基于GIS/RS的灾区土壤保持功能恢复效应评价
|
摘要
土壤侵蚀是土地退化的根本原因,也是导致生态环境恶化的重要影响因素,随着地震等重大地质灾害的发生,灾区土壤保持功能遭到严重破坏,因而进行地震灾区土壤保持功能恢复效应评价具有重大意义。选择"5·12"汶川大地震极重灾区为研究区,以2007年、2009年、2011年研究区Landsat5 TM数据及DEM数据为主要数据源,结合降雨信息数据等其他数据,运用修订的通用土壤流失方程(RUSLE),以ArcGIS软件作为平台,建立了灾区土壤保持功能恢复效应评估模型。研究结果表明:灾区2007年平均土壤侵蚀模数为3 389.57 t/(hm~2·a),年侵蚀总量为8.75×10~7 t,2009年土壤侵蚀模数增加了64.64%,平均为5 580.60 t/(hm~2·a),年侵蚀总量为1.44亿t,相比2009年、2011年土壤侵蚀模数减少了24.08%,年侵蚀总量为1.09亿t,土壤保持功能有所恢复;从土壤侵蚀面积和土壤侵蚀模数两个角度来看,灾区土壤保持功能也达到了一定的恢复;此外,离地震中心越近的地方,土壤保持功能受到的削弱程度越大,其恢复能力也越差,因而,建议有关部门在进行灾后重建的工作中,应当重点加强对震中及其周边地区的改善。
Soil erosion is the fundamental cause of land degradation, and is also an important factor that causes the deterioration of the ecological environment. With the occurrence of earthquake and other major geological disasters, the soil conservation function of the disaster areas has been seriously damaged. Therefore, it is of great significance to evaluate the restoration effect of soil conservation function in earthquake stricken areas. We selected ‘5·12' Wenchuan earthquake extremely heavy disaster area as the research area, and took the Landsat5 TM data and DEM data in the 2007, 2009, 2011 research area as the main data source, combined the other data of rainfall information and other data, used the revised universal soil loss equation, and used ArcGIS software as the platform to establish the evaluation model of the restoration effect of the soil conservation function in the disaster area. The results showed that the average soil erosion modulus was 3 389.57 t/(hm~2·a) in 2007, the annual total erosion amount was 8.75×10~(7 )t, the soil erosion modulus increased by 64.64% in 2009, the average was 5 580.60 t/(hm~2·a), the annual total erosion amount was 1.44×10~8 t; compared with the parameters in 2009, the soil erosion modulus decreased by 24.08%, the annual erosion amount was 1.09×10~8 t, and the soil retention function was restored in 2010. From the aspects of the soil erosion area and the soil erosion modulus, the soil conservation function of the disaster area had also reached a certain recovery. In addition, the closer to the earthquake center, the more weakened the soil conservation function is, the worse the recovery capacity of the soil is. Therefore, it is suggested that the relevant departments should focus on strengthening the change of the epicenter and its surrounding areas in the work of post disaster reconstruction.
Soil erosion is the fundamental cause of land degradation, and is also an important factor that causes the deterioration of the ecological environment. With the occurrence of earthquake and other major geological disasters, the soil conservation function of the disaster areas has been seriously damaged. Therefore, it is of great significance to evaluate the restoration effect of soil conservation function in earthquake stricken areas. We selected ‘5·12' Wenchuan earthquake extremely heavy disaster area as the research area, and took the Landsat5 TM data and DEM data in the 2007, 2009, 2011 research area as the main data source, combined the other data of rainfall information and other data, used the revised universal soil loss equation, and used ArcGIS software as the platform to establish the evaluation model of the restoration effect of the soil conservation function in the disaster area. The results showed that the average soil erosion modulus was 3 389.57 t/(hm~2·a) in 2007, the annual total erosion amount was 8.75×10~(7 )t, the soil erosion modulus increased by 64.64% in 2009, the average was 5 580.60 t/(hm~2·a), the annual total erosion amount was 1.44×10~8 t; compared with the parameters in 2009, the soil erosion modulus decreased by 24.08%, the annual erosion amount was 1.09×10~8 t, and the soil retention function was restored in 2010. From the aspects of the soil erosion area and the soil erosion modulus, the soil conservation function of the disaster area had also reached a certain recovery. In addition, the closer to the earthquake center, the more weakened the soil conservation function is, the worse the recovery capacity of the soil is. Therefore, it is suggested that the relevant departments should focus on strengthening the change of the epicenter and its surrounding areas in the work of post disaster reconstruction.
