Urban water security: A comparative assessment and policy analysis of five cities in diverse developing countries of Asia

Chapagain, Kaushal; Aboelnga, Hassan Tolba; Babel, Mukand S.; Ribbe, Lars; Shinde, Victor R.; Sharma, Devesh; Dang, Nguyen Mai

doi:10.1016/j.envdev.2022.100713

Cited by 40 publications

(17 citation statements)

References 63 publications

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“…Green space is an effective factor in reducing and mitigating flood disasters and the urban microclimate. The green rate of the built-up area (P2) and the forest coverage rate (P3) have been defined (Zhang et al, 2017;Chapagain et al, 2022). The supply of standard drinking water is the basis of the social water cycle, which can be indicated by the water supply pervasion in urban (P4) and the water supply capacity (P5) (Zhang et al, 2017;Yin et al, 2020;Chapagain et al, 2022).…”

Section: Construction Of An Indicator Systemmentioning

confidence: 99%

“…The green rate of the built-up area (P2) and the forest coverage rate (P3) have been defined (Zhang et al, 2017;Chapagain et al, 2022). The supply of standard drinking water is the basis of the social water cycle, which can be indicated by the water supply pervasion in urban (P4) and the water supply capacity (P5) (Zhang et al, 2017;Yin et al, 2020;Chapagain et al, 2022). Water use and drainage in production and life are important links in the social water cycle.…”

Section: Construction Of An Indicator Systemmentioning

confidence: 99%

“…The utilization efficiency of water resources has a profound impact on the health of a water ecosystem. Per capita comprehensive water use (P6), per capita domestic water use in urban (P7), unit gross domestic product (GDP) water use (P8), and water use of unit industrial added value (P9) all reflect the efficiency of water use (Zhang et al, 2017;Chapagain et al, 2022). The unit GDP wastewater discharge (P10) represents the level of wastewater discharge (Yin et al, 2020).…”

Section: Construction Of An Indicator Systemmentioning

confidence: 99%

“…

The negative effects of climate change and large-scale urbanization on the water cycle and natural water bodies can cause frequent flood disasters, water pollution, ecological degradation, and limited water resources, all of which pose a real challenge to water management (Yu et al, 2018;Chapagain et al, 2022). Therefore, it is critical to understand the status of the water cycle and water resources to maintain a healthy and sustainable water system (Xia et al, 2017;Yang et al, 2021).

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confidence: 99%

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Urban water health: A conceptual framework and assessment system

et al. 2023

Front. Ecol. Evol.

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The quantitative evaluation of urban water health (UWH) is a crucial decision-making process in water management. Healthy water not only encompasses excellent water quality and a diverse ecology but also has other characteristics, such as the amount of water resources, supply-use-drainage problems, flooding, water cycle, and so on. This study proposes a theoretical framework and an indicator system for UWH that integrates ecosystem health and water cycle health. Subsequently, considering the time scale and regional characteristics, an objective evaluation model that combined the real coding accelerated genetic algorithm (RAGA) method and the projection pursuit (PP) method was applied to calculate indicator weights and thresholds for the urban water health index (UWHI). UWHI standard thresholds were calculated as (0.04, 0.87], (0.87, 1.80], (1.80, 2.73], (2.73, 3.50], and (3.50, 4.01] corresponding to the categories of Sick, Unhealthy, Subhealthy, Healthy, and Excellent, respectively. Using Chongqing as a case study, the results showed that the UWHI increased from 1.796 to 2.668 in 2011–2020, and the health level improved from Unhealthy to Subhealthy, approaching Healthy. For each subsystem, the results indicated that the health status of the water cycle was superior to that of the water ecosystem. Finally, a detailed analysis of the changes in the indicators identified important factors affecting water health. The results of this study revealed that the main weaknesses in Chongqing were severe soil erosion, large domestic water use, high water consumption rates, and unsatisfactory water functional areas and indicated key priorities on the path to future water management.

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Section: Construction Of An Indicator Systemmentioning

confidence: 99%

Section: Construction Of An Indicator Systemmentioning

confidence: 99%

Section: Construction Of An Indicator Systemmentioning

confidence: 99%

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Urban water health: A conceptual framework and assessment system

et al. 2023

Front. Ecol. Evol.

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“…Worldwide, endeavors and resolutions to upgrade water security have been taken by numerous organizations and parties, including the World Water Forum, the Group of Eight (G8), the United Nations, and many researchers (Jones et al, 2009). These researchers have discussed water security issues in many ways and areas, for example, Chapagain et al (2022) carried out qualified analyses of the outcomes of the indicators and interconnected the strategies, plans, and policies of the cities with the indicators of the combined framework to detect policy gaps and propose steps to enhance urban water management in the five cities. Demerdash et al (2022) introduced a new theory for water security: the Irrigation Water Security Quality-based index, where irrigation water security was offered based on quality and quantity.…”

Section: Introductionmentioning

confidence: 99%

An analysis of finding the best strategies of water security for water source areas using an integrated IT2FVIKOR with machine learning

Zamri

Azman

Pairan

et al. 2023

Front. Environ. Sci.

