Sustainable Utilization Of Water Resources Research Articles

Response of Sandy Soil–Water Migration to Different Conditions under Unidirectional Freezing

In order to conserve valuable soil and water resources and avoid problems related to frozen soil, it is important to study the migration of frozen soil water. A greater understanding of frozen soil–water migration can assist with sustainable development and utilization of soil and water resources in frozen areas. This study used an indoor soil column test device to conduct a one-way indoor freezing test of unsaturated soil and the response of soil sample water migration to different freezing temperatures, initial moisture contents, soil densities, freezing times, solute concentrations, and solute types. The experimental and analytical results showed that the temperature field of the soil sample could be divided into three stages: sharp cooling, slow cooling, and stability. After the soil sample had been frozen for 100 h, the temperature field stabilized. The freezing temperature, initial water content, soil density, and freezing time affected water migration in the soil sample. Lower freezing temperatures and greater initial water content resulted in higher levels of water migration. By contrast, greater soil density led to lower water migration levels. In addition, longer freezing times produced smoother soil–water migration curves. The solute concentration and solute type also affected water migration in frozen soil; the higher the solute concentration, the greater the water migration. Compared with CaCl2, NaCl had a stronger effect, causing more water migration and leading to a higher water content. The research findings will aid further studies on soil and water utilization, environmental maintenance, and restoration in areas with seasonally frozen soil, as well as promote the sustainable development of agriculture, water conservancy project development, and the social economy.

Exploring Surface Water-Groundwater Interactions: A Multidisciplinary Approach

Surface water-ground water interaction plays a crucial role in hydrological systems, influencing water availability, quality and ecosystem sustainability. To maintain drinking water resources and ecosystem health, a mechanistic understanding of the underlying processes controlling the spatial patterns and temporal dynamics of groundwater–surface water interactions is crucial. Understanding these interactions requires a multidisciplinary approach that integrates insights from hydrology, geology, ecology, and geochemistry. Several software applications are available to model and analyze these interactions. This abstract presents the framework and key findings of a comprehensive study aimed at elucidating the complex dynamics of surface water-groundwater interactions through different software. Key finding highlights the significance of spatial and temporal variability in surface water-groundwater interactions, emphasizing the need for comprehensive monitoring networks and advanced modeling tools. It underscores the interconnected nature of surface water and groundwater resources, emphasizing the importance of integrated management strategies for sustainable water resource utilization and ecosystem health. It provides an overview of current research advances and innovative approaches in the broad field of surface water-ground water interactions. By adopting a multidisciplinary approach, we can understand the complex interactions shaping the surface water-groundwater systems, facilitating informed decision-making and effective resource management in a dynamic environment.

A simple method for evaluating the relative water uptake rate of drip‐irrigated crops

AbstractDrip irrigation is widely acknowledged for its water use efficiency, yet evaluating relative water uptake rates (RWURs, ratios between the water uptake rates and the irrigation rates) remains pivotal for effective system design and management. This article presents a novel method employing straightforward measurements of wetted soil surfaces around emitters or perpendicular to driplines, both with and without water uptake, emphasizing simplicity and practicality. The proposed method offers valuable insights into agronomic water use efficiency, facilitating the optimization of drip irrigation for both annual and perennial crops. While effective for intensively irrigated crops, the method does have limitations for smaller wetted areas and longer irrigation cycles, depending also upon a reasonable determination of the active root zone depth and the soil capillary length. Despite relying on a simplified water uptake model, the accessibility and cost‐effectiveness of the method render it a valuable tool for assessing RWURs in diverse agricultural settings, contributing to the sustainable utilization of water resources in drip irrigation.

