Development of Dynamic Nonlinear Water Demand Equation and Comprehensive Dataset for Residential

This study introduces an innovative approach to modeling residential water demand in India by developing a dynamic nonlinear water demand function. Our primary contribution is the creation of a comprehensive and dynamic dataset, which addresses the absence of such data tailored to urban settings. Utilizing this dataset, we developed a sophisticated water demand equation that enhances the accuracy of demand forecasts. Key influences analyzed include water price elasticity, household infrastructure, climatic conditions, income levels, population density, elevation, water flow, socio-economic status, peer effects, and energy costs. Our findings highlight the need to revise water pricing strategies to manage demand effectively, particularly given the significant disparities in income and infrastructure between urban and rural areas. This study underscores the importance of policy interventions in fostering sustainable water management practices that meet local needs. Additionally, we explore the anticipated impacts of climate change on future water demand in urban India, providing critical insights for policymakers. By proposing this dynamic dataset and a newly formulated water demand equation, we present a robust framework for addressing India’s water sustainability challenges, supporting informed policy decisions to mitigate water scarcity and enhance resilience in water resource management.

Authors

Publication Details

Journal
Communications on Applied Nonlinear Analysis
Published
2024-11-30
DOI
https://doi.org/10.52783/cana.v32.2567
Primary Topic
Korean Urban and Social Studies
Type
article
Field-Weighted Citation Impact
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article

Development of Dynamic Nonlinear Water Demand Equation and Comprehensive Dataset for Residential

Loukik S. Salvi
Communications on Applied Nonlinear Analysis
Korean Urban and Social Studies
article

Development of Dynamic Nonlinear Water Demand Equation and Comprehensive Dataset for Residential

Loukik S. Salvi
article en

Abstract

This study introduces an innovative approach to modeling residential water demand in India by developing a dynamic nonlinear water demand function. Our primary contribution is the creation of a comprehensive and dynamic dataset, which addresses the absence of such data tailored to urban settings. Utilizing this dataset, we developed a sophisticated water demand equation that enhances the accuracy of demand forecasts. Key influences analyzed include water price elasticity, household infrastructure, climatic conditions, income levels, population density, elevation, water flow, socio-economic status, peer effects, and energy costs. Our findings highlight the need to revise water pricing strategies to manage demand effectively, particularly given the significant disparities in income and infrastructure between urban and rural areas. This study underscores the importance of policy interventions in fostering sustainable water management practices that meet local needs. Additionally, we explore the anticipated impacts of climate change on future water demand in urban India, providing critical insights for policymakers. By proposing this dynamic dataset and a newly formulated water demand equation, we present a robust framework for addressing India’s water sustainability challenges, supporting informed policy decisions to mitigate water scarcity and enhance resilience in water resource management.

Communications on Applied Nonlinear AnalysisVol. 32(3s)
Openalex Percentile: Top 59%
Korean Urban and Social Studies
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Development of Dynamic Nonlinear Water Demand Equation and Comprehensive Dataset for Residential — Loukik S. Salvi · Communications on Applied Nonlinear Analysis (2024) | TGRS Research Map | TGRS