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Volume 21 Issue 6
Dec 2010
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Article Contents
Li Hui, Chen Xiaoling, Kyoung Jae Lim, Cai Xiaobin, Myung Sagong. Assessment of Soil Erosion and Sediment Yield in Liao Watershed, Jiangxi Province, China, Using USLE, GIS, and RS. Journal of Earth Science, 2010, 21(6): 941-953. doi: 10.1007/s12583-010-0147-4
Citation: Li Hui, Chen Xiaoling, Kyoung Jae Lim, Cai Xiaobin, Myung Sagong. Assessment of Soil Erosion and Sediment Yield in Liao Watershed, Jiangxi Province, China, Using USLE, GIS, and RS. Journal of Earth Science, 2010, 21(6): 941-953. doi: 10.1007/s12583-010-0147-4

Assessment of Soil Erosion and Sediment Yield in Liao Watershed, Jiangxi Province, China, Using USLE, GIS, and RS

doi: 10.1007/s12583-010-0147-4
Funds:  This study was supported by China Technological Supporting Program (No. 2007BAC23B05), the Special Research Fund for Prevention of Geological Disasters in Three Gorges Reservoir Area (No. SXKY3-6-1), the Natural Science Foundation of Hubei Province (No. 2009CDB104), and the Opening Foundation of State Key Laboratory for Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University (No. (09)Key 01)
More Information
  • Corresponding author: Li Hui, leelmars@gmail.com
  • Received Date: 13 Jul 2010
  • Accepted Date: 10 Sep 2010
  • Publish Date: 01 Dec 2010
  • Soil erosion by water is a serious problem all over the world. In China, about 1 790 000 km2 of land suffers from water erosion, which accounts for 18.3% of China's total area. This study was conducted in the Liao (潦) watershed in Jiangxi (江西) Province to assess annual soil erosion and sediment yield using the Universal Soil Loss Equation (USLE). A geographic information system (GIS) was used to generate maps of the USLE factors, which include rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover (C), and conservation practice (P) factors. By integrating these factors in a GIS, a spatial distribution of soil erosion over the Liao watershed was obtained. The soil erosion was found to vary from nil for flat and well-covered areas to more than 500 t/ha/a in mountainous places with sparse vegetation. The average soil erosion is 18.2 t/ha/a with a standard deviation of 109.3 t/ha/a. The spatial distribution of erosion classes was estimated. About 39.5% of the watershed is under the tolerant erosion rate, and 60.5% of the study area experienced erosion to different extents. A spatially distributed sediment delivery ratio (SDR) module was developed to account for soil erosion and deposition. It was found that the SDR value at the outlet of the Liao watershed was 0.206, and the sediment yield was 1.32 million t/a, which was 20% higher than the measured sediment. The results can be used to identify the soil erosion hot spots and develop the best soil erosion management practices and help estimate the quantity of soil that was transported into the downstream Poyang (鄱阳) Lake.

     

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  • Ahmet, I., Fatih, T., Veli, U., 2007. Estimating Spatial Distribution of Soil Loss over Seyhan River Basin in Turkey. Journal of Hydrology, 336: 30–37 doi: 10.1016/j.jhydrol.2006.12.009
    Arnoldus, H. M. J., 1977. Methodology Used to Determinate the Maximum Potential Average Soil Loss due to Sheet and Rill Erosion in Marocco: Assessing Soil Degradation. FAO Soils Bull. , 34: 8–9
    Bahadur, K. C. K., 2009. Mapping Soil Erosion Susceptibility Using Remote Sensing and GIS: A Case of the Upper Name Wa Watershed, Nan Province, Thailand. Environmental Geololy, 57(3): 695–705 doi: 10.1007/s00254-008-1348-3
    Bakoariniaina, L. N., Kusky, T., Raharimahefa, T., 2006. Disappearing Lake Alaotra: Monitoring Catastrophic Erosion, Waterway Silting, and Land Degradation Hazards in Madagascar Using Landsat Imagery. Journal of African Earth Sciences, 44(2): 241–252 doi: 10.1016/j.jafrearsci.2005.10.013
