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Satellite-based irrigation advisory services: A common tool for different experiences from Europe to Australia

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  • Vuolo, Francesco
  • D’Urso, Guido
  • De Michele, Carlo
  • Bianchi, Biagio
  • Cutting, Michael

Abstract

Earth Observation techniques are widely recognised in supporting the management of land and water resources and they are nowadays being transferred to operative applications. In this paper, we present the current status of a satellite-based irrigation advisory system based on dedicated webGIS or farmers and district managers, in three different agricultural systems and environments: Southern Italy, Austria and Southern Australia. Maps of canopy development (leaf area index, albedo and soil cover) are derived from high-resolution (20m) multispectral satellite images, delivered in near real time (24–36h) and processed by using in-situ agro-meteorological data. The outputs of this procedure are: (i) a personalised irrigation advice, based on the calculation of crop evapotranspiration under standard conditions (according to FAO-56 definition and by using the direct approach) by taking into account the actual canopy development and crop variability at sub-plot scale; (ii) timely delivery of the information, consisting in maps and suggested irrigation volume applications, timely published on a dedicated webGIS-site with access restricted to growers and basin authorities in order to better control the irrigation process and consequently improve its overall efficiency. The key-points of this procedure are: (a) personalised irrigation advice; (b) timely delivery of the information. Final users have provided important feedback on the usage of the information provided; i.e. farmers are able to recognise without difficulties their parcels on the images and they schedule the irrigations by taking into account the information provided. The crop heterogeneity captured by the high resolution images is considered as a valuable add-on information to identify the variability of soil texture and fertility, plant nutrition, or different performance of irrigation systems. All the farmers have evaluated positively the usefulness of the information provided, and in most cases an increase of irrigation efficiency was achieved, because of the reduction of water volumes.

Suggested Citation

  • Vuolo, Francesco & D’Urso, Guido & De Michele, Carlo & Bianchi, Biagio & Cutting, Michael, 2015. "Satellite-based irrigation advisory services: A common tool for different experiences from Europe to Australia," Agricultural Water Management, Elsevier, vol. 147(C), pages 82-95.
    • Handle: RePEc:eee:agiwat:v:147:y:2015:i:c:p:82-95
    DOI: 10.1016/j.agwat.2014.08.004
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    1. D'Urso, G. & Richter, K. & Calera, A. & Osann, M.A. & Escadafal, R. & Garatuza-Pajan, J. & Hanich, L. & Perdigão, A. & Tapia, J.B. & Vuolo, F., 2010. "Earth Observation products for operational irrigation management in the context of the PLEIADeS project," Agricultural Water Management, Elsevier, vol. 98(2), pages 271-282, December.
    2. Campos, Isidro & Neale, Christopher M.U. & Calera, Alfonso & Balbontín, Claudio & González-Piqueras, Jose, 2010. "Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.)," Agricultural Water Management, Elsevier, vol. 98(1), pages 45-54, December.
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    8. George P. Petropoulos & Prashant K. Srivastava & Maria Piles & Simon Pearson, 2018. "Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management," Sustainability, MDPI, vol. 10(1), pages 1-20, January.
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    10. Garrido-Rubio, Jesús & González-Piqueras, Jose & Campos, Isidro & Osann, Anna & González-Gómez, Laura & Calera, Alfonso, 2020. "Remote sensing–based soil water balance for irrigation water accounting at plot and water user association management scale," Agricultural Water Management, Elsevier, vol. 238(C).
    11. Ying-Jung Chen & Joseph McFadden & Keith Clarke & Dar Roberts, 2015. "Measuring Spatio-temporal Trends in Residential Landscape Irrigation Extent and Rate in Los Angeles, California Using SPOT-5 Satellite Imagery," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5749-5763, December.
    12. Alessandra Santini & Antonella Di Fonzo & Elisa Giampietri & Andrea Martelli & Orlando Cimino & Anna Dalla Marta & Maria Carmela Annosi & Francisco José Blanco-Velázquez & Teresa Del Giudice & Filiber, 2023. "A Step toward Water Use Sustainability: Implementing a Business Model Canvas for Irrigation Advisory Services," Agriculture, MDPI, vol. 13(5), pages 1-13, May.
    13. Zhao, Wenzhi & Chang, Xuexiang & Chang, Xueli & Zhang, Dengrong & Liu, Bing & Du, Jun & Lin, Pengfei, 2018. "Estimating water consumption based on meta-analysis and MODIS data for an oasis region in northwestern China," Agricultural Water Management, Elsevier, vol. 208(C), pages 478-489.
    14. Pôças, I. & Calera, A. & Campos, I. & Cunha, M., 2020. "Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches," Agricultural Water Management, Elsevier, vol. 233(C).
    15. Jovanovic, N. & Pereira, L.S. & Paredes, P. & Pôças, I. & Cantore, V. & Todorovic, M., 2020. "A review of strategies, methods and technologies to reduce non-beneficial consumptive water use on farms considering the FAO56 methods," Agricultural Water Management, Elsevier, vol. 239(C).

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