|
|
|
|
|
| Assessment for soil loss by using a scheme of alterative sub-models based on the RUSLE in a Karst Basin of Southwest China |
| CHEN Hao1, 2, Takashi Oguchi2, 3, WU Pan4 |
1 School of Political Science and Public Administration, Huaqiao University, Quanzhou 362021, P.R.China
2 Department of Natural Environment Studies, The University of Tokyo, Kashiwa 277-8568, Japan
3 Center for Spatial Information Science, The University of Tokyo, Kashiwa 277-8568, Japan 4 College of Resources and Environmental Engineering, Guizhou University, Guiyang 550025, P.R.China |
|
|
|
|
Abstract Accurate assessment of soil loss caused by rainfall is essential for natural and agricultural resources management. Soil erosion directly affects the environment and human sustainability. In this work, the empirical and contemporary model of revised universal soil loss equation (RUSLE) was applied for simulating the soil erosion rate in a karst catchment using remote sensing data and geographical information systems. A scheme of alterative sub-models was adopted to calculate the rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors in the geographic information system (GIS) environment. A map showing the potential of soil erosion rate was produced by the RUSLE and it indicated the severe soil erosion in the study area. Six classes of erosion rate are distinguished from the map: 1) minimal, 2) low, 3) medium, 4) high, 5) very high, and 6) extremely high. The RUSLE gave a mean annual erosion rate of 30.24 Mg ha–1 yr–1 from the 1980s to 2000s. The mean annual erosion rate obtained using RUSLE is consistent with the result of previous research based on in situ measurement from 1980 to 2009. The high performance of the RUSLE model indicates the reliability of the sub-models and possibility of applying the RUSLE on quantitative estimation. The result of the RUSLE model is sensitive to the slope steepness, slope length, vegetation factors and digital elevation model (DEM) resolution. The study suggests that attention should be given to the topographic factors and DEM resolution when applying the RUSLE on quantitative estimation of soil loss.
|
|
Received: 18 March 2016
Accepted:
|
|
Corresponding Authors:
WU Pan, E-mail: pwu@gzu.edu.cn
|
| About author: CHEN Hao, Tel: +86-595-22693526, E-mail: chenhao@hqu.edu.cn |
Cite this article:
CHEN Hao, Takashi Oguchi, WU Pan .
2017.
Assessment for soil loss by using a scheme of alterative sub-models based on the RUSLE in a Karst Basin of Southwest China. Journal of Integrative Agriculture, 16(02): 377-388.
|
| ACW (Agricultural Committee of Weining). 1989. Agriculture Division of Weining County. Guizhou People Press, Guiyang. (in Chinese)Alexakis D D, Hadjimitsis D G, Agapiou A. 2013. Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus. Atmospheric Research, 131, 108–124.Boardman J, Poesen J. 2006. Soil Erosion in Europe. John Wiley & Sons, New York.Chen H, Wu P, LIU P, Gu S Y. 2012. Landscape patterns of rocky desertification in the mawoshan karst basin of northwest Guizhou Province. Research of Soil and Water Conservation, 19, 239–243. (in Chinese)Feng T, Chen H, Polyakov V O, Wang K, Zhang X, Zhang W. 2016. Soil erosion rates in two karst peak-cluster depression basins of northwest Guangxi, China: Comparison of the RUSLE model with 137Cs measurements. Geomorphology, 253, 217–224.Ford D C, Williams P W, 2007. Karst Hydrogeology and Geomorphology. John Wiley & Sons, New York.Gao H, Li R. 2007. Erodibility of original soil in Karst area. Science of Soil and Water Conservation, 5, 1–4. (in Chinese)Haan C T, Barfield B J, Hayes J C. 1994. Design Hydrology and Sedimentology for Small Catchments. Academic Press, New York.Jenson S K, Domingue J O. 1988. Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote Sensing, 54, 1593–1600.Kheir R B, Abdallah C, Khawlie A. 2008. Assessing soil erosion in Mediterranean karst landscapes of Lebanon using remote sensing and GIS. Engineering Geology, 99, 239–254.Kinnell P I A. 2010. Event soil loss, runoff and the Universal Soil Loss Equation family of models: A review. Journal of Hydrology, 385, 384–397.Van der Knijff J, Jones R, Montanarella L. 2000. Soil Erosion Risk Assessment in Europe. European Soil Bureau, European Commission, Italy.Lee G S, Lee K H. 2006. Scaling effect for estimating soil loss in the RUSLE model using remotely sensed geospatial data in Korea. Hydrology & Earth System Sciences Discussions, 3, 135–157.Liu B, Nearing M, Risse L. 1994. Slope gradient effects on soil loss for steep slopes. Transactions of the ASAE, 37, 1835–1840.López-Vicente M, Navas A. 2009. Predicting soil erosion with RUSLE in Mediterranean agricultural systems at catchment scale. Soil Science, 174, 272–282.López-Vicente M, Navas A, Machín J. 2009. Geomorphic mapping in endorheic catchments in the Spanish Pyrenees: An integrated GIS analysis of karstic features. Geomorphology, 111, 38–47.Lu X X, Shen R M. 1992. A preliminary study on the values K of soil erosibility factor. Journal of Soil and Water Conservation, 6, 63–70. (in Chinese)McCool D, Brown L, Foster G, Mutchler C, Meyer L. 1987. Revised slope steepness factor for the universal soil loss equation. Transactions of the ASAE, 30, 1387–1396.McCool D, Foster G, Mutchler C, Meyer L. 1989. Revised slope length factor for the universal soil loss equation. Transactions of the ASAE, 32, 1571–1576.Mikhailova E A, Bryant R, Schwager S, Smith S. 1997. Predicting rainfall erosivity in Honduras. Soil Science Society of America Journal, 61, 273–279.Moore I D, Burch G J. 1986. Physical basis of the length-slope factor in the Universal Soil Loss Equation. Soil Science Society of America Journal, 50, 1294–1298.Morgan R, Quinton J, Smith R, Govers G, Poesen J, Auerswald K, Chisci G, Torri D, Styczen M. 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, 527–544.Nearing M, Foster G, Lane L, Finkner S. 1989. A process-based soil erosion model for USDA-Water Erosion Prediction Project technology. Transactions of the ASAE, 32, 1587–1593.Onori F, Bonis P, Grauso S. 2006. Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy). Environmental Geology, 50, 1129–1140.Pimentel D, Harvey C, Resosudarmo P, Sinclair K, Kurz D, McNair M, Crist S, Shpritz L, Fitton L, Saffouri R. 1995. Environmental and economic costs of soil erosion and conservation benefits. Science, 267, 1117–1122.Rahman M R, Shi Z H, Chongfa C. 2009. Soil erosion hazard evaluation - An integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies. Ecological Modelling, 220, 1724–1734.Renard K G, Foster G R, Weesies G A, McCool D, Yoder D. 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE). Agriculture Handbook. Washington D.C.Van Rompaey A J, Govers G, Baudet M. 1999. A strategy for controlling error of distributed environmental models by aggregation. International Journal of Geographical Information Science, 13, 577–590.SL190-96. 