Capability of Infrared & Passive Microwaves Remotely Sensed Data for Rainfall Estimation and Flood Monitoring (Case Study: Golestan Province, Iran)

Among all kinds of natural hazards in the world, flood is probably the most devastating, wide spread and frequent one that often results from excessive rainfall within a short period of time. Due to excessive rainfall during warm seasons, Golestan province has encountered with severe floods in recent years. Since rainfall intensity in this area is variable, the rain gauge cannot illustrate this variation, so that using remote sensing for rainfall estimation is inevitable. Satellite rainfall estimation algorithms frequently use infrared (IR) and Passive Micro Wave (PMW) data. IR data have high spatial and temporal resolution but cannot penetrate clouds; whereas PMW data can penetrate and estimate rainfall more accurately but have lower spatial and temporal resolution. Thus, by combining these two datasets, the advantage of reducing deficiencies can be achived.This paper describes the ability of combined METEOSAT and TRMM data for rainfall estimation of 10th of August 2005 and its application in flood monitoring in Golestan province. For flood monitoring the Geospatial Stream Flow Model (GeoSFM) was used. The correlation between predicted and rain gauge data was found to be 0.533; also calculated RMSE and MAD were 9.74 and 6.67 respectively. It was also distinguished that as the most sub-basin in the catchment had dried soil before raining in 10th of August, eastern and southeastern parts of the catchments (the place of exteme raining) were expreinced high flow of runoff. Hydrograph also showed that the maximum runoff occurred at 10th of August and after that time runoff decreased, but the decreasing slope is slight. The reason for this behavior seems to be the soil moisture and reduction in soil penetration due to extreme rainfall.