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Spatiotemporal dynamics of soil erosion risk for Anji County, China

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Abstract

Soil erosion, as a serious environmental problem worldwide, poses a great threat to human sustainability. Spatiotemporal information on soil erosion is of vital importance to finding a solution for this problem. A case study was conducted to characterize the dynamics of soil erosion risk in 1985, 1994, 2003 and 2008 for Anji County, China, a region with seemingly high ecological quality. Remote sensing and geographic information systems were integrated to parameterize soil erosion-controlling factors. By using the Revised Universal Soil Loss Equation, we estimated annual soil loss, and generated categorical maps of soil erosion risk in the County for the 4 years. Results showed that, while appearing to improve in some areas, soil erosion risk increased and eroded area expanded from 1985 to 2008. Spatial analysis revealed that the most vulnerable hotspots were erosion-free forests, where newly eroded areas were most likely to occur. These results implied that, similar to findings in many parts of the world, soil erosion is an important issue in the study area, which could be closely associated with local eutrophication and algal blooms. Our research indicated that there should be more focus on this issue. From a methodological point of view, we believe that the approach used to estimate soil loss in the study area has the potential to be applied in other similar regions.

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References

  • Adams JB, Sabol DE, Kapos V, Almeida R, Roberts DA, Smith MO, Gillespie AR (1995) Classification of multispectral images based on fractions of endmembers-application to land-cover change in the Brazilian Amazon. Remote Sens Environ 52:137–154

    Article  Google Scholar 

  • Angima SD, Stott DE, O’Neill MK, Ong CK, Weesies GA (2003) Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agric Ecosyst Environ 97:295–308

    Article  Google Scholar 

  • Arnoldus JMJ (1977) Methodology used to determine the maximum potential average annual soil loss due to sheet and rill erosion in Morocco. Food Agric Org Soils Bull 34:39–51

    Google Scholar 

  • Bahadur KCK (2009) Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand. Environ Geol 57:695–705

    Article  Google Scholar 

  • Chander G, Markham BL, Helder DL (2009) Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens Environ 113:893–903

    Article  Google Scholar 

  • Cohen MJ, Shepherd KD, Walsh MG (2005) Empirical reformulation of the Universal Soil Loss Equation for erosion risk assessment in a tropical watershed. Geoderma 124:235–252

    Article  Google Scholar 

  • Congalton RG (1991) A review of assessing the accuracy of classification of remotely sensed data. Remote Sens Environ 37:35–46

    Article  Google Scholar 

  • De Asis AM, Omasa K (2007) Estimation of vegetation parameter for modeling soil erosion using linear Spectral Mixture Analysis of Landsat ETM data. Isprs J Photogramm 62:309–324

    Article  Google Scholar 

  • De Asis AM, Omasa K, Oki K, Shimizu Y (2008) Accuracy and applicability of linear spectral unmixing in delineating potential erosion areas in tropical watersheds. Int J Remote Sens 29:4151–4171

    Article  Google Scholar 

  • de Vente J, Poesen J, Govers G, Boix-Fayos C (2009) The implications of data selection for regional erosion and sediment yield modelling. Earth Surf Proc Land 34:1994–2007

    Article  Google Scholar 

  • Deng H, Zhang B, Yin R, Wang H, Mitchell SM, Griffiths BS, Daniell TJ (2010) Long-term effect of re-vegetation on the microbial community of a severely eroded soil in sub-tropical China. Plant Soil 328:447–458

    Article  CAS  Google Scholar 

  • Di BF, Zeng HJ, Zhang MH, Ustin SL, Tang Y, Wang ZY, Chen NS, Zhang B (2010) Quantifying the spatial distribution of soil mass wasting processes after the 2008 earthquake in Wenchuan, China A case study of the Longmenshan area. Remote Sens Environ 114:761–771

    Article  Google Scholar 

  • Eroglu H, Cakir G, Sivrikaya F, Akay AE (2010) Using high resolution images and elevation data in classifying erosion risks of bare soil areas in the Hatila Valley Natural Protected Area, Turkey. Stoch Environ Res Risk Assess 24:699–704

    Article  Google Scholar 

  • Fan JR, Zhang JH, Zhong XH, Liu SZ, Tao HP (2004) Monitoring of soil erosion and assessment for contribution of sediments to rivers in a typical watershed of the Upper Yangtze River Basin. Land Degrad Dev 15:411–421

