Better irrigation management using the satellite-based adjusted single crop coefficient (aKc) for over sixty crop types in California, USA

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Elsevier B.V.

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Several Surface Energy Balance (SEB) models are currently used to unleash the boundless potential of Geographic Information System (GIS) and Remote Sensing (RS) techniques. Their main output, namely the actual evapotranspiration (ETa), is required for the assessment of water budget at basin, regional and national levels. Still, the lack of the required expertise coupled with sometimes missing input data limits their usage by researchers, policy makers, water managers and farmers. In this study, a novel comprehensive monthly adjusted crop coefficients (aKc) list was produced, in which these coefficients are usually used to retrieve the much-needed ETa using the climate-sensitive reference crop evapotranspiration (ET0). More particularly, the ETa is calculated for more than sixty different crop types present in the Mediterranean-climate California, United States. It is based on the two consecutive years of 2018 and 2019, which were wet and dry, respectively. The Google Earth Engine (GEE) version of the Surface Energy Balance Algorithm for Land-Improved (SEBALI), surnamed SEBALIGEE, with an Absolute Mean Error (AME) of 9.56 mm/month in the study area was used along the annual crop map from the United States Department of Agriculture (USDA). The main results showed that the average monthly aKc values ranged between 0.45 and 1.53. More specifically, October and November presented the lowest aKc values averaged among all crop types with aKc values around 0.76. On the other hand, March, April and June had the largest average aKc values at nearly 1.17. The monthly aKc values of the 60 crops studied in the plain of California, would potentially assist authorities and hydrologists to better calculate the actual monthly plant water consumption, in a simpler way over the upcoming years. © 2021 Elsevier B.V.

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Actual evapotranspiration, Crop coefficient, Surface energy balance algorithm for land-improved (sebali), Water consumption, California, United states, Budget control, Energy balance, Evapotranspiration, Interfacial energy, Remote sensing, Water supply, Geographic information, Irrigation management, Remote sensing techniques, Surface energy balance algorithm for land-improved, Surface energy balance models, Water budget, Agricultural management, Agricultural modeling, Detection method, Irrigation system, Mediterranean environment, Spatiotemporal analysis, Crops

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