Applicability assessment of six drought indices in different maize producing regions of China

As the most widely planted food crop in China, maize (Zea mays) often suffers drought stresses during its growing period, which further leads to substantial yield reducing and great economic losses. Therefore, timely and accurate monitoring of drought conditions is essential for maize production. In this paper, six widely used daily drought indices, including Standardized Precipitation Index (SPI10, SPI30) and Standardized Precipitation Evaporation Index (SPEI10, SPEI30) at 10-day and 30-day scales, Meteorological Drought Composite Index (MCI), and Crop Water Deficit Index (CWDI), were calculated by using meteorological data from 1971–2020. Maize drought disaster records were segmented into different maize growing periods in terms of maize phenophase data. The drought identification capacity of each drought index was evaluated by the multi-dimensionality, sensitivity and accuracy in four different maize producing regions of China, i.e., the North SPring maize region (NSP), the Huang-huai-hai SUmmer maize region (HSU), the South SPring maize region (SSP), and the SouthWest SPring maize region (SWSP). The results showed that CWDI demonstrated the highest sensitivity and accuracy in the NSP Region, the HSU Region, and the SWSP Region, and MCI was superior in the SSP Region. From the perspective of maize development stages, the most applicable index during planting — tasseling period (V0–VT) and tasseling — ripening period (V0-R6), as well as the entire growing period from planting to ripening period (V0-R6) was also CWDI, with exceptions for V0-R6 in the SSP region and VT–R6 in the SWSP region. Nevertheless, since CWDI had the highest false negative identification rate among all indices, it was recommended that MCI in conjunction with CWDI to enhance the accuracy of identifying maize droughts in China. This research provides a technical basis for selecting suitable drought indices in different maize producing regions, and also for improving the precision of maize drought identification in China.