    Article  Google Scholar 

  • Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80:185–201

    Article  Google Scholar 

  • Fu BJ (2008) Blue skies for China. Science 321:611–611

    Google Scholar 

  • Fu BJ, Zhao WW, Chen LD, Zhang QJ, Lu YH, Gulinck H, Poesen J (2005) Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the Loess Plateau of China. Land Degrad Dev 16:73–85

    Article  Google Scholar 

  • Gao J, Liu YS (2010) Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection. Int J Appl Earth Obs 12:9–16

    Article  Google Scholar 

  • Hickey R, Smith A, Jankowski P (1994) Slope length calculations from DEM within ARC/INFO grid. Comput Environ Urban 18:365–380

    Article  Google Scholar 

  • Huang CC, Pang J, Su H, Yang Q, Ha Y (2007) Climatic and anthropogenic impacts on soil formation in the semiarid loess tablelands in the middle reaches of the Yellow River, China. J Arid Environ 71:280–298

    Article  Google Scholar 

  • Irvem A, Topaloglu F, Uygur V (2007) Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. J Hydrol 336:30–37

    Article  Google Scholar 

  • Ismail J, Ravichandran S (2008) RUSLE2 model application for soil erosion assessment using remote sensing and GIS. Water Resour Manag 22:83–102

    Article  Google Scholar 

  • Jiang X, Huang C-h, Fushui R (2008) Impacts of land cover changes on runoff and sediment in the Cedar Creek Watershed, St. Joseph River, Indiana. United States. J Mt Sci-Engl 5:113–121

    Article  Google Scholar 

  • Jiang Z, Qi J, Su S, Zhang Z, Wu J (2012) Water body delineation using index composition and HIS transformation. Int J Remote Sens 33:3402–3421

    Article  Google Scholar 

  • Le Bissonnais Y, Montier C, Jamagne M, Daroussin J, King D (2002) Mapping erosion risk for cultivated soil in France. Catena 46:207–220

    Article  Google Scholar 

  • Li YK, Ni J, Yang QK, Li R (2006) Human impacts on soil erosion identified using land-use changes: a case study from the Loess Plateau, China. Phys Geog 27:109–126

    Article  Google Scholar 

  • Liang Y, Li D, Lu X, Yang X, Pan X, Mu H, Shi D, Zhang B (2010) Soil erosion changes over the past five decades in the red soil region of southern China. J Mt Sci-Engl 7:92–99

    Article  CAS  Google Scholar 

  • Liang XQ, Xu L, Li H, He MM, Qian YC, Liu J, Nie ZY, Ye YS, Chen YX (2011) Influence of N fertilization rates, rainfall, and temperature on nitrate leaching from a rainfed winter wheat field in Taihu watershed. Phys Chem Earth 36:395–400

    Article  Google Scholar 

  • Lim HS, MatJafri MZ, Abdullah K, IEEE (2009) Turbidity measurement from ALOS satellite imagery. Oceans 2009—Europe, vols 1 and 2. IEEE, New York, pp 1155–1159

  • Long HL, Liu YS, Wu XQ, Dong GH (2009) Spatio-temporal dynamic patterns of farmland and rural settlements in Su–Xi–Chang region: implications for building a new countryside in coastal China. Land Use Policy 26:322–333

    Article  Google Scholar 

  • Lu D, Weng Q (2007) A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens 28(5):823–870

    Article  Google Scholar 

  • Lu D, Mausel P, Brondizio E, Moran E (2002) Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research. Int J Remote Sens 23:2651–2671

    Article  Google Scholar 

  • Lu D, Li G, Valladares GS, Batistella M (2004) Mapping soil erosion risk in Rondonia, Brazilian Amazonia: using RULSE, remote sensing and GIS. Land Degrad Dev 15:499–512

    Article  Google Scholar 

  • Lu D, Batistella A, Mausel P, Moran E (2007) Mapping and monitoring land degradation risks in the Western Brazilian Amazon using multitemporal landsat TM/ETM plus images. Land Degrad Dev 18:41–54

    Article  Google Scholar 

  • Ma JW, Xue Y, Ma CF, Wang ZG (2003) A data fusion approach for soil erosion monitoring in the Upper Yangtze River Basin of China based on Universal Soil Loss Equation (USLE) model. Int J Remote Sens 24:4777–4789

    Article  Google Scholar 

  • Mahesh P, Mather PM (2003) An assessment of the effectiveness of the decision tree method for land cover classification. Remote Sens Environ 86:554–565

