Evaluation method for effects of drought disaster on yields of maize in Southwest China

Abstract: Impacts of climate change on agriculture has received wide concerns, yet evaluation technology of the effect of the drought disaster on the crop yields needs further research particularly in developing countries. Maize cultivation occupies extremely important position in agricultural production in this region. It holds great importance to study the evolution of the drought to provide references for disaster prevention and avoiding disadvantages. Drought is the main meteorological disasters during maize growth periods, and high frequency and large-scale drought poses serious threat to maize growth and yield. Recently, the government departments and related research institutions have focused on the drought matter in Southwest. Based on the principle of similar climate growth period and agricultural production level, corn planting areas in Southwest China are divided into 6 sub-regions. Using the daily meteorological data and maize data from 63 representative stations in Southwest China from 1961 to 2010, the study calculated water profit and loss index in each sub-region, then computed the weighted sum of the water profit and loss index over the past three ten-day, finally got the ten-day wetness index. According to the ten-day wetness index and influence coefficient, the maize cumulative index was built. The study developed yield drought loss assessment model and verified the model by selecting some typical drought years and representative stations in each sub-region. The results showed that the wetness index by 10 days in the growth period had a good relationship with soil moisture. The assessment model of maize drought loss yield in 6 sub-regions passed F-test (p<0.05) and corn cumulative indices of drought in drought year in Southwest China had good relation to the yield loss in drought through the statistical analysis of the representative station. With changes of the same drought cumulative indices, there were slight differences in yield loss in each sub-region. Yield loss in the sub-regions of Ⅱ and Ⅲ were relatively small, while relatively large in the sub-regions of Ⅰ and Ⅴ. The model can estimate the yield loss in drought accurately, and provide references for application and deep research.