Document Type : Original Article
Authors
1 Assistant Professor, Department of Civil Engineering, Materials and Energy Research Center, Dez.C., Islamic Azad University, Dezful, Iran.
2 Associate Professor, Department of Civil Engineering, Islamic Azad University, Khorramabad branch, Khorramabad, Iran
3 PhD in Water Sciences and Engineering, Department of Soil Conservation and Watershed Management, Lorestan Province Agriculture and Natural Resources Research and Education Center, Areeo, Khorramabad, Iran
Abstract
In recent years, global warming, climatic fluctuations, and the pressure of water resource extraction have led to a decline in groundwater levels. Therefore, to prevent the intensification of the above trend and to optimally manage the exploitation of groundwater resources in plains, simulating and predicting groundwater levels is essential and inevitable. To predict groundwater level changes in the Kuhdasht aquifer, meteorological parameters were first predicted and analyzed using the CIMP6 General Circulation Model under various scenarios. Then, using temperature, precipitation, and aquifer extraction data from the 2002-2022 statistical period, the performance of hybrid Artificial Neural Network-Wavelet (WANN) and Artificial Neural Network-Creative Shooter (CSO-ANN) models in estimating groundwater levels was investigated. In the next step, using the selected hybrid model, groundwater level changes in the region were predicted for the 2022-2042 statistical period. The results from the General Circulation Model indicated that with increasing temperature, precipitation decreases. The simulated temperature in all investigated climate models (SSp126, SSP245, and SSP585) for the future period (2022-2042) showed an increase compared to the baseline period in all months, while the average precipitation did not show a clear trend. Furthermore, the modeling results showed that the Artificial Neural Network-Wavelet model performed better than other models in estimating the groundwater level of the Kuhdasht plain. The results from the selected model also indicated a groundwater level decline of 3 to 4.5 meters in this plain during the years 2022-2042.
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