    Article  Google Scholar 

  • Masoudi M, Patwardhan AM, Gore SD (2006) Risk assessment of water erosion for the Qareh Aghaj subbasin, southern Iran. Stoch Environ Res Risk Assess 21:15–24

    Article  Google Scholar 

  • Mati BM, Veihe A (2001) Application of the USLE in a Savannah environment: comparative experiences from East and West Africa. Singap J Trop Geogr 22:138–155

    Article  Google Scholar 

  • Metternicht GI, Zinck JA (1998) Evaluating the information content of JERS-1 SAR and Landsat TM data for discrimination of soil erosion features. Isprs J Photogramm 53:143–153

    Article  Google Scholar 

  • Meusburger K, Banninger D, Alewell C (2010) Estimating vegetation parameter for soil erosion assessment in an alpine catchment by means of QuickBird imagery. Int J Appl Earth Obs 12:201–207

    Article  Google Scholar 

  • MWR (Ministry of Water Resources, PRC) (2007) National professional standards for classification and gradation of soil erosion (SL190-2007). China Hydraulic and Hydropower Press, Beijing (in Chinese)

  • MWR (Ministry of Water Resources, PRC), Chinese Academy of Sciences (CAS), Chinese Academy of Engineering (CAE) (2010) Soil erosion control and eco-security in China-A volume on red soil area of South China. Science Press, Beijing (in Chinese)

  • Onyando JO, Kisoyan P, Chemelil MC (2005) Estimation of potential soil erosion for River Perkerra catchment in Kenya. Water Resour Manag 19:133–143

    Article  Google Scholar 

  • Ouyang W, Skidmore AK, Hao FH, Wang TJ (2010) Soil erosion dynamics response to landscape pattern. Sci Total Environ 408:1358–1366

    Article  CAS  Google Scholar 

  • Quinlan R (1993) Programs for machine learning. Morgan Kaufman, San Mateo

    Google Scholar 

  • Rahman MR, Shi ZH, Chongfa C (2009) Soil erosion hazard evaluation—an integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies. Ecol Model 220:1724–1734

    Article  Google Scholar 

  • Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R-factor in the revised USLE. J Hydrol 157:287–306

    Article  Google Scholar 

  • Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). Handbook #703. US Department of Agriculture, Washington, DC

  • Rey F (2003) Influence of vegetation distribution on sediment yield in forested marly gullies. Catena 50:549–562

    Article  Google Scholar 

  • Romken MJM (1985) The soil erodibility factor: a perspective. Soil Erosion and Conservation, Soil Conservation Society of America, Ankeny, lowa

  • SCPRC (The State Council of the People’s Republic of China) (2006) Guidelines of PRC’s 11th Five-Year Plan for national economic and social development. People’s Press, Beijing (in Chinese)

  • Shi ZH, Cai CF, Ding SW, Wang TW, Chow TL (2004) Soil conservation planning at the small watershed level using RUSLE with GIS: a case study in the Three Gorge Area of China. Catena 55:33–48

    Article  Google Scholar 

  • Shrestha DP, Zinck JA, Van Ranst E (2004) Modelling land degradation in the Nepalese Himalaya. Catena 57:135–156

    Article  Google Scholar 

  • Solaimani K, Modallaldoust S, Lotfi S (2009) Investigation of land use changes on soil erosion process using geographical information system. Int J Environ Sci Technol 6:415–424

    CAS  Google Scholar 

  • Su SL, Li D, Zhang Q, Xiao R, Huang F, Wu JP (2011) Temporal trend and source apportionment of water pollution in different functional zones of Qiantang River, China. Water Res 45:1781–1795

    Article  CAS  Google Scholar 

  • Theseira MA, Thomas G, Taylor JC, Gemmell F, Varjo J (2003) Sensitivity of mixture modelling to end-member selection. Int J Remote Sens 24:1559–1575

    Article  Google Scholar 

  • Tian YC, Zhou YM, Wu BF, Zhou WF (2009) Risk assessment of water soil erosion in upper basin of Miyun Reservoir, Beijing, China. Environ Geol 57:937–942

    Article  Google Scholar 

  • Van Remortel RD, Hamilton ME, Hickey RJ (2001) Estimating the LS factor for RUSLE through iterative slope length processing of digital elevation data. Cartography 30:27–35

