-RCP scenario projections, socioeconomic development has a significant impact on the growth of water demand, and climate and land use change may exacerbate the spatiotemporal heterogeneity of water supply–demand in the karst region. The systematic study of land use change and water supply–demand in Guizhou can provide a scientific basis for the sustainable management of regional ecosystems and the rational allocation of land and water resources.

Method of Calculation the Efficiency and Economic Viability of Rainwater Harvesting Systems

Purpose: study the methodology for designing a rainwater harvesting system and evaluate its technical and economic viability for supplying water for washing vehicles in the garage of the State University of Rio de Janeiro (UERJ), Maracanã campus. Theoretical framework: water supply in urban areas faces complex challenges, due to changes in minimum flows, pollution of water sources, demand growth, variability and uncertainties in the rainfall regime. Rainwater harvesting systems have become an alternative to supply non-potable demand, reducing the need for consumption by the public supply system. Method: evaluation of rainfall in the region of Tijuca, Rio de Janeiro, to meet the demand for water for washing vehicles through a rainwater harvesting system. The calculations of the catchment area and volume of the reservoirs used data, with a historical series between 2009 and 2018, statistical adjustment of the Gumbel frequency distribution and a ten-year recurrence period. Results and conclusion: An average percentage of 61 to 75% of demand was met, depending on rainfall variations and the capacity of the reservoir adopted. Average monthly savings of between US$ 200 and US$ 300 were found, corresponding to a period of 4 to 24 months for cushioning investments in the implementation of the system. Research implications: The research contributes with data that reinforce the importance and efficiency of correctly sized systems, as an alternative source to meet non-potable demands. Originality/value: the article presents a specific methodology for sizing the main elements in a system (catchment area and reservoir volume) and configures excellent technical and economic viability in the proposed use.

Quality index metrics with Bi-GRU-based water quality prediction

ABSTRACT The precise assessment of groundwater resources is significant in the face of growing water demands, environmental pollution, and degradation. However, traditional methods of water quality prediction are inadequate in dealing with large volumes of data or missing data. Machine learning-based prediction methods are being explored to address this issue. Currently, single-indicator techniques are commonly used, but they may not accurately forecast multimodal water quality or capture inter-indicator connections. In this study, a Bi-GRU is proposed to predicting water quality based on quality index data. To evaluate the performance of our proposed method, we utilize Kaggle Datasets, which provide a diverse range of water quality data. We compare our results with existing methods such as MLP, LSTM, and GRU, using metrics including accuracy, precision, recall, and f-score. Overall, our study demonstrates that the Bi-GRU model is highly effective in predicting water quality based on quality index data. The results of our experiments indicate that our proposed method surpasses traditional approaches like MLP, LSTM, and GRU in terms of accuracy, precision, recall, and f-score. These findings have significant implications for improving water quality monitoring and pollution prevention efforts, enabling better management of groundwater resources in the face of growing water demands and environmental challenges.

Kuwait household water demand in 2050: Spatial microsimulation and impact appraisal

AbstractHousehold water demand has increased dramatically in Kuwait over the last few decades, due to rapid population growth and changing lifestyles. Avoiding a water deficit through a supply‐side approach has been the default strategy in Kuwait, yet this approach is unsustainable, associated with declining groundwater levels, and reliance on desalination that results in major carbon emission and environmental impact and that takes a large and growing share of oil revenues. In this study, we forecast household water demand in Kuwait to 2050 under a Business‐As‐Usual (BAU) scenario and evaluate the economic and environmental impacts. A spatial microsimulation, constrained by the national population projection of the Kuwait Institute of Scientific Research (KISR), was developed to overcome data limitations in forecasting household demand. Results show a 45% increase in water demand by 2050, to 664.1 million cubic metres (MCM), relative to the 2019 base year. Annual production costs increase from 1.39 billion USD in 2019 to 1.99 billion USD by 2050, whilst carbon emissions increase from 10.85 to 15.54 million tonnes/year. These results should alert policymakers to the potential impacts of the growing water demand and provide further support for water conservation action to reduce demand.