Estimating of point rainfall and determination the range of its variation in arid zones

During precipitation event, an area of land is prone to rainfall, but precipitation measuring is only accomplished in few points. So estimating of precipitation in other points can be done in several methods such as: correlation method, normal ratio method, and representative stations and inverse distance method. According to the principle of existing spatial structure among point rainfalls, the less distance between tow points, the less difference in precipitation received by them. The purpose of this research is to find the relationship between distance of two points and depth of precipitation. Then it is possible to estimate the precipitation in points without rain gauges via this relationship. To display this relationship existing rain gauge data in Daryacheh Namak Watershed were used. In this research distances among any rain gauge from others are calculated. Then variations between their monthly precipitations are calculated. Maximum and minimum of the variations are upper and lower limits of variations respectively. The best curve is fitted between variation limits and distance between two points. These equations are calculated at 3 levels of likelihood (80, 90, and 95%) and results are displayed in curves and equations. Using results of this research, it is possible to estimate the depths of precipitation in pointes without gauges by having the data of other rain gauges and the distance from the points to rain gauges. For example: if monthly precipitation in a rain gauge station is "X mm" and other point is "L km" far from this station, this point can receive precipitation between "X + Y1" to "X + Y2". In which "Y1" and "Y2" are the upper and lower limits of difference respectively. By calculating the average the upper and lower limits the monthly precipitation of that point can be estimated. To promote the likelihood, estimation precipitation in the point is possible by many rain gauges data and then calculating the average of results.