Towards an integrated soil moisture drought monitor for East Africa

Abstract

Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010–2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically-based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa

Hydrological change detection using modeling: Half a century of runoff from four rivers in the Blue Nile Basin

“…The three adjacent watersheds (Gilgel Abbay, Birr, and Upper‐Didesa) showed difference in parameter changes; this implies that the status and change of soil water availability are watershed specific. Changes in soil moisture are crucial as they are the constraining factors for the small‐scale farming systems in the study area [ Anderson et al ., ].…”

Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data‐Poor Regions

“…One promising approach is to use the water budget to enforce closure by distributing errors across individual water budget components based on their errors (e.g., Pan et al, ; Zhang, Pan, et al, ). These approaches do require an estimate of errors of individual products, but comparison with competing and alternative products (e.g., from remote sensing, modeling and gridded observational analyses) through methods such as triple colocation (e.g., Anderson, Zaitchik, et al, ) can provide a first‐order approximation.…”

An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian Peninsula

“…Yilmaz et al (2012) merged the same three products using triple collocation-based errors in a least squares framework using an objective methodology and validated them using ground station data. Anderson et al (2012) used the same three products over the Horn of Africa to obtain an integrated SM product designed specifically for drought monitoring. Here, we analyse all available ALEXI SM retrievals (year-round) for the period 2007-2011, spatially aggregated (linear averaging) from the native 3 × 3 km 2 resolution to 25 × 25-and 10 × 10 km 2 grids.…”