Estimation of soil erosion using RUSLE in Caijiamiao watershed, China

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km2. This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha−1 year−1 in 2002 and 70.58 ton ha−1 year−1 in 2010, while the estimated sediment yield was found to be 327.96 × 104 and 293.85 × 104 ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.

[1]  V. Prasannakumar,et al.  Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology , 2012 .

[2]  K. Sistani,et al.  Tillage, cover cropping, and poultry litter effects on selected soil chemical properties , 2001 .

[3]  Quanqin Shao,et al.  Soil erosion and its response to the changes of precipitation and vegetation cover on the Loess Plateau , 2013, Journal of Geographical Sciences.

[4]  Jianping Guo,et al.  Assessment of soil erosion susceptibility using empirical modeling , 2013, Acta Meteorologica Sinica.

[5]  M. Todorović,et al.  Spatial modelling of soil erosion potential in a mountainous watershed of South-eastern Serbia , 2012, Environmental Earth Sciences.

[6]  C. Prat,et al.  Erosion extension of indurated volcanic soils of Mexico by aerial photographs and remote sensing analysis , 2003 .

[7]  Jian Peng,et al.  Land use change and soil erosion in the Maotiao River watershed of Guizhou Province , 2011 .

[8]  Kenji Omasa,et al.  Estimation of vegetation parameter for modeling soil erosion using linear Spectral Mixture Analysis of Landsat ETM data , 2007 .

[9]  Jacob Cohen A Coefficient of Agreement for Nominal Scales , 1960 .

[10]  Lei Wang,et al.  Estimation of soil erosion in some sections of Lower Jinsha River based on RUSLE , 2015, Natural Hazards.

[11]  Ruiliang Pu,et al.  Spectral mixture analysis for mapping abundance of urban surface components from the Terra/ASTER data , 2008 .

[12]  Peng Jian,et al.  Retraction Note: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed, Guizhou Province, China , 2009, Environmental Earth Sciences.

[13]  S. D. Angima,et al.  Soil erosion prediction using RUSLE for central Kenyan highland conditions , 2003 .

[14]  F. J. García-Haro,et al.  A Mixture Modeling Approach to Estimate Vegetation Parameters for Heterogeneous Canopies in Remote Sensing , 2000 .

[15]  G. R. Foster,et al.  Estimating soil loss on topographically non-uniform field and farm units , 1988 .

[16]  C. Bini,et al.  Effect of different land use on soil erosion in the pre-alpine fringe (North-East Italy): Ion budget and sediment yield. , 2006, The Science of the total environment.

[17]  A. Karaburun,et al.  Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed, northwest Turkey , 2012, Environmental Earth Sciences.

[18]  Wan Wei-wu,et al.  Managing soil erosion potential by integrating digital elevation models with the southern China's revised universal soil loss equation - A case study for the west lake scenic spots area of Hangzhou, China , 2007 .

[19]  Bo Du,et al.  Regional soil erosion risk mapping using RUSLE, GIS, and remote sensing: a case study in Miyun Watershed, North China , 2011 .

[20]  Christine Pohl,et al.  Multisensor image fusion in remote sensing: concepts, methods and applications , 1998 .

[21]  Peng Jian,et al.  RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed, Guizhou Province, China , 2009 .

[22]  B. Fu,et al.  Modeling soil erosion and its response to land-use change in hilly catchments of the Chinese Loess Plateau. , 2010 .

[23]  W. H. Wischmeier,et al.  SOIL ERODIBILITY NOMOGRAPH FOR FARMLAND AND CONSTRUCTION SITES , 1971 .

[24]  W. H. Wischmeier,et al.  Predicting rainfall erosion losses : a guide to conservation planning , 1978 .

[25]  G. R. Foster,et al.  Predicting soil erosion by water : a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) , 1997 .

[26]  Guangxing Wang,et al.  Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation , 2003 .

[27]  Guangxing Wang,et al.  Improvement in mapping vegetation cover factor for the universal soil loss equation by geostatistical methods with Landsat Thematic Mapper images , 2002 .

