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A nonparametric standardized runoff index for characterizing hydrological drought on the Loess Plateau, China

Author:
Wu, Jingwen, Miao, Chiyuan, Tang, Xu, Duan, Qingyun, He, Xiaojia
Source:
Global and planetary change 2018 v.161 pp. 53-65
ISSN:
0921-8181
Subject:
El Nino, climate change, drought, humans, prediction, risk, runoff, spring, watersheds, winter, China
Abstract:
Drought is one of the world's most recurrent and destructive hazards, and the evolution of drought events has become increasingly complex against a background of climate change and changing human activities. Over the last five decades, there have been frequent droughts on the Loess Plateau in China. In this study, we used the nonparametric standardized runoff index (NSRI) to investigate the temporal characteristics of hydrological drought in 17 Loess Plateau catchments during the period 1961–2013. Furthermore, we used a cross-wavelet transform to reveal linkages between an El Niño-Southern Oscillation (ENSO) index and the NSRI series. The primary results indicated that the annual and seasonal NSRI series displayed statistically significantly downward trends in all catchments, with the only exception being the winter NSRI series in Yanhe. Furthermore, our analyses showed downward trends persisting into the future in all 17 catchments except Yanhe. We also found that, overall, the risk of hydrological drought was high on the Loess Plateau, with the mean duration at the seasonal scale exceeding 4 months and the mean duration at the annual scale exceeding 12 months. Moreover, during recent years, the trend towards hydrological drought was greater in the spring than in other seasons. ENSO events were closely associated with annual and seasonal hydrological drought on the Loess Plateau, and the impact of ENSO events was stronger in the southeast of the plateau than the northwest at both seasonal and annual scales. These results may provide valuable information about the evolutionary characteristics of hydrological drought across the Loess Plateau and may also be useful for predicting and mitigating future hydrological drought on the plateau.
Agid:
6111994