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Energy-Based Modeling of Water Withdrawals in the Snake River Basin Using Refined K-Factors and Power-Consumption Coefficients
Conference proceeding

Energy-Based Modeling of Water Withdrawals in the Snake River Basin Using Refined K-Factors and Power-Consumption Coefficients

Sai Teja Kothapalli, Brian K. Johnson and Yacine Chakhchoukh
2026 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), pp.1-5
2026 IEEE/PES Transmission and Distribution Conference and Exposition (T&D) (Chicago, IL, 05/04/2026–05/07/2026)
06/17/2026

Abstract

Energy Equations Head Modeling Point cloud compression Power demand power-consumption coefficients Pumps regression analysis resource management Rivers Snake River U.S. Geological Survey (USGS) data Water water withdrawals Irrigation Water Rights
The energy needed to pump water from the Snake River Basin to the Boise metropolitan area in southern Idaho is determined in this study by utilizing updated datasets and modeling approaches. We refine previous methods based on power-consumption coefficients (PCCs) and K-factors by using recent U.S. Geological Survey (USGS) data from 39 pump locations, including elevation measurements and discharge rates. Regression analysis allows us to derive a more accurate model that shows significant agreement with observed data for estimating energy demands related to water withdrawals. When direct monitoring is not feasible, the results demonstrate how these enhanced coefficients can be applied to contemporary water systems, providing a dependable and affordable method of calculating withdrawals. Given the conflicting demands of population increase, climate unpredictability and competing water rights in the Snake River Basin, our model offers a comprehensive framework for measuring energy-water interdependence. When compared to historical methods, the improved PCC approach significantly lowers withdrawal estimation errors, providing utilities with a vital tool for infrastructure design in the face of hydrological uncertainty. This work helps sustainable resource management in the area and provides water districts with a scalable tool for estimating withdrawals in unmonitored locations.
url
doi.org/10.1109/TD48022.2026.11562834View

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