Articles | Volume 21, issue 11
https://doi.org/10.5194/hess-21-5477-2017
https://doi.org/10.5194/hess-21-5477-2017
Research article
 | 
07 Nov 2017
Research article |  | 07 Nov 2017

Understanding and seasonal forecasting of hydrological drought in the Anthropocene

Xing Yuan, Miao Zhang, Linying Wang, and Tian Zhou

Abstract. Hydrological drought is not only caused by natural hydroclimate variability but can also be directly altered by human interventions including reservoir operation, irrigation, groundwater exploitation, etc. Understanding and forecasting of hydrological drought in the Anthropocene are grand challenges due to complicated interactions among climate, hydrology and humans. In this paper, five decades (1961–2010) of naturalized and observed streamflow datasets are used to investigate hydrological drought characteristics in a heavily managed river basin, the Yellow River basin in north China. Human interventions decrease the correlation between hydrological and meteorological droughts, and make the hydrological drought respond to longer timescales of meteorological drought. Due to large water consumptions in the middle and lower reaches, there are 118–262 % increases in the hydrological drought frequency, up to 8-fold increases in the drought severity, 21–99 % increases in the drought duration and the drought onset is earlier. The non-stationarity due to anthropogenic climate change and human water use basically decreases the correlation between meteorological and hydrological droughts and reduces the effect of human interventions on hydrological drought frequency while increasing the effect on drought duration and severity. A set of 29-year (1982–2010) hindcasts from an established seasonal hydrological forecasting system are used to assess the forecast skill of hydrological drought. In the naturalized condition, the climate-model-based approach outperforms the climatology method in predicting the 2001 severe hydrological drought event. Based on the 29-year hindcasts, the former method has a Brier skill score of 11–26 % against the latter for the probabilistic hydrological drought forecasting. In the Anthropocene, the skill for both approaches increases due to the dominant influence of human interventions that have been implicitly incorporated by the hydrological post-processing, while the difference between the two predictions decreases. This suggests that human interventions can outweigh the climate variability for the hydrological drought forecasting in the Anthropocene, and the predictability for human interventions needs more attention.

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Short summary
Understanding and forecasting of hydrological drought in the Anthropocene are grand challenges. Human interventions exacerbate hydrological drought conditions and result in earlier drought onset. By considering their effects in the forecast, the probabilistic drought forecast skill increases for both climate-model-based and climatology methods but their difference decreases, suggesting that human interventions can outweigh the climate variability for drought forecasting in the Anthropocene.