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[Purpose] Crop’s risk assessment induced by natural disasters needs to develop in the fine scale. It is required that risk assessment can be performed on county-level space scale and month-based time scale. But with the thinning of space and time scales, disaster samples would decl ine greatly and severely limit the us age of risk assessment method based on the statistic of samples. Therefore, in this paper, a new method on base of metrological data and crop’s vulnerability models was proposed to assess risk variability among months on county scale. [Methods] Since the weather stations cannot cover all the counties, the IDW method was used to interpolate the daily rainfall for each coun ty by its nearby 3 stations. Moreover, ba sed on the flood recor d data, the vulnerability function between crop’s flood-effected area and av erage daily rainfall in a storm wa s regressed. Using the informatio n diffusion model of nonp arametric kernel density, the probability density function of average daily rainfall in a storm for each month of each county was fitted. Finally, the expected disaster-effected area of crops as risk measure for each month of each county was calculated on the combination of probability function and vulnerability function. [Results] Through the case study in three northeastern provinces of China, a serial of risk maps on county-level and month-level scales were produced to be used to recognize the rules of risk variability in space and time.

Risk Assessment of Crops Induced by Flood in the Three Northeastern Provinces of China on Small Space-and-Time Scales