引文
[1]Wischmeier W, Smith D. Predicting Rainfall Erosion Losses From Cropland East of the Rocky Mountains[Z]. Agriculture Handbook 282. Washington DC: Usda-Ars, 1965.
[2]Wischmeier W, Smith D. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning[Z]. Agriculture Handbook 537. Washington DC: Usda-Ars, 1978.
[3]Renard K, Foster G, Weesies G, et al. RUSLE: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation[Z]. Agricultural Handbook. Washington DC: Usda-Ars, 1997.
[4]刘宝元,谢云,张科利.土壤侵蚀预报模型[M].北京:中国科学技术出版社,2001.
[5]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.
[6]Yue L, Shen H, Zhang L, et al. High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations[J]. Isprs Journal of Photogrammetry & Remote Sensing, 2017,123:20-34.
[7]张兆明,何国金.Landsat5 TM数据辐射定标[J].科技导报,2008,26(7):54-58.
[8]刘小平,邓孺孺,彭晓鹃,等.基于TM影象的快速大气校正方法[J].地理科学,2005,25(1):89-95.
[9]中华人民共和国国家质量监督检验检疫总局.土地利用现状分类GB/T21010—2007[S].北京:中国标准出版社,2007.
[10]李福根,辛晓洲,李小军.地震灾区植被净初级生产力恢复效应评价[J].水土保持研究,2017,24(6):139-146.
[11]王万忠,焦菊英.中国的土壤侵蚀因子定量评价研究[J].水土保持通报,1996,16(5):1-20.
[12]刘秉正.渭北地区R的估算及分布[J].西北林学院学报,1993,8(2):21-29.
[13]章文波,谢云,刘宝元.降雨侵蚀力研究进展[J].水土保持学报,2002,5(16):43-46.
[14]梁音,史学正.长江以南东部丘陵山区土壤可蚀性K值研究[J].水土保持研究,1999,6(2):48-53.
[15]US Department of Agriculture RUSLE Development Team. Revised Universal Soil Loss Equation Version 2(RUSLE2) Handbook[Z]. Washington DC:Us Department of Agriculture Rusle Development Team,2001.
[16]刘淼,胡远满,徐崇刚.基于GIS、RS和RUSLE的林区土壤侵蚀定量研究:以大兴安岭呼中地区为例[J].水土保持研究,2004,11(3):21-24.
[17]杨维,刘云国,曾光明,等.定量遥感支持下的红壤丘陵区土壤侵蚀敏感性评价:以长沙市为例[J].环境科学与管理,2007,32(1):120-125.
[18]Shirazi M A, Boersma L. A unifying quantitative analysis of soil texture[J]. Soil Science Society of America Journal, 1984,48(1):142-147.
[19]吴昌广,李生,任华东,等.USLE/RUSLE模型中植被覆盖管理因子的遥感定量估算研究进展[J].应用生态学报,2012,23(6):1728-1732.
[20]Jong S M D. Derivation of vegetative variables from a landsat tm image for modelling soil erosion[J]. Earth Surface Processes & Landforms, 2010, 19(2):165-178.
[21]傅世锋,查轩.基于GIS和USLE的东圳库区土壤侵蚀量预测研究[J].地球信息科学,2008,10(3):390-395.
[22]黄金良,洪华生,张路平,等.基于GIS和USLE的九龙江流域土壤侵蚀量预测研究[J].水土保持学报,2004,18(5):75-79.
[23]彭建,李丹丹,张玉清.基于GIS和RUSLE的滇西北山区土壤侵蚀空间特征分析[J].山地学报,2007,25(5):548-556.
