Evaluating the performance of eight drought indices for capturing soil moisture dynamics in various vegetation regions over China

• Published in: The Science of the total environment 2021-10, Vol.789, p.147803-147803, Article 147803
• Main Authors: Liu, Qi, Zhang, Jiahua, Zhang, Hairu, Yao, Fengmei, Bai, Yun, Zhang, Sha, Meng, Xianglei, Liu, Quan
• Format: Article
• Language: English
• Subjects: China; Drought indices; Soil moisture dynamics; Uncertainty; Vegetation types
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2021.147803

Drought is pervasive global hazard and seriously impacts ecology. Particularly, vegetation drought, which is chiefly driven by soil moisture (SM) deficiency, has a direct bearing on grain production and human livelihoods. Various drought indices associated with vegetation and SM conditions have been proposed to monitor and detect vegetation drought. In this study, we evaluated the performance of eight drought indices, including Drought Severity Index (DSI), Evaporation Stress Index (ESI), Normalized Vegetation Supply Water Index (NVSWI), Temperature-Vegetation Dryness Index (TVDI), Temperature Vegetation Precipitation Dryness Index (TVPDI), Vegetation Health Index (VHI), Self-calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Evapotranspiration Index (SPEI), for capturing SM dynamic (derived from Copernicus Climate Change Service) across the six main vegetation coverage types of China. Our results showed DSI and ESI had the best overall performance. When exploring the reasons for the uncertainty of these indices (except SC-PDSI and SPEI) in the evaluation, we found that, in the non-arable regions, the time lag effect of drought indices on SM, the average state and rangeability of corresponding variables and the climatic conditions (precipitation and temperature) all impacted the performance of DSI, ESI, NVSWI, TVPDI and VHI. In the arable region, cropland types (paddy field and non-paddy field) and the uncertainty of SM data mainly caused the uncertainties of the above five indices. With regard to the TVDI, abnormalities of dry and wet edges fitting may be the primary factor affecting its performance. These results demonstrated that these drought indices with reliable and robust performance of capturing SM dynamics can be suggested to characterize the trend of SM. Certainly, this study can provide a reference for the improvement of existing drought indices and the establishment of new drought indices. [Display omitted] •Assessed the performance of eight drought indices for capturing SM dynamics.•DSI and ESI had the outstanding overall performance.•Explored the causes of the uncertainties of drought indices in the evaluation.•Time lag effect, variables characteristics and climatic conditions impacted performance of indices.