Analyzing the climate sensitivity of the coupled water-electricity demand nexus in the Midwestern United States

R. Obringer, R. Kumar and R. Nateghi

Applied Energy, 2019, vol. 252, issue C, -

Abstract: Accounting for the nexus between water and electricity demand is critical for ensuring efficiency and conservation measures are successful in lowering the net water and electricity use in a city. Considering the nexus is also critical for accurately estimating the price elasticity of demand and designing effective demand response programs. The importance of the water-electricity demand nexus is rapidly increasing as cities are stressed by factors such as global climatic and socioeconomic changes as well as unprecedented rates of urbanization and growth. Despite the extensive recent research efforts on electricity and water demand modeling, significant knowledge gaps remain that are primarily rooted in (i) the use of univariate approaches that cannot adequately account for the nexus and (ii) the lack of a comprehensive assessment of the role of climate drivers on the demand nexus. To address these gaps, we propose a multivariate (i.e., multi-response), algorithmic framework for assessing the climate-sensitivity of the coupled water-electricity demand nexus. To illustrate the applicability of the proposed framework, six Midwestern cities were selected as test cases. The results indicated that climate variability alone could account for 23–71% of variability in the water-electricity demand nexus with the seasonally adjusted dataset, and 47–87% of the variability on the non-adjusted dataset. The results also revealed that water use was more climate-sensitive than electricity use. Additionally, the importance of the variability in the global climate drivers such as the El Niño/Southern Oscillation cycle was demonstrated. The modeling results suggest that stronger El Niños lead to an overall decrease in the climate-sensitive portion of the water and electricity use in the selected cities.

Keywords: Water-energy nexus; Multivariate tree boosting; Climate sensitivity; Multidimensional modeling (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.apenergy.2019.113466

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