[1]YANG Kuanda,XIE Hongxia,SUI Bing,et al.Research on Spatial Interpolation of Rainfall Based on GIS-A Case Study of Hunan Province[J].Research of Soil and Water Conservation,2020,27(03):134-138,145.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
27
Number of periods:
2020 03
Page number:
134-138,145
Column:
目次
Public date:
2020-04-20
- Title:
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Research on Spatial Interpolation of Rainfall Based on GIS-A Case Study of Hunan Province
- Author(s):
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YANG Kuanda1,3, XIE Hongxia1, SUI Bing2, ZHOU Qing1, LIU Pei1, WANG Haitao1
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(1.College of Resources and Environment, Hunan Agricultural University, Changsha 410128, China; 2.Hunan Key Laboratory for Meteorological Disaster Prevention and Reduction, Changsha 410007, China; 3.School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)
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- Keywords:
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ordinary Kriging interpolation; CoKriging interpolation; rainfall; interpolation accuracy
- CLC:
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P426.6; P426.62+2
- DOI:
-
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- Abstract:
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Rainfall data are the basic for regional hydrological simulation, water resources analysis and management, geological hazard warning, etc. It is of great theoretical and practical significance to improve the interpolation accuracy of rainfall data. Hunan Province is taken as the research area. The station data, TRMM data and DEM data are used for rainfall interpolation by the ways of Kriging and CoKriging. The interpolation results are compared to study the accuracy of rainfall interpolation. The results show that:(1)CoKriging interpolation using the TRMM and DEM as data source which is related to rainfall spatial information can improve interpolation accuracy; the average relative errors of CoKriging interpolation with TRMM and DEM as auxiliary variable are 0.02% and 0.23% lower than Kriging interpolation, respectively;(2)The interpolation results of station data show different sensitivity to the auxiliary variables of TRMM data and DEM data; The interpolation accuracy of CoKriging with DEM as auxiliary variable is higher than CoKriging with TRMM as auxiliary variable. The rainfall in the study area has a higher correlation with the topographic factors.