A Multimethod Analysis for Average Annual Precipitation Mapping in the Khorasan Razavi Province (Northeastern Iran)

The spatial distribution of precipitation is one the most important climatic variables used in geographic and environmental studies. However, when there a lack full coverage meteorological stations, estimations are necessary to interpolate for larger areas. purpose this research was find best interpolation method mapping partly densely populated Khorasan Razavi province northeastern Iran. To achieve this, we compared five methods by applying average data from 97 rain gauge stations that period 20 years (1994–2014): Inverse Distance Weighting, Radial Basis Functions (Completely Regularized Spline, Spline with Tension, Multiquadric, Thin Plate Spline), Kriging (Simple, Ordinary, Universal), Co-Kriging Universal) an auxiliary elevation parameter, non-linear Regression. Root Mean Square Error (RMSE), Absolute (MAE), Coefficient Determination (R2) were determine best-performing interpolation. Our study shows Ordinary parameter determining annual region, showing highest coefficient determination 0.46% between estimated observed values. Therefore, application would form mandatory base regional planning policy making arid semi-arid during future.