Using the Least Squares Method for the Ggeneration of Digital Precipitation Model

One of the most important procedures in the water sources studies is the estimation of the local distribution of precipitation in different time scales. The study of precipitation is a basic element in the water balance studies and is an important factor in the natural sources programs of each country. Also, because of the rain-evaluation stations deficiency and their discreteness, it is necessary to use a special model. Besides the interpolation of precipitation amounts of stations, this model should interpolate topography, moisture and the slope direction of precipitation. In this work, at first, some data were gathered, in one year. These data were connected with the precipitation and moisture of 9 synoptic stations and 31 rainevaluation stations. These stations were located in the Lorestan province. Second, using the least square method and with the help of Maple software, the relations between precipitation and moisture was extracted. Third, by using the Python programming language, these relations were linked into the GIS. Finally, by so doing, the digital precipitation modal was achieved. The results obtained from the digital precipitation model show that, the precipitation amounts are different from the measured data in the stations, from 0.02 to 11.6 mm. Also, to investigate the efficiency of the considered model, the data obtained from this model were compared with the precipitation data achieved from TRMM radar at 21 April 2010. The concluded result show that, the determination coefficients are 79 and 86% for the TRMM data and for the digital precipitation model, respectively.