Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in Northwestern China

Feng Ma, Lifeng Luo, Aizhong Ye, Qingyun Duan
2018 Hydrology and Earth System Sciences Discussions  
<p><strong>Abstract.</strong> Endorheic and arid regions around the world are suffering from serious drought problems. In this study, a drought forecasting system based on eight state-of-the-art climate models from North American Multi-Model Ensemble (NMME) and a Distributed Time-Variant Gain Hydrological Model (DTVGM) was established and assessed over the upstream and midstream of Heihe River basin (UHRB and MHRB), a typical arid endorheic basin. The 3-month Standardized Precipitation Index
more » ... cipitation Index (SPI3) and 1-month Standardized Streamflow Index (SSI1) were used to capture meteorological and hydrological drought, and values below -1 indicate drought events. The skill of the forecasting systems was evaluated in terms of Anomaly Correlation (AC) and Brier skill score (BSS). The UHRB and MHRB showed season-dependent meteorological drought predictability and forecast skill, with higher values during winter and autumn than that during spring. For hydrological forecasts, the forecast skill in the UHRB was higher than that in MHRB. Predicting meteorological droughts more than 2 months in advance became difficult because of complex climate mechanism. However, the hydrological drought forecasts could show some skills up to 3&amp;ndash;6 lead months due to memory of initial hydrologic conditions (ICs) during cold and dry seasons. During wet seasons, there's no skillful hydrological predictions since lead-2 month because the dominant role of meteorological forcings. During spring, the improvement of hydrological drought predictions is the most significant as more streamflow was generated by seasonal snowmelt. Besides meteorological forcings and ICs, human activities have reduced the hydrological variability and increased hydrological predictability during the wet seasons in the MHRB.</p>
doi:10.5194/hess-2018-405 fatcat:gokqwaycazfavpibtmvyrk5oei