1997. Chinese Standard for Classification and Gradation of Soil Erosion SL190-96. China Water Power Press, Beijing. (in Chinese)Tanya? H, Kolat Ç, Süzen M L. 2015. A new approach to estimate cover-management factor of RUSLE and validation of RUSLE model in the watershed of Kartalkaya Dam. Journal of Hydrology, 528, 584–598.Tetzlaff B, Friedrich K, Vorderbrügge T, Vereecken H, Wendland F. 2013. Distributed modelling of mean annual soil erosion and sediment delivery rates to surface waters. Catena, 102, 13–20.Tiwari A, Risse L, Nearing M. 2000. Evaluation of WEPP and its comparison with USLE and RUSLE. Transactions of the ASAE, 43, 1129–1135.de Vente J, Poesen J, Verstraeten G, Govers G, Vanmaercke M, Van Rompaey A, Arabkhedri M, Boix-Fayos C. 2013. Predicting soil erosion and sediment yield at regional scales: Where do we stand? Earth-Science Reviews, 127, 16–29.De Waele J. 2009. Evaluating disturbance on mediterranean karst areas: the example of Sardinia (Italy). Environmental Geology, 58, 239–255.Wan J. 2003. Land degradation and ecological rehabilitation in karst areas of Guizhou Province, South Western China. Advance in Earth Sciences, 18, 447–453.Wang H, Huo Y, Zeng L, Wu X, Cai Y. 2008. A 42-yr soil erosion record inferred from mineral magnetism of reservoir sediments in a small carbonate-rock catchment, Guizhou Plateau, southwest China. Journal of Paleolimnology, 40, 897–921.Wang S J, Liu Q M, Zhang D F. 2004. Karst rocky desertification in southwestern China: Geomorphology, landuse, impact and rehabilitation. Land Degradation & Development, 15, 115–121.Wang W, Jiao J, Hao X, Zhang X, Lu X. 1996. Distribution of rainfall erosivity R value in China. Journal of Soil Erosion and Water Conservation, 2, 29–39. (in Chinese)Williams J, Renard K, Dyke P. 1983. EPIC: A new method for assessing erosion’s effect on soil productivity. Journal of Soil and water Conservation, 38, 381–383.Wischmeier W H, Smith D D. 1965. Predicting Rainfall-Erosion Losses from Cropland East of the Rocky Mountains: Guide for Selection of Practices for Soil and Water Conservation, 282. Agricultural Research Service, US Department of Agriculture, USA.Wischmeier W H, Smith D D. 1978. Predicting rainfall erosion losses - A guide to conservation planning. In: Agriculture Handbook 537. United States Department of Agriculture, Washington, D.C.Wu P, Xie L S. 2011. Recording of soil sediment in the Mawoshan Karst Basin of Northwest Guizhou Province. Science of Soil and Water Conservation, 9, 83–87. (in Chinese)Wu S, Li J, Huang G. 2005. An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models. Environmental Modeling & Assessment, 10, 33–42.Xie L S, Wu P, Gu S H, Cao Z X, Ge J J. 2010a. Calculation of the soil erosion modulus of basin with the measurement method of sedimentation in Karst area. Science of Soil and Water Conservation, 8, 20–23. (in Chinese)Xie L S, Wu P, Gu S Y. 2010b. Records of erosion and accumulation of red clay in karst mountain area during process of rocky desertification. Soil and Water Conservation in China, 4, 47–51. (in Chinese)Xu Y, Zhou Q, Li S. 2005. An Analysis on spatial-temporal distribution of rainfall erosivity in Guizhou Province. Bulletin of Soil and Water Conservation, 25, 11–15. (in Chinese)Xu Y Q, Peng J, Shao X M. 2008a. Assessment of soil erosion using RUSLE and GIS: A case study of the Maotiao River watershed, Guizhou Province, China. Environmental Geology, 56, 1643–1652.Xu Y Q, Shao X M, Kong X B, Peng J, Cao Y L. 2008b. Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environmental Monitoring and Assessment, 141, 275–286.Yang G, Li Y, An Y. 2006. Pixel-based assesment and spatial distribution of sensitivity of soil erosion in Guizhou. Carsologica Sinica, 25, 73–78. (in Chinese)Yang Z. 1999. Soil erosibility factor of sloping cultivated land in the northeast mountain region of Yunnan Province. Journal of Mountain Research Science, 17, 10–15. (in Chinese)Yang Z. 2002. Study on soil loss equation in Jinsha river basin of Yunnan Province. Journal of Mountain Research, 20, 1–9.Zhang J P. 1999. Soil erosion in Guizhou province of China: A case study in Bijie prefecture. Soil Use and Management, 15, 68–70. |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
