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Predicting soil erosion risk at the Alqueva dam watershed

Author

Listed:
  • Vera Ferreira

    (cieo - research centre for spatial and organizational dynamics)

  • Thomas Panagopoulos

    (cieo - research centre for spatial and organizational dynamics)

Abstract

Soil erosion is serious economic and environmental concern. Assessing soil erosion risk in the Alqueva dam watershed is urgently needed to conserve soil and water resources and prevent the accelerated dam siltation, taking into account the possible land-use changes, due to tourism development, intensification of irrigated farming and biomass production, as well as climate change. A comprehensive methodology that integrates Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information Systems (GIS) with geostatistical techniques was adopted to study different land-use and management scenarios. The main objective of this study stage is to determine the soil erosion vulnerability of an agro-silvo pastoral system. The resultant soil erosion map shows an average of 14.1 t/ha/ year, with serious erosion risk (higher than 50 t/ha/year) in 4.3% of area. The highest values are associated mainly to high slopes and low vegetation. The final prediction maps for soil erosion and for each factor considered, can be used as a solid base to create a Decision Support System so as to provide specific procedures for decision-makers, promoting for sustainability of the ecosystems, reducing the risk of erosion and consequently increase lifetime of dam, under various land use and management scenarios

Suggested Citation

  • Vera Ferreira & Thomas Panagopoulos, 2012. "Predicting soil erosion risk at the Alqueva dam watershed," Spatial and Organizational Dynamics Discussion Papers 2012-4, CIEO-Research Centre for Spatial and Organizational Dynamics, University of Algarve.
    • Handle: RePEc:ris:cieodp:2012_004
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    References listed on IDEAS

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    1. Lindim, C. & Pinho, J.L. & Vieira, J.M.P., 2011. "Analysis of spatial and temporal patterns in a large reservoir using water quality and hydrodynamic modeling," Ecological Modelling, Elsevier, vol. 222(14), pages 2485-2494.
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    3. Ashish Pandey & V. Chowdary & B. Mal, 2007. "Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(4), pages 729-746, April.
    4. Borges, P.J. & Fragoso, R. & Garcia-Gonzalo, J. & Borges, J.G. & Marques, S. & Lucas, M.R., 2010. "Assessing impacts of Common Agricultural Policy changes on regional land use patterns with a decision support system: An application in Southern Portugal," Forest Policy and Economics, Elsevier, vol. 12(2), pages 111-120, February.
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    Cited by:

    1. Jose Antonio Gonzalez-Duque & Thomas Panagopoulos, 2013. "Evaluation of the Urban Green Infrastructure using Landscape Modules, GIS and a Population Survey: Linking Environmental with Social Aspects in Studying and Managing Urban Forests," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 1(2), pages 82-95.
    2. Thomas Panagopoulos, 2013. "Factors of Reclamation Success at the Lignite Strip-Mined Land in Northern Greece," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 1(2), pages 96-122.

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    More about this item

    Keywords

    Soil Erosion; Land-use; Geostatistic; RUSLE; Geographic Information System;
    All these keywords.

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land

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