| Abstract: | In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique. |
| Genre: | Article |
| ProdID: | 70020872 |
| Citation Author: | Heidari, M.; Ranjithan, S. R. |
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| Citation End Page: | 920 |
| Citation Issue: | 4 |
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| Citation Language: | English |
| Citation Larger Work Title: | Journal of the American Water Resources Association |
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| Citation Number Of Pages: | 12 |
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| Citation Publisher: | American Water Resources Assoc |
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| Citation Search Results Text: | A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers; 1998; Article; Journal; Journal of the American Water Resources Association; Heidari, M.; Ranjithan, S. R. |
| Citation Start Page: | 909 |
| Citation Volume: | 34 |
| Citation Year: | 1998 |
| Type: | citation/reference |
| Text: | A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers; 1998; Article; Journal; Journal of the American Water Resources Association; Heidari, M.; Ranjithan, S. R. |
| URL (THUMBNAIL): | http://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg |
| Date Other: | Thu, 1 Jan 1998 00:00 -0600 |
| Publisher: | American Water Resources Assoc |