Anomalies identification in Smart Water Metering Networks: Fostering improved water efficiency

Smart Water Metering Networks (SWMNs) stand as pivotal infrastructure, crucial for communities and industries. The escalating value of water resources due to climate change and overexploitation underscores the urgency of optimizing these networks for efficiency and resilience. This study focuses on identifying anomalies within SWMNs to address challenges impeding efficient water resource management. Leveraging a comprehensive 72-month dataset from Windhoek, Namibia, this research employs a meticulous analytical approach to unveil diverse anomaly types prevalent within SWMNs. Anomalies, including irregular consumption patterns, leakages, and inaccurate meters, contribute significantly to both apparent and real losses. By scrutinizing this dataset, the study reveals nuanced anomaly patterns like persistent zero consumption and unexpected fluctuations, highlighting the pervasive nature of these issues within the network. The findings not only shed light on these multifaceted anomalies but also lay the groundwork for future advancements in machine learning-based anomaly detection techniques. This research holds promise beyond academia, offering practical implications for water utility management. Identifying and understanding these anomalies serves as a stepping stone toward developing robust detection systems, ultimately fostering heightened efficiency and resilience in water networks. This study serves as a catalyst for strategic improvements, enabling more sustainable and efficient utilization of water resources amidst evolving environmental challenges.

Spatial-temporal evolution of plateau and plain lakes and climate driving factors based on Google Earth Engine platform

Accurate understanding of lake water dynamic changes is beneficial to sustainable utilization of water resources and maintenance of ecological balance. Lake change is sensitively reflective of climate and environment change. This study chooses plateau lake and plain lake as the study area, and uses Landsat TM/ETM+/OLI and meteorological data as data source. Based on the Google Earth Engine platform, lake areas are extracted using NDWI method, and lake morphological characteristics are analyzed. The model between climate factors and lake area is established and analyzed in sections according to the difference of lake change trend. The results indicate that the morphological characteristic index of the plateau lakes changes little, but that of the plain lakes changes greatly. Precipitation in the plain lakes fluctuates more violently than that in the plateau lakes. The temperature fluctuation in the plateau lakes is larger than that in the plain lakes.

Mathematical modelling for groundwater management for multilayers aquifers (Erbil basin)

This study addresses the pressing issues of groundwater depletion and drought problems in the Erbil basin, a vital resource region in the Middle East. Focused on an area of strategic importance due to its large size and critical water resources, the study employs the Groundwater Modeling System (GMS) software to create a detailed 3D hydrogeological model based on extensive borehole data. With over 240 boreholes analyzed, the study strategically selects 70 accurate wells drilled by the Groundwater Directorate. The construction of the 3D stratigraphic models for the Erbil basin relies on three main historical data including boreholes, geological formations and a comprehensive approach, incorporating deep well logging data and the definition of distinct geological layers. By discerning the presence of previous and impervious layers, the model effectively categorizes the aquifer types within the Erbil basin. The aquifer system is delineated based on stratigraphic units, designating materials with high conductivity (silt, sand, and gravel) as aquifers and clay (or claystone) as aquitards. A 3D steady-state groundwater flow model is successfully executed, employing PEST pilot point for automated parameter estimation. The model, validated with a coefficient of determination (R2) of 0.9998, reveals hydraulic conductivity values ranging from 0.000980705 to 100 m/day and a recharge value of 0.000976443 m/day. The study classifies Erbil's aquifer types as unconfined, confined, and semi-confined, providing a valuable foundation for groundwater management. The primary objective of this study is to construct a calibrated numerical groundwater model for the multi-aquifer system in the Erbil basin. The model aims to serve as a robust tool for analyzing the sustainability of diverse groundwater infrastructure development strategies within the region. The Erbil basin poses unique challenges for groundwater modeling, marked by a scarcity of critical data such as monitoring well information, pumping rates, recharge rates, and flow budgets. In response to these limitations, the study adopts an innovative approach by integrating in situ data with earth observation data. The integration of these datasets seeks to overcome data constraints and enhance the accuracy of the groundwater model. By achieving calibration and validation of the numerical model, this research strives to provide a valuable resource for decision-makers, planners, and stakeholders involved in groundwater management in the Erbil basin. Ultimately, the study aims to contribute to the development of sustainable and effective strategies for the utilization and preservation of groundwater resources in this vital region and also to enhance practical management strategies for the Erbil groundwater basin, ensuring sustainable utilization of the crucial sub-surface water resources, an objective successfully achieved through this research.

