Research on Influencing Factors of Soil Erosion Based on Random Forest Algorithm—A Case Study in Upper Reaches of Ganjiang River Basin

Zhu Qing; Guo Jiaxin; Guo Xi; Han Yi; Liu Shiyu; Chen Lei; Luo Hailing

doi:10.13961/j.cnki.stbctb.2020.02.009

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Research on Influencing Factors of Soil Erosion Based on Random Forest Algorithm—A Case Study in Upper Reaches of Ganjiang River Basin

- Research on Influencing Factors of Soil Erosion Based on Random Forest Algorithm—A Case Study in Upper Reaches of Ganjiang River Basin
- Bulletin of Soiland Water Conservation Vol. 40, Issue 2, Pages: 59-68(2020)
- 作者机构：
  
  江西农业大学国土资源与环境学院江西省鄱阳湖流域农业资源与生态重点实验室,江西,南昌,330045
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2020.02.009
  CLC： S157.1
- Published：2020
- 稿件说明：
移动端阅览
Zhu Qing, Guo Jiaxin, Guo Xi, et al. Research on Influencing Factors of Soil Erosion Based on Random Forest Algorithm—A Case Study in Upper Reaches of Ganjiang River Basin[J]. Bulletin of Soiland Water Conservation, 2020, 40(2): 59-68.
DOI：

Zhu Qing, Guo Jiaxin, Guo Xi, et al. Research on Influencing Factors of Soil Erosion Based on Random Forest Algorithm—A Case Study in Upper Reaches of Ganjiang River Basin[J]. Bulletin of Soiland Water Conservation, 2020, 40(2): 59-68. DOI： 10.13961/j.cnki.stbctb.2020.02.009.

摘要

[目的

]

分析影响赣江上游流域土壤侵蚀的主要因素，为该区水土流失治理与科学管理提供科学依据。[方法

]

基于2015年Landsat 8遥感影像、MODIS NDVI数据、数字高程模型（DEM）、土壤类型和降雨数据，采用RUSLE模型和随机森林算法对赣江上游流域土壤侵蚀及其影响因子进行定量化分析。[结果

]

2015年赣江上游流域土壤侵蚀强度由东南向西北逐渐加剧，总体上处于轻度侵蚀水平，土壤侵蚀总量为3.45×10

t/a，平均土壤侵蚀模数为1 046.38 t/（km

·a），比南方红壤丘陵区土壤允许流失量[500 t/（km

·a）

]

高出2倍之多；子流域9，11，15平均土壤侵蚀模数分别为1 672.66，1 715.83和1 565.36 t/（km

·a），处于中度侵蚀级别，为研究区重点防治区域；其余子流域均为轻度侵蚀级别。[结论

]

各子流域的土壤侵蚀受植被覆盖与管理因子（C）和坡长坡度因子（LS）影响较大，两者重要程度分别在30%和20%以上，土壤可蚀性因子（K）和降雨侵蚀力因子（R）的重要程度偏低，均未超过10%。其中子流域9，11，21主要受LS因子影响，其余子流域均受C因子主控。

Abstract

[Objective] The main factors affecting soil erosion in upper reaches of the Ganjiang River basin were analyzed

in order to provide a reference for local soil erosion control and scientific management.[Methods] The data involved in this paper including Landsat 8 remote sensing image in 2015

MODIS NDVI

digital elevation model (DEM)

soil type and rainfall. The RUSLE model and the random forest algorithm were used to quantitatively analyze soil erosion and its influencing factors in the upper reaches of the Ganjiang River basin.[Results] In 2015

the soil erosion intensity was gradually increased from southeast to northwest in the upper reaches of the Ganjiang River basin

and the soil was at a mild erosion level in general. The total amount of the soil erosion was 3.45×107 t/a. The average soil erosion modulus was 1 046.38 t/(km2·a)

which was about two times higher than the allowable amount of soil erosion 500 t/(km2·a) in the red soil hilly region of Southern China. The average soil erosion moduli of sub-basins 9

11 and 15 were 1 672.66

1 715.83 and 1 565.36 t/(km2·a) respectively

which were at a moderate erosion level. These sub-basins were the key regions which need to be prevented and controlled in the study area. The rest of the sub-basins were under a mild erosion level.[Conclusion] Soil erosion in every sub-basin was greatly affected by the vegetation cover and management factor (C) and the slope length and slope (LS)

and the importance of which was 30% and 20% respectively. The importance of soil erodibility factor (K) and the rainfall erosive force factor (R) were less than 10%. Among all sub-basins

sub-basin 9

and 21 were mainly affected by LS factor

and the rest were mainly controlled by C factor.

关键词

Keywords

references

余新晓,毕华兴.水土保持学[M].北京:中国林业出版社,2013.

Ganasri B P, Ramesh H. Assessment of soil erosion by RUSLE model using remote sensing and GIS:A case study of Nethravathi Basin[J]. Geoscience Frontiers, 2016,7(6):953-961.

陈思旭,杨小唤,肖林林,等.基于RUSLE模型的南方丘陵山区土壤侵蚀研究[J].资源科学,2014,36(6):1288-1297.

齐述华,蒋梅鑫,于秀波.基于遥感和ULSE模型评价1995-2005年江西土壤侵蚀[J].中国环境科学,2011,31(7):1197-1203.

