Early warning indexes determination of the crop injuries caused by waterlogging based on DHSVM model

Early warning on crop injuries aroused by waterlogging is the guarantee of crop yield in the middle and lower reaches of the Yangtze River. The waterlogging warning measures based on precipitation index were often inaccurate. In this literature, a new method based on DHSVM (Distributed Hydrology Soil Vegetation Model) was used for practice in summer crops at county-level, real-time and high-precision forecasting, which simulates soil groundwater depth and soil volumetric moisture content in grid unit on time step of 1 day. According to the agricultural standard of waterlogging level, the meteorology characteristic data were calculated, and then spatial distribution of the waterlogging eigenvalues was mapped. Waterlogging distribution from Jianli County was clustered into five types of regions with a 90-m spatial resolution via the unsupervised classification method (k-means) algorithm. Based on the partition statistics of waterlogging eigenvalues, the character values of each kind were extracted. Using these eigenvalues as criteria, we predicted the waterlogging in the years from 1970 to 2015. The experimental results show that the average value of kappa coefficient is between 0.87 and 0.93, which illustrates that our method is effective for warning waterlogging level.