A STUDY ON DETERMINATION OF TOTAL PHENOLIC AND PROTEIN AMOUNTS OF WASTE GREEN ALGAE OF MAMASIN DAM LAKE (AKSARAY-TURKEY)

The excessive proliferation of green algae in aquatic ecosystems threatens aquatic life, leading to oxygen depletion and water pollution. This study investigates two common green algae species, Ulva sp. and Cladophora sp., with potential in terms of protein and phenolic compounds. Cladophora sp. and Ulva sp. extracts were analyzed for total phenolic content using the Folin-Ciocalteau method. Despite lower phenolic content compared to specific plant species, both algae species exhibit various phenolic compounds. GC-MS analysis indicates the presence of major compounds such as limonene in Cladophora sp. and Tetradec-1-ene in Ulva sp., suggesting potential applications in the pharmaceutical and cosmetic industries. Despite modest protein amounts, the study emphasizes that algae, aligned with the increasing interest in plant-based nutrition, are a promising source for plant-based protein production. Ulva sp. and Cladophora sp. algae demonstrate potential as alternative protein sources and reservoirs of bioactive phenolic compounds from waste sources. This study pioneers further research in the food, pharmaceutical, and cosmetic industries to contribute to sustainable water resource utilization.

Nitzschiatranstagensis Morales, Novais, Wetzel, Morais & Ector (Bacillariophyceae) - the second record in the Mediterranean Region.

The Mediterranean Region holds significant ecological importance, characterised by its unique climate, biodiversity and the crucial role it plays in global ecosystems. Mediterranean streams are naturally highly-stressed environments mainly due to fluctuations in water quantity. River flow generally varies from perennial to ephemeral and temporary rivers constitute significant water resources. Streams that flow through Balearic Islands are subjected to these conditions. The majority of these streams sustain water flow for 4-5 months annually, with exceptions noted for streams associated with springs, which typically maintain water throughout most of the year.Benthic diatoms are widely recognised as reliable bioindicators of water quality, used in many aquatic ecosystems. Analysing diatom communities and their biodiversity serves as a valuable tool to ensure the ecological and sustainable utilisation of water resources as well as the accurate development of guidelines for their conservation.The field of diatom taxonomy and distribution plays a crucial role in advancing our understanding of aquatic ecosystems and their biodiversity. Species of the genus Nitzschia are extensively found throughout the Mediterranean Region, including the Balearic Islands. However, they have rarely been investigated in temporary streams. This study presents the first record of Nitzschiatranstagensis Morales, Novais, Wetzel, Morais & Ector, outside the type locality and being the second record in Europe. In this study, the authors found this taxon in one temporary stream of Majorca Island, Torrent des Castellot in November 2005 (Balearic Islands). Nitzschiatranstagensis occurred at 2.6% abundance in this stream with oligotrophic waters (0.052 mg∙l-1 of nitrate), slightly alkaline pH values (7.8) and water conductivity levels of 626.5 µS cm-1. This species was recorded in the biofilm of the stones together with other taxa such as Achnanthidiumminutissimum (Kützing) Czarnecki (39.2%), Gomphonemarosenstockianum Lange-Bertalot & Reichardt (28.9%) and Halamphoraoligotraphenta (Lange-Bertalot) Levkov (20.4%). The Nitzschiatranstagensis frustules found in the examined material have similar dimensions and a higher fibulae count (8-11 in 10 μm vs. 6-10 in 10 μm) compared to the type material of Nitzschiatranstagensis. The habitat characteristics in which this species was found are described, together with LM micrographs of this taxon.

