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[1]ZHU Yuguo,DU Lingtong,XIE Yingzhong,et al.Evaluation on Accuracy of Three Meteorological Interpolation Methods and Their Impacts on Grassland NPP Estimation[J].Research of Soil and Water Conservation,2018,25(06):160-167.

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Evaluation on Accuracy of Three Meteorological Interpolation Methods and Their Impacts on Grassland NPP Estimation

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 25 Number of periods: 2018 06 Page number: 160-167 Column: Public date: 2018-10-26

Title:: Evaluation on Accuracy of Three Meteorological Interpolation Methods and Their Impacts on Grassland NPP Estimation

Author(s):: ZHU Yuguo^1,2, DU Lingtong^1,2, XIE Yingzhong^1,2,3, LIU Ke^1,2, GONG Fei^1,2, DAN Yang^1,2, WANG Le^1,2; 1. Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest China, Ningxia University, Yinchuan 750021, China;
2. Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwest China, Ministry of Education, Ningxia University, Yinchuan 750021, China;
3. School of Agriculture, Ningxia University, Yinchuan 750021, China

Keywords:: CASA model; spatial interpolation; grassland NPP

CLC:: Q948

DOI:: -

Abstract:: Based on the mean annual temperature and mean annual precipitation from 14 meteorological observation sites during 2000—2015 in Ningxia Province and its adjacent areas, three spatial interpolation methods including the inverse distance weighted interpolation (IDW)，spline interpolation and Anusplin were used to interpolate the climate factors respectively. The cross checking method was used to verify the results of interpolation. Based on those results, we had been analyzed the feasibility of CASA model in estimating grassland NPP and the effects of improving interpolate precision on NPP estimation in Ningxia. The main conclusions are as follows. (1) Anusplin method had minimum error and the highest accuracy of interpolating meteorological factors in Ningxia area. IDW method’s interpolating error was the maximum, especially in air temperature interpolation. (2) The CASA model has shown the strong applicability grassland NPP estimating by comparing with the measured data and the spatial distribution pattern of NPP is consistent with the actual situation in Ningxia, therefore, the simulation data are reliable. (3) In NPP estimation of different grassland types, CASA model based on Anusplin interpolation that enhances interpolation accuracy has the little estimating error and improves the precision of NPP estimation by referencing to MOD17A3 NPP data as a verified data. The results indicate that CASA model has more accurate in estimation of NPP of semi-arid grassland, shrub grassland, shrub grassland, desert grassland and desert steppe, and the estimation accuracies of NPP of wetland grassland and mountain meadow are poor, and these estimation accuracies should be further improved.

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