{"title":"分析运输方程参数估计研究","authors":"Andrew Mills","doi":"10.1111/gwmr.12684","DOIUrl":null,"url":null,"abstract":"Three new programs have been developed to perform parameter estimation to assist in the calibration of analytical contaminant transport models. The Domenico equation was chosen as an example analytical model for each of the three programs rather than a model with the exact solution, because the former is a closed‐form expression involving significantly less processing time. One of the programs studied is a quasi‐exhaustive search method and the second is a successive parameter variation method. The third program is based on Box's Complex nonlinear, direct‐search optimization method. The three programs and an already available calibration tool (PEST) were compared in tests using data from two different sites in southeastern Pennsylvania. These tests demonstrated the validity of the three programs as examples to assist the calibration of groundwater analytical transport models. The final estimates for the parameter values for the three methods and PEST applied to the data from each of the two sites compared quite closely and, with two exceptions were well within an order of magnitude of each other. The three newly available programs individually should serve as calibrating tools indispensable for field hydrogeologists, environmental project managers, and others who have been asked to run analytical transport models. The results from the runs performed on the two sites indicate the Complex method to be the best option as a calibration tool, with the quasi‐exhaustive method and the successive parameter estimation method being acceptable alternatives.","PeriodicalId":501449,"journal":{"name":"Groundwater Monitoring & Remediation","volume":"26 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Studies in Parameter Estimation for Analytical Transport Equations\",\"authors\":\"Andrew Mills\",\"doi\":\"10.1111/gwmr.12684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Three new programs have been developed to perform parameter estimation to assist in the calibration of analytical contaminant transport models. The Domenico equation was chosen as an example analytical model for each of the three programs rather than a model with the exact solution, because the former is a closed‐form expression involving significantly less processing time. One of the programs studied is a quasi‐exhaustive search method and the second is a successive parameter variation method. The third program is based on Box's Complex nonlinear, direct‐search optimization method. The three programs and an already available calibration tool (PEST) were compared in tests using data from two different sites in southeastern Pennsylvania. These tests demonstrated the validity of the three programs as examples to assist the calibration of groundwater analytical transport models. The final estimates for the parameter values for the three methods and PEST applied to the data from each of the two sites compared quite closely and, with two exceptions were well within an order of magnitude of each other. The three newly available programs individually should serve as calibrating tools indispensable for field hydrogeologists, environmental project managers, and others who have been asked to run analytical transport models. The results from the runs performed on the two sites indicate the Complex method to be the best option as a calibration tool, with the quasi‐exhaustive method and the successive parameter estimation method being acceptable alternatives.\",\"PeriodicalId\":501449,\"journal\":{\"name\":\"Groundwater Monitoring & Remediation\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Groundwater Monitoring & Remediation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/gwmr.12684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Groundwater Monitoring & Remediation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/gwmr.12684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
我们开发了三个新程序来进行参数估计,以帮助校准污染物迁移分析模型。这三个程序都选择了多梅尼科方程作为分析模型的示例,而不是精确解的模型,因为前者是闭式表达,处理时间大大减少。所研究的程序之一是准穷举搜索法,第二个是连续参数变化法。第三个程序基于 Box 的复杂非线性直接搜索优化方法。在使用宾夕法尼亚州东南部两个不同地点的数据进行的测试中,对这三个程序和已有的校准工具(PEST)进行了比较。这些测试证明了这三个程序作为协助校准地下水分析传输模型的示例的有效性。这三种方法和 PEST 应用于两个地点数据的参数值的最终估计值非常接近,除两个例外情况外,彼此都在一个数量级之内。对于现场水文地质学家、环境项目经理和其他被要求运行分析迁移模型的人来说,这三个新推出的程序都是不可或缺的校准工具。在两个地点进行的运行结果表明,复合方法是校准工具的最佳选择,而准穷举法和连续参数估计法是可以接受的替代方法。
Studies in Parameter Estimation for Analytical Transport Equations
Three new programs have been developed to perform parameter estimation to assist in the calibration of analytical contaminant transport models. The Domenico equation was chosen as an example analytical model for each of the three programs rather than a model with the exact solution, because the former is a closed‐form expression involving significantly less processing time. One of the programs studied is a quasi‐exhaustive search method and the second is a successive parameter variation method. The third program is based on Box's Complex nonlinear, direct‐search optimization method. The three programs and an already available calibration tool (PEST) were compared in tests using data from two different sites in southeastern Pennsylvania. These tests demonstrated the validity of the three programs as examples to assist the calibration of groundwater analytical transport models. The final estimates for the parameter values for the three methods and PEST applied to the data from each of the two sites compared quite closely and, with two exceptions were well within an order of magnitude of each other. The three newly available programs individually should serve as calibrating tools indispensable for field hydrogeologists, environmental project managers, and others who have been asked to run analytical transport models. The results from the runs performed on the two sites indicate the Complex method to be the best option as a calibration tool, with the quasi‐exhaustive method and the successive parameter estimation method being acceptable alternatives.