{"title":"A Probabilistic Approach for Spring Recession Flows Analysis","authors":"E. Carlier, J. E. Khattabi","doi":"10.4236/OJMH.2015.52002","DOIUrl":null,"url":null,"abstract":"Spring recession flows are analyzed from a Bayesian point of view. Two \ngeneral equations are derived and it is shown that the classical formulas of \nrecession flow are particular cases of both equations. It is shown that most of \nthe recession equations reflect a non-Markovian process. That means that the \ngroundwater storage exhibits a memory effect and that there is a nonlinear \nrelationship between flow and storage. The Bayesian approach presented in this \npaper makes it possible to give a probabilistic meaning to recession flow \nequations derived according to a physical approach and can be an alternative to \nthe study of complex reservoir for which the physical processes governing \nrecession flow are unclear. Twelve spring recession flow series are analysed in \norder to validate the probabilistic approach presented in this paper and a \nconceptual model of storage-outflow is proposed.","PeriodicalId":70695,"journal":{"name":"现代水文学期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"现代水文学期刊(英文)","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.4236/OJMH.2015.52002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Spring recession flows are analyzed from a Bayesian point of view. Two
general equations are derived and it is shown that the classical formulas of
recession flow are particular cases of both equations. It is shown that most of
the recession equations reflect a non-Markovian process. That means that the
groundwater storage exhibits a memory effect and that there is a nonlinear
relationship between flow and storage. The Bayesian approach presented in this
paper makes it possible to give a probabilistic meaning to recession flow
equations derived according to a physical approach and can be an alternative to
the study of complex reservoir for which the physical processes governing
recession flow are unclear. Twelve spring recession flow series are analysed in
order to validate the probabilistic approach presented in this paper and a
conceptual model of storage-outflow is proposed.