    Bartsch, K. P., van Miegroet, H., Boettinger, J., et al., 2002. Using Empirical Erosion Models and GIS to Determine Erosion Risk at Camp William, Utah. J. Soil Water Conserv. , 57(1): 29–37
    Beskow, S., Mello, C. R., Norton, L. D., et al., 2009. Soil Erosion Prediction in the Grande River Basin, Brazil Using Distributed Modeling. Catena, 79(1): 49–59 doi: 10.1016/j.catena.2009.05.010
    Bhattarai, R., Dutta, D., 2007. Estimation of Soil Erosion and Sediment Yield Using GIS at Catchment Scale. Water Resources Management, 21(10): 1635–1647 doi: 10.1007/s11269-006-9118-z
    Bingner, R. L., Murphree, C. E., Mutchler, C. K., 1989. Comparison of Sediment Yield Models on Various Watershed in Mississippi. Trans. ASAE, 32(2): 529–534 doi: 10.13031/2013.31035
    Brown, L. C., Foster, G. R., 1987. Storm Erosivity Using Idealized Intensity Distributions. Trans. ASAE, 30: 379–386 doi: 10.13031/2013.31957
    Cerri, C. E. P., Dematte, J. A. M., Ballester, M. V. R., et al., 2001. GIS Erosion Risk Assessment of the Piracicaba River Basin, Southeastern Brazil. Mapping Sci. Remote Sensing, 38: 157–171 doi: 10.1080/07493878.2001.10642173
    Chai, Z. X., 1996. On Land Erosion in South China. Mountain Research, 14(4): 215–220 (in Chinese with English Abstract)
    E, J. P., Liu, N., Deng, J., 2004. Sediment Bulletin for China Rivers. Chinese Ministry of Water Resources, Beijing, China (in Chinese with English Abstract)
    Fistikoglu, O., Harmancioglu, N. B., 2002. Integration of GIS with USLE in Assessment of Soil Erosion. Water Resources Management, 16(6): 447–467 doi: 10.1023/A:1022282125760
    Flügel, W. A., Märker, M., Moretti, S., et al., 2003. Integrating Geographical Information Systems, Remote Sensing, Ground Truthing and Modelling Approaches for Regional Erosion Classification of Semi-arid Catchments in South Africa. Hydrological Processes, 17(5): 929–942 doi: 10.1002/hyp.1171
    Folly, A., Bronsveld, M. C., Clavaux, M., 1996. A Knowledge-Based Approach for C Factor Mapping in Spain Using Landsat TM and GIS. International Journal of Remote Sensing, 17(12): 2401–2415 doi: 10.1080/01431169608948780
    Hamlett, J. M., Miller, D. A., Day, R. L., et al., 1992. Statewide GIS-Based Ranking of Watersheds for Agricultural Pollution Prevention. Journal of Soil and Water Conservation, 47(5): 399–404
    Hickey, R., 2000. Slope Angle and Slope Length Solutions for GIS. Cartography, 29(1): 1–8 doi: 10.1080/00690805.2000.9714334
    Hickey, R., Smith, A., Jankowski, P., 1994. Slope Length Calculations from a DEM within ARC/INFO GRID. Comput. Environ. Urban Syst. , 18(5): 365–380 doi: 10.1016/0198-9715(94)90017-5
    Jian, M. K., Kothyari, U. C., 2000. Estimation of Soil Erosion and Sediment Yield Using GIS. Hydrol. Sci. J. , 45(5): 771–786 doi: 10.1080/02626660009492376
    Jain, S. K., Kumar, S., Varghese, J., 2001. Estimation of Soil Erosion for a Himalayan Watershed Using a GIS Technique. Water Resources Management, 15(1): 41–54 doi: 10.1023/A:1012246029263
    Jiang, W. S., Kong, F. B., 2003. Countermeasures for Water and Soil Erosion and Forest Ecosystem Management in Poyang Lake Watersheds. Forest Resources Management, 6: 36–40 (in Chinese with English Abstract)
    Johnson, R., 1988. Putting Soil Movement into Perspective. Journal of Production Agriculture, 1(1): 5–12 doi: 10.2134/jpa1988.0005
    Lee, S., 2004. Soil Erosion Assessment and Its Verification Using the Universal Soil Loss Equation and Geographic Information System: A Case Study at Boun, Korea. Environmental Geology, 45(4): 457–465 doi: 10.1007/s00254-003-0897-8
    Liang, Y., Shi, X. Z., 1999. Soil Erodiable K in East Hillyfields of the Southern Yangtze River. Research of Soil and Water Conservation, 6(2): 47–52 (in Chinese with English Abstract)
