A Hybrid Model-Based Adaptive Framework for the Analysis of Climate Change Impact on Reservoir Performance

P Biglarbeigi,P Griffiths,R Mcdermott,W A Strong,D Finlay

doi:10.1007/s11269-020-02654-w

P Biglarbeigi, P Griffiths + Show 3 more

Open Access

https://doi.org/10.1007/s11269-020-02654-w

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Abstract

Climate change and population growth have influenced social and physical water scarcity in many regions. Accordingly, the future performance of water storage reservoirs, as one of the fundamental elements in the water resource management, are anticipated to be affected by climate change. This study reports on a framework that can model Reliability-Resiliency-Vulnerability (RRV) measures of water reservoirs in the context of climate change. The framework first develops a hydrological model of a reservoir system using its historical data. The model is then optimised to minimise the water deficit and flooding around the catchment area of the reservoir. The resulting optimal policies are simulated back to the model considering the GCMs. Finally, RRV indices are calculated. RRV indices are effective measures for defining the performance of reservoir systems. Reliability is defined as the probability of the failure of the system, Resiliency is defined as the time needed for the system to go back to its satisfactory state once it entered the failure state, and Vulnerability is defined as the “magnitude of the failure” of a system. The proposed framework has been applied to a reservoir system located in the south-west of Iran on the Dez river. The results show climate change may increase the reliability and resiliency of the system under study while increasing its vulnerability. Therefore, the output of this framework can also provide supplementary information to authorities and decision-makers to inform future water management and planning policies.

Highlights

Global water resources are rarely distributed in proportion to the population density of any particular region (Oki and Kanae 2006). Mekonnen and Hoekstra (2016) estimated that 4 billion of the world’s population encounter water scarcity, for at least a short period of time in a year
In order to represent a better understanding of the framework and the effect of climate change on Dez reservoir operation, the results are reported on a mean annual basis for 2020, 2050, 2080, and 2100
The same Kernel Density Distribution Mapping (KDDM) parameters obtained from bias-correction of historical data are used to reduce the bias for the projection of precipitation and evaporation

Summary

Introduction

Global water resources are rarely distributed in proportion to the population density of any particular region (Oki and Kanae 2006). Mekonnen and Hoekstra (2016) estimated that 4 billion of the world’s population encounter water scarcity, for at least a short period of time in a year. Global water resources are rarely distributed in proportion to the population density of any particular region (Oki and Kanae 2006). Mekonnen and Hoekstra (2016) estimated that 4 billion of the world’s population encounter water scarcity, for at least a short period of time in a year. Water scarcity is one of the major issues facing different societies today. Climate change is a growing factor that is affecting water systems, hydrological cycle, and its regime (Hallett 2002). Alterations in the hydrological cycle have severe impacts on the environmental, economic, and social aspects of societies. The variability in water resource availability, due to global warming and distribution of the population in different areas, will affect the estimations of the impacts of climate change (Arnell 2004)

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