Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/13309
Title: GENETIC ALGORITHM ASSISTED ANALYSIS OF PUMPING TEST DATA
Authors: Rajesh, M.
Keywords: CIVIL ENGINEERING;GENETIC ALGORITHM ASSISTED ANALYSIS;PUMPING TEST DATA;GENETIC ALGORITHM
Issue Date: 2005
Abstract: Adequate and reliable estimates of aquifer parameters are of utmost importance for proper management of vital groundwater resources. The pumping (aquifer) test is the standard technique for estimating aquifer parameters viz., transmissivity (T), storage coefficient (S), specific yield (Sy), leakage factor (L), and delay index (lea), for which the graphical method is widely used. Various numerical methods have been developed to estimate aquifer parameters and eliminate the subjectivity of traditional graphical type curve methods. In the present day, the efficacy of the genetic algorithm (GA) optimization technique is assessed in estimating the leaky confined and unconfined. aquifer parameters from the pumping test data. Computer codes were developed to obtain optimal leaky confined and unconfined aquifer parameters using GA optimization technique. In case of unconfined aquifer, a detailed statistical analysis is carried out to study the effect of three objective functions on the estimated parameters, when the data contain errors. The results indicate that these objective functions induce a bias in the estimated parameters and as such selecting a suitable objective function should also be given due importance in the aquifer parameter estimation. Applicability, adequacy, and robustness of the developed codes were tested using 2 sets of the published aquifer test data. The GA technique yielded significantly low values of the sum of squares errors (SSE) as compared to graphical method. The results revealed that the GA technique is an efficient and reliable method for estimating various aquifer parameters, especially in the simulation when the graphical matching is poor. Also, it was found that because of its inherent characteristics, GA avoids the subjectivity, long computation time and ill- posedness often associated with conventional optimization technique. The GA- based computer programs with interactive windows developed in this study are user- friendly and can serve as a teaching and research tool, which could also be useful for practicing hydrologists and hydro geologists.
URI: http://hdl.handle.net/123456789/13309
Other Identifiers: M.Tech
Research Supervisor/ Guide: Prasad, K. S. Hari
Kashyap, Deepak
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (Civil Engg)

Files in This Item:
File Description SizeFormat 
G12275.pdf2.53 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.