Abstract
Rain gages data represents limited spatial coverage, especially in rugged terrains like Lebanon. Other precipitation data sources are the developing satellite and radar technologies. In this study, Tropical Rain Measurement Mission (TRMM) monthly rainfall data of 18 years (1998-2014 and 2017) was used to understand monthly and yearly precipitation spatial distribution overall Lebanon. Topographic effect of rainfall spatial distribution was investigated in comparison to Plassard’s map of 1971. The annual precipitation over the country ranged between 850 mm and 200 mm that differs than the existing historical map. The maximum rainfall rate decreased by about 700 mm between the derived TRMM rainfall map and Plassard’s one. Spatial distribution of maximum precipitation rates does not coincide between maps. TRMM map of elevated terrains did not show similar trends of rainfall distribution as Plassard’s. Pixels (Lebanon was divided into 27 pixels) of lower rainfall rates was found toward the eastern side of Lebanon, in contrast to Plassard’s results. Anti-Lebanon did not show an increase in precipitation in accordance to altitude. Spatial variability of precipitation was about 50 mm between pixels which reveals the importance of considering topography while implemented rain gages as observation points. TRMM and satellite rainfall data aid in investigating complete spatial distribution of rainfall over continuous periods. Accumulating knowledge of spatial rainfall distribution on timely basis will lead to better future modelling on floods and drought conditions in Lebanon.
Highlights
Observation points have been the main source of rainfall distribution for more than a century
Pixels (Lebanon was divided into 27 pixels) of lower rainfall rates was found toward the eastern side of Lebanon, in contrast to Plassard’s results
This study focused on temporal and spatial variability of rainfall, overall Lebanon, for the sake of knowing homogeneous areas for representative distribution of point observation gages
Summary
Observation points have been the main source of rainfall distribution for more than a century. Rain gages are placed at spatial network of coverage, seeking representative localities for larger area depiction [1]. Users of rainfall data, especially, watershed hydrological modeler and agriculture management, are faced by low spatial accuracy while interpolating rainfall gages point readings. Runoff estimation is never precise without accurate spatial reproduction of rainfall distribution to cover the whole watershed area [2] [3] [4] [5]. Since the 1980s, precipitation is being recorded on continuous spatial scale, using satellite rainfall products. To improve precipitation data collection of satellite images [6] [7]
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