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Developing a satellite-based combined drought indicator to monitor agricultural drought: a case study for Ethiopia

机译:开发一种卫星组合干旱指标,监测农业干旱:埃塞俄比亚的案例研究

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Developing a robust drought monitoring tool is vital to mitigate the adverse impacts of drought. A drought monitoring system that integrates multiple agrometeorological variables into a single drought indicator is lacking in areas such as Ethiopia, which is extremely susceptible to this natural hazard. The overarching goal of this study is to develop a combined drought indicator (CDI-E) to monitor the spatial and temporal extents of historic agricultural drought events in Ethiopia. The CDI-E was developed by combining four satellite-based agrometeorological input parameters - the Standardized Precipitation Index (SPI), Land Surface Temperature (LST) anomaly, Standardized Normalized Difference Vegetation Index (stdNDVI) and Soil Moisture (SM) anomaly - for the period from 2001 to 2015. The method used to combine these indices is based on a quantitative approach that assigns a weight to each input parameter using Principal Component Analysis (PCA). The CDI-E results were evaluated using satellite-based gridded rainfall (3-month SPI) and crop yield data for 36 intra-country crop growing zones for a 15-year period (2001 to 2015). The evaluation was carried out for the main rainfall season, Kiremt (June-September), and the short rainfall season, Belg (February-May). The results showed that moderate to severe droughts were detected by the CDI-E across the food insecure regions reported by FEWS NET during Kiremt and Belg rainfall seasons. Relatively higher correlation coefficient values (r 0.65) were obtained when CDI-E was compared with the 3-month SPI across the majority of Ethiopia. The spatial correlation analyses of CDI-E and cereal crop yields showed relatively good correlations (r 0.5) in some of the crop growing zones in the northern, eastern and southwestern parts of the country. The CDI-E generally mapped the spatial and temporal patterns of historic drought and non-drought years and hence the CDI-E could potentially be used to develop an agricultural drought monitoring and early warning system in Ethiopia. Moreover, decision makers and donors may potentially use CDI-E to more accurately monitor crop yields across the food-insecure regions in Ethiopia.
机译:开发强大的干旱监测工具对于减轻干旱的不利影响至关重要。将多个农业气象变量集成到一个干旱指标中的干旱监测系统缺乏埃塞俄比亚等地区,这极易于这种自然危害。本研究的总体目标是开发一个组合的干旱指标(CDI-E),以监测埃塞俄比亚历史农业干旱事件的空间和时间范围。 CDI-e是通过组合四种基于卫星的农业气象投入参数 - 标准化降水指数(SPI),陆地表面温度(LST)异常,标准化归一化差异植被指数(STDNDVI)和土壤水分(SM)异常 - 从2001年到2015年的时间。用于组合这些指标的方法是基于使用主成分分析(PCA)为每个输入参数分配权重的定量方法。使用基于卫星的网格降雨(3个月SPI)和36个乡村作物生长区的作物产量数据进行评估CDI-E的结果,为15年(2001年至2015年)。该评价是为主要的降雨季节,Kiremt(九月)以及短的降雨季节,Belg(2月至5月)进行了评价。结果表明,在Kiremt和Belg降雨赛期间,CDI-E通过CDI-E检测到中度至严重的干旱。当CDI-E与大多数埃塞俄比亚的3个月SPI进行比较时,获得比较较高的相关系数值(R> 0.65)。 CDI-E和谷物作物产量的空间相关分析显示了该国北部,东部和西南部地区的一些作物生长区中的相对良好的相关性(R> 0.5)。 CDI-E一般绘制了历史灾害干旱和无干旱岁月的空间和时间模式,因此CDI-E可能用于在埃塞俄比亚开发农业干旱监测和预警系统。此外,决策者和捐助者可能会在埃塞俄比亚的食物不安全地区更准确地使用CDI-E来监测作物产量。

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