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黄河流域土壤侵蚀及植被水保效益研究 被引量:25

Study on Soil Erosion and Vegetation Effect on Soil Conservation in the Yellow River Basin
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摘要 基于土壤侵蚀快速评估法,以最小图斑为研究单元,评估了黄河流域20世纪90年代末土壤侵蚀的状况,并分析了黄河流域土壤侵蚀的分布特点.在此基础上,设定流域不同植被覆盖度情景,计算了不同植被覆盖度下黄河流域的土壤侵蚀状况,获得了1.1km分辨率条件下的植被覆盖度变化对水保效益的影响,给出了对应于产生显著水保效益的植被覆盖度变化范围.研究表明,从黄河流域整体上来看,当流域较低植被覆盖度提高到15%以上时会产生显著的水保效益,在25%处显著性开始降低,而超过45%时水保效益的增加则很不显著.综合考虑经济投入及当地环境限制,最佳水保效益对应的植被覆盖度约为25%. Based on the rapid soil erosion assessment approach, the soil erosion intensity of the Yellow River basin at the end of 1990s is assessed using minimum polygon as study units. The distribution characteristics of soil erosion in the Yellow River basin are analyzed. Based on the assessment results, a parameter study investigates the soil conservation effects of vegetation coverage with a resolution of 1. 1 km. And the vegetation coverage range that could generate obvious soil conversation effect is obtained. It is indicated that, on the whole view of the basin, the lower and upper threshold of vegetation coverage for obvious soil conservation effect respectively are 15% and 45% ,and the best vegetation coverage is 25%.
作者 韩鹏 李秀霞
出处 《应用基础与工程科学学报》 EI CSCD 2008年第2期181-190,共10页 Journal of Basic Science and Engineering
基金 国家自然科学基金委资助项目(50579001)
关键词 土壤侵蚀 快速评估 植被覆盖度 水保效益 黄河流域 soil erosion rapid assessment vegetation coverage soil conservation effects Yellow River basin
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  • 1Wischmeier W H, Smith D D. Predicting rainfall erosion losses from cropland east of the rocky mountains [ A ]. Agric. Handbook 282 [ C ] , Washington DC : USDA, 1965:47
  • 2Wischmeier W H, Smith D D. Predicting rainfall erosion losses [ A ]. Agric. Handbook 537 [ C ], Washington DC : USDA, 1978:58
  • 3Renard 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 ) [ A ]. Agricultural Handbook No. 703 [ C ]. Washington DC : USDA, 1997:404
  • 4Neitsch S L, Arnold J G, Kiniry J R, et al. Soil and water assessment tool theoretical documentation/Version 2000 [ R ]. Temple, Texas, Grassland, Soil and Water Research Laboratory, Agricultural Research Service, 2001. http ://www. brc. tamus. edu/swat/swat2000doc, html
  • 5Flanagan D C ,Nearing M A ,Lafien J M. USDA-Water erosion prediction project:hillslope profile and watershed model documentation[ A ]. USDA-ARS National Soil Erosion Research laboratory, West Lafayette. NSER Report No. 10 [C] ,1995
  • 6Misra R K, Rose C W. Application and sensitivity analysis of process-based erosion model GUEST [ J ]. European Journal of Soil Science,1996,47:593-604
  • 7Mettemicht G I, Zinck J A. Evaluating the information content of JERS-1 SAR and landsat TM data for discrimination of soil erosion features[ J]. ISPRS J. Photogram. Remote Sens. , 1998,53 : 143-153
  • 8De Jong S M, Paracchini M L, Bertolo F,et al. Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data[ J ]. Catena, 1999,37:291-308
  • 9Folly A,Bronsveld M C, Clavaux M. A Knowledge-based approach for C-factor mapping in Spain using TM and GIS [ J ]. Int J Remote Sens,1996,17:2401-2415
  • 10王协康,方铎.土壤侵蚀产沙量的人工神经网络模拟[J].成都理工学院学报,2000,27(2):197-201. 被引量:14

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