{"title":"A Close-to-Optimal Discretization Strategy for Pumping Test Numerical Simulation.","authors":"Ronny Figueroa, Etienne Bresciani","doi":"10.1111/gwat.13442","DOIUrl":null,"url":null,"abstract":"<p><p>Numerical modeling offers a valuable alternative to analytical solutions for pumping test analysis. However, little is known about how discretization impacts results accuracy and runtime. This study presents a systematic method for defining the spatiotemporal discretization of pumping test numerical models based on dimensionless parameters. Two types of analysis are considered: one where observations are made in the pumping well, and another one where observations are made in different wells. The influence of the discretization parameters on results accuracy and runtime is investigated and an optimal set of parameters is determined that minimizes runtime while maintaining the maximum error under 1% for an \"average\" aquifer. Lower runtimes are achieved when the analysis focuses on the pumping well, which is attributed to the steady-state analytical solution approximating drawdown in the well in the numerical scheme employed. Additional tests demonstrate the robustness of the derived set of parameters in different configurations.</p>","PeriodicalId":94022,"journal":{"name":"Ground water","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ground water","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/gwat.13442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Numerical modeling offers a valuable alternative to analytical solutions for pumping test analysis. However, little is known about how discretization impacts results accuracy and runtime. This study presents a systematic method for defining the spatiotemporal discretization of pumping test numerical models based on dimensionless parameters. Two types of analysis are considered: one where observations are made in the pumping well, and another one where observations are made in different wells. The influence of the discretization parameters on results accuracy and runtime is investigated and an optimal set of parameters is determined that minimizes runtime while maintaining the maximum error under 1% for an "average" aquifer. Lower runtimes are achieved when the analysis focuses on the pumping well, which is attributed to the steady-state analytical solution approximating drawdown in the well in the numerical scheme employed. Additional tests demonstrate the robustness of the derived set of parameters in different configurations.