Assessing Hydro-Ecological Vulnerability from Space

Thursday, 17 December 2015: 13:55
3003 (Moscone West)
Dimitrios Stampoulis1, Konstantinos Andreadis1, Stephanie L Granger1, Joshua B Fisher2, Francis J Turk1, Ali Behrangi1, Narendra N Das1 and Amor Ines3, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Lab, Pasadena, CA, United States, (3)Michigan State University, Departments of Plant, Soil and Micriobial Sciences, and Biosystems and Agricultural Engineering, East Lansing, MI, United States
The main driver of economic growth in East Africa is agriculture. However, climate change and the resulting intensification of the hydrologic cycle will increase water limitation in this already drought-burdened region, and the challenge of ensuring food security is bound to become critical. Efforts must, therefore, be made to develop appropriate adaptation strategies for agriculture in such regions. Assessing and predicting ecosystem responses to global environmental change can advance management and decision support systems that would improve food security and economic development.

The current study uses a plethora of multi-year remote sensing earth observations to study the hydro-ecological vulnerability of the various ecosystems in the water-stressed East African region to droughts. More specifically, we assess the hydrologic sensitivity and resilience of soil moisture and vegetation water content (derived from NRL’s WindSat radiometer), during dry spells, for different dry-period durations, and for various vegetation categories. Spatiotemporal patterns and characteristics of the response of the two aforementioned variables to sustained precipitation deficits (derived from TRMM 3B42 V7), as well as their persistence in maintaining their stability are identified. We also assess changes, in space and time, in the normalized radar surface-backscattering cross-sections from NASA’s QuikSCAT Scatterometer, to obtain information on the vegetation regimes, as well as changes in vegetation phenometrics using the enhanced vegetation index (EVI) derived from MODIS. Quantifying the response and characterizing the resilience of the two aforementioned major hydrological attributes using various remote sensing techniques that complement each other, can provide critical insight into the region’s vulnerability and adaptive capacity with respect to rainfall variability.