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Assessment of potential changes in soil erosion using remote sensing and GIS: a case study of Dacaozi Watershed, China

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Abstract

Soil erosion is a major global environmental problem. Therefore, a method of calculating potential soil erosion is necessary for soil and water resource management, as well as for assessing the risk of soil erosion. This study aimed to develop a simple method for calculating potential soil erosion change (PSEC) by combining the Universal Soil Loss Equation (USLE) and a Geographic Information System (GIS). The USLE model includes a rainfall erosivity factor (R), soil erodibility factor (K), cover management factor (C), slope gradient factor (S), length factor (L), and the supporting practice factor (P). Using a measured patch of soil and water conservation as the experimental unit, weather and soil data were combined to calculate R and K. Remote sensing images were used to extract vegetation cover (VC) and calculate C, while digital elevation models were used to extract and calculate S and L; land use maps were used to determine the P of each patch. The PSEC of each patch was then calculated according to the results of the above mentioned six factors. Finally, the PSEC of the entire study area was calculated on the basis of a patch area weighting method, which was validated in the Dacaozi Watershed in China, where a 1-year soil and water conservation project was implemented, beginning in November of 2013. In this study, the PSEC of the Dacaozi Watershed in May of 2017 was calculated, accounting for approximately 3 years of project implementation. The results showed that the average VC increased by 21.6% after 3 years of project implementation, whereas C decreased by 46.4%. The value of P did not change significantly from before to after project implementation. The average S decreased from 22.6 ± 12.1° to 21.3 ± 10.6°, and S decreased by 6.8%. In contrast, L increased by 33.3%. On the whole, the PSEC in the Dacaozi Watershed was 0.3925 and the potential soil erosion decreased by 60.75% after 3 years of conservation.

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References

  • Cai, C. F., Ding, S. W., Shi, Z. H., Huang, L., & Zhang, G. Y. (2000). Study of applying USLE and geographical information system IDRISI to predict soil erosion in small watershed. Journal of Soil and Water Conservation, 14(2), 19–24 (in Chinese with English abstract).

    CAS  Google Scholar 

  • Foster, G. R., McCool, D. K., Renard, K. G., & Moldenhauer, W. C. (1981). Conversion of the Universal Soil Loss Equation to SI metric units. Journal of Soil and Water Conservation, 36(6), 355–359.

    Google Scholar 

  • Honore, G. (1999). Our land, ourselves-guide to watershed management in India (pp. 238). New Delhi: Government of India New Delhi.

  • Khadse, G. K., Vijay, R., & Labhasetwar, P. K. (2015). Prioritization of catchments based on soil erosion using remote sensing and GIS. Environmental Monitoring and Assessment, 187(6), 333.

    Article  Google Scholar 

  • Khan, M. A. (1999). Water balance and hydrochemistry of precipitation components in forested ecosystems in the arid zone of Rajasthan, India. Hydrological Sciences Journal, 44(2), 149–161.

    Article  CAS  Google Scholar 

  • Le Bissonnais, Y., Montier, C., Jamagne, M., Daroussin, J., & King, D. (2002). Mapping erosion risk for cultivated soil in France. Catena, 46(2), 207–220.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Li, J., Chen, X., Tian, L., Huang, J., & Feng, L. (2015). Improved capabilities of the Chinese high-resolution remote sensing satellite GF-1 for monitoring suspended particulate matter (SPM) in inland waters: radiometric and spatial considerations. ISPRS Journal of Photogrammetry and Remote Sensing, 106, 145–156.

    Article  Google Scholar 

  • Liu, Z. (2005). Retrospect and prospect on integrated management of soil conservation in small river basins. China Water Resources, 22, 17–18 (in Chinese with English abstract).

    Google Scholar 

  • Liu, B. Y., Nearing, M. A., & Risse, L. M. (1994). Slope gradient effects on soil loss for steep slopes. Transactions of ASAE, 37(6), 1835–1840.

    Article  Google Scholar 

  • Mati, B. M., Morgan, R. P. C., Gichuki, F. N., Quinton, J. N., Brewer, T. R., & Liniger, H. P. (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.

    Article  Google Scholar 

  • Millward, A. A., & Mersey, J. E. (1999). Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. CATENA, 38(2), 109–129.

    Article  Google Scholar 

  • Moore, I. D., Gessler, P. E., Nielsen, G. A., & Peterson, G. A. (1993). Soil attribute prediction using terrain analysis. Soil Science Society of America Journal, 57, 443–452.

