Automating physics-based models to estimate thermoelectric-power water use

IF 4.6 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2025-02-01 Epub Date: 2024-11-14 DOI:10.1016/j.envsoft.2024.106265
M.A. Harris , T.H. Diehl , L.E. Gorman Sanisaca , A.E. Galanter , M.A. Lombard , K.D. Skinner , C. Chamberlin , B.A. McCarthy , R. Niswonger , J.S. Stewart , K.J. Valseth
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Abstract

Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).
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自动化基于物理的模型来估计热电-电力-水的使用
在美国,热电(TE)发电厂的取水量比任何其他用水部门都要多,而且耗水量很大,特别是在缺水地区。历史TE用水数据不一致、不完整或存在差异,因此研究越来越关注使用建模方法提高TE用水数据的准确性和可用性。本文描述并测试了开发用于自动化和更新先前发布的基于物理的TE用水模型的新代码。利用基于自动化物理的模型,计算了2008-2020年历史再分析期间共有1341家TE发电厂的每月TE电力取水量和耗水量。更新和自动化的基于物理的热电发电用水模型提供了与空间和时间相关的TE用水估算,这些估算是一致的、可重复的、透明的,并且可以有效地为美国相邻地区(CONUS)的公用事业规模的用水TE发电厂生成。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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