    Article  Google Scholar 

  • Van Remortel RD, Maichle RW, Hickey RJ (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. Comput Geosci-UK 30:1043–1053

    Article  Google Scholar 

  • Van Rompaey AJJ, Govers G (2002) Data quality and model complexity for regional scale soil erosion prediction. Int J Geogr Inf Sci 16:663–680

    Article  Google Scholar 

  • Van Rompaey AJJ, Govers G, Van Hecke E, Jacobs K (2001) The impacts of land use policy on the soil erosion risk: a case study in central Belgium. Agric Ecosyst Environ 83:83–94

    Article  Google Scholar 

  • Vezina K, Bonn F, Van CP (2006) Agricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam’s northern highlands. Landscape Ecol 21:1311–1325

    Article  Google Scholar 

  • Vrieling A (2006) Satellite remote sensing for water erosion assessment: a review. Catena 65:2–18

    Article  Google Scholar 

  • Vrieling A, Sterk G, de Jong SM (2010) Satellite-based estimation of rainfall erosivity for Africa. J Hydrol 395:235–241

    Article  Google Scholar 

  • Wang G, Wente S, Gertner GZ, Anderson A (2002) Improvement in mapping vegetation cover factor for the universal soil loss equation by geostatistical methods with Landsat Thematic Mapper images. Int J Remote Sens 23:3649–3667

    Article  Google Scholar 

  • Wang K, Wang HJ, Shi XZ, Weindorf DC, Yu DS, Liang Y, Shi DM (2009) Landscape analysis of dynamic soil erosion in Subtropical China: a case study in Xingguo County, Jiangxi Province. Soil Till Res 105:313–321

    Article  Google Scholar 

  • Williams JR, Jones CA, Dyke PT (1984) A Modelling approach to determining the relationship between erosion and soil productivity. Trans ASABE 27:129–144

    Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses-a guide to conservation. Agricultural Handbook 537. US Department of Agriculture, Washington, DC

  • Wu J, Nellis MD, Ransom MD, Price KP, Egbert SL (1997) Evaluating soil properties of CRP land using remote sensing and GIS in Finney County, Kansas. J Soil Water Conserv 52:352–358

    Google Scholar 

  • Xu YQ, Peng J, Shao XM (2008a) Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed, Guizhou Province, China. Environ Geol 56:1643–1652

    Google Scholar 

  • Xu YQ, Shao XM, Kong XB, Peng J, Cai YL (2008b) Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China. Environ Monit Assess 141:275–286

    Article  Google Scholar 

  • Yang T, Xu CY, Zhang Q (2011) DEM-based numerical modelling of runoff and soil erosion processes in the hilly-gully loess regions. Stoch Environ Res Risk Assess. doi:10.1007/s00477-011-0515-3

    Google Scholar 

  • Zhang KL, Shu AP, Xu XL, Yang QK, Yu B (2008) Soil erodibility and its estimation for agricultural soils in China. J Arid Environ 72:1002–1011

    Article  Google Scholar 

  • Zhejiang Office of Soil Survey, China (1985) Zhejiang soil. Zhejiang Science Technology Press, Hangzhou (in Chinese)

  • Zhou P, Luukkanen O, Tokola T, Nieminen J (2008) Effect of vegetation cover on soil erosion in a mountainous watershed. Catena 75:319–325

    Article  Google Scholar 

  • Zhu, MY (2011) Soil erosion risk assessment with CORINE model:case study in the Danjiangkou Reservoir region, China. Stoch Environ Res Risk Assess. doi:10.1007/s00477-011-0511-7

  • Zhu D, Wang TW, Cai CF, Li L, Shi ZH (2009) Large-scale assessment of soil erosion using a neuro-fuzzy model combined with GIS: a case study of Hubei province, China. Land Degrad Dev 20:654–666

    Article  Google Scholar 

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Acknowledgements

We were very grateful to the Editor-in-Chief and the two reviewers for their providing constructive comments and suggestions. This work was partly supported by the Fundamental Research Funds for the Central Universities, Fujian Education Department Project Fund (No. JB11150), and Minjiang University Project Fund (No. YKY1106).

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Correspondence to Jiaping Wu.

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Jiang, Z., Su, S., Jing, C. et al. Spatiotemporal dynamics of soil erosion risk for Anji County, China. Stoch Environ Res Risk Assess 26, 751–763 (2012). https://doi.org/10.1007/s00477-012-0590-0

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