Searching for the optimal drought index and time scale combination to detect drought: a case study from the lower Jinsha River Basin, China

Autor: Javier Fluixá-Sanmartín, Deng Pan, Luzia Fischer, Boris Orlowsky, Javier García-Hernández, Frédéric Jordan, Christoph Haemmig, Fangwei Zhang, Jijun Xu
Rok vydání: 2017
Popis: Drought indices based on precipitation are commonly used to identify and characterize droughts. Due to the general complexity of droughts, comparison of index-identified events with droughts rely typically on model simulations of the complete hydrological system (e.g., soil humidity or river discharges), entailing potentially significant uncertainties. The present study explores the potential of using precipitation based indices to reproduce observed droughts in the lower part of the Jinsha River Basin, proposing an innovative approach for a catchment-wide drought detection and characterization. Two new indicators, namely the Overall Drought Extension (ODE) and the Overall Drought Intensity (ODI), have been developed. These indicators aim at identifying and characterizing drought events at basin scale, using results from four meteorological drought indices (Standardized Precipitation Index, SPI; Rainfall Anomaly Index, RAI; Percent of Normal precipitation, PN; Deciles, DEC) calculated at different locations of the basin and for different time scales. Collected historical information on drought events is used to contrast results obtained with the indicators. This method has been successfully applied to the lower Jinsha River Basin, in China, a region prone to frequent and severe droughts. Historical drought events occurred from 1960 to 2014 have been compiled and catalogued from different sources, in a challenging process. The analysis of the newly developed indicators shows a good agreement with the recorded historical drought at basin scale. It has been found that the combinations of index and time scale that best reproduces observed events are the SPI-12 and PN-12 for long droughts (1 year or more) and the RAI-6, PN-6 and DEC-6 for shorter or more consecutive events.
Databáze: OpenAIRE