Evaluation of rainfall on a daily, monthly and annual basis using satellite imagery (Case study: west boundary basin of Iran)

Precipitation variable is the key parameter of agricultural and hydrometeorology studies. Therefore, measurement and estimation of rainfall at the regional level help to understand the manner of water and energy cycles. In spite of the high variability of temporal and spatial precipitation quantity, precipitation monitoring using ground stations at regional scales is considerably difficult. The use of satellite images with high spatial resolution is therefore recommended. However, it is first necessary to evaluate temporal and spatial accuracy of data. The aim of this study was to evaluate the accuracy of Tropical Rainfall Measuring Mission (TRMM) satellite data for estimating daily, monthly, and annual rainfall on a regular spatial scale (0.25° ×0.25°) during 2000-2012, and to compare these estimated data with precipitation data at 30 stations (synoptic and climatological) in the west boundary basin of Iran. The Pearson correlation coefficient was calculated daily, monthly, and annually for the mentioned rainfall period changes. The results indicated a significant correlation (p<0.05) among the monthly and annual collected data of terrestrial and satellite precipitation. The relationship between monthly precipitation data from satellite images and observed data from stations were also determined using a linear and nonlinear regression for each year. The model reliability was also subsequently determined using statistical validation.