Energy Poverty Impact on Sustainable Development of Water Resources in China: The Study of an Entropy Recycling Dynamic Two-Stage SBM Model

Water scarcity is increasingly being recognized as a global concern. Sustainable Development Goal 6 (SDG-6) was established by the United Nations to address water resource governance within its sustainable development framework. This study employs the entropy weight method and a two-stage cyclical dynamic slacks-based measure (SBM) model to scientifically evaluate water resource utilization and governance across various regions in China. The findings reveal notable disparities in both the production and governance efficiency of water resources. Recognizing governance efficiency is crucial for promoting sustainable water resource utilization and socioeconomic development. The eastern, central, and western regions encounter unique challenges in attaining sustainability. The eastern region exhibits minimal potential for enhancing technical efficiency, necessitating interventions in management strategies and resource allocation. Conversely, the challenges in the central and western regions are more pronounced, demanding immediate implementation of new technologies and equipment. The data analysis in this study yields conclusions that offer targeted improvement recommendations to address disparities across China’s eastern, central, and western regions, and this is achieved by considering various developmental stages and regional contexts. These recommendations cover areas such as technical support, financial investment, and policy incentives, with the aim of enhancing the sustainable utilization of water resources in the country.

Geochemical processes, salinity sources and utility characterization of groundwater in a semi-arid region of Iraq through geostatistical and isotopic techniques.

Identifying factors contributing to water salinity is paramount in efficiently managing limited water resources in arid environments. The primary objective of this study is to enhance understanding regarding the hydrochemistry, source, and mechanism of water salinity, as well as to assess the suitability of water for various uses in southern Iraq. The groundwater samples were collected from water wells and springs and analyzed for major cations and anions along with stable isotopes (δ18O and δ2H) to accomplish the objective. The analysis of major ion chemistry, hydrochemical techniques, principal component analysis (PCA), and isotope signatures were adopted to determine the primary factors contributing to water mineralization. The study inferred that evaporation and geological processes encompassing water-rock interactions, such as dissolution precipitation and ion exchange, were key processes. The stable isotope analysis revealed that the water originated from meteoric sources and underwent significant evaporation during or before infiltration. The utility assessment of water samples indicates that most samples are not appropriate for consumption and are significantly below the established standards for potable water. In contrast, a significant portion of the groundwater samples were found to meet the criteria for irrigation suitability by adopting Wilcox and the US Salinity Laboratory criteria. The groundwater could be considered for irrigation with proper salinity control management. Overall, this study has significantly improved the understanding of the hydrogeochemical regimes and acts as a first step toward the sustainable utilization of water resources.

Vegetation restoration strategies based on plant water use patterns

The study on the water source of plants in alpine mountainous is of great significance to optimize the allocation and management of water resources, and can also provide important reference for ecological restoration and protection. However, the controls of water sources for different plants in alpine mountainous region remain poorly understood. Based on the advantages of stable isotope tracer and Bayesian (MixSIAR) model, the water source of plants in Qilian Mountains was quantitatively analyzed. The results showed that the water sources of plants in Qilian Mountain mainly included two parts: direct source and indirect source. The direct source is soil water, which provides most of the water that plants need. The highest contribution of soil water to shrubs was 80 %, followed by trees (73 %) and herbs (72 %). It is worth mentioning that trees mainly use deeper soil water (below 60 cm), shrubs mainly use surface and intermediate soil water (0-60 cm), and herbs mainly use surface soil water (0-40 cm). What is more noteworthy is that indirect sources, such as precipitation, glacier and snow meltwater, and groundwater, are also water sources that cannot be ignored for plant growth in study area. Shrubs and Herbs use more soil water in the range of 40-60 cm, which leads to the possibility of water competition between these two planting types. Therefore, attention should be paid to this phenomenon in the process of vegetation restoration and water resources management. Especially when planting or restoring artificial plants, it is necessary to consider the water use strategy of the two plants to avoid unnecessary water competition and water waste. This is of great significance for ecological stability and sustainable utilization of water resources in the study region.