王欢,高江波,侯文娟.基于地理探测器的喀斯特不同地貌形态类型区土壤侵蚀定量归因[J].地理学报,2018,73(9):1674-1686.

方广玲,香宝,赵卫,等.基于GIS和RUSLE的拉萨河流域土壤侵蚀研究[J].水土保持学报,2015,29(3):6-12.

Renard K G, Foster G R, Weesies G A, et al. Predicting soil erosion by water:A guide to conservation planning with the revised universal soil loss equation(RUSLE)[M]. US:Agricultural Handbook, 1997.

Yao Xiaolei, Yu Jingshan, Hong Jiang, et al. Roles of soil erodibility, rainfall erosivity and land use in affecting soil erosion at the basin scale[J]. Agricultural Water Management, 2016,174:82-92.

Sun Wenyi, Shao Quanqin, Liu Jiyuan, et al. Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China[J]. Catena, 2014,121(121):151-163.

姜腾龙,丁程程,张水燕,等.基于遥感的济南市南部山区土壤侵蚀精细化评价[J].中国人口·资源与环境,2017,27(S1):132-137.

丁杰,杨新兵,朱辰光,等.崇礼清水河流域土壤侵蚀空间格局及其影响因素研究[J].水土保持学报,2018,32(4):73-80.

李恒凯,杨柳,雷军,等.利用HJ-CCD影像的红壤丘陵区土壤侵蚀分析:以赣州市为例[J].遥感信息,2016,31(3):122-129.

肖继兵,孙占祥,蒋春光,等.辽西地区农耕坡地土壤侵蚀影响因素及相关关系[J].水土保持学报,2015,29(5):13-19.

胡刚,宋慧,石星军,等.基于RUSLE的卧虎山水库流域土壤侵蚀特征分析[J].地理科学,2018,38(4):610-617.

张雷,王琳琳,张旭东,等.随机森林算法基本思想及其在生态学中的应用:以云南松分布模拟为例[J].生态学报,2014,34(3):650-659.

Breiman L. Random Forests[J]. Machine Learning, 2001,45(1):5-32.

张春兰,杨贵军,李贺丽,等.基于随机森林算法的冬小麦叶面积指数遥感反演研究[J].中国农业科学,2018,51(5):855-867.

刘丹,丁明军,文超,等.赣南红壤丘陵区

137

Cs示踪土壤侵蚀对土壤养分元素的影响[J].水土保持学报,2019,33(1):62-67.

李恒凯,刘小生,李博,等.红壤区植被覆盖变化及与地貌因子关系:以赣南地区为例[J].地理科学,2014,34(1):103-109.

袁再健,马东方,聂小东,等.南方红壤丘陵区林下水土流失防治研究进展[J/OL].土壤学报:1-12[2019-08-24]. http://kns.cnki.net/kcms/detail/32.1119.P.20190528.0934.004.html.

Renard K G, Freimund J R, et al. Using monthly precipitation data to estimate the R-factor in the revised USLE[J]. Journal of Hydrology, 1994,157(1/4):287-306.

陆建忠,陈晓玲,李辉,等.基于GIS/RS和USLE鄱阳湖流域土壤侵蚀变化[J].农业工程学报,2011,27(2):337-344.

Williams J R. EPIC:The erosion-productivity impact calculator[J]. Technical Bulletin-United States Department of Agriculture, 1990,4(4):206-207.

Liu B Y, Nearing M A, Shi P J, et al. Slope length effects on soil loss for steep slopes[J]. Soil Science Society of America Journal, 2000,64(5):1759-1763.

McCool D K, Foster G R, Mutchler C K, et al. Revised slope length factor for the universal soil loss equation[J]. Transactions of the Asae, 1989,30(5):1387-1396.

田鹏,赵广举,穆兴民,等.基于改进RUSLE模型的皇甫川流域土壤侵蚀产沙模拟研究[J].资源科学,2015,37(4):832-840.

马良,姜广辉,左长清,等.江西省50余年来降雨侵蚀力变化的时空分布特征[J].农业工程学报,2009,25(10):61-68.

朱成刚,李卫红,李大龙,等.伊犁河谷土壤理化性质及可蚀性特征分析[J].资源科学,2016,38(7):1212-1221.

李新艳,杨勤科,王春梅.赣南地区侵蚀地形因子研究[J].西北农林科技大学学报(自然科学版),2014,42(1):175-182.

谢颂华,曾建玲,杨洁,等.江西水土流失省情分析[J].南昌工程学院学报,2010,29(3):69-72.

张平仓,程冬兵. SL657-2014南方红壤丘陵区水土流失综合治理技术标准[S].北京:中国水利水电出版社,2019.

Mehri A, Salmanmahiny A, Tabrizi A R M, et al. Investigation of likely effects of land use planning on reduction of soil erosion rate in river basins:Case study of the Gharesoo River basin[J]. Catena, 2018,167:116-129.

Kosmas C, Danalatos N, Cammeraat L H, et al. The effect of land use on runoff and soil erosion rates under Mediterranean conditions[J]. Catena, 1997,29(1):45-59.

柳冬青,张金茜,李红瑛,等.基于地理探测器的流域土壤磷流失影响因素分析[J].环境科学学报,2018,38(12):4814-4822.

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