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Drought assessment in a typical rainfed agricultural region of Inner-Mongolia, China

机译:内蒙古典型雨养农业区的干旱评估

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Agricultural drought is a type of natural disaster that has a serious impact on food security.Because the relationships among short-term rainfall,soil moisture,and crop growth are complex,the accurate identification of a drought situation is difficult.In this study,using a conceptual model based on the relationship between water deficit and yield reduction,we evaluated the drought process in a typical rainfed agricultural region,Hailar County in Inner Mongolia,China.To quantify drought,we used the three precipitation indices(Precipitation Anomaly(PA),Standardized Precipitation Index(SPI),Effective Drought Index(EDI),and the soil moisture–based Crop Moisture Index(CMI)as well as the Normalized Difference Vegetation Index(NDVI).Correlation analysis was conducted to examine the relationships between dekad-scale drought indices during the growing season(May–September)and final yield,using data collected from 2000 to 2010.The results showed that the yield has positive relationships with both EDI and CMI from mid-June to mid-July and with the NDVI anomaly throughout July.Further analysis of the relationship between the drought indices showed that the NDVI anomaly responds to both EDI and CMI with a lag of 1 dekad,particularly in July.To examine the feasibility of employing these indices for monitoring the drought process at a dekad time scale,a detailed drought assessment was carried out for selected drought years.It confirmed that the drought indices in the late vegetative to early reproductive growth stages can be used to detect agricultural drought in the study area.Therefore,the framework of the conceptual model developed for drought monitoring can be employed to support drought mitigation in the rainfed agricultural region of northern China.
机译:农业干旱是一种严重影响粮食安全的自然灾害。由于短期降雨,土壤水分和作物生长之间的关系复杂,因此难以准确识别干旱情况。基于水分亏缺与减产之间关系的概念模型,我们评估了典型的雨养农业地区内蒙古海拉尔县的干旱过程。为了量化干旱,我们使用了三个降水指数(降水异常(PA)) ,标准化降水指数(SPI),有效干旱指数(EDI),基于土壤水分的作物水分指数(CMI)以及归一化植被指数(NDVI)。利用2000年至2010年收集的数据,确定生长季(5月至9月)的干旱指数和最终产量。 h EDI和CMI从6月中旬到7月中旬,并在整个7月出现NDVI异常。对干旱指数之间关系的进一步分析表明,NDVI异常对EDI和CMI的响应都滞后了1 dkad,特别是在7月为了检验使用这些指数在十足的时间尺度上监测干旱过程的可行性,针对选定的干旱年份进行了详细的干旱评估,证实了可以使用植物生长晚期到生殖早期的干旱指数因此,可以将为干旱监测开发的概念模型的框架用于支持中国北方雨养农业区的干旱缓解。

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