Mapping of Temperature Trend Slope in Iran′s Zayanderud River Basin: A Comparison of Interpolation Methods

Abstract

The spatial distribution of daily, nightly and mean temperature trend in Iran′s Zayanderud river basin was carried out in this study by applying three approaches of interpolation including Inverse Distance Weighting (IDW), Multiple Linear Regression (MLR) and integration of these two methods (IDW+MLR). In this paper, t-test and statistical measures including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), systematic Root Mean Square Error (RMSEs) and unsystematic Root Mean Square Error (RMSEu) were used to evaluate the performance of approaches. This study reveals that temperature trends are inversely correlated with the altitude. All three interpolation methods overestimate in the prediction of daily and mean temperature trend and underestimate in estimating nightly temperature trend. Among three methods, IDW is the most accurate and precise in predicting daily and mean temperature trends. IDW is the most accurate and IDW+MLR is the most precise method to estimate nightly temperature trend. The MLR method for estimating nightly, mean temperature trend and the IDW method for estimating daily temperature trend have the lowest systematic error.