An empirical method for approximating stream baseflow time series using groundwater table fluctuations

• Published in: Journal of hydrology (Amsterdam) Vol. 519; pp. 1031 - 1041
• Main Authors: Meshgi, Ali, Schmitter, Petra, Babovic, Vladan, Chui, Ting Fong May
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 27.11.2014; Elsevier
• Subjects: artificial intelligence; base flow; Baseflow; basins; Earth sciences; Earth, ocean, space; Empirical equation; empirical research; equations; Exact sciences and technology; Genetic Programming; groundwater; Hydrology. Hydrogeology; mathematical models; Numerical modeling; Singapore; soil; streams; time series analysis; United States; water table; watershed management; watersheds; Far East; Asia; Singapore; United States; Numerical modeling; Baseflow; Empirical equation; Genetic Programming; base flow; streams; ground water; vegetation; artificial intelligence; drainage basins; aquifers; fluctuations; management; numerical models; discharge; soils

•Genetic programming is a successful tool for predicting baseflow.•Empirical equation predicts baseflow using groundwater table fluctuations.•The proposed equation performs as well as a recursive filter or a numerical model.•The generalized equation predicts baseflow irrespective of land use or scal...