【摘要】 坡谱信息熵可综合反映地形起伏特征,计算便捷,为探索其能否替代计算繁杂的地形因子应用在土壤侵蚀评价中,该研究以西南紫色土水蚀区为研究对象,基于ASTER GDEM(30 m分辨率),计算坡谱信息熵、坡度坡长因子及沟壑密度等地形因子,分析坡谱信息熵与地形因子量化关系。结果表明:全区坡谱曲线形态有"S"、"L"及近似钟型,峰值集中分布在0°～3°、15°～18°、24°～27°;全区坡度坡长因子均值为11.03,空间北大南小的分布差异明显。区域尺度的沟壑密度为0.66km/km~2,流域尺度沟壑密度为0.33～0.88km/km~2;坡谱信息熵与坡度坡长因子在一级区(R~2=0.949 4,P<0.01)、二级区(R~2=0.960 3,P<0.01)均具有显著的对数或幂函数关系。与沟壑密度在川渝山地丘陵区呈显著的指数关系(R~2=0.747 5,P<0.05),在其他区域尺度虽存在显著的多项式函数关系,但相关度较低。研究结果可为紫色土区水土流失评价、土壤侵蚀预报提供科学依据。更多还原

【Abstract】 In conventional soil erosion evaluation, the calculation of slope length and steepness(LS) factor requires the relatively complicated extraction of slope grade and slope length, and there are certain thresholds due to the determination of slope length to the location. Slope Spectrum’s Information Entropy(SSIE) can comprehensively represent the characteristics of topographic relief, but it is not clear that how to apply for the prediction of soil erosion. This paper aims to explore the relationship between the SSIE and topographic factors, while the research area is taking the water erosion area of purple soil in southwest China, including the Qinba mountains region, Wuling mountain hilly area, and Sichuan and Chongqing mountainous region. The slope gradient, slope length, and hydrographic net were extracted using ArcGIS based on ASTER GDEM(30 m resolution). After the calculation, two relationships were established between the SSIE and LS factor, as well the SSIE and gully density based on 63 basins. The results showed that: 1) The whole region displayed the curves of slope spectrum in the shape of "L", "S" and approximate bell, while the different curves of slope spectrum were successively distributed in Sichuan and Chongqing mountainous region, Wuling mountain hilly area and Qinba mountains region. Meanwhile, the main peaks of slope spectrum curves were concentrated in 0°-3°,15°-18° and 24°-27°. 2) The mean of LS factor was 11.03, and the distribution range of LS factors was 0-5, 10-15 and greater than 20 in Qinba mountainous region and Wuling mountain hilly area. However, that in Sichuan and Chongqing mountainous region was mainly concentrated in 0-15, showing obvious north-south difference. 3) The gully density was 0.66 km/km~2 at the regional scale, particularly 0.72 km/km~2 in Qinba mountains region, and 0.75 km/km~2 in Wuling mountain hilly area. In Sichuan and Chongqing mountainous region, the gully density reached the minimum, 0.57 km/km~2, lower than 17.39% mean value of the regional scale. The gully density ranged from 0.33 to 0.88 km/km~2 at the watershed scale. 4) The SSIE showed a logarithmic relationship with LS factor in the different scales, expressed as y=0.589 7 lnx+1.201(R~2=0.949 4, P<0.01) in first zone, y=0.577 7 lnx+1.200 3(R~2=0.960 3, P<0.01), y=0.749 lnx+0.907 3(R~2=0.983 8,P<0.01), and y=1.3165 x0.302(R~2=0.989 1,P<0.01) in Qinba mountains region, Wuling mountain hilly area, and Sichuan and Chongqing mountainous region, respectively. However, there were significant differences in the relationships between the SSIE and gully density in the various scales. The relationship between the SSIE and gully density was a polynomial function with low degree of correlation in first and other secondary zone, except for the highly correlated exponential function(y=1.3045 e1.0452 x(R~2=0.7475,P<0.05)) in Sichuan and Chongqing mountainous region. The method can reduce the tedious calculation of LS factor and gully density, while the calculation of SSIE can make the evaluation of soil erosion easier and simpler than before. The findings can be expected to provide a scientific basis for the evaluation and prediction of soil erosion in purple soil and water erosion areas.更多还原