A Comprehensive Analysis of China’s Water Resources Tax Reform

In response to the growing disparity between the supply and demand of water resources, the Chinese government has piloted a more binding and reformed water resources tax to realize the sustainable utilization of water resources. However, reasonable tax standards and their water-saving effects and economic benefits are important and worthy of attention. Therefore, in this study, we combine the virtual water theory with the price input–output model to discuss the impact of water resources taxation on the economy and its water-saving effects. The results show the following: (1) A water resources tax has a significant water-saving effect, and is predicted to save 33.12 billion cubic meters of virtual water. (2) Consumers’ expected reductions in spending on food and tobacco manufacturing and agriculture are predicted to save more virtual water at a lower economic cost. (3) The collection of water resources taxes can actively and simultaneously guide water savings in terms of consumption and production. The water consumption of the construction industry is worthy of attention. The expected output value reduction accounts for 67.2% of the total output value reduction, and its water savings account for 96% of the total water savings. Other service sectors also have ample room to optimize the utilization of their water resources.

Risk analysis and assessment of water resource carrying capacity based on weighted gray model with improved entropy weighting method in the central plains region of China

The issue of global water shortage is a serious concern. The scientific evaluation of water resource carrying capacity (WRCC) serves as the foundation for implementing measures to protect water resources. In addition, most of the studies are based on the analysis and research of regional WRCC from the aspects of water quantity and water quality. There are few studies on the four aspects of water resources endowment conditions, society, economy and ecological environment, which is difficult to scientifically and accurately reflect the analysis and evaluation of regional WRCC by the four systems. Therefore, it is necessary to conduct a deeper discussion and Analysis on this topic. This study presents a WRCC index system and corresponding ranking criteria based on 20 influencing factors from four aspects: water resources endowment (WRE), economy, society, and ecological environment. In addition, by combining the improved entropy weighting method (EWM) with gray correlation analysis, the weighted gray technique for order preference by similarity to an ideal solution (TOPSIS) model is proposed for analyzing and assessing WRCC risk. Finally, the WRCC of the study area from 2012 to 2021 is comprehensively evaluated in the central plains region of China (CPROC) as an example. The results show that the comprehensive evaluation obtained a multi-year average value of 0.2935, and the water resources shortage in the CPROC is generally in grade III status. The comprehensive average value of Beijing is 0.345, and the comprehensive average value of Henan is 0.397. The overall degree of water resources shortage is in the state of grade V shortage, Shaanxi is in the state of grade IV shortage, and the degree of water resources in Tianjin and Shanxi is relatively good. This study provides corresponding scientific basis and methodological guidance for the sustainable utilization of water resources and healthy socio-economic performance in the CPROC.

Long-Term Monitoring of Surface Water Dynamics and Analysis of Its Driving Mechanism: A Case Study of the Yangtze River Basin

In-depth insights into the profound impacts of climate change and human activities on water resources are garnered through the dynamic changes in surface water, a crucial aspect of effective water resource management and the preservation of aquatic ecosystems. This paper introduces an innovative approach employing the random forest algorithm for the systematic extraction and monitoring of surface water at large regional or national scales. This method integrates spectral bands, spectral indices, and digital elevation model data, offering a novel perspective on this critical task. A data-filling model is proposed to mitigate the impact of missing data due to cloud cover. Leveraging the capabilities of the Google Earth Engine (GEE), detailed information on surface water dynamics during the rainy and dry seasons in the Yangtze River Basin (YRB) from 1991 to 2021 is extracted using Landsat time series imagery. The analysis encompasses spatial-temporal variation characteristics and trends, with a specific focus on the intricate interplay between the areal extent of surface water and hydro-meteorological factors in each sub-basin of the YRB. Importantly, this includes considerations of potential groundwater contributions to surface water. Key findings from our research include: (1) Achieving a remarkable overall classification accuracy of 0.96 ± 0.03 in obtaining reliable surface water datasets with the support of GEE. (2) Identifying significant trends, such as a noteworthy increase in rainy season surface water bodies (+248.0 km2·yr−1) and a concerning decrease in surface ice/snow cover during both rainy and dry seasons, with change rates of −39.7 km2·yr−1 and −651.3 km2·yr−1, respectively. (3) Uncovering the driving mechanisms behind these changes, revealing positive correlations between the areal extent of rainy season surface water bodies and precipitation, as well as negative correlations between surface ice/snow cover area and average surface skin temperature. It is crucial to note that these driving factors exhibit variation among secondary river systems, underscoring the complexity of surface water dynamics. Furthermore, comparative analyses with existing surface water products are conducted, contributing to a deeper understanding of the advantages and uncertainties inherent in our proposed extraction method. The proposed method for large-scale surface water extraction not only enhances the monitoring of spatio-temporal surface water dynamics in the YRB but also provides valuable insights for the sustainable utilization and protection of water resources, considering the potential role of groundwater in supplementing surface water.

