Evaluation and Modifying of Multispectral Drought Severity Index

Drought is a very destructive natural disaster. In recent years, affected by climate change, the frequency of drought is increasing all over the world, causing serious economic losses. Accurate monitoring of drought information is the basis of disaster prevention and reduction. Drought Severity Index (DSI) is a kind of index that can effectively capture regional drought information. It has been proved that it has great potential in global drought monitoring, but its classification of drought grade is obviously regional. In order to test the applicability of DSI on the provincial scale and correct the classification differences, DSIMODIS and DSIAVHRR from 2001 to 2014 were obtained based on the data sets of MODIS ET/PET, NDVI and AVHRR NDVI in Shanxi Province. Meanwhile, combined with SPEI, the spatial and temporal distribution of drought in these three indexes was compared and analyzed. To verify the reliability of SPEI, long time series SPEIs were compared with historical drought records. In order to investigate the errors of DSI in the region, DSIMODIS DSIAVHRR and SPEI were compared in time frequency and spatial distribution. Finally, as SPEI a reference and based on the original DSI classification standard, the new drought classification standard was obtained by adjusting the threshold of drought grade of DSIMODIS with 0. 1 as the step size. In addition, DSIMM was used to monitor the provincial seasonal scale from 2001 to 2014, to capture the typical drought events in 2001 and 2002, and to verify the applicability and robustness of DSIMM in drought monitoring in Shanxi. Studies show that there is a high correlation between DSIMODIS and DSTAVHRR, with a correlation coefficient of 0. 75. Both of them have consistent performance in spatial distribution and time frequency of drought, indicating that DSI can be extended to AVHRR data set in the absence of data to make up for the deficiency of MODIS data in long time series monitoring. DI was underestimated by DSIMODIS while D2, D3 and D4 were overestimated in Shanxi province. In the four grades of mild drought Dl, moderate drought D2, severe drought D3 and extreme drought D4, DSIMM and SPEI showed a high degree of consistency in the occurrence frequency and spatial ratio of drought. The time frequency of D3 was completely consistent, and the spatial distribution consistency of D4 was 0. 98. The drought classification standard of DSIMM can monitor the drought information at different temporal and spatial scale accurately, which can be applied to the whole governor time series drought monitoring. The results can be used for reference in regional scale drought monitoring using DSI, and a simple calculation method with high accuracy is obtained for Shanxi Province drought information monitoring.