Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000-2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO
Identifying Droughts Affecting Agriculture in Africa Based on Remote Sensing Time Series between 2000-2016: Rainfall Anomalies and Vegetation Condition in the Context of ENSO
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DOI：
10.3390/rs9080831
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发表时间：
2017-08
期刊：
影响因子：
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通讯作者：
K. Winkler;U. Gessner;V. Hochschild
中科院分区：
文献类型：
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作者：
K. Winkler;U. Gessner;V. Hochschild
干旱是世界上最具破坏性的自然灾害之一。在非洲大片地区，水是一个限制因素，人们强烈依赖雨养农业，干旱经常导致作物歉收、粮食短缺甚至人道主义危机。在非洲东部和南部，重大干旱事件与厄尔尼诺-南方涛动（ENSO）事件有关。在这种情况下，在现有的原位数据有限的情况下，遥感为在全大陆范围内以高空间和时间分辨率评估干旱提供了宝贵的机会。本研究旨在监测2000-2016年非洲农业相关干旱，并利用基于遥感的干旱指数特别关注生长季节。特别注意观察ENSO大事件期间的干旱动态，以阐明ENSO与东部和南部非洲干旱之间的联系。我们使用了基于热带降雨测量任务（TRMM）的标准化降水指数（SPI）。分辨率和中分辨率成像光谱仪（MODIS）衍生的500米分辨率植被状况指数（VCI），作为分析干旱时空格局的指标。我们将干旱指数与基于modis的归一化植被指数（NDVI）多年平均值的立地特定生长季节时间信息结合起来。我们证明了SPI-3和VCI作为大陆尺度农业相关干旱综合监测指标的适用性。2009年和2011年可能是东非的大旱年，而南部非洲在2003年和2015/2016年受到严重干旱的影响。在强厄尔尼诺现象期间，非洲南部大部分地区发生了干旱。我们在非洲东部观察到一种混合干旱模式，在那里，有两个生长季节的地区在拉尼娜现象期间经常受到干旱的影响，而单峰降雨地区在厄尔尼诺现象发生期间也出现了干旱。在2010/2011年拉尼娜现象期间，索马里（88%）、苏丹（64%）和南苏丹（51%）的大部分农田在生长季节受到严重到极端干旱的影响。然而，在16年的观测期内，无法推断出与厄尔尼诺或拉尼娜相关的普遍干旱响应模式。在这方面，我们讨论了ENSO变异体的多年大气波动和特征，作为ENSO与干旱之间相互关系的进一步影响。本研究利用以农业区和农业时期为重点的基于遥感的干旱指数，试图有助于更好地了解影响非洲农业的干旱的时空格局，这对于实施干旱减灾战略至关重要。
Droughts are amongst the most destructive natural disasters in the world. In large regions of Africa, where water is a limiting factor and people strongly rely on rain-fed agriculture, droughts have frequently led to crop failure, food shortages and even humanitarian crises. In eastern and southern Africa, major drought episodes have been linked to El Nino-Southern Oscillation (ENSO) events. In this context and with limited in-situ data available, remote sensing provides valuable opportunities for continent-wide assessment of droughts with high spatial and temporal resolutions. This study aimed to monitor agriculturally relevant droughts over Africa between 2000–2016 with a specific focus on growing seasons using remote sensing-based drought indices. Special attention was paid to the observation of drought dynamics during major ENSO episodes to illuminate the connection between ENSO and droughts in eastern and southern Africa. We utilized Tropical Rainfall Measuring Mission (TRMM)-based Standardized Precipitation Index (SPI) with 0 . 25 ∘ resolution and Moderate-resolution Imaging Spectroradiometer (MODIS)-derived Vegetation Condition Index (VCI) with 500 m resolution as indices for analysing the spatio-temporal patterns of droughts. We combined the drought indices with information on the timing of site-specific growing seasons derived from MODIS-based multi-annual average of Normalized Difference Vegetation Index (NDVI). We proved the applicability of SPI-3 and VCI as indices for a comprehensive continental-scale monitoring of agriculturally relevant droughts. The years 2009 and 2011 could be revealed as major drought years in eastern Africa, whereas southern Africa was affected by severe droughts in 2003 and 2015/2016. Drought episodes occurred over large parts of southern Africa during strong El Nino events. We observed a mixed drought pattern in eastern Africa, where areas with two growing seasons were frequently affected by droughts during La Nina and zones of unimodal rainfall regimes showed droughts during the onset of El Nino. During La Nina 2010/2011, large parts of cropland areas in Somalia (88%), Sudan (64%) and South Sudan (51%) were affected by severe to extreme droughts during the growing seasons. However, no universal El Nino- or La Nina-related response pattern of droughts could be deduced for the observation period of 16 years. In this regard, we discussed multi-year atmospheric fluctuations and characteristics of ENSO variants as further influences on the interconnection between ENSO and droughts. By utilizing remote sensing-based drought indices focussed on agricultural zones and periods, this study attempts to contribute to a better understanding of spatio-temporal patterns of droughts affecting agriculture in Africa, which can be essential for implementing strategies of drought hazard mitigation.