Liu Xiaoni, Guo Jing, Ren Zhengchao, Hu Zizhi, Chen Quangong, Zhang Degang, Zhu Huazhong. Chinese rangeland CSCS classification based on optimal simulation for spatial distribution of meteorological factors[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(9): 222-229.
    Citation: Liu Xiaoni, Guo Jing, Ren Zhengchao, Hu Zizhi, Chen Quangong, Zhang Degang, Zhu Huazhong. Chinese rangeland CSCS classification based on optimal simulation for spatial distribution of meteorological factors[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(9): 222-229.

    Chinese rangeland CSCS classification based on optimal simulation for spatial distribution of meteorological factors

    • According to Comprehensive and Sequential Classification System of Rangeland (CSCS) and ArcGIS platform, an improved interpolation method named analytic method based on multiple regression and residues (AMMRR), and 3 traditional interpolation methods, in conjunction with 1 km resolution DEM and meteorological data from 1961 to 2004 in China as main data sources, were applied in simulating the spatial distribution pattern of annual accumulative temperature (>0℃ Σθ) and annual precipitation (r), and carrying out classification for Chinese rangeland with AMMRR after the comparison among 4 interpolation methods. The results showed that: 1) The correlation coefficents between simulative and observational value of Σθ and r were 0.976 and 0.974 with highly significant correlation (p<0.01) based on AMMRR, respectively. Its relative mean error (RME), mean absolute error (MAE) and root-mean-square error (RMSE) were entirely lower than traditional interpolation methods. 2) AMMRR method can remedy the shortcoming and heterogeneous distribution of meteorological stations, and fully reflect the vertical variation of meteorological factors in the regions of big net height via modifying residual errors between observational and simulative value and implementing multiple regression among meteorological factors and longitude, latitude, elevation. In the region with densely meteorological stations, the simulative effects of 4 simulative methods were highly agreement with each other, and the spatial distribution pattern of Σθ and r were similar with their actual geographical conditions. Compared to the region of sparsely and heterogeneously meteorological stations, only AMMRR method with ideal interpolation effect can reflect the spatial heterogeneity of topography on the spatial distribution pattern of Σθ and r in the small scale regions. 3) Associate with CSCS, Chinese rangeland could be classified into 41 classes exception of Tropical-extrarid tropical desert(ⅦA7). Subsequently Tropical-perhumid rain forest(ⅦF42), Sub-tropical perhumid evergreen broad leaved forest (ⅥF41), Warm-perhumid deciduous-evergreen broad leaved forest (ⅤF40), Warm temperate perhumid deciduous broad leaved forest (ⅣF39) and Cool temperate perhumid mixed coniferous broad leaved forest (ⅢF38), Cool temperate-humid forest steppe, deciduous broad leaved forest (ⅢE31), Cool temperate-subhumid meadow steppe(ⅢD24), Cool temperate semiarid temperate typical steppe (ⅢC17) distributed with the decreasing Σθ and r from south to north and from east to west, which indicated significantly zonality patterns.s
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