Mapping of Temperature Trend Slope in Iran′s Zayanderud River Basin: A Comparison of Interpolation Methods
- 1 University of Tehran, Iran
- 2 Isfahan University of Technology, Iran
- 3 Shahid Bahonar University of Kerman, Iran
- 4 Islamic Azad University, Iran
- 5 Aghigh University, Iran
Copyright: © 2020 Ali Zahraei, Saeid Eslamian, Ali Saeidi Rizi, Neda Azam, Morteza Soltani, Mohammad Mousavi, Sona Pazdar and Kaveh Ostad-Ali-Askari. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.
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- Spatial Distribution
- Temperature Trend
- Ayanderud River Basin