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Congress: 2008
Author(s): ARONICA Giuseppe T. (1), BONACCORSO Brunella (2), CANCELLIERE Antonino (2)
1 Department of Civil Engineering University of Messina, Strada Panoramica dello Stretto, 98166 Messina - Italy 2 Department of Civil and Environmental Engineering University of Catania V.le A. Doria 6, 95125 Catania, Italy

Keyword(s): droughts, monitoring, hydrology, water management
AbstractWater resources management under shortage conditions due to drought poses several problems. In particular, there is no general agreement neither regarding drought definitions, the methods to be adopted for drought risk assessment nor the proper mitigation measures. Since the 60ís, several drought indices have been proposed with the objective to identify and characterize droughts. Some indices related to meteorological drought are based on the rainfall and temperature series, such as the Palmer index, or only on precipitation, like the Standard Precipitation Index (SPI); other indices describe hydrological droughts, such as the Surface Water Supply Index (SWSI). The aim of the present study is to investigate the potential of SPI index as a proxy for monitoring hydrological droughts with reference to one river basin in Sicily, Italy. More specifically, droughts are identified and characterized by means of SPI series at a proper aggregation time scale k computed on synthetic rainfall series, and by computing the SWSI index or by applying the run method directly on runoff series. The synthetic series are generated 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). Then, a statistical comparison between the characteristics of the identified drought events is carried out making use of several statistical tests, in order to determine the level of agreement between droughts identified by the different indices thus verifying the capability of SPI index to monitor also hydrological droughts. Results indicate that SPI has a potential to monitor hydrological droughts, provided an appropriate time scale is choosen for its computation.
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