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Assessment of wind-induced environmental lodging stress for maize based on GIS

机译:基于GIS的玉米风致环境倒伏应力评估。

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Lodging in maize is one of the major problems in maize production worldwide. This study is to assess environmental lodging stress for maize based on probability analysis of extreme wind event in maize vegetative stage. A total of 687 growing counties in Huang-Huai-Hai Plain, China were chosen as study area. There were 148 meteorology stations with daily extreme wind speed data in recent 59 years. At first, for each station, the maximum value of daily extreme wind speed in maize vegetative stage (MEWSV for short) was calculated yearly, and the mean and standard deviation of MEWSV in all stations were interpolated into all growing counties. Then, the probability distribution of MEWSV was simulated using Gumbel distribution and Normal distribution, and the result showed that Gumbel distribution was better. At last, for each growing counties, the probability of extreme wind event (that MEWSV was equal or higher than 19m/s) was calculated based on Gumbel distribution, and the assessed stress values were divided into 5 levels and visualized in GIS using a thematic map. It showed us clearly that most growing counties in the northwest of the study area had very severe lodging stress. In order to validate the obtained results, some field survey data were used in current study and it showed that they were consistent in general. But this method using meteorology data to indirectly measure the environmental lodging stress is less costly and more operational than the traditional field-based survey approach, especially when the region to be evaluated is very large. This study can facilitate the identification of better-adapted growing environments, so as to reduce the risk and loss of lodging in maize.
机译:玉米寄宿是全世界玉米生产中的主要问题之一。这项研究是基于玉米营养期极端风事件的概率分析来评估玉米的环境倒伏压力。中国黄淮海平原的总共687个生长县被选为研究区域。在最近的59年中,有148个气象站每天都有极端风速数据。首先,每个站点每年都要计算玉米营养期的每日极端风速最大值(简称MEWSV),并将所有站点MEWSV的均值和标准差内插到所有生长县。然后,利用Gumbel分布和正态分布对MEWSV的概率分布进行了模拟,结果表明,Gumbel分布较好。最后,针对每个成长县,根据Gumbel分布计算极端风事件(MEWSV等于或高于19m / s)的概率,并将评估的应力值分为5个等级,并通过GIS在专题图中可视化地图。它清楚地向我们显示,研究区域西北部大多数正在发展的县都有非常严重的倒伏压力。为了验证所获得的结果,当前研究中使用了一些现场调查数据,结果表明它们总体上是一致的。但是,与传统的基于现场的调查方法相比,这种使用气象数据间接测量环境倒伏压力的方法成本更低,并且更具操作性,尤其是在要评估的区域非常大的情况下。这项研究可以帮助确定适应性更好的生长环境,从而降低玉米倒伏的风险和损失。

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