Earth Observation-Based Operational Estimation of Crop Water Requirements in a Mediterranean context

Irrigation is essential for global agricultural production and food security since irrigated land represents 20% of the world’s cultivated area but supply about 40% of the world’s food production. Even if agriculture is the greatest consumer of water (it is estimated that over 70 % of global freshwater is consumed by irrigation) and irrigation represents the most important intervention on the hydrological cycle, we have only partial knowledge on the areas irrigated and on the amount of water applied. Currently, agriculture is facing a great dilemma: on the one hand, a growing world population demands more food and biomass. On the other hand, natural re-sources (such as water) are only available in limited quantities and their excessive use often leads to the degradation of ecosystems, which in turn has adverse effects on agricultural production and local livelihoods. Thus, efficient agricultural water management is a major issue that even more involves not only in traditionally water-scarce regions. However, water use rationalization is especially needed for regions suffering from water scarcity and that probably would suffer from water restrictions according to climate change scenarios. The Mediterranean region is one of these ar-eas and is considered of the most prominent “hot spots” in future climate change projection. Here are expected larger warming than the global average and a pro-nounced increase in precipitation interannual variability which will lead to a further re-duction of resources available and to exacerbate the conflicts among users and sec-tors for the use of the resources. To enable sustainable water management two measures are necessary: - Water demand and availability at the regional level must be known to identify possible overuse and adjust water allocation rights. - Adopt intelligent irrigation management, which reduces water losses to the minimum, providing the right amount of water at the right time. The present work demonstrates as in both aspects, investigated the possibil-ity offered by the present Remote Sensing (RS) model and dataset to estimate the Crop Water Requirements (CWR) and the Irrigation Water Requirements (IWR) at dif-ferent temporal and spatial scale. The EO-based FAO-PM method was selected and adopted to estimate in an operative way the CWR using a combination of in situ clas-sical agrometeorological data with optical RS-derived crop biophysical parameters. The application of the method over two different test site and over both herbaceous and woody crops highlighted the necessity of adjustment to consider the actual (and not the potential or standard) status of the crops considering the water deficit condi-tion. The adjusted EO-based FAO-PM, in combination with the use of Sentinel2-derived information (Leaf Area Index and Surface Albedo), demonstrates its ability to retrieve at field scale CWR coherent with the international adopted FAO-PM method. The procedure was then extended to the CWR estimation at the irrigation district scale. Lastly, the retrieved CWR information was used to estimate the extension of the irrigated areas and the irrigation volume applied both at field and irrigation district-scale over the two selected study area