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Accuracy Analysis of Precipitation Regionalization Methods Based on Spatial Interpolation Techniques in Zayandeh-Rud River Basin

机译:基于空间插值技术的赞丹德-拉德河流域降水分区方法的精度分析

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In the present study, we used 27 precipitation average monthly data from synoptic, climatologic, rain-guage and evaporative stations located in Zayandeh-Rud river basin for the period of 1970-2014. Before interpolating, the missing data in the time series of each station was reconstructed by the normal ratio method. Also, for the data quality control, the Dickey-Fuller and Shapiro-Wilk tests were used to check the data stationarity and normality. Then, these data were interpolated by six interpolation methods including Inverse Distance Weighting,Natural Neighbor, Tension Spline, Regularized Spline, Ordinary Kriging and Universal Kriging; theneach method was evaluated using the cross-validation technique with MAE, MBE and RMSE indices. The results showed that among the spatial interpolation methods, Natural Neighbor method with MAE of 0.24 had the best performance for interpolating precipitation among all of the methods. Also, among Ordinary Kriging, Universal Kriging, Spline and Inverse Distance Weighting methods, respectively, Exponential Kriging with MAE 0.54, Quadratic Drift Kriging with MAE of 0.5, Tension Spline with the MAE of 0.54 and Inverse Distance Weighting with the power of 4 with MAE of 0.57 had the least error compared to other IDW methods.
机译:在本研究中,我们使用了1970-2014年间Zayandeh-Rud流域天气,气候,雨量和蒸发站的27个降水月度平均值。在插值之前,每个站点的时间序列中的丢失数据通过正常比率方法进行重构。此外,对于数据质量控制,使用Dickey-Fuller和Shapiro-Wilk测试来检查数据的平稳性和正常性。然后,通过反距离加权,自然邻域,张力样条,正则样条,普通克里格法和通用克里格法等六种插值方法对这些数据进行插值;然后使用具有MAE,MBE和RMSE指数的交叉验证技术评估每种方法。结果表明,在所有空间插值方法中,MAE为0.24的自然邻域方法在所有方法中对降水的插值性能最佳。此外,在普通克里金法,通用克里金法,样条法和反距离权重方法中,分别使用MAE 0.54的指数克里金,MAE 0.5的二次漂移Kriging,MAE 0.54的张力样条和使用MAE的4的幂的逆距离加权与其他IDW方法相比,0.57的误差最小。

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