Estimation of parameters in groundwater modelling by modified Clonalg
Yükleniyor...
Dosyalar
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ivva Publishing
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The purpose of this study was to improve the optimization model for predicting more parameters in more difficult conditions (more grid cell numbers and high time interval numbers) than other studies in groundwater flow modelling. Also, the model needs fewer observation numbers for estimating parameters than other studies. In the present study, an optimization model based on model calibration was developed to estimate simultaneously four groundwater flow parameters - hydraulic conductivity, transmissivity, storage coefficient and leakance. The modified clonal selection algorithm, a class of artificial immune systems, was used as a heuristic optimization method. In order to simulate the groundwater flow, MODFLOW was used in conjunction with the model in MATLAB. The input files for MODFLOW were obtained by GMS groundwater simulator. The model was applied to two different hypothetical groundwater systems (two- and three-dimensional) under transient conditions to evaluate its performance. The results showed that the model was feasible for groundwater flow modelling and it could determine the groundwater flow parameters successfully with less observations and more grid cell numbers than the other studies.
Açıklama
This study was performed while the author was at Purdue University. The author thanks Prof. Dr Bernard Engel for his acceptance as a visiting scholar at Purdue University. Also, the author thanks The Scientific and Technological Research Council of Turkey (TUBITAK) for financial support (No. 1059B191800383).
Anahtar Kelimeler
Groundwater Modelling, Heuristic Optimization, Model Calibration, Parameter Estimation
Kaynak
Journal of Hydroinformatics
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
23
Sayı
2
Künye
Eryiğit, M. (2021). Estimation of parameters in groundwater modelling by modified Clonalg. Journal of Hydroinformatics, 23(2), 298-306.
