Abstract
Abstract. Climate change is predicted to affect water resources infrastructure due to its effect on rainfall, temperature and evapotranspiration. However, there are huge uncertainties on both the magnitude and direction of these effects. The Pong reservoir on the Beas River in northern India serves irrigation and hydropower needs. The hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall; the changing pattern of the latter and the predicted disappearance of the former will have profound effects on the performance of the reservoir. This study employed a Monte-Carlo simulation approach to characterise the uncertainties in the future storage requirements and performance of the reservoir. Using a calibrated rainfall-runoff (R-R) model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change perturbed future scenarios. The resulting runoff ensembles were used to simulate the behaviour of the reservoir and determine "populations" of reservoir storage capacity and performance characteristics. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the uncertainties. The results show that contrary to the usual practice of using single records, there is wide variability in the assessed impacts. This variability or uncertainty will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of its sheer magnitude as demonstrated in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.
Highlights
Climate change is predicted to affect the hydrology of most regions through its influence on temperature, rainfall, evapotranspiration (IPCC, 2007) and the runoff and performance of water resources infrastructures such as reservoirs
HYSIM has been extensively used in several research studies including snowy catchments of the United Kingdom to address climate change impacts issues (Murphy et al, 2006)
The Monte Carlo experiments have revealed the limitation of single runoff impact models for water resources impact assessments
Summary
Climate change is predicted to affect the hydrology of most regions through its influence on temperature, rainfall, evapotranspiration (IPCC, 2007) and the runoff and performance of water resources infrastructures such as reservoirs. These impacts must be quantified for better planning and operation of water resource systems. This has been attempted using outputs from general circulation models (GCMs) to force catchment hydrological models for the assessment of runoff impacts. To avoid the complications and uncertainties in downscaled GCM climate predictions, change factor (delta perturbation) method is suggested, in which plausible changes in the runoff impacting weather variables such as precipitation and temperature are assumed and the effect
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