Development And Application Of Agricultural Drought Index Based On Multi-source Data

As the most destructive climate disaster,drought has a significant impact on hydrology,ecology and society,and caused huge economic losses.Understanding and evaluating drought,especially agricultural drought,is of great significance for improving the ability of drought resistance,disaster reduction and promoting the sustainable development of social economy and environment.Therefore,based on multi-source data,this paper constructs and optimizes drought indexes,and analyzes the relationship between different drought types in China.The main contents and conclusions are as follows(1)The ESA CCI soil moisture product and GLDAS soil moisture product were combined,and the combined soil moisture product was verified by in situ soil moisture.The combined product not only ensures the accuracy,but also has the advantage of long time series.The agricultural drought index SWDI was constructed using the combined soil moisture product.Evaluated by the actual drought events,SWDI can accurately reflect the agricultural drought situation in China.Drought condition is the most serious in Qinghai Tibet region,which is more sensitive to temperature.Drought in the South and north is more sensitive to rainfall.Northwest China is a perennial arid area,and the drought situation is basically unchanged.(2)Through correlation analysis,grey incidence analysis,the time lag relationship between agricultural drought and meteorological drought in different geographical regions was analyzed.In arid areas,it takes a short time for meteorological drought to develop into agricultural drought.When the drought in winter and spring is serious and lasts for a long time,the transmission time from meteorological drought to agricultural drought is often longer than that in summer.In different regions,it takes 1 to 2.5 months for meteorological drought to develop into agricultural drought.In grassland,the correlation between agricultural drought and vegetation drought is better.Compared with agricultural drought,the occurrence of vegetation drought in a few provinces in southern China was delayed by about one month.(3)In situ meteorological data and GLDAS data were used to calculate the potential evapotranspiration.By comparing with the in-situ-based potential evapotranspiration,the potential evapotranspiration based on GLDAS data is evaluated,and the correlation between them is very good.In the southern region,the potential evapotranspiration based on GLDAS dataset is generally small.The areas with large relative deviation are mainly concentrated in Northwest China.The cumulative distribution function was used to combine the soil moisture of ESA CCI and GLDAS.Considering the multi-layer soil moisture and potential evapotranspiration,the SSEI index was constructed through three parameter logarithmic distribution.The index has good performance in the range of drought occurrence and the development and mitigation of drought events.The performance of SSEI in Northwest China is significantly improved compared with SWDI.In Northwest China,the correlation between SSEI and SPEI is good.In the southern region,the correlation between the two is not good.Northwest China and Qinghai Tibet Plateau are the two main drought affected areas,with drought frequency ranging from 0.35 to 0.45.The frequency of drought in Northwest China is high,but most of them are moderate drought.The frequency of drought is low in the South and Greater Khingan Mountains area,but the drought is more serious.Severe drought and extreme drought often occur in these areas.