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机构地区:[1]贵州师范大学地理与环境科学学院,贵州贵阳550001
出 处:《贵州农业科学》2013年第7期111-115,共5页Guizhou Agricultural Sciences
基 金:国家"十二五"科技支撑计划"中低产田障碍因子消减与地力提升共性关键技术研究"(2012BAD05B06);贵州省优秀青年科技人才培养对象专项资金"喀斯特土壤侵蚀机理及预报预测系统的研究"[黔科合人字(2011)14]
摘 要:为了进一步认识喀斯特山区土壤侵蚀特征及准确估算土壤侵蚀量,通过对野外调查结果、已有研究成果的综合评判,选取坡度、雨强、植被覆盖度及裸岩率为主要土壤侵蚀因子,选取该区域广布的黄壤作为试验土样,采用针管式人工降雨模拟装置,模拟不同坡度条件下雨强、植被覆盖度、裸岩率与土壤侵蚀量之间的相关性,并对试验数据进行多元线性回归、逐步回归和多元非线性回归分析,建立不同坡度条件下土壤侵蚀模数的多因子方程,筛选出不同坡度下复相关系数较高的回归模型,对模型精度进行了分析。结果表明:1)非线性回归模型达到极显著或非常显著水平(0.692<R2<0.988),线性回归模型达到显著水平(0.523<R2<0.634)。2)当坡度为6°、16°、26°、36°时,侵蚀模数的影响程度随着坡度的增大先减小后增大;侵蚀因子对侵蚀模数的影响程度为雨强>植被覆盖度>裸岩率。3)模型具有较好的预报精度,对缓坡、陡坡侵蚀产沙预测较准。研究初步揭示了喀斯特地区侵蚀模数与侵蚀因子的相关关系。In order to further understand characteristics of soil erosion and accurately estimate amount of soil erosion in karst mountainous area. By evaluating comprehensively geography trip result and researched results, the main factors of soil erosion included slope, rainfall intensity, vegetation coverage and bare rock rate, and the authors chose the yellow soil as the experimental sample that widely existed in southwest karst area. And simulated correlation between the main soil erosion factors and soil erosion modulus by using designed equipment of artificial simulation of rainfall, and according to researched equation form, established soil erosion model by using Multiple Linear Regression, Stepwise Regression and Nonlinear Regression method. Results: 1) Nonlinear regression models showed extremely significant level(0.692〈R2〈0. 988), linear regression models showed significant level(0. 523〈R2〈O. 634); 2) Effect of the factors on erosion modulus under 6°, 16°, 26°and 36°: rainfall intensity〉 vegetation coverage〉bare rock ratio; with the slope increasing, the influence degree of the erosion modulus decreased first, and then increased. 3)The model had a good prediction accuracy, and was quite accurate for sediment event of gentle and steep slope. The research revealed initially correlation between the main soil erosion factors and soil erosion modulus in karst area.
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