资源生态

基于RUSLE模型的延河流域2001-2010年土壤侵蚀动态变化

展开
  • 1. 北京大学 深圳研究生院环境与能源学院城市人居环境科学与技术重点实验室, 广东 深圳 518055;
    2. 北京大学 环境科学与工程学院水沙科学教育部重点实验室, 北京 100871

收稿日期: 2011-08-12

  修回日期: 2011-12-12

  网络出版日期: 2012-07-20

基金资助

国家自然科学基金项目(50979003)。

Soil Erosion Changes in the Yanhe Watershed from 2001 to 2010 Based on RUSLE Model

Expand
  • 1. The Key Laboratory for Environmental and Urban Sciences, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China;
    2. College of Environmental Sciences, The Key Laboratory for Water and Sediment Sciences, Peking University, Beijing 100871, China

Received date: 2011-08-12

  Revised date: 2011-12-12

  Online published: 2012-07-20

摘要

以黄土高原典型丘陵沟壑区——延河流域为研究区, 基于GIS和RS技术, 利用2001-2010年延河流域水文站月降雨量数据、MODIS NDVI数据、DEM数据、土壤类型数据和土地利用数据,率定了修正的通用土壤流失方程(RUSLE)的相关参数,计算了研究区2001-2010年逐年的土壤侵蚀模数, 利用杏河水文站实测的泥沙数据, 验证了模型的有效性,分析了延河流域土壤侵蚀强度的时空变化特征。结果表明,2001年到2010年延河流域土壤侵蚀模数呈减小趋势,2001年土壤侵蚀模数最大,为6 596.72 t/(km2·a),2008年土壤侵蚀模数最小,减小到2 485.46 t/(km2·a),降低62.32%;2009年由于暴雨冲刷,土壤侵蚀模数显著增大;2010年土壤侵蚀模数和2006、2007年相差不多;土壤侵蚀强度分布比例变化明显,土壤侵蚀强度为强度、极强、剧烈的面积比分别由16.21%、21.93%和12.36%降低为10.85%、4.58%和0.39%。土壤侵蚀强度等级转移矩阵表明大部分地区的土壤侵蚀强度向低一级转移,2001-2005年31.68%的面积土壤侵蚀强度降低一级,2005-2010年42.13%的面积土壤侵蚀强度降低一级。

本文引用格式

李天宏, 郑丽娜 . 基于RUSLE模型的延河流域2001-2010年土壤侵蚀动态变化[J]. 自然资源学报, 2012 , (7) : 1164 -1175 . DOI: 10.11849/zrzyxb.2012.07.008

Abstract

Soil erosion has become a worldwide environmental problem because it could threaten soil structure, agricultural production, water quality, and so on. During the past decade, much effort has been made to control soil erosion in the Loess Plateau, thus the distribution of soil erosion intensity in this region has experienced a great change. So it is necessary to take more effective soil and water conservation measures and realize the sustainable utilization of water resource by knowing soil erosion changes. Based on RUSLE model, soil erosion changes from 2001 to 2010 in the Yanhe Watershed, a typical hilly-gully region on the Loess Plateau, were studied with the support of GIS and RS. The data set used in the model includes monthly precipitation, MODIS NDVI data, DEM, land use and soil type maps. Having localized the coefficients in RUSLE, the gauged data from Xingzihe Hydrological Station was used to verify the model and the proved reasonable results were produced with this model. The annual soil erosion modulus and the temporal and spatial change of soil erosion intensity in the Yanhe Watershed were analyzed. The main conclusions are as follows: Firstly, in the period 2001-2010, soil erosion in the Yanhe Watershed experienced a decreasing trend from the maximal value of 6596.72 t/(km2穉) in 2001 to the minimal value of 2485.46 t/(km2穉) in 2008, decreased by 62.32%; the soil erosion modulus increased obviously in 2009 because of heavy rainfall. Secondly, the distribution of soil erosion intensity changed obviously and the area ratio of intense, extremely intense, and most intense soil erosion decreased from 16.21%, 21.93% and 12.36% to 10.85%, 4.58% and 0.39% respectively. Thirdly, the transformation matrix of soil erosion intensity indicated that the soil erosion intensity transformed from high level to low level in most of the area with 31.68% of the total area of the watershed from 2001 to 2005 and 42.13% from 2005 to 2010. The distribution pattern of soil erosion intensity during the past decade revealed in this study could provide support for soil and water conservation and ecological environmental construction in the study area and even in the similar watersheds of the Loess Plateau.

