Abstract

Agro-meteorological condition plays a fundamental role in crop production. For a specific region, the comprehensive effects of multiple meteorological factors are important indicators for the climatic suitability of the crops. To evaluate the synthetic effects, an integrated climatic assessment indicator (ICAI) are developed in Jiangsu Province, China. A newly produced meteorological assimilation driving datasets (CMADS V1.0) combined with observation data are used in establishing the indicator. The procedure to construct the indicator involves building statistical crop models by meteorological factors and determining the indicator values by classification. In modeling, two machine learning algorithms: Random Forest (RF) and Support Vector Machine (SVM) are compared and the classification model of RF is chosen to build ICAI due to its better performance in the independent test set. To determine a reasonable division in classification, distribution detection of climatic yield is carried out and Monte Carlo simulations are applied for the Kolmogorov–Smirnov (KS) test. The generated indicator includes three values: yield loss, normal and yield increment, with the spatial and temporal prediction accuracy from 67.86% to 100% in the test set for the Northern, Central and Southern Jiangsu. The ICAI are used to estimate the past climatic suitability of winter wheat and the future suitability under global warming conditions in Jiangsu Province. The results show that the climate in 1990s has more adverse effects on wheat production than the other two sub-periods in Northern and Southern Jiangsu. The adaptability of wheat production in Southern Jiangsu has improved greatly to the local environments during the past three decades. In addition, when annual temperature accelerates upwards, both possibilities of yield loss in Northern Jiangsu and yield increment in Southern Jiangsu will increase. Therefore, more concerns should be given to the North in future warming climate, while yield potential in the South may be further improved in this circumstance.

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