ISPRS Int. J. Geo-Inf. 2018, 7(1), 22; doi:10.3390/ijgi7010022
Inverse Parametrization of a Regional Groundwater Flow Model with the Aid of Modelling and GIS: Test and Application of Different Approaches
Muhammad Usman 1,2,*
, Thomas Reimann 3, Rudolf Liedl 3, Azhar Abbas 2, Christopher Conrad 1 and Shoaib Saleem 4
, Thomas Reimann 3, Rudolf Liedl 3, Azhar Abbas 2, Christopher Conrad 1 and Shoaib Saleem 41
Department of Remote Sensing, Institute for Geography and Geology, Julius Maximillian’s University Wuerzburg, Oswald Külpe Weg 86, 97074 Wuerzburg, Germany
2
Department of Irrigation & Drainage, Department of Resource Economics, University of Agriculture, 38040 Faisalabad, Pakistan
3
Institute for Groundwater Management, TU Dresden, Bergstrasse 66, 01069 Dresden, Germany
4
School of Engineering, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
*
Author to whom correspondence should be addressed.
Received: 15 November 2017 / Revised: 30 December 2017 / Accepted: 6 January 2018 / Published: 12 January 2018
(This article belongs to the Special Issue Geographic Information Science and Spatial Analysis in Water Resources)
Abstract
The use of inverse methods allow efficient model calibration. This study employs PEST to calibrate a large catchment scale transient flow model. Results are demonstrated by comparing manually calibrated approaches with the automated approach. An advanced Tikhonov regularization algorithm was employed for carrying out the automated pilot point (PP) method. The results indicate that automated PP is more flexible and robust as compared to other approaches. Different statistical indicators show that this method yields reliable calibration as values of coefficient of determination (R2) range from 0.98 to 0.99, Nash Sutcliffe efficiency (ME) range from 0.964 to 0.976, and root mean square errors (RMSE) range from 1.68 m to 1.23 m, for manual and automated approaches, respectively. Validation results of automated PP show ME as 0.969 and RMSE as 1.31 m. The results of output sensitivity suggest that hydraulic conductivity is a more influential parameter. Considering the limitations of the current study, it is recommended to perform global sensitivity and linear uncertainty analysis for the better estimation of the modelling results. View Full-TextKeywords:
groundwater; sensitivity analysis; pilot-point-approach; tikhonov regularization; PEST; inverse parameterization
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Usman, M.; Reimann, T.; Liedl, R.; Abbas, A.; Conrad, C.; Saleem, S. Inverse Parametrization of a Regional Groundwater Flow Model with the Aid of Modelling and GIS: Test and Application of Different Approaches. ISPRS Int. J. Geo-Inf. 2018, 7, 22.
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ISPRS Int. J. Geo-Inf.
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