Remote Sensing Contributions to Rainfall-Runoff and Recharge Modeling

Efforts to quantify precipitation, runoff, and recharge are often hampered by the absence 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, Landsat TM, AVHRR, AMSR-E) using the arid Sinai Peninsula (SP) and the Eastern Desert (ED) 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 throughout the past nine years (1998-2006). The verification process is an automated technique which first identifies the presence of clouds and then test for an increase in soil moisture and vegetation intensity difference images following a precipitation event. A SWAT model was developed and calibrated against observed runoff values from Wadi Girafi and then used to provide a continuous simulation (1998-2006) of the hydrologic variables for the major (area ≥ 2000 km²) watersheds in the SP (Watir, El-Arish, Dahab, Awag) and the ED (Qena, Hammamat, Asyuti, Tarfa, El-Quffa, El-Batur, Kharit, Hodein, Allaqi). For the investigated watersheds in the SP, average annual runoff, and average annual recharge through transmission losses were found to be: 80.5 x 10⁶m³, and 87.3 x 10⁶m³, respectively, whereas in the ED these values are: 17.5 x 10⁶m³, and 86.1 x 10⁶m³, respectively. The adopted approach is not a substitute for traditional methodologies that rely on extensive datasets from rain gauge and stream flow networks, yet could provide first order estimates for rainfall, runoff, and recharge over large sectors of the arid world lacking adequate coverage with spatial and temporal precipitation and field data.