Title: A framework for the assessment of reservoir operation adaptation to climate change in an arid region

Authors: Mohammad Ebrahim Banihabib; Khadijeh Hasani; Ali Reza Massah Bavani; Kamran Asgari

Addresses: Department of Irrigation and Drainage Engineering, University College of Abureyhan, University of Tehran, P.O. Box 3391653755, Tehran, Iran ' Department of Irrigation and Drainage Engineering, University College of Abureyhan, University of Tehran, P.O. Box 3391653755, Tehran, Iran ' Department of Irrigation and Drainage Engineering, University College of Abureyhan, University of Tehran, P.O. Box 3391653755, Tehran, Iran ' Young Researchers and Elite Club, Khorasgan (Isfahan) Branch, Islamic Azad University, Isfahan, Iran

Abstract: It is essential to assess the adaptation of reservoir operation to climate change in arid regions. The main objective of this research is to propose a framework for assessment of reservoir rule-curve (RRC) adaptation for climate change scenarios. The framework is applied to an arid zone in Iran and consists of the three models: downscaling, rainfall-runoff and reservoir optimisation models. LARS-WG is tested in 99% confidence level before to using it as downscaling model. Seven artificial neural network models are proposed, examined and compared with IHACRES to find proper rainfall-runoff model for arid zone. Current and adapted reservoir rule curves are derived by dynamic programming optimisation. The results demonstrate capability of proposed framework in assessment of adaptation and show that global warming negatively influences proposed index (water supply index) in normal and wet years, but has positive influence for dry years. It also improves reservoir reliability, but it cannot restore current reliability.

Keywords: arid regions; artificial neural networks; ANNs; climate change; adaptation assessment; downscaling; global warming; IHACRES; rainfall runoff modelling; reservoir rule curves; reservoir operations; water supply index; Iran; reservoir optimisation; reservoir reliability.

DOI: 10.1504/IJGW.2016.075446

International Journal of Global Warming, 2016 Vol.9 No.3, pp.286 - 305

Received: 17 Jun 2014
Accepted: 10 Aug 2014
Published online: 23 Mar 2016 *

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