Dryland land crop yield sensitivity to drought in Botswana: Development ofstatistical tools based on satellite remote sensing, observation and climate models foruse in risk assessment

AbstractAssessing agricultural drought is of great importance as it is viewed as the most serious problem in mostcountries in terms of food security, economy, and social stability. Various drought indices have beendeveloped in order to describe the characteristics of drought such as severity, extent, frequency andduration. These indices can be classified into two categories: ground-based and remotely-sensed indices.Ground-based drought indices are more accurate but limited in coverage, while remote sensing droughtindices cover large areas but have poor precision. Therefore there is need to apply advanced data fusionmethods based on satellite data and ground-based drought indices to fill this gap. However there is a lagtime between drought events and the impacts they cause.Due to the semi arid conditions of Botswana, the country is prone to the occurrence of droughts and hasa great influence on agriculture and economy of the country at large. In order to monitor droughts inBotswana this paper proposes that it is necessary to link the pre meteorological observations and theconsequential vegetation drought. This is neededed for effective monitoring of agricultural drought andearly warning. In this study, MODIS reflectance data and data from recent satellites such as landsat OLI,Sentinel will be used to discover relationships between vegetative drought and meteorological droughtusing vegetation condition index (VCI) derived from NDVI and NDWI, and meteorological droughtderived from SPI and SPEI in Botswana. Dataset derived from Soil Moisture Active Passive (SMAP)will be used to generate %soil moisture content. The %moisture content will be compared withexperimental results from the field. Pearson correlation analyses were performed between single remotesensing drought indices and in-situ drought indices, NDVI and SPEI. Preliminary studies show that VCIderived from NDWI (VCI-2) over Southern District of Botswana can be used as an approach to monitorand provide early warnings. However, there is weak correlation SPEI and VCI-1 and VCI-2 rangingfrom -1 to 0.2.