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Droughts are increasing in frequency and intensity as the global climate changes. Risk assessment for agricultural drought disasters is an important approach for disaster prevention and mitigation. Based on the formation mechanism of natural disaster risk, the index system model of agricultural drought risk assessment in North China was constructed, and the robustness of the established risk assessment model was tested by using the internal test method. Then based on the characteristics of agricultural drought risk formation in North China, the paper proposes corresponding risk prevention recommendations. The conclusions were as follows: when adjusting the indices and methods in the risk assessment model, the range of changes in the agricultural drought risk ranking for each city was mostly 1-2.5 places, and the model was relatively robust. With the exception of Beijing and Tianjin, which had the highest disaster prevention and mitigation capacity, central and northern China had the highest agricultural drought risk, which was previously linked to the high risk and vulnerability of these regions. The agricultural drought risk in northern Henan and southern Shandong is low, mainly due to the low risk. The 34 cities in North China can be divided into 6 agricultural drought risk clusters, which are not dispersed in space and cross-city distribution, and have good aggregation. Cluster 4, located in the northernmost mountainous areas, has the highest risk of drought, which is associated with high environmental vulnerability and low capacity for disaster prevention and mitigation, so agricultural areas should be reduced and agricultural input should be increased. Clusters 2, 5 and 6, located in the central and southern regions, have higher grain acreage and yields due to drought, so agricultural drought risk can be further reduced by increasing agricultural input and improving irrigation guarantee rate. [ABSTRACT FROM AUTHOR]

Drought has become a problem that is universally faced by global terrestrial ecosystems. Northeast China is dominated by a temperate monsoon climate and located in an area sensitive to global climate changes, and one of the main impacts of climate changes in Northeast China is manifested as drought in growing seasons. The drought area has a gradual increase trend, and drought has become the main agro-meteorological disaster in this region which is also the main maize planting area in China. Drought normalization seriously restricts the stable development of maize production in Northeast China. So in this paper, we took spring maize in Liaoning Province as an example and made clear the drought variation characteristics in different growth stages by using the data of MODIS, FY-3A, relative soil moisture and growth stages and the methods of RS, GIS and statistical analysis. Then we analyzed the correlation between multi-time scale remote sensing indexes and relative soil moisture in different soil depth, and established the remote sensing monitoring index set and models of relative soil moisture for each growth stage and soil depth. The accuracy of the monitoring models was verified and the application research of monitoring the drought of spring maize in Liaoning Province was studied. The results showed that: From 1993 to 2012, drought occurred in each growth stage of spring maize in Liaoning Province and the highly frequent drought occurred in the period from 1999 to 2002. The drought grade in each year was mainly light drought, and the drought was the most serious at milk stage, followed by heading stage. There was no significant correlation between the monitoring indexes and relative soil moisture at sowing and emergence stage, but there was a significant or extremely significant correlation between them at three-leaf and maturity stage. The monitoring index LSWI (land surface water index) had a strong ability to monitor relative soil moisture, followed by WI (water index). Multi-index coordination could improve the monitoring ability of relative soil moisture by remote sensing means, and the monitoring ability at 10-day scale was generally higher than that at 5-day scale and 20-day scale. Based on the monitoring models of soil relative humidity, the drought condition of partial growth stages and soil depth from 2001 to 2004 was monitored. The overall monitoring accuracy was 73.32%, in which the monitoring accuracy of jointing and three-leaf stage was more than 85%. The dynamic monitoring of drought grades in different growth stages in 2000 was realized. The monitoring results were consistent with the agro-meteorological observation records in terms of the growth stages and space. This study would be very significant to improve the capacity of disaster prevention and mitigation by monitoring spring maize accurately and synchronously on a large range. [ABSTRACT FROM AUTHOR]