[28]  Q. Yuliang,et al.  Fast soil erosion investigation and dynamic analysis in the loess plateau of China by using information composite technique , 2002 .

[29]  J. Poesen,et al.  The European Soil Erosion Model (EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments. , 1998 .

[30]  R. Leemans,et al.  Comparing global vegetation maps with the Kappa statistic , 1992 .

[31]  Steven M. de Jong,et al.  Derivation of vegetative variables from a landsat tm image for modelling soil erosion , 1994 .

[32]  Claudio O. Stöckle,et al.  Estimating water erosion and sediment yield with GIS, RUSLE, and SEDD , 2003 .

[33]  Xu Yue-qing,et al.  Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China , 2008, Environmental monitoring and assessment.

[34]  Mark A. Nearing,et al.  Projected rainfall erosivity changes under climate change from multimodel and multiscenario projections in Northeast China , 2010 .

[35]  D. Rozos,et al.  Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece , 2013, Environmental Earth Sciences.

[36]  Sun Xi-hua GIS-AND-RS-BASED EVALUATION OF SOIL EROSION POTENTIALITY——A CASE STUDY OF QINGDAO , 2004 .

[37]  Achim Röder,et al.  Mediterranean desertification and land degradation: Mapping related land use change syndromes based on satellite observations , 2008 .

[38]  Katrin Meusburger,et al.  oil erosion modelled with USLE and PESERA using QuickBird derived vegetation arameters in an alpine catchment , 2010 .

[39]  B. Rudolf,et al.  World Map of the Köppen-Geiger climate classification updated , 2006 .

[40]  I. Moore,et al.  Physical basis of the length-slope factor in the universal soil loss equation , 1986 .

[41]  Wang Jianhua,et al.  Analysis of the landscape change at River Basin scale based on SPOT and TM fusion remote sensing images: a case study of the Weigou River Basin on the Chinese Loess Plateau , 2009 .

[42]  W. H. Wischmeier,et al.  Rainfall energy and its relationship to soil loss , 1958 .

[43]  K. C. Krishna Bahadur,et al.  Mapping soil erosion susceptibility using remote sensing and GIS : a case of the Upper Nam Wa Watershed, Nan Province, Thailand , 2009 .

[44]  V. Singh,et al.  The EPIC model. , 1995 .

[45]  J. M. Laflen,et al.  Effect of Crop Residue on Soil Loss from Continuous Row Cropping , 1981 .

[46]  James A. Lewis,et al.  The dynamics of soil erosion in US agriculture , 1998 .

[47]  Dengsheng Lu,et al.  Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS , 2004 .

[48]  Qinke Yang,et al.  A GIS-based modeling approach for fast assessment of soil erosion by water at regional scale, loess plateau of China , 2010 .

[49]  Steven W. Running,et al.  Community type differentiation using NOAA/AVHRR data within a sagebrush-steppe ecosystem , 1993 .

[50]  L. Liu,et al.  Dynamic analysis of eco-environmental changes based on remote sensing and geographic information system: an example in Longdong region of the Chinese Loess Plateau , 2007 .

[51]  Shenglu Zhou,et al.  Relationships Between Intensity Gradation and Evolution of Soil Erosion: A Case Study of Changting in Fujian Province, China , 2012 .

[52]  D. Roberts,et al.  Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data , 1993 .

[53]  Luca Montanarella,et al.  Soil erosion risk assessment in Europe , 2000 .

[54]  W. H. Wischmeier,et al.  Predicting rainfall-erosion losses from cropland east of the Rocky Mountains , 1965 .

[55]  Yaonan Wang,et al.  Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images , 2002, Inf. Fusion.

[56]  Gerard Govers,et al.  A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units , 1996 .

[57]  Pierre Y. Julien,et al.  Erosion and Sedimentation: Physical properties and dimensional analysis , 1995 .

[58]  Y. Lü,et al.  Assessing the soil erosion control service of ecosystems change in the Loess Plateau of China , 2011 .

[59]  M. Ridd Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities , 1995 .