Active in situ and passive airborne fluorescence measurements for water stress detection on a fescue field.

Ledflex is a fluorometer adapted to measure chlorophyll fluorescence at the canopy level. It has been described in detail by Moya et al. (2019), Photosynthesis Research. https://doi.org/10.1007/s11120-019-00642-9 . We used this instrument to determine the effect of water stress on the fluorescence of a fescue field under extreme temperature and light conditions through a 12 days campaign during summer in a Mediterranean area. The fescue field formed part of a lysimeter station in "las Tiesas," near Albacete-Spain. In addition to the fluorescence data, the surface temperature was measured using infrared radiometers. Furthermore, "Airflex," a passive fluorometer measuring the filling-in of the atmospheric oxygen absorption band at 760 nm, was installed in an ultralight plane and flown during the most critical days of the campaign. We observed with the Ledflex fluorometer a considerable decrease of about 53% of the stationary chlorophyll fluorescence level at noon under water stress, which was well correlated with the surface temperature difference between the stressed and control plots. Airflex data also showed a decrease in far-red solar-induced fluorescence upon water stress in agreement with surface temperature data and active fluorescence measurements after correction for PS I contribution. Notwithstanding, the results from airborne remote sensing are not as precise as in situ active data.

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users.

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.