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[1]ZHANG Yu-qing,CHEN Chang-chun,YIN Yi-xing,et al.Spatial Interpolation Model Selection of Multi-Year Average Precipitation in Jiangxi Province[J].Research of Soil and Water Conservation,2013,20(04):69-74.

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Spatial Interpolation Model Selection of Multi-Year Average Precipitation in Jiangxi Province

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 20 Number of periods: 2013 04 Page number: 69-74 Column: Public date: 2013-08-28

Title:: Spatial Interpolation Model Selection of Multi-Year Average Precipitation in Jiangxi Province

Author(s):: ZHANG Yu-qing¹, CHEN Chang-chun¹, YIN Yi-xing², YANG Xu-hong³; 1. College of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2. College of Hydrometeorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;
3. College of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China

Keywords:: Jiangxi province; precipitation; spatial interpolation model; kriging interpolation

CLC:: P333.1

DOI:: -

Abstract:: To explore the distribution pattern of multi-year average annual precipitation in Jiangxi Province, 81 complete sequence time series of 81 weather stations were used, which included precipitation data of 30 years (1976—2005) in Jiangxi Province. The universal kriging is used in different semivariogram model to fit the precipitation data after exploring the distribution features of the data; according to test of 65 cross validation and inspection of 16 stations, it is indicated that the multi-year average annual precipitation has strong spatial correlation. Through the comparison of different semivariogram function models, it is found that exponential model and spherical model in the results of cross validation stations were 1.024, 1.023 for Root-Mean-Square Standardized, which is close to 1 and error was small. Exponential model and spherical model in the results of inspection stations were 1.105, 1.104 for Root-Mean-Square Standardized, showing that the fitting effect of the two models is better than the others, it can more perfectly reflect the spatial distribution of multi-year average precipitation in Jiangxi Province, in which the result of exponential model can obtain the better integer effect within the existing weather stations network.

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