Integrated Methodological Framework for Assessing the Risk of Failure in Water Supply Incorporating Drought Forecasts. Case Study: Andean Regulated River Basin

Alex Avilés (), Abel Solera Solera, Javier Paredes-Arquiola and María Pedro-Monzonís
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Alex Avilés: Universidad de Cuenca
Abel Solera Solera: Universitat Politècnica de València
Javier Paredes-Arquiola: Universitat Politècnica de València
María Pedro-Monzonís: Universitat Politècnica de València

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 4, No 2, 1209-1223

Abstract: Abstract Hydroclimatic drought conditions can affect the hydrological services offered by mountain river basins causing severe impacts on the population, becoming a challenge for water resource managers in Andean river basins. This study proposes an integrated methodological framework for assessing the risk of failure in water supply, incorporating probabilistic drought forecasts, which assists in making decisions regarding the satisfaction of consumptive, non-consumptive and environmental requirements under water scarcity conditions. Monte Carlo simulation was used to assess the risk of failure in multiple stochastic scenarios, which incorporate probabilistic forecasts of drought events based on a Markov chains (MC) model using a recently developed drought index (DI). This methodology was tested in the Machángara river basin located in the south of Ecuador. Results were grouped in integrated satisfaction indexes of the system (DSIG). They demonstrated that the incorporation of probabilistic drought forecasts could better target the projections of simulation scenarios, with a view of obtaining realistic situations instead of optimistic projections that would lead to riskier decisions. Moreover, they contribute to more effective results in order to propose multiple alternatives for prevention and/or mitigation under drought conditions.

Keywords: Risk assessment; Probabilistic drought forecasts; Simulation of stochastic scenarios; Water resource systems management (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11269-017-1863-7

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