Reliability, resilience and vulnerability of a multipurpose storage reservoir / Confiance, résilience et vulnérabilité d'un barrage multi-objectifs

Abstract

The behaviour of statistical performance indices, namely, reliability, resilience and vulnerability for a multipurpose storage reservoir is examined. Monte Carlo simulations were carried using data of the Dharoi Reservoir (India) and the inflows to the reservoir were generated by following two approaches: long-memory models and short-memory models. Statistical behaviour of three indices were examined for two cases: (i) municipal and industrial water supply; and (ii) irrigation, thus making a total of six indices for the analysis. To interpret the behaviour of these indices, a probabilistic approach was followed. It was noted that when inflows generated using long-memory models were input in simulation, there were large variations in reliability, resilience and vulnerability among the runs. In contrast, when data from short-memory models were used, the indices were confined to a narrow band. Average values of reliabilities and their variance for both the demands were much higher when the data generated using short-memory models were used. Since natural geophysical hydrological data series display persistence, the results pertaining to long-memory model are closer to reality. It was also shown that the framework of analysis presented can be very useful for multicriteria analysis and interpretation of trade-offs in the reliability space.