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Worldwide, water security is adversely affected by factors such as population growth, rural–urban migration, climate, hydrological conditions, over-abstraction of groundwater, and increased per-capita water use. Water security modeling is one of the key strategies to better manage water safety and develop appropriate policies to improve security. In view of the growing global demand for safe water, intelligent methods and algorithms must be developed. Therefore, this paper proposes an integrated interval type-2 Fuzzy VIseKriterijumska Optimizcija I Kompromisno Resenje (IT2FVIKOR) with unsupervised machine learning (ML). This includes IT2FVIKOR for ranking and selecting a set of alternatives. Unsupervised machine learning includes hierarchical clustering, self-organizing map, and autoencoder for clustering, silhouette analysis and elbow method to find the most optimal cluster count, and finally Adjusted Rank Index (ARI) to find the best comparison within two clusters. This proposed integrated method can be divided into a two-phase fuzzy-machine learning-based framework to select the best water security strategies and categorize the polluted area using the water datasets from the Terengganu River, one of Malaysia’s rivers. Phase 1 focuses on the IT2FVIKOR method to select five different strategies with five different criteria using five decision makers for finding the best water security strategies. Phase 2 continues the unsupervised machine learning where three different clustering algorithms, namely, hierarchical clustering, self-organizing map, and autoencoder, are used to cluster the polluted area in the Terengganu River. Silhouette analysis is applied along with the clustering algorithms to estimate the number of optimal clusters in a dataset. Then, the ARI is applied to find the best comparison within the original data with hierarchical clustering, self-organizing map, and autoencoder. Next, the elbow method is applied to double-confirm the best clusters for each clustering algorithm. Last, lists of polluted areas in each cluster are retrieved. Finally, this 2-phase fuzzy-Machine learning–based framework offers an alternative intelligent model to solve the water security problems and find the most polluted area.

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Exploring the link between drought‐related terms and public interests: Global insights from LSTM‐based predictions and Google Trends analysis

Shahabi‐Haghighi,

Hamidifar

2023

Hydrological Processes

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Effective drought monitoring is of paramount importance in hydrology. It aids in mitigating the detrimental effects of water scarcity, facilitates sustainable resource management, and informs policy decisions. Therefore, it is crucial to comprehensively comprehend the dynamics and trends of drought‐related phenomena. This study aims to explore the relationship between six low water quantity terms including drought, water crisis, water scarcity, water shortage, water stress, and water insecurity and some socio‐economic, geographic, and demographic parameters for different regions of the world and to predict the future trend of public interest in the mentioned terms using Long Short‐Term Memory neural network (LSTM) models. Google Trend data analysis was used to examine the public interest in these terms from 2017 to 2022. The LSTM models were trained using historical data on the studied terms, and their performance was evaluated using Root Mean Square Error (RMSE) indicator. The Google Trend data analysis showed that public interest in water shortage and water insecurity increased significantly from 2017 to 2022. The LSTM models showed promising results for predicting future trends in the mentioned water related issues, with RMSE scores (dimensionless) ranging from 0.04 to 0.43. The most significant socio‐economic, geographic and demographic parameters were found to be population, life expectancy, access to drinking water, and access to Internet while there was no correlation between precipitation and searched terms. The results suggest that LSTM models can be an effective tool for forecasting water related issues and emphasizes the importance of socio‐economic, geographic and demographic parameters in the public search behaviour around the world. The study also highlights the increasing public awareness of water related issues and the need for sustainable water management practices, particularly in regions with high water shortage and insecurity. The LSTM‐based prediction models in this study have practical applications in early warning systems for droughts, community education on water conservation, prioritizing vulnerable areas, assessing public perception of climate change's relation to droughts, and evaluating water policies. Further research is needed to improve the accuracy of these models incorporating the effective parameters and to develop effective strategies for managing water resources in regions facing water scarcity.

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Urban water security: A comparative assessment and policy analysis of five cities in diverse developing countries of Asia

Cited by 40 publications

References 63 publications

Urban water health: A conceptual framework and assessment system

Urban water health: A conceptual framework and assessment system

An analysis of finding the best strategies of water security for water source areas using an integrated IT2FVIKOR with machine learning

Exploring the link between drought‐related terms and public interests: Global insights from LSTM‐based predictions and Google Trends analysis

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