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Prediction of Aquifer Fluctuations Using Neural Networks Models and HARTT Model (Case Study: Yazd-Ardakan Plain)
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فاطمه برزگری *   |
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Abstract: (5949 Views) |
| Over the last decades, ground waters are considered as substantial water resources in many parts of the world. Unfortunately, the intensive use of groundwater resources has often affected ground water levels. Yazd-Ardakan region is one of the critical areas from water resources perspective. This paper analyzes the impacts of climate change and human pressures on Yazd- Ardakan aquifer. HADCM3 circulation Model and different scenarios were used for future climate changes prediction in the study area. Water levels in the study aquifer were simulated using Artificial Neural Networks and HARTT model for present and future (2016-2033) periods. Validation of applied models showed that HARTT model has good ability in modeling the water table fluctuations. Ground water fluctuation prediction by HARTT model showed that if climate changes and groundwater extra exploitation continues, this trend will lead to nine m degradation in aquifer level till 2033 year. The continuation of this situation will involve serious degradation of aquifers in quantitative and qualitative terms. Therefore, with regard to limited water resources and fragile climate of the study area, it is suggested that decision makers consider this issue in planning the future perspectives of the study area. |
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| Keywords: Aquifer, HARTT Model, Artificial Neural Networks, Climate Changes |
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Full-Text [PDF 900 kb]
(28 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2017/06/6 | Accepted: 2018/01/30 | Published: 2018/10/10
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