ABSTRACT
ABSTRACT: In this article, spatial-and-temporal risk assessment of crops caused by flood using county as spatial unit and month as temporal unit was performed in Northeast China under the support of metrological data, terrain data, flood record data and crops’ planting area data. With Inverse Distance Weighting (IDW) model, daily rainfall data for each county was interpolated by using daily rainfall data of meteorological stations. With bivariate regression, vulnerability function of crop caused by flood among variables of crops’ disaster affected area, rainfall process volume and terrain was built. Using non-parametric kernel density model, the probability density function of total precipitation in a storm for each month of each county was fitted. The expected disaster-affected area of crops as risk measure for each month of each county was calculated on the combination of probability density function and vulnerability function. As a result, a serial of risk maps on county and month levels were produced to be used to recognize the rules of risk variance in both space and time.
