Investigation of different interpolation methods for estimation and zoning of precipitation variables in agricultural lands of Aq-Qalla township for rainfed cropping of autumn cereals

Determination of the precipitation spatial variability in agricultural lands is particularly very importance. For this propose, the spatial distribution of precipitation on agricultural lands of Aq-Qalla township evaluated using 18 method-models from deterministic and geostatistic interpolation such as, Inverse Distance Weighted (IDW), Universal Kriging (UK), Ordinary Kriging (OK), Radial Basis Function (RBF) and Local Polynomial Interpolation (LPI). The performance criteria for evaluation were Root Mean Square Error (RMSE) and General Standard Deviation (GSD) with the Cross Validation methods. The results showed that Local Polynomial Interpolation (1 and 2 degree) was the best method to estimate precipitation parameters except spring and June precipitation. Because, it had the highest accuracy and the lowest error for estimating of these parameters. Semivariograms analysis indicated that annual and June precipitation were best fitted to Exponential model, also, autumn, spring and May precipitation by Spherical model. Results of final maps showed that amount of annual, autumn, and June rainfall were lower in north than south regions. Moreover, the results of this research showed that about 65.62 percentage of agricultural lands of Aq-Qalla had suitable level of annual rainfall (300-400 mm). Also, in this area amount autumn rainfall was 101.11 to 166.08 mm. The results indicated that same as temperature requirements, the annual and autumn rainfall requirements of current crops such as wheat and barley are provided in this township. But, amount of spring and June rainfall are non-suitable in this area. Wide area in Aq-Qalla township were under 10 mm rainfall in June.