Assessing ecological health in a semi-arid basin: a case study of the Wei River Basin, China.

A healthy water ecosystem within a river basin is essential for maintaining ecological security, preserving species diversity, and ensuring sustainable socio-economic development. Unfortunately, human activities have significantly threatened the health of water ecosystems in various basins. Consequently, timely restoration and targeted protection of damaged river ecosystems have become crucial objectives in watershed management. As a prerequisite and cornerstone for river protection and management, assessing river ecological health has emerged as a primary focus in current research. In this study, we selected the Wei River Basin, a representative area of the Yellow River Basin, as our research subject. We identified multiple influencing factors, including society, biology, water quality, and habitat, which collectively impact this semi-arid region. To assess the overall impact of these factors on ecological health, we developed a comprehensive River Ecological Health Assessment Index (REHAI) system. The research findings indicate that the Wei River system, as a whole, is currently in a healthy state, while the Jing and Luo River systems are classified as sub-healthy. Furthermore, we observed variations within the Wei River system itself; the upper reaches of the Wei River exhibit higher levels of health compared to the middle reaches, whereas the water environment in the lower reaches is the most compromised. This degradation can be attributed to downstream subsidence, increased pollution, and rapid urbanization. By establishing a river ecosystem health assessment methodology and conducting a comprehensive evaluation of the health status of river ecosystems, this paper puts forward management recommendations for river basins. These findings provide a scientific basis for the sustainable utilization of water resources in river basins and promote the harmonious coexistence of humanity and nature.

Deep hierarchical cluster analysis for assessing the water quality indicators for sustainable groundwater

Groundwater quality assessment is a paramount aspect of ensuring the availability of safe drinking water. The conventional reliance on individual parameter thresholds often overlooks intricate interdependencies within the dataset. To overcome this, deep learning algorithms are employed to automatically extract meaningful features from multidimensional data. This innovative approach aims to capture complex relationships between water quality parameters that may be missed by traditional methods. The research identifies a significant gap in current groundwater quality assessment methodologies, emphasizing the need for a more data-driven approach. This research addresses the limitations of traditional methods by introducing a pioneering approach that integrates deep learning and hierarchical cluster analysis to identify comprehensive water quality indicators. The study collects data from diverse monitoring wells, encompassing chemical, physical, and biological parameters. By applying deep cluster analysis to the feature-extracted data, latent patterns and relationships among water quality parameters are unveiled. This clustering method reveals hidden structures within the dataset, leading to the identification of water quality indicators that consider both individual parameters and their interactions. The proposed method in this research offers an understanding of groundwater quality dynamics, contributing to the advancement of water resource management strategies. The results of the deep cluster analysis provide a more comprehensive and accurate representation of groundwater quality, enabling better-informed decision-making for sustainable water resource utilization.

Estimation of loss in arable land and irrigation requirements using high‐resolution imagery and Google Earth Engine

AbstractWater resources planning and management are critical in intricate basins such as the Indus Basin, shared by India and Pakistan under the Indus Water Treaty (IWT) for food security, conserving the environment, sustainable economic development and supporting livelihoods. The present study assesses arable land loss within the Padshahi and Sindh Extension (SE) canal catchments over 54 years, utilizing high‐resolution satellite imagery and Google Earth Engine's normalized difference vegetation index (NDVI) derivations for strategizing irrigation efficiency, minimizing water loss and ensuring sustainable utilization of limited water resources under the IWT. Results revealed that irrigated land has decreased from 5127 ha (1966) to 3501 ha (2020) in both canals. The Padshahi canal sees substantial loss (1278 ha), primarily due to the highest transitions from agricultural land/crop land (−69%) to built‐up areas. The SE canal, experiencing shifts to horticulture and plantation, records relatively fewer changes in built‐up areas (348 ha). The monthly variation in the NDVI clearly depicted the high demand for irrigation to cater to agricultural lands with the onset of the sowing season for paddy in the Padshahi (1900 ha) and SE (2600 ha) canals in May.

