Assessing the performance of a large-scale irrigation system by estimations of actual evapotranspiration obtained by Landsat satellite images resampled with cubic convolution |
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| Institution: | 1. Dept. of Civil, Environmental, Aerospace, Materials Engineering (DICAM), Università degli Studi di Palermo, Bld. 8, Viale delle Scienze, 90128 Palermo, Italy;2. Dept. of Agriculture, Food and Forest Sciences (SAAF), Università degli Studi di Palermo, Bld. 4, Viale delle Scienze 12, 90128 Palermo, Italy;3. Regional Center for Water Research (CREA), University of Castilla-La Mancha, Carretera de Las Peñas, km 3200, 02071 Albacete, Spain;1. Federal University of Paraíba, Department of Geosciences, João Pessoa, PB, Brazil;2. Federal University of Paraíba, Department of Civil and Environmental Engineering, PB, Brazil;1. School of Engineering, The University of Newcastle, Callaghan, New South Wales, 2308, Australia;2. School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, 2308, Australia;3. School of Natural and Built Environments, University of South Australia, Mawson Lakes, South Australia, 5095, Australia;4. Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt;1. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;2. College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;3. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China;4. CGCEO/Geography, Michigan State University, East Lansing, MI 48823, USA;5. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA;6. Climate and Water Institute, Research Center of Natural Resources, National Institute of Agricultural Technology (CIRN-INTA), Hurlingham, Argentina;7. Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;8. CNR-Institute of Mediterranean Forest and Agricultural Systems, Via Patacca, 85, 80040-Ercolano (Napoli), Italy;9. A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow 119071, Russia;10. Wageningen Environmental Research, Wageningen University and Research, Wageningen, The Netherlands;11. Alfred Wegener Institute for Polar and Marine Research, Telegrafenberg A43, 14473 Potsdam, Germany;12. CSIRO Land and Water, Floreat W.A. 6014, Australia;13. Research Faculty of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan;14. Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland;15. Department of Biological Systems Engineering and School of Natural Resources, University of Nebraska, Lincoln, Nebraska 68583, USA;p. School of Agriculture and Environment, The University of Western Australia, Crawley, WA 6020, Australia;q. School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA;r. Institute of Ecology, University of Innsbruck, Innsbruck 6020, Austria;s. Faculty of Science and Technology, Free University of Bolzano, Piazza Università 5, Bolzano, Italy;t. Physical Geography and Ecosystem Science Lund University Sölvegatan 12, SE-223 62 Lund, Sweden;u. GFZ German Research Centre for Geosciences, Section Remote Sensing, 14473 Potsdam, Germany;v. European Commission, Joint Research Centre, Ispra, Italy;w. Institute of Biometeorology, National Research Council, Via Caproni 8, 50145 Firenze, Italy;x. Department of Ecology, Faculty of Sciences, University of Granada, Granada, 18071, Spain;y. Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-IFU), 82467 Garmisch-Partenkirchen, Germany;z. Centre of Excellence PLECO, Department of Biology, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk, Belgium;1. Department of Civil and Environmental Engineering, Tokyo Institute of Technology, O-okayama, Meguro-ku, Tokyo, 152-8552, Japan;2. Egypt-Japan University of Science and Technology (E-JUST), Environmental Engineering Department, P.O. Box 179, New Borg Al-Arab City, Postal Code 21934, Alexandria, Egypt;3. Irrigation and Hydraulic Engineering Department, Faculty of Engineering, Tanta University, 31734, Tanta, Egypt;4. Water Pollution Research Department, National Research Centre, Giza, 12622, Egypt |
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| Abstract: | Remote sensing techniques allow monitoring the Earth surface and acquiring worthwhile information that can be used efficiently in agro-hydrological systems. Satellite images associated to computational models represent reliable resources to estimate actual evapotranspiration fluxes, ETa, based on surface energy balance. The knowledge of ETa and its spatial distribution is crucial for a broad range of applications at different scales, from fields to large irrigation districts. In single plots and/or in irrigation districts, linking water volumes delivered to the plots with the estimations of remote sensed ETa can have a great potential to develop new cost-effective indicators of irrigation performance, as well as to increase water use efficiency. With the aim to assess the irrigation system performance and the opportunities to save irrigation water resources at the “SAT Llano Verde” district in Albacete, Castilla-La Mancha (Spain), the Surface Energy Balance Algorithm for Land (SEBAL) was applied on cloud-free Landsat 5 Thematic Mapper (TM) images, processed by cubic convolution resampling method, for three irrigation seasons (May to September 2006, 2007 and 2008). The model allowed quantifying instantaneous, daily, monthly and seasonal ETa over the irrigation district. The comparison between monthly irrigation volumes distributed by each hydrant and the corresponding spatially averaged ETa, obtained by assuming an overall efficiency of irrigation network equal to 85%, allowed the assessment of the irrigation system performance for the area served by each hydrant, as well as for the whole irrigation district. It was observed that in all the investigated years, irrigation volumes applied monthly by farmers resulted generally higher than the corresponding evapotranspiration fluxes retrieved by SEBAL, with the exception of May, in which abundant rainfall occurred. When considering the entire irrigation seasons, it was demonstrated that a considerable amount of water could have been saved in the district, respectively equal to 26.2, 28.0 and 16.4% of the total water consumption evaluated in the three years. |
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| Keywords: | Remote sensing Surface energy balance Resampling methods Latent heat flux Irrigation system performance Water saving |
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