Ation techniques. The values of four error indicators are distinguished in colour degree–light blue indicates a bigger value, dark blue indicates a smaller sized worth. The smaller the error indicator, the superior the interpolation approach plus the higher the accuracy in estimating the spatial patterns of precipitation. General, interpolation models estimate the spatial patterns of precipitation to a reasonable degree; however, outliers appear at some stations. For instance, meteorological station 15 has the largest estimation error, followed by meteorological station 18. The estimation anomaly for any Pyrroloquinoline quinone Technical Information particular spatial place could be attributed for the complicated weather variability [38] caused by the substantial elevation variations [45] in Chongqing, which could influence the overall performance of interpolation process [33]. four.four. Complete Ranking by Entropy-Weighted TOPSIS To establish the optimal process for estimating spatial precipitation patterns in Chongqing, Entropy-Weighted TOPSIS was adopted to quantize and rank the performance of six interpolation solutions. Depending on the overall performance evaluation indices (MSE, MAE, MAPE, SMAPE, NSE), the six interpolation strategies are ranked when it comes to their efficiency in estimating spatial patterns below various Histamine dihydrochloride Autophagy rainfall magnitudes and integrated multiple rainfall magnitudes. Initial, the indicators are standardized, exactly where MSE, MAE, MAPE, SMAPE are unfavorable indices and NSE is a good indicator. According to weighting outcomes of entropy technique, the distance involving good and adverse best options of every system is calculated to establish the comparatively proximity (C-value) towards the best option, and lastly the C-value is ranked to qualitatively evaluate the efficiency of six techniques in estimating the spatial pattern of precipitation in Chongqing under diverse climatic situations. The calculation results of TOPSIS evaluation are shown in Table 2. According to TOPSIS evaluation, KIB may be the optimum interpolation technique under the imply annual precipitation pattern, with all the comparative proximity (C-value) the highest at 0.964, followed by EBK. RBF may be the optimal approach inside the rainy-season precipitation pattern, with all the C-value the highest at 0.978, followed by KIB. KIB was the optimal method within the dry-season precipitation pattern, together with the C-value the highest at 1, followed by OK. IDW was the worst method in the all precipitation patterns, with the C-value was the lowest to 0 with out exception.Table two. TOPSIS superiority ranking of six spatial interpolation methods based on both distinct rainfall magnitudes and integrated numerous rainfall magnitudes. Solutions with superior performance are shown in bold.Strategy KIB EBK OK RBF DIB IDW RBF KIB EBK OK DIB IDWPositive Distance (D) 0.016 0.083 0.155 0.18 0.191 0.448 0.01 0.046 0.06 0.104 0.238 0.Adverse Distance (D-) 0.441 0.374 0.311 0.269 0.265 0 0.442 0.41 0.401 0.353 0.214Comparatively Proximity (C) 0.964 0.818 0.667 0.6 0.581 0 0.978 0.899 0.87 0.773 0.474Sort Result 1 two three four five six 1 two three 4 5Mean AnnualRainy SeasonAtmosphere 2021, 12,20 ofTable two. Cont.Method KIB OK EBK DIB RBF IDW KIB EBK OK RBF DIB IDWPositive Distance (D) 0 0.063 0.073 0.189 0.213 0.447 0.024 0.07 0.126 0.127 0.241 0.Unfavorable Distance (D-) 0.447 0.386 0.375 0.27 0.238 0 0.49 0.44 0.379 0.373 0.265Comparatively Proximity (C) 1 0.86 0.836 0.588 0.528 0 0.954 0.863 0.75 0.746 0.524Sort Result 1 two three four five 6 1 2 3 four 5Dry SeasonIntegrated ScenarioFinally, depending on the C-value on the six methods below unique.