    Lim, K. J., Sagong, M., Engel, B. A., et al., 2005. GIS-Based Sediment Assessment Tool. Catena, 64(1): 61–80 doi: 10.1016/j.catena.2005.06.013
    Lin, C. Y., Lin, W. T., Chou, W. C., 2002. Soil Erosion Prediction and Sediment Yield Estimation: The Taiwan Experience. Soil and Tillage Research, 68(2): 143–152 doi: 10.1016/S0167-1987(02)00114-9
    Lu, D., Li, G., Valladares, G. S., et al., 2004. Mapping Soil Erosion Risk in Rondonia, Brazilian Amazonia: Using RULSE, Remote Sensing and GIS. Land Degrad. Develop. , 15(5): 499–512 doi: 10.1002/ldr.634
    Lufafa, A., Tenywa, M. M., Iasbirye, M., et al., 2003. Prediction of Soil Erosion in a Lake Victoria Basin Catchment Using a GIS-Based Universal Soil Loss Model. Agricultural Systems, 76(3): 883–894 doi: 10.1016/S0308-521X(02)00012-4
    Maidment, D. R., 2002. Arc Hydro: GIS for Water Resources. ESRI Press, Redlands, CA
    Mati, B. M., Morgan, R. P. C., Gichuki, F. N., et al., 2000. Assessment of Erosion Hazard with the USLE and GIS: A Case Study of the Upper Ewaso Ng'iro North Basin of Kenya. International Journal of Applied Earth Observation and Geoinformation, 2(2): 78–86 doi: 10.1016/S0303-2434(00)85002-3
    Meyer, L. D., Bauer, A., Heil, R. D., 1985. Experimental Approaches for Quantifying the Effect of Soil Erosion on Productivity. In: Follett, R. F., Stewart, B. A., Ballew, I. Y., eds., Soil Erosion and Crop Productivity. American Society of Agronomy, Crop Science Society of America and Soil Science Society of America Publishers, Madison, WI, USA. 213–234
    Mitra, B., Scott, H. D., Dixon, J. C., et al., 1998. Applications of Fuzzy Logic to the Prediction of Soil Erosion in a Large Watershed. Geoderma, 86(3–4): 183–209
    Morgan, R. P. C., 1995. Soil Erosion and Conservation. John Wiley & Sons, Essex, England
    Morgan, R. P. C., Quinton, J. N., Smith, R. E., et al., 1998. The European Soil Erosion Model (EUROSEM): A Dynamic Approach for Predicting Sediment Transport from Fields and Small Catchments. Earth Surface Processes and Landforms, 23(6): 527–544 doi: 10.1002/(SICI)1096-9837(199806)23:6<527::AID-ESP868>3.0.CO;2-5
    Natalia, H., 2005. Spatial Modeling of Soil Erosion Potential in a Tropical Watershed of the Colombian Andes. Catena, 63: 85–108 doi: 10.1016/j.catena.2005.05.012
    Nearing, M. A., Lane, L. J., Lopes, V. L., 1994. Modeling Soil Erosion. In: Lal, R., ed., Soil Erosion: Research Methods. St. Lucie Press, Delray Beach, FL. 127–135
    Nisar, T. R., Ahamed, K., Rao, G., et al., 2000. Fuzzy Class Membership Approach to Soil Erosion Modelling. Agricultural Systems, 63: 97–110 doi: 10.1016/S0308-521X(99)00066-9
    Nyakatawa, E. Z., Reddy, K. C., Lemunyon, J. L., 2001. Predicting Soil Erosion in Conservation Tillage Cotton Production Systems Using the Revised Universal Soil Loss Equation (RUSLE). Soil & Tillage Research, 57(4): 213–224
    Onyando, J. O., Kisoyan, P., Chemelil, M. C., 2005. Estimation of Potential Soil Erosion for River Perkerra Catchment in Kenya. Water Resources Management, 19(2): 133–143 doi: 10.1007/s11269-005-2706-5
    Oyedele, J. D., 1996. Effects of Erosion on the Productivity of Selected Southwestern Nigerian Soils: [Dissertaion]. Department of Soil Science, Obafemi Awolowo University, Ile-Ife, Nigeria
    Ozcan, A. U., Erpul, G., Basaran, M., et al., 2008. Use of USLE/GIS Technology Integrated with Geostatistics to Assess Soil Erosion Risk in Different Land Uses of Indagi Mountain Pass—Cankiri, Turkey. Environmental Geology, 53(8): 1731–1741 doi: 10.1007/s00254-007-0779-6
    Pan, J. J., Zhang, T. L., Zhao, Q. G., 2005. Dynamics of Soil Erosion in Xingguo County, China, Determined Using Remote Sensing and GIS. Pedosphere, 15(3): 356–362
    Pandey, A., Chowdary, V. M., Mal, B. C., 2007. Identification of Critical Erosion Prone Areas in the Small Agricultural Watershed Using USLE, GIS and Remote Sensing. Water Resources Management, 21(4): 729–746 doi: 10.1007/s11269-006-9061-z
