Satellite based remote sensing of soil moisture for drought detection and monitoring in the Horn of Africa

Drought is a natural hazard characterized by a high degree of complexity thus its investigation could be best performed only through a complex analysis involving a set of environmental variables and their intricate relationships. Therefore, the development of an effective early drought detection and monitoring system requires integration of observations on vegetation condition, climate-based drought index data, and several biophysical and social variables of the environment. One of the fundamental drought variables is of course soil moisture, a key parameter determining crop yield potential in drought-affected parts of the world like in the developing nations of the Horn of Africa. Hence soil moisture deficit can be regarded as an important component of, if not synonymous with especially agricultural drought. However, to date model components taken into consideration in the existing drought detection and monitoring systems are only data on precipitation and vegetation condition. Cognizant of this fact, the current work targets integrating historical and real-time monitoring of soil moisture conditions in existing prediction and warning systems to make efforts of early detection of drought events more efficient and reliable. The dissertation addressed the gap through investigation of spatial and temporal soil moisture dynamics in the Horn of Africa using data from microwave observations, and the subsequent definition of monitoring procedures and/or triggers suitable to drought early warning activities. For these purposes, satellite based soil moisture long-term time-series data, obtained from the Water Cycle Multi-Mission Observation Strategy (WACMOS), has been processed, investigated and analyzed using proper statistical methodologies. The specific objectives were investigating the historical time-series soil moisture spatio-temporal dynamics and assess interactions with land cover/vegetation types; to identify historical soil moisture anomalies and establish the relationships with historical agricultural drought events in the Horn of Africa and to explore the relationships between soil moisture and vegetation conditions, a commonly used drought variable. Results of the study has clearly revealed that the WACMOS soil moisture data set and methodology implemented proved useful to identify the behaviors of different vegetation types; the soil moisture index developed (SMCI), is an effective tool in identifying historical drought events; the highly significant correlation between the vegetation and soil moisture data observed at the time lag -1, justifies the potential use of the soil moisture data for drought detection purposes, in order to complement NDVI analysis for an effective drought early warning. Further quantitative validation of the results is possible and helpful if sufficient geospatial data about drought distribution in time and space are available. Eventually, potential of the satellite based WAMOS soil moisture data for detection and monitoring of drought can still be improved if the following points are taken into consideration: Guaranteeing that the soil moisture data retrieved from the different microwave instruments are physically consistent and data available in near-real time, the level of missing data which account for low accuracy need refining and development and the low spatial resolution of the data set is a limitation compromising the level of details many investigations require.