[24]唐克丽.中国水土保持[M].北京:科学出版社,2004.
[25]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.
[26]肖寒,欧阳志云.森林生态系统服务功能及其生态价值评估初探[J].应用生态学报,2000,11(4):481-484.
[27]中华人民共和国水利部.土壤侵蚀分类分级标准SL190—2007[S].北京:中国水利水电出版社,2008.
[2]Wischmeier W, Smith D. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning[Z]. Agriculture Handbook 537. Washington DC: Usda-Ars, 1978.
[3]Renard K, Foster G, Weesies G, et al. RUSLE: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation[Z]. Agricultural Handbook. Washington DC: Usda-Ars, 1997.
[4]刘宝元,谢云,张科利.土壤侵蚀预报模型[M].北京:中国科学技术出版社,2001.
[5]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.
[6]Yue L, Shen H, Zhang L, et al. High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations[J]. Isprs Journal of Photogrammetry & Remote Sensing, 2017,123:20-34.
[7]张兆明,何国金.Landsat5 TM数据辐射定标[J].科技导报,2008,26(7):54-58.
[8]刘小平,邓孺孺,彭晓鹃,等.基于TM影象的快速大气校正方法[J].地理科学,2005,25(1):89-95.
[9]中华人民共和国国家质量监督检验检疫总局.土地利用现状分类GB/T21010—2007[S].北京:中国标准出版社,2007.
[10]李福根,辛晓洲,李小军.地震灾区植被净初级生产力恢复效应评价[J].水土保持研究,2017,24(6):139-146.
[11]王万忠,焦菊英.中国的土壤侵蚀因子定量评价研究[J].水土保持通报,1996,16(5):1-20.
[12]刘秉正.渭北地区R的估算及分布[J].西北林学院学报,1993,8(2):21-29.
[13]章文波,谢云,刘宝元.降雨侵蚀力研究进展[J].水土保持学报,2002,5(16):43-46.
[14]梁音,史学正.长江以南东部丘陵山区土壤可蚀性K值研究[J].水土保持研究,1999,6(2):48-53.
[15]US Department of Agriculture RUSLE Development Team. Revised Universal Soil Loss Equation Version 2(RUSLE2) Handbook[Z]. Washington DC:Us Department of Agriculture Rusle Development Team,2001.
[16]刘淼,胡远满,徐崇刚.基于GIS、RS和RUSLE的林区土壤侵蚀定量研究:以大兴安岭呼中地区为例[J].水土保持研究,2004,11(3):21-24.
[17]杨维,刘云国,曾光明,等.定量遥感支持下的红壤丘陵区土壤侵蚀敏感性评价:以长沙市为例[J].环境科学与管理,2007,32(1):120-125.
[18]Shirazi M A, Boersma L. A unifying quantitative analysis of soil texture[J]. Soil Science Society of America Journal, 1984,48(1):142-147.
[19]吴昌广,李生,任华东,等.USLE/RUSLE模型中植被覆盖管理因子的遥感定量估算研究进展[J].应用生态学报,2012,23(6):1728-1732.
[20]Jong S M D. Derivation of vegetative variables from a landsat tm image for modelling soil erosion[J]. Earth Surface Processes & Landforms, 2010, 19(2):165-178.
[21]傅世锋,查轩.基于GIS和USLE的东圳库区土壤侵蚀量预测研究[J].地球信息科学,2008,10(3):390-395.
[22]黄金良,洪华生,张路平,等.基于GIS和USLE的九龙江流域土壤侵蚀量预测研究[J].水土保持学报,2004,18(5):75-79.
[23]彭建,李丹丹,张玉清.基于GIS和RUSLE的滇西北山区土壤侵蚀空间特征分析[J].山地学报,2007,25(5):548-556.
[24]唐克丽.中国水土保持[M].北京:科学出版社,2004.
[25]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.
[26]肖寒,欧阳志云.森林生态系统服务功能及其生态价值评估初探[J].应用生态学报,2000,11(4):481-484.
[27]中华人民共和国水利部.土壤侵蚀分类分级标准SL190—2007[S].北京:中国水利水电出版社,2008.