    Article  Google Scholar 

  • Pradhan, B., Chaudhari, A., Adinarayana, J., & Buchroithner, M. F. (2012). Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia. Environmental Monitoring and Assessment, 184(2), 715–727.

    Article  Google Scholar 

  • Qin, W., Zhu, Q. K., & Zhang, Y. (2009). Soil erosion assessment of small watershed in Loess Plateau based on GIS and RUSLE. Transactions of the Chinese Society of Agricultural Engineering, 25(8), 157–163.

    Google Scholar 

  • Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., & Yoder, D. C. (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). In K. G. Renard, G. R. Foster, G. A. Weesies, D. K. McCool, & D. C. Yoder (Eds.), Agriculture handbook (pp. 1–251) Washington.

    Google Scholar 

  • Sharpley, A. N., & Williams, J. R. (1990). EPIC-Erosion/Productivity Impact Calculator: 1. Model documentation. Washington (DC): USDA Agricultural Reaserch Service.

    Google Scholar 

  • Shi, Z. H., Cai, C. F., Ding, S. W., Li, C. X., & Li, T. W. (2002). Soil conservation planning at small watershed level using GIS-based Revised Universal Soil Loss Equation (RUSLE). Transactions of the Chinese Society of Agricultural Engineering, 18(4), 172–175 (in Chinese with English abstract).

    Google Scholar 

  • Vittala, S. S., Govindaiah, S., & Gowda, H. H. (2008). Prioritization of sub-watersheds for sustainable development and management of natural resources: an integrated approach using remote sensing, GIS and socio-economic data. Current Science, 95(3), 345–354.

    Google Scholar 

  • Wang, W. Z., & Jiao, J. Y. (1996). Qutantitative evaluation on factor influencing soil erosion in China. Bulletin of Soil and Water Conservation, 16(5), 1–20 (in Chinese with English abstract).

    Google Scholar 

  • Wang, X. Q., Wang, M. M., Wang, S. Q., & Wu, Y. D. (2015). Extraction of vegetation information from visible unmanned aerial vehicle images. Transactions of the Chinese Society of Agricultural Engineering, 31(5), 152–159 (in Chinese with English abstract).

    Google Scholar 

  • Wischmeier, W. H., & Smith, D. D. (1958). Rainfall energy and its relationship to soil loss. Eos, Transactions American Geophysical Union, 39(2), 285–291.

    Article  Google Scholar 

  • Wischmeier, W. H., & Smith, D. D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains. Washington DC: Soil Conservation Service, USDA.

    Google Scholar 

  • Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses-a guide to conservation planning. Washington DC: US Government Printing Office.

    Google Scholar 

  • Xu, Y. Q., & Shao, X. M. (2006). Estimation of soil erosion supported by GIS and RUSLE: a case study of Maotiaohe Watershed, Guizhou Province. Journal of Beijing Forest University, 28(4), 67–71 (in Chinese with English abstract).

    Google Scholar 

  • Youssef, A. M., Pradhan, B., Gaber, A. F. D., & Buchroithner, M. F. (2009). Geomorphological hazard analysis along the Egyptian red sea coast between Safaga and Quseir. Natural Hazards and Earth System Sciences, 9(3), 751–766.

    Article  Google Scholar 

  • Zhang, Y. Q., Gong, H. L., Zhao, W. J., & Li, X. J. (2007). Quantitative evaluation and spatial analysis of soil erosion in Miyun County base on GIS and USLE. Research of Soil and Water Conservation, 14(3), 358–362,364 (in Chinese with English abstract).

    Google Scholar 

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Funding

This work was jointly supported by the Changjiang River Scientific Research Institute (CRSRI) Open Research Program [grant no. CKWV2016389/KY], the National Natural Science Foundation of China [grant no. 41501019], and the National Soil and Water Loss Monitor and Announcement [grant no. 1261520610101].

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Authors and Affiliations

  1. Pearl River Hydraulic Research Institute, Pearl River Water Resources Commission, Ministry of Water Resources, Guangzhou, 510611, China

    Jun Huang

  2. Soil and Water Conservation Monitoring Center of Pearl River Basin, Pearl River Water Resources Commission, Ministry of Water Resources, Guangzhou, 510611, China

    Jun Huang

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  1. Jun Huang
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Correspondence to Jun Huang.

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Huang, J. Assessment of potential changes in soil erosion using remote sensing and GIS: a case study of Dacaozi Watershed, China. Environ Monit Assess 190, 736 (2018). https://doi.org/10.1007/s10661-018-7120-6

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