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Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed, Nan Province, Thailand

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Environmental Geology

Abstract

Land degradation is still a very common problem in the mountains of Asia because of inappropriate land use practice in steep topography. Many studies have been carried out to map shifting cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area. Factors that influence soil erosion are: rainfall erosivity, soil erodibility, slope length and steepness, crop management and conservation practices. Thus the reliability of estimated soil loss is based on how accurately the different factors were estimated or prepared. As each and every small pixel of our earth surface is different from one area to another, the manner in which the study area was discretized into smaller homogenous sizes and how the most accurate and efficient technique were adopted to estimate the soil loss are very important. The purpose of this study is to produce erosion susceptibility maps for an area that has suffered because of shifting cultivation located in the mountainous regions of Northern Thailand. For this purpose, an integrated approach using RS and GIS-based methods is proposed. Data from the Upper Nam Wa Watershed, a mountainous area of the Northern Thailand were used. An Earth Resources Data Analysis System (ERDAS) imagine image processor has been used for the digital analysis of satellite data and topographical analysis of the contour data for deriving the land use/land cover and the topographical data of the watershed, respectively. ARCInfo and ARCView have been used for carrying out geographical data analysis. The watershed was discretized into hydrologically, topographically, and geographically homogeneous grid cells to capture the watershed heterogeneity. The soil erosion in each cell was calculated using the universal soil loss equation (USLE) by carefully determining its various parameters and classifying the watershed into different levels of soil erosion severity. Results show that during the time of this study most of the areas under shifting cultivation fell in the highest severity class of susceptibility.

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References

  • Beven KJ (1996) A discussion of distributed modeling. In: Abbott MB, Refsgaard JC (eds) Distributed hydrological modeling. Kluwer, Dordrecht, pp 255–278

    Google Scholar 

  • El-swaify SA, Moldenhauer WC, Lo A (1985) Soil erosion and conservation. Soil conservation society of America, Ankeny

    Google Scholar 

  • ERDAS (1998) ERDAS Imagine 8.3.1. ERDAS, Atlanta

    Google Scholar 

  • Ferro V (1997) Further remarks on a distributed approach to sediment delivery. Hydrol Sci J 42(5):633–647

    Article  Google Scholar 

  • Ferro V, Minacapilli M (1995) Sediment delivery processes at basin scale. Hydrol Sci J 40(6):703–717

    Article  Google Scholar 

  • Ferro V, Porto P, Tusa G (1998) Testing a distributed approach for modeling sediment delivery. Hydrol Sci J 43(3):425–442

    Article  Google Scholar 

  • Funnpheng P, Patinavin S, Mekpaiboon Wattana S, Pramojanee P (1991) Application of remote sensing and a geographic information system for appraising soil erosion hazard. In: Proceedings of the international workshop on conservation and sustainable development. Asian Institute of Technology Bangkok and Khao Yai National Park, Thailand, pp 79–91

  • Haen HD (1991) Environmental consequences of agricultural growth In: Vosti SA, Reardon T, Winfried Von Urff (eds) Agricultural sustainability, growth and poverty alleviation and policies, Feldafing, pp 31–46

  • Harper D (1987) Improving the accuracy of the universal soil loss equation in Thailand. Paper presented at the fifth international conservation conferences, Bangkok, Thailand

  • Hitzhusen FJ (1993) Land degradation and sustainability of agricultural growth. some economic concepts and evidence from selected developing countries. Agric Ecosyst Environ 46:69–79

    Article  Google Scholar 

  • Kothyari UC, Jain SK (1997) Sediment yield estimation using GIS. Hydrol Sci J 42(6):833–843

    Article  Google Scholar 

  • Monchareon L (1982) Application of soil maps and report for soil and water conservation. department of land development, Bangkok

    Google Scholar 

  • Moore ID, Burch GJ (1986a) Physical basis of the length slope factor in the Universal Soil Loss Equation. Soil Sci Soc Am 50(5):1294–1298

    Article  Google Scholar 

  • Moore ID, Burch GJ (1986b) Modeling erosion and deposition. Topographic effects. Trans Am Soc Agric Eng 29(6):1624–1630

    Article  Google Scholar 

  • Onchan T (1993) Land use, conservation and sustainable land management in Asia. Rural land use in the Asia and the Pacific. Asian Productivity Organization (APO), Tokyo

    Google Scholar 

  • Rauschkalb RS (1971) Land degradation, FAO, Rome, Soil bulletin no. 13

  • Renard KG, Foster GR, Weesies GA, Porter JP (1991) RUSLE, revised universal soil loss equation. J Soil Water Conserv 46(1):30–33

    Google Scholar 

  • Rodda HJ, Demuth S, Shankar U (1999) The application of a GIS based decision support system to predict nitrate leaching to ground water in south Germany. Hydrol Sci J 44(2):221–236

    Article  Google Scholar 

  • Sabins FS (1997) Remote sensing. Principles and interpretations. 3rd edn, W. H. Freeman, NY

    Google Scholar 

  • Sanders DW (1992) Developing national and regional conservation policies. In: Arsyad S et al. (eds) Conservation policies for sustainable hillslope farming, soil and water conservation society, pp 3–13

  • Shamsi UM (1996) Storm-water management implementation through modeling and GIS. J Water Resour Plann Manage 122(2):114–127

    Article  Google Scholar 

  • Suddhapreda N, Paningbatan EP, Chakong W, Piadong B (1988) In: Rimwanich S (ed) Land conservation for future generations. Prediction of soil erosion in Northern Thailand using a physical model, vol 1. Bangkok, pp 489–502

  • Wicks JM, Bathurst JC (1996) A physically based distributed erosion and sediment yield component for the SHE hydrological modeling system. J Hydrol 175:213–238

    Article  Google Scholar 

  • Wischmeier WH, Smith DD (1965) Predicting rainfall erosion losses from cropland east of the Rocky Mountains. Handbook no. 282, USDA. Washington, DC

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses. Agriculture handbook no. 537, USDA science and education administration

  • Williams JR (1975) Sediment routing for agricultural watersheds. Water Resour Bull 11:965–974

    Article  Google Scholar 

  • Young RA, Onstad CA, Bosch DD, Anderson WP (1987) An agricultural non point source pollution model (AGNPS). Conservation Research Report 35, US Department of Agricultural Research Services, WA

Download references

Acknowledgements

I would like to thank Dr. Apisit Eiumnoh and Dr. Rajendra P. Shrestha for the helpful discussions, encouragements and their valuable criticism and constructive comments on the draft paper. The author is grateful to anonymous reviewers whose valuable comments and suggestions helped to consolidate and strengthens this article.

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Correspondence to K. C. Krishna Bahadur.

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Krishna Bahadur, K.C. 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 (2009). https://doi.org/10.1007/s00254-008-1348-3

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  • DOI: https://doi.org/10.1007/s00254-008-1348-3

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