Abstract：
Droughts in winter and spring are one of the most prominent natural disasters in the Yunnan Province in China. They occur frequently, with long durations and have a wide range of damage, which has a serious impact on social and economic development, as well as agricultural production and, therefore, strongly impacts the lives of the people living in the region. The traditional drought monitoring model does not take terrain into consideration, thereby affecting the comparative nature of results, as baseline conditions are not the same. Therefore, this study proposed a comprehensive drought monitoring model considering the influence of terrain factors to improve the evaluation effect. Firstly, based on NASA\'s Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measurement Mission (TRMM 3B43) data, vegetation condition index (VCI), temperature condition index (TCI), precipitation condition index (TRCI), and three terrain factors ground elevation (DEM), slope (SLOPE), aspect (ASPECT) were selected as model parameters. Then, a comprehensive drought monitoring model without considering terrain factors (Model A) and a comprehensive drought monitoring model of considering terrain factors (Model B) were constructed by using multiple linear regression models. Finally, the effects of the two models were evaluated by using standardized precipitation evapotranspiration index (SPEI) in southwest Yunnan Province, China, and model B was used to analyze the drought in winter and spring in the study area from 2008 to 2019. The results showed that (1) the correlation coefficient of model B was higher than that of model A in winter and spring and the standard error of model B was lower than that of model A. (2) The grade consistency rate of Model A and SPEI was 0.92 in winter and 0.33 in spring; the grade consistency between model B and SPEI was 0.83 in winter and 0.75 in spring, and therefore the monitoring effect of model B was more stable. (3) There were periodic droughts during the study period, and the degree of drought in spring was less than in winter. Medium and severe droughts were observed in winter. Thus, this study concluded that the effect of terrain has an important influence on the evaluation of droughts. The comprehensive drought monitoring model which considers topographic factors can effectively identify the occurrence of drought, and therefore provide significant input with regards to disaster prevention and mitigation policies in southwest Yunnan.
摘要：
冬春干旱是我国云南省最突出的自然灾害之一。它们经常发生，持续时间长，伤害范围广，这对社会和经济发展产生了严重影响，以及农业生产和,因此,严重影响了该地区人民的生活。传统的干旱监测模型没有考虑地形,从而影响结果的比较性质，因为基线条件不相同。因此,本研究提出了一种考虑地形因素影响的干旱综合监测模型，以提高评价效果。首先,基于NASA的中分辨率成像光谱辐射计（MODIS）和热带降雨测量任务（TRMM3B43）数据，植被状况指数(VCI)，温度条件指数(TCI),降水条件指数（TRCI），和三个地形因子地面高程(DEM)，坡度(SLOPE),选择纵横比(ASPECT)作为模型参数。然后，利用多元线性回归模型构建了不考虑地形因素的干旱综合监测模型(模型A)和考虑地形因素的干旱综合监测模型(模型B)。最后,采用标准化降水蒸散指数(SPEI)对两种模式的效果进行评价,中国,采用模型B对研究区2008-2019年冬春干旱进行分析。结果表明：（1）模型B的相关系数在冬季和春季均高于模型A，模型B的标准误差低于模型A。（2）模型A和SPEI的等级一致率冬季为0.92，春季为0.33；模型B和SPEI的等级一致率冬季为0.83，春季为0.75。因此模型B的监测效果更加稳定。(3)研究期间存在周期性干旱,春季的干旱程度小于冬季。冬季出现中度和重度干旱。因此，这项研究的结论是，地形的影响对干旱的评估有重要的影响。考虑地形因素的干旱综合监测模型可以有效识别干旱的发生,因此，为云南西南部的防灾减灾政策提供了重要的投入。