参考文献

[1] Qiao Y L, Qiao Y. Fast soil erosion investigation and dynamic analysis in the Loess Plateau of China by using information composite technique [J]. Advances in Space Research, 2002, 29(1): 85-88. [2] Vrieling A, Sterk G, Vigiak O. Spatial evaluation of soil erosion risk in the West Usambara Mountains, Tanzania [J]. Land Degradation and Development, 2006, 17(3): 301-319. [3] 张喜旺, 周月敏, 李晓松, 等. 土壤侵蚀评价遥感研究进展[J]. 土壤通报, 2010, 41(4): 1010-1017. [4] Ni J R, Li X X, Borthwick A G L. Soil erosion assessment based on minimum polygons in the Yellow River basin, China [J]. Geomorphology, 2008, 93(34): 233-252. [5] Wischmeier W H, Smith D D. Predicting Rainfall Erosion Losses-A Guide for Conservation Planning [M]. U. S. Department of Agriculture, Agriculture Handbook 537, 1978. [6] Renard K G, Ferreira V A. RUSLE model description and database sensitivity [J]. Journal of Environmental Quality, 1993, 22(3): 458-466. [7] 江忠善, 郑粉莉. 坡面水蚀预报模型研究[J]. 水土保持学报, 2004, 18(1): 66-69. [8] Liu B Y, Zhang K L, Xie Y. An empirical soil loss equation//Proceedings12th International Soil Conservation Organization Conference, Vol 1 Ⅱ: Process of Soil Erosion and Its Environment Effect. Beijing, China: Qinghua University Press, 2002. [9] 刘宝元, 史培军. WEPP水蚀预报流域模型[J]. 水土保持通报, 1998, 18(5): 6-11. [10] Morgan R PC, Quinton J N, Smith R E, et al. The European Soil Erosion Model(EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments [J]. Earth Surface Processes and Landforms, 1998, 23(6): 527-544. [11] De Roo A P J, Wesseling C G and Ritsema C J. LISEM: A single-event physically based hydrological and soil erosion model for drainage basins [J]. Hydrological Processes, 1996, 10(8): 1107-1118. [12] De 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. [13] Arnoldus H M J. Methodology used to determine the maximum potential average annual soil loss due to sheet and rill erosion in Morocco [J]. FAO Soils Bulletin, 1977, 34: 39-51. [14] 章文波, 付金生. 不同类型雨量资料估算降雨侵蚀力[J]. 资源科学, 2003, 25(1): 35-41. [15] 陈明华, 周伏建, 黄炎和. 土壤可蚀性因子的研究[J]. 水土保持学报, 1995, 9(1): 19-24. [16] Shririza M A, Boersmal. Unifying quantitative analysis of soil texture[J]. Soil Science Society of America Journal, 1984: 142-147. [17] Peel T C. The relation of certain physical characteristics to the erodibility of soils [J]. Soil Science Society Proceedings, 1937, 2: 79-84. [18] Wischmeier W H. A soil erodility nomograph farm land and construction sites [J]. Journal of Soil and Water Conservation, 1971, 26: 189-193. [19] 谢红霞. 延河流域土壤侵蚀时空变化及水土保持环境效应评价研究. 西安: 陕西师范大学, 2008. [20] MeCool D K, Brown L C, Foster G R, et al. Revised slope steepness factor for the universal soil loss equation [J]. Transactions of the ASAE, 1987, 30(5): 1387-1396. [21] Liu B Y, Nearing M A, Risse L M. Slope gradient effects on soil loss for steep slopes [J]. Transactions of the ASAE, 1994, 37: 1835-1840. [22] Alejandro M A, Kenji O. Estimation of vegetation parameter for modeling soil erosion using linear spectral mixture analysis of Landsat ETM data [J]. Journal of Photogrammetry & Remote Sensing, 2007, 62: 309-324. [23] DeJong S M. Applications of Reflective Remote Sensing for Land Degradation Studies in a Mediterranean Environment [M]. Koninklijk Nederlandse Aardrijksundig Genootschap, 1994. [24] 游松财, 李文卿. GIS支持下的土壤侵蚀量估算——以江西省泰和县灌溪乡为例[J]. 自然资源学报, 1999, 14(1): 61-68. [25] 许月卿, 邵晓梅. 基于GIS和RUSLE的土壤侵蚀量计算——以贵州省猫跳河流域为例[J]. 北京林业大学学报, 2006, 28(4): 67-71. [26] 王超. 基于RS/GIS的渭河流域土壤侵蚀评价研究. 西安: 西北大学, 2010. [27] 中华人民共和国水利部. SL190-2007土壤侵蚀分类分级标准[S]. 北京: 中国水利水电出版社, 2007. [28] 李传哲, 王浩, 于福亮, 等. 延河流域水土保持对径流泥沙的影响[J]. 中国水土保持科学, 2011, 9(1): 1-8.
文章导航

/