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Remote Sensing and Economic Indicators for Supporting Water Resources Management Decisions

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  • Petra Hellegers
  • Richard Soppe
  • Chris Perry
  • Wim Bastiaanssen

Abstract

This paper demonstrates that combining spatial land surface data with socio-economic analysis provides a number of indicators to strengthen decision making in integrated water and environmental management. It provides a basis to: track current water consumption in the Inkomati Basin in South-Africa; adjust irrigation water management; select crop types; facilitate planning; estimate crop yields before harvesting, and consequently to forecast market price development. Remote sensing data and economic analysis can also be used to study the spatial distribution of water consumption as an indicator of equity in access to water resources. It even enables identification of farms that consume more irrigation water than formally allocated. Finally, it provides a basis to assess the cost-effectiveness of various ways to reduce agricultural water consumption. So, this approach is potentially useful for determining water consumption, refining water allocation policies, and determining the potential for water transfers through mechanisms such as water trading. Copyright The Author(s) 2010

Suggested Citation

  • Petra Hellegers & Richard Soppe & Chris Perry & Wim Bastiaanssen, 2010. "Remote Sensing and Economic Indicators for Supporting Water Resources Management Decisions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2419-2436, September.
    • Handle: RePEc:spr:waterr:v:24:y:2010:i:11:p:2419-2436
    DOI: 10.1007/s11269-009-9559-2
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    References listed on IDEAS

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    1. Bastiaanssen, W. G. M. & Chandrapala, L., 2003. "Water balance variability across Sri Lanka for assessing agricultural and environmental water use," Agricultural Water Management, Elsevier, vol. 58(2), pages 171-192, February.
    2. Zwart, Sander J. & Bastiaanssen, Wim G.M., 2007. "SEBAL for detecting spatial variation of water productivity and scope for improvement in eight irrigated wheat systems," Agricultural Water Management, Elsevier, vol. 89(3), pages 287-296, May.
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    5. Droogers, P. & Malik, R.P.S. & Kroes, J. G. & Bastiaanssen, W. G. M. & van Dam, J. C., 2003. "Future water management in Sirsa district: options to improve water productivity," Book Chapters,, International Water Management Institute.
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    Cited by:

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    2. Nadine Wittmann, 2014. "A Microeconomic Perspective on Water Resources Management: Analyzing the Effects on Optimal Land Rents Along a River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1309-1325, March.
    3. Fernández, J.E. & Alcon, F. & Diaz-Espejo, A. & Hernandez-Santana, V. & Cuevas, M.V., 2020. "Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard," Agricultural Water Management, Elsevier, vol. 237(C).
    4. Hazimeh, Rim & Jaafar, Hadi, 2024. "Impact of ET and biomass model choices on economic irrigation water productivity in water-scarce basins," Agricultural Water Management, Elsevier, vol. 292(C).
    5. Giorgos Papadavid & Diofantos Hadjimitsis & Leonidas Toulios & Silas Michaelides, 2013. "A Modified SEBAL Modeling Approach for Estimating Crop Evapotranspiration in Semi-arid Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3493-3506, July.

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