| Agricultural drought is a natural disaster with large spatial scope,long time span and complex development process.With the increase of climate change and the frequency and severity of drought,drought and its impact have attracted more and more public and government attention.Timely and accurate large-scale monitoring of agricultural drought is of great significance to the development of modern agriculture.Drought stress has a great impact on crop yield at different stages of phenology.Therefore,understanding the impact of crop agronomic phenology on agricultural drought is particularly key in drought monitoring research.Compared with timeconsuming and laborious ground investigation,agricultural drought assessment by monitoring the phenological stage and drought stage of crops by remote sensing can better understand the situation of crop drought from a wide range of spatial and temporal scales.In particular,the drought index constructed from remote sensing data is widely used in drought monitoring and has made remarkable achievements.However,there are still some problems in agricultural drought monitoring at this stage:(1)there is a lack of understanding of the temporal and spatial differences of crop agronomic phenology in agricultural drought,and there are few agricultural drought monitoring studies combined with Crop Agronomic phenology;(2)The impact of crop phenology on crop yield is not considered in traditional drought monitoring.Therefore,a multi-source remote sensing data comprehensive drought index(PCDI)considering phenological process is proposed in this study.Based on the data of the Yangtze River Basin in China and the corn belt in the United States,the index model is constructed by combining the water stress factors,high temperature stress factors,vegetation status and crop phenological period in agricultural drought,Realize the accurate adjustment and quantification of crop agronomic phenology in the study area by stages.Based on the study area of the United States from 2001 to 2019,the monthly PCDI model drought distribution spatial map and annual PCDI model drought map in 2003 and 2012 are drawn.The results show that:(1)the anomaly index based on Evapotranspiration ratio(ET/PET),Killing Degree Days(KDD),Vegetation Condition Index(VCI)and temporal and spatial difference of crop phenology is better than the condition index without considering temporal and spatial difference of crop phenology,and the correlation coefficient(R2)with crop yield loss rate is increased by 0.32,0.07 and 0.26 respectively;(2)The PCDI model improves the monitoring ability of crop yield loss rate by considering the impact of different crop phenological periods on crop yield.In the study area of the United States,the correlation coefficient(R2)between PCDI index and yield loss rate is 0.72.In addition,compared with other drought indexes,such as Standardized Precipitation Index(SPI)with different time scales,the agricultural drought monitoring ability of PCDI model has been significantly improved;(3)The application of PCDI model in China and the United States has successfully proved the robustness and practicability of the index.The results show that the comprehensive drought index model(PCDI)based on crop phenology can more accurately monitor the degree of crop yield loss and its spatial distribution,provide key information for the prevention and control decision-making of agricultural management departments,and provide scientific basis for the study of agricultural drought mechanism and the quantitative evaluation of crop drought impact. |
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