Ation approaches. The values of 4 error indicators are distinguished in color degree–light blue indicates a bigger value, dark blue indicates a smaller sized value. The smaller the error indicator, the improved the interpolation method along with the greater the accuracy in estimating the spatial patterns of precipitation. Overall, interpolation models estimate the spatial patterns of precipitation to a reasonable degree; nevertheless, outliers appear at some stations. For example, meteorological station 15 has the biggest estimation error, followed by meteorological station 18. The estimation anomaly for a specific spatial location could possibly be attributed to the complex weather variability [38] caused by the substantial elevation differences [45] in Chongqing, which could influence the efficiency of interpolation approach [33]. 4.four. Complete Ranking by Entropy-Weighted TOPSIS To figure out the optimal strategy for estimating spatial precipitation patterns in Chongqing, Entropy-Weighted TOPSIS was adopted to quantize and rank the efficiency of six interpolation strategies. According to the performance evaluation indices (MSE, MAE, MAPE, SMAPE, NSE), the six interpolation solutions are ranked when it comes to their efficiency in estimating spatial patterns beneath different rainfall magnitudes and integrated several rainfall magnitudes. Initially, the indicators are standardized, where MSE, MAE, MAPE, SMAPE are negative indices and NSE is a optimistic indicator. According to weighting outcomes of entropy technique, the distance among optimistic and adverse perfect options of every single process is calculated to determine the comparatively proximity (C-value) to the perfect option, and ultimately the C-value is ranked to qualitatively evaluate the performance of six techniques in estimating the spatial pattern of precipitation in Chongqing under unique climatic conditions. The calculation outcomes of TOPSIS evaluation are shown in Table two. According to TOPSIS evaluation, KIB is the optimum interpolation process below the imply annual precipitation pattern, with all the comparative proximity (C-value) the highest at 0.964, followed by EBK. RBF would be the optimal system within the rainy-season precipitation pattern, using the C-value the highest at 0.978, followed by KIB. KIB was the optimal approach in the dry-season precipitation pattern, using the C-value the highest at 1, followed by OK. IDW was the worst Lactacystin Technical Information technique within the all precipitation patterns, with all the C-value was the lowest to 0 devoid of exception.Table two. TOPSIS superiority ranking of six spatial interpolation solutions according to both distinctive rainfall magnitudes and integrated several rainfall magnitudes. Approaches with superior functionality are shown in bold.Approach 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.Damaging 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.six 0.581 0 0.978 0.899 0.87 0.773 0.474Sort Result 1 2 three 4 5 six 1 2 3 four 5Mean AnnualRainy SeasonAtmosphere 2021, 12,20 ofTable 2. Cont.Strategy 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 3 four five six 1 two 3 four 5Dry SeasonIntegrated ScenarioFinally, based on the C-value of the six solutions under distinct.