    Renard, K. G., Foster, G. R., Weesies, G. A., et al., 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture Handbook No. 703, USDA Agricultural Research Services, Washington, DC
    Renard, K. G., Laflen, J. M., Foster, G. R., et al., 1994. The Revised Universal Soil Loss Equation. In: Lal, R., ed., Soil Erosion Research Methods. St. Lucie Press, Delray Beach, FL. 105–124
    Renschler, C. S., Mannaerts, C., Diekkrüeger, B., 1999. Evaluating Spatial and Temporal Variability in Soil Erosion Risk—Rainfall Erosivity and Soil Loss Ratios in Andalusia, Spain. Catena, 34(3–4): 209–225
    Rodda, H. J. E., Demuth, S., Shankar, U., 1999. The Application of a GIS Based Decision Support System to Predict Nitrate Leaching to Groundwater in Southern Germany. Hydrol. Sci. J. , 44(2): 221–236 doi: 10.1080/02626669909492219
    Shi, Z. H., Cai, C. F., Ding, S. W., et al., 2004. Soil Conservation Planning at the Small Watershed Level Using RUSLE with GIS: A Case Study in the Three Gorge Area of China. Catena, 55(1): 33–48 doi: 10.1016/S0341-8162(03)00088-2
    Trimble, S. W., Lund, S. W., 1982. Soil Conservation and the Reduction of Erosion and Sedimentation in the Coon Creek Basin, Wisconsin. U.S. Geological Survey Professional Paper, 1234: 35
    van Remortel, R. D., Maichle, R. W., Hickey, R. J., 2004. Computing the LS Factor for the Revised Universal Soil Loss Equation through Array-Based Slope Processing of Digital Elevation Data Using a C++ Executable. Computers & Geosciences, 30(9–10): 1043–1053
    Walling, D. E., 1983. The Sediment Delivery Problem. J. Hydrol. , 65(1–3): 209–237
    Walling, D. E., 1988. Erosion and Sediment Yield Research—Some Recent Perspectives. J. Hydrol. , 100(1–4): 113–141
    Wang, G. X., Gertner, G., Fang, S. F., et al., 2003. Mapping Multiple Variables for Predicting Soil Loss by Geostatistical Methods with TM Images and a Slope Map. Photogramm. Eng. Remote Sens. , 69(8): 889–898 doi: 10.14358/PERS.69.8.889
    Wang, G., Wente, S., Gertner, G. Z., et al., 2002. Improvement in Mapping Vegetation Cover Factor for the Universal Soil Loss Equation by Geostatistical Methods with Landsat Thematic Mapper Images. International Journal of Remote Sensing, 23(18): 3649–3667 doi: 10.1080/01431160110114538
    Wang, G. Q., Hapuarachchi, H., Ishidaira, H., 2009. Estimation of Soil Erosion and Sediment Yield during Individual Rainstorms at Catchment Scale. Water Resources Management, 23(8): 1447–1465 doi: 10.1007/s11269-008-9335-8
    Williams, J. R., Berndt, H. D., 1974. Sediment Yield Computed with Universal Equation. J. Hydraul. Div. , 100(HY11): 1719–1720
    Wischmeier, W. H., Smith, D. D., 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning, Agricultural Handbook 537. U.S. Department of Agriculture, Science and Education Administration, Washington, DC
    Young, R. A., Onstad, C. A., Bosch, D. D., et al., 1987. An Agricultural Non-point Source Pollution Model, a Watershed Analysis Toll. U.S. Department of Agricultural Research Services, Conservation Research Report 35
    Zhang, R. F., 1990. Impaction of Soil and Water Loss to the Ecological Environment and Economy Construction of the Poyang Lake Watershed. Acta Conservationis Soli et Aquae Sinica, 4(3): 80–86 (in Chinese with English Abstract)
    Zhang, W. B., Fu, J. S., 2003. Rainfall Erosivity Estimation under Different Rainfall Amount. Resources Science, 25(1): 35–41 (in Chinese with English Abstract)
    Zhou, W. F., Wu, B. F., 2008. Assessment of Soil Erosion and Sediment Delivery Ratio Using Remote Sensing and GIS: A Case Study of Upstream Chaobaihe River Catchment, North China. International Journal of Sediment Research, 23(2): 167–173 doi: 10.1016/S1001-6279(08)60016-5
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