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DROUGT IDENTIFICATION USING A STOCHASTIC APPROACH: A COMPARISON BETWEEN HYDROMETEOROGICAL AND HYDROLOGICAL INDEXES

Congress: 2008
Author(s): Brunella Bonaccorso, Antonino Cancelliere
Brunella Bonaccorso Department of Civil and Environmental Engineering University of Catania V.le A. Doria 6, 95125 Catania, Italy Antonino Cancelliere Department of Civil and Environmental Engineering University of Catania V.le A. Doria 6, 95125 Cata
AbstractWater resources management under shortage conditions due to drought is a rather complicated task: in particular, there is no general agreement neither regarding drought definitions, the analytical techniques for drought risk assessment and the proper mitigation measures. Following the well-known literature, it may distinguish between drought, which is a natural temporary condition of consistent reduction in precipitation and water availability with respect to normal values, spanning along a significant period of time and covering a wide region, and aridity, which is a natural permanent climatic condition with very low average annual or seasonal precipitation. Since 60ís, several drought indexes were proposed, each with reference to a particular definition. Some indices referring to meteorological droughts are based on the rainfall series, such as the Standard Precipitation Index (SPI) (McKee et al., 1993); other indices describe hydrological or agricultural droughts, such as the Surface Water Supply Index (SWSI) (Gibbs e Maher, 1967). The aim of the present study is to investigate the potential of SPI index as a proxy for monitoring hydrological droughts, by coupling a stochastic model for generating daily rainfall series (based on a two-state Markov process) with a lumped conceptual daily rainfall-runoff model (IHACRES). More specifically, droughts are identified and characterized first by means of SPI series at a proper aggregation time scale k (i.e. 6 months) computed on synthetic rainfall series, and then by computing SWSI index or by applying the run method directly on runoff series. Then a statistical comparison between the characteristics of the identified drought events is made in order to determine the level of agreement of the derived results, potentially stating the capability of SPI index to monitor also hydrological droughts. Application of the proposed methodology is carried out with reference to the river basin in Sicily, Italy.
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