Remote Sensing Solutions for Estimating Runoff and Recharge in Arid Environments
Abstract
Efforts to understand and to quantify the interplay between precipitation, runoff, and recharge are often hampered by the paucity of appropriate monitoring systems. We developed methodologies for rainfall-runoff and groundwater recharge computations that heavily rely on observations extracted from a wide-range of global remote sensing data sets (TRMM, SSM/I, AVHRR, and AMSR-E,) using the and Sinai Peninsula (SP; area: 61,000 km2) and the Eastern Desert (ED; area: 220,000 km2) of Egypt as our test sites. A two-fold exercise was conducted. Temporal remote sensing data (TRMM, AVHRR and AMSR-E) were extracted from global data sets over the test sites using RESDEM, the Remote Sensing Data Extraction Model, and were then used to identify and to verify precipitation events from 1998-2006. This was accomplished by using an automated cloud detection technique to identify the presence of clouds during the identified precipitation events, and by examining changes in soil moisture (extracted from AMSR-E data) following the identification of clouds. A catchment-based, continuous, semi-distributed hydrologic model (Soil Water and Assessment Tool model; SWAT) was calibrated against observed runoff values from Wadi Girafi Watershed (area: 3350 km2) and then used to provide a continuous simulation (1998-2006) of the overland flow, channel flow, transmission losses, evaporation, evapo-transpiration, and groundwater recharge for the major (area ≥ 2000 km2) watersheds in the SP and the ED covering 48% and 51% of the total areas, respectively. For the investigated watersheds in the SP, the average annual runoff, and average annual recharge through transmission losses were found to be: 80.5 x 106m3 (10.3% total precipitation (TP)) and 87.3 x 106m3 (11.2% TP), respectively, whereas in the ED these values are: 17.5 x 106m3 (4.1% TP) and 86.1 x 106m3 (20.1 % TP), respectively. Results demonstrate the enhanced opportunities for groundwater development in the SP (compared to the ED) and highlight the potential for similar applications in arid areas elsewhere. The adopted approach is not a substitute for traditional methodologies that rely on extensive datasets from rain gauge and stream flow networks, but rather a tool for providing first order estimates for rainfall, runoff, and recharge over large sectors of the world.