Developing a novel social–water capital index by gene expression programming

Omid Bozorg-Haddad (), Mohammad Delpasand (), Sarvin ZamanZad-Ghavidel () and Xuefeng Chu ()
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Omid Bozorg-Haddad: University of Tehran
Mohammad Delpasand: University of Tehran
Sarvin ZamanZad-Ghavidel: University of Tehran
Xuefeng Chu: North Dakota State University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 11, No 42, 28187-28217

Abstract: Abstract The development of social capital of societies is affected by many factors such as the availability of water resources. The main social capital of a country is its rural communities. Thus, it is necessary to analyze and investigate the relationship between social capital and water resources. In this research, a comprehensive gene expression programming (GEP) model is developed and integrated with the social and water sciences, for the first time, to determine the social–water capital index based on native cultural studies. According to this model, selection of dimensions and reagents is the most important and influential stage. Therefore, researchers and policymakers need to study all aspects in the study area. The model for determining the social–water capital index can be developed for various spatial and temporal scales. In an application of the model, farmers from nine villages in the province of West Azerbaijan, Iran, were selected and the effects of water poverty on social capital were evaluated by examining 39 reagents. The relationship between the social–water capital index and various dimensions of societies was characterized by using soft computing, and the model was verified. To quantitatively and qualitatively analyze the social–water capital index at poor, tolerable, and rich levels with different dimensions such as economic outcome, socio-culture, behavioral norms, and awareness-tacit knowledge, multi-stage Delphi and principal component analysis (PCA) techniques were applied. The results showed that the economic outcome dimension had the most important role in the social capital associated with water, accounting for more than 61% of the variance of the social–water capital. The City of Miandoab was rich with an index value of $$+ 1.003 \ge + 1$$ + 1.003 ≥ + 1 , and eight other cities were tolerable in terms of the social–water capital index. It is recommended that the government increases the budget allocated to the implementation of water pipelines and the pressurized irrigation systems in the province of West Azerbaijan.

Keywords: Social–water capital index (SWCI); Delphi method; Water poverty; Gene expression programming (GEP); Principal component analysis (PCA) (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03807-8

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