Impact Assessment of Maize Cold Damage and Drought Cross-Stress in Northeast China Based on WOFOST Model

This paper focuses on the cold damage and drought cross-stress in maize in Northeast China. The WOFOST model based on parameter localization was used to simulate the growth and development process of maize using daily meteorological data from 110 stations in the research area from 1981 to 2020. The experiment determined that the grouting index and the number of drought days were the indicators for identifying the low-temperature and drought cross-stress in maize, as well as the impact assessment indicators for the fluctuation percentage of dry matter weight in storage organs. It also achieved a quantitative assessment of the impact of cross-stress of low-temperature and drought between 1981 and 2020 and typical years. The results indicated that the WOFOST model can effectively simulate the impact of low-temperature and drought on maize growth, and the historical occurrence of cold damage identified by using the grouting index and drought days as indicators of the low-temperature and drought cross-stress in maize is basically in line with the actual situation. Compared with the average temperature from May to September and the regional cold damage index of > 105 °C supplemented by the meteorological industry standard “Technical Specification for Assessment of Cold Damage to Spring Maize in Northern China”, as well as the identification results of the “Drought Grade of Spring Maize in Northern China”, the average identification accuracy of low-temperature drought cross-stress in Northeast China based on the WOFOST model is 82.0%, 76.4% of stations have an accuracy of 80.0% or above, and only 4.5% of stations have an accuracy of less than 50.0%. Under the combined influence of low temperature and drought cross-stress, 88.9% of the years showed a reduction in maize production. The evaluation results reflect the historical production reality of maize in Northeast China and are consistent with existing research results.