Document Type : Research Paper

Authors

• MohammadHoseein Rezaei Moghaddam ¹
• Khalil Valizadeh Kamran ²
• Mehdi Belvasi ³
• Hoseein KheiriAstiyar ⁴
• Sayad Asghari Saraskanroud ⁵

¹ Group Geomorphology Tabriz University

² Department of Remote Sensing and GIS University of Tabriz

³ Remote sensing and GIS University of Tabriz

⁴ Department of Applied Mathematics, University of Tabriz

⁵ Group geomorphology, Urmia University

Abstract

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
 

Keywords

• Precipitation Interpolate
• Least squares method
• Lorestan province
• Digital Precipitation Model

Main Subjects

• Climatology