Uncertainties in assessing hydrological drought using streamflow drought index for the upper Yangtze River basin

Abstract

Drought is an environmental disaster which is frequently and world-widely occurred in recent years. Precisely assessment and prediction of drought is important for water resources planning and management. Sampling uncertainty commonly exists in frequency analysis-based hydrological drought assessment due to the limited length of observed data series. Based on the daily streamflow data of the Yichang hydrological station from 1882 to 2009, the streamflow drought index (SDI) series with 12-month time scale was calculated and the hydrological drought of the upper Yangtze River was assessed. By employing the bootstrap method, the impact of sample size on the sampling uncertainty of the SDI was analyzed. The longer record is used to derive the SDI, the narrower the shifting ranges of the parameters of the streamflow volume probability distribution functions and corresponding interval estimators of SDI are. The upper Yangtze River basin has experienced successive alternation of wet and dry years, and the spring seems to be the driest season within a year. The current difficulty in fighting against increasing droughts in upper Yangtze River basin is upgrading. Considering the possible misjudgment of drought degree results from the sampling uncertainty, attention should be paid to the preparation of drought relief strategies in order to reduce the potential losses.