HR: 1330h
AN: H23A-11    [Abstracts]
TI: An Integrated Approach (TRMM, MODIS, AVHRR, and Rain Gauge) for Assessment of Precipitation in Arid Areas: A Case Study from the Eastern Desert of Egypt
AU: * Milewski, A
EM: adam.m.milewski@wmich.edu
AF: Western Michigan University, Geosciences Department, 1903 W. Michigan Ave, Kalamazoo, MI 49008 United States
AU: Sultan, M
EM: mohamed.sultan@wmich.edu
AF: Western Michigan University, Geosciences Department, 1903 W. Michigan Ave, Kalamazoo, MI 49008 United States
AU: Becker, R
EM: richard.becker@wmich.edu
AF: Western Michigan University, Geosciences Department, 1903 W. Michigan Ave, Kalamazoo, MI 49008 United States
AU: Abdeldayem, A W
EM: abdeldayem@eng.cu.edu.eg
AF: Cairo University,Irrigation and Hydraulics Engineering Department, Gamaa Street, Giza, 12613 Egypt
AB: Water shortages are major obstacles to sustainable development and a cause for poverty in arid and semiarid countries. In these domains often the case, the appropriate systems (precipitation networks) that are needed to estimate precipitation on a regional scale are absent. We developed an integrated methodology to address this problem using data sets that are available on a global scale. We developed an integrated approach to improve estimates of renewable water resources. The approach utilizes the following data sets (1) TRMM-3B42V6 to extract 3-hourly precipitation data, (2) daily AVHRR data for soil moisture and NDVI measurements, (3) METEOSAT-7 for monitoring cloud movement, and (4) rain gauge data for ground truthing. Our approach entails identifying rain storm events from TRMM data. Following the identification of the events, we verify the individual events by examining the cloud patterns, examining the temporal variations in NDVI and soil moisture, and through comparisons with rain gauge data. For the year 1998, we examined in a GIS environment the following: TRMM scenes (2920 scenes), AVHRR data (365 scenes), METEOSAT (8760 scenes), and available rain gauge data. Findings indicate: (1) A general correspondence between TRMM data and rain gauge data, (2) A progressive increase in NDVI measurements following precipitation (peak after ~10 days), and (3) instantaneous increase in soil moisture. A similar (yet with a more restricted data set) exercise was conducted in year 1994, where a major flood occurred.
DE: 1640 Remote sensing
DE: 1800 HYDROLOGY
DE: 1829 Groundwater hydrology
DE: 9305 Africa
SC: Hydrology [H]
MN: 2005 Joint Assembly