Gqing 400074, China Correspondence: [email protected]; Tel.: +86-Citation: Yang, R.; Xing, B. A Comparison from the Efficiency of Unique Interpolation Strategies in Replicating Rainfall Magnitudes beneath Distinctive Climatic Conditions in Chongqing Province (China). Atmosphere 2021, 12, 1318. https:// doi.org/10.3390/atmos12101318 Academic Editor: Corene Matyas Received: 31 July 2021 Accepted: 28 September 2021 Published: 9 OctoberAbstract: Precipitation is thought of a vital element 5-Hydroxy-1-tetralone site within the hydrological cycle and adjustments in its spatial pattern straight influence the water resources. We compare distinct interpolation techniques in predicting the spatial distribution pattern of precipitation in Chongqing. Six interpolation techniques, i.e., Inverse Distance Weighting (IDW), Radial Basis Function (RBF), Diffusion Interpolation with Barrier (DIB), Kernel Interpolation with Barrier (KIB), Ordinary Kriging (OK) and Empirical Bayesian Kriging (EBK), were applied to estimate diverse rainfall patterns. Annual imply, rainy season and dry-season precipitation was calculated in the everyday precipitation time series of 34 meteorological stations with a time span of 1991 to 2019, according to Leave-One-Out Cross-Validation (LOOCV), Mean Square Error (MSE), Imply Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Symmetric Imply Absolute Percentage Error (SMAPE) and Nash utcliffe Efficiency coefficient (NSE) as validation indexes of your applied models for calculating the error degree and accuracy. Correlation test and Spearman coefficient was performed on the estimated and observed values. A strategy combining Entropy Weight and Strategy for Order Preference by Similarity to Excellent Remedy (Entropy-Weighted TOPSIS) was introduced to rank the efficiency of six interpolation techniques. The results indicate that interpolation approach performs improved in estimating during periods of low precipitation (i.e., dry season, relative to rainy season and imply annual). The performance priorities on the six methods below the combined various precipitation distribution patterns are KIB EBK OK RBF DIB IDW. Among them, KIB system has the highest accuracy which maps far more precise precipitation surfaces, with all the disadvantage that estimation error is prone to outliers. EBK method could be the second highest, and IDW process has the lowest accuracy with a higher degree of error. This paper provides data for the application of interpolation procedures in estimating rainfall spatial pattern and for water resource management of concerned regions. Keyword phrases: spatial interpolation; deterministic solutions; geostatistical methods; precipitation; Geographical Data SystemsPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.1. Introduction Precipitation may be the most important climatic variable in hydrology and in water resource management, due to its essential impact on the spatial patterns of water availability [1]. The details of precipitation is vital for analyzing of regional water sources, the prediction and management of drought and flood disasters, along with the management with the ecological atmosphere [2,3]. Precipitation models have quite a few purposes, among other individuals, long-term organizing, climate change situation building, hydrological forecasting, hydrochemical modeling and human effect research, along with the assessment of water sources is normally depending on models interpolated from precipitation.
