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Response of the Shabestar Plain aquifer to climate-change scenarios through statistical and hybrid soft computing techniques
Groundwater-level prediction has a significant impact on sustainable water-resources management. In this research, the impact of climate change on groundwater level on Shabestar Plain, Iran, was investigated. First, through General Circulation Models (GCM), temperature and precipitation values were...
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Published in: | Groundwater for sustainable development 2021-11, Vol.15, p.100649, Article 100649 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Groundwater-level prediction has a significant impact on sustainable water-resources management. In this research, the impact of climate change on groundwater level on Shabestar Plain, Iran, was investigated. First, through General Circulation Models (GCM), temperature and precipitation values were projected under future scenarios of Representative Concentration Pathway (i.e., RCP2.6, RCP4.5, RCP8.5). In the next phase, groundwater-level variations in the Shabestar Plain through the Autoregressive Integrated Moving Average (ARIMA) statistical model and Artificial Neural Network (ANN) and Nonlinear Autoregressive Neural Network with Exogenous Inputs (NARX) soft-computing techniques were evaluated. The climate projections showed that the temperature would increase while precipitation would decrease in the future period (2020–2050). Comparing performance criteria among statistical and soft-computing models in simulation groundwater levels demonstrated that the Wavelet-NARX has superior performance compared to the others. Prediction of future groundwater levels showed that the average groundwater levels would decline in a future period (2020–2025) with 1.2 m, 2.2 m, and 3.0 m, under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. These results emphasize an urgent need for dynamic management for the conservation of water resources in the study area.
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•Investigates the impacts of climate change on groundwater levels in Shabestar Plain, Iran.•The capability of four GCM models in projection of future precipitation and temperature.•Groundwater levels is expected to decrease in future under RCP scenarios. |
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ISSN: | 2352-801X 2352-801X |
DOI: | 10.1016/j.gsd.2021.100649 |