A comprehensive analysis of surface water changes in Dau Tieng Lake, Vietnam, across dry and wet seasons

This study investigates the seasonal dynamics of Dau Tieng Lake near Tay Ninh, Vietnam, employing remote sensing technology, specifically the Modified Normalized Difference Water Index (MNDWI) and Normalized Difference Vegetation Index (NDVI). Focused on the period from 2016 to 2020, the research aims to detect changes in the water surface area during dry and wet seasons. As the largest reservoir for water supply and irrigation in Vietnam, Dau Tieng Lake faces operational challenges due to seasonal rainfall variations and increasing water demands. The results reveal significant differences in water body areas between wet and dry seasons, with MNDWI proving more effective in capturing these variations compared to NDVI. The study concludes that the seasonal change in Dau Tieng Lake is 21.76 km2 (NDVI) and 25.55 km2 (MNDWI), emphasizing the latter's superiority in accurately detecting water body changes. These findings contribute valuable insights for improved reservoir management and sustainable utilization of water resources in the region.

Review of smart water management: IoT and AI in water and wastewater treatment

Integrating the Internet of Things (IoT) and Artificial Intelligence (AI) in smart water management revolutionizes sustainable water resource utilization. This comprehensive review explores these technologies' benefits, challenges, regulatory implications, and future trends. Smart water management enhances operational efficiency, predictive maintenance, and resource conservation while addressing data security and infrastructure investment challenges. Regulatory frameworks play a pivotal role in shaping the responsible deployment of AI and IoT, ensuring data privacy and ethical use. Future trends include advanced sensors, decentralized systems, quantum computing, and blockchain for enhanced water data security. The alignment with Sustainable Development Goals (SDGs) underscores the transformative potential of smart water management in achieving universal access to clean water, climate resilience, and inclusive, sustainable development. As we embrace these technologies, collaboration, public awareness, and ethical considerations will guide the evolution of intelligent and equitable water management systems.

Assessment of Water Resource Utilization and Analysis of Driving Factors in Zhoushan City Based on Water Footprint Theory and LMDI Model

Accurately analyzing the water system’s status in a region is crucial for mitigating water resource constraints on the development of island areas. This study centers on Zhoushan, an archipelago city, and employs the water footprint theory (WFT) and the logarithmic mean Divisia index (LMDI) model to scrutinize the evolution of water footprints from 2010 to 2020. It also dissects the impacts of economic, technological, and population factors on these changes. The findings are as follows: From 2010 to 2020, Zhoushan’s total water footprint has remained relatively stable, but its structure is imbalanced, indicating an unhealthy development. The agricultural water footprint dominates, though its proportion has steadily declined from 64% to 28%, while the imported water footprint has significantly increased from 2% to 29%. The skewed distribution of internal and external water consumption contributes to this imbalance, with internal water use accounting for a staggering 86.43%. The ecological security of water resources appears bleak, with average water scarcity and pressure indices reaching 0.42 and 0.41, respectively, indicating an overloaded state of water resources. Despite a 144.50% growth in water footprint efficiency from 2010 to 2020, the average water resource sustainability index merely stands at 0.531, and its sustainability remains precarious. The LMDI model results unveil that technological factors are the primary negative driving factors, contributing to 47.06% of the changes in Zhoushan’s water resource utilization. Conversely, economic and population factors play positive roles, contributing 42.29% and 10.65%, respectively. Therefore, in the course of development, there should be a focus on promoting water-saving tec-nologies, and continuously enhancing the efficiency of water resource utilization. Simultaneously, attention should be given to the development of the tertiary sector and the water resource pressure resulting from the mobile population, aiming to achieve sustainable water resource utilization and further ensure the ecological security of Zhoushan City.