Abstract
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.
Highlights
Drought is a natural phenomenon occurring due to climate variability that is associated with oceanic and/or terrestrial anomalies (Hong and Kalnay, 2000; Hoerling and Kumar, 2003)
The reasons are threefold: (1) a skilful seasonal forecasting of streamflow usually occurs over basins with large storages of snow, surface and/or subsurface water (Wood and Lettenmaier, 2008; Koster et al, 2010), and strong control from initial hydrological conditions limits the added value from climate predictions (Wood et al, 2016; Yuan, 2016); (2) unlike meteorological drought forecasts, both agricultural and hydrological drought forecasts are influenced by the uncertainty in the hydrological model, and the hydrological drought forecasting tends to be more challenging since the errors from upstream areas can be transferred to or even amplified in downstream areas; and (3) many river basins are altered by human activities, where the management impacts are often neglected in most dynamical forecasting systems
Except for the Tangnaihai gauge in the headwater region, the Standardized Precipitation Index (SPI) timescales with the maximum correlation are longer for observed streamflow than that for naturalized streamflow, suggesting that human interventions basically make the hydrological drought respond to longer timescale of meteorological drought
Summary
Drought is a natural phenomenon occurring due to climate variability that is associated with oceanic and/or terrestrial anomalies (Hong and Kalnay, 2000; Hoerling and Kumar, 2003). The reasons are threefold: (1) a skilful seasonal forecasting of streamflow usually occurs over basins with large storages of snow, surface and/or subsurface water (Wood and Lettenmaier, 2008; Koster et al, 2010), and strong control from initial hydrological conditions limits the added value from climate predictions (Wood et al, 2016; Yuan, 2016); (2) unlike meteorological drought forecasts, both agricultural and hydrological drought forecasts are influenced by the uncertainty in the hydrological model, and the hydrological drought forecasting tends to be more challenging since the errors from upstream areas can be transferred to or even amplified in downstream areas; and (3) many river basins are altered by human activities, where the management impacts are often neglected in most dynamical forecasting systems. Both naturalized and observed streamflow along the mainstream of the Yellow River will be used to (i) investigate the relationship between meteorological and hydrological droughts under natural and anthropogenic conditions, (ii) to quantify the influence of human activities on the characteristics of hydrological drought (e.g., drought frequency, duration and severity, and seasonality of hydrological drought onset), and (iii) to assess hydrological drought forecasting in the Anthropocene with an experimental seasonal hydrological forecasting system established over the Yellow River basin (Yuan et al, 2016)
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