Optimal Design of Groundwater Monitoring Network Using Kalman Filtering and Genetic Algorithm
碩士 === 國立交通大學 === 土木工程系 === 91 === This study develops a groundwater monitoring network design model that integrates the Kalman Filtering, groundwater numerical model and a Genetic Algorithm. The KALMOD is an existing model that integrates the Kalman filter and MODFLOW. KALMOD functions primarily to...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2002
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| Online Access: | http://ndltd.ncl.edu.tw/handle/04509401139286834354 |
| Summary: | 碩士 === 國立交通大學 === 土木工程系 === 91 === This study develops a groundwater monitoring network design model that integrates the Kalman Filtering, groundwater numerical model and a Genetic Algorithm. The KALMOD is an existing model that integrates the Kalman filter and MODFLOW. KALMOD functions primarily to calculate the head that is updated according to the data of a monitoring network and its uncertainty represented by the covariance. However, the KALMOD can not determine the optimal monitoring network. Therefore, this work combines it with a Genetic Algorithm to compute the optimal monitoring network automatically. The network design focuses mainly on reducing the uncertainty of the updated groundwater head at the monitoring sites. The proposed model can describe the physical conditions of a groundwater system through the numerical modeling and consider the modeling uncertainty. The Kalman Filtering also clearly identifies the role of the monitoring system. A hypothetical case is also presented to verify the effectiveness of the proposed model and investigate those factors affecting the network design. Simulation results demonstrate that success of the monitoring network design largely depends on the accuracy of the numerical model.
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