Post-doctoral researcher: crop growth models remote sensing data assimilation for irrigation management
Date added: 29 July 2019
Organization: University of Tuscia
Location: Rome, Italy
The goal of the research that will be carried out by the candidate is the development and/or improvement of algorithms exploiting satellite data for assimilation into crop growth models in support of irrigation management. The work is carried out within the international ERANETMED project "Real time soil moisture forecast for smart irrigation" (RET-SIF) with partners from Italy, France, Morocco, Spain and China.
Crop models will be employed to determine the crop development stage and yield according to water availability, irrigation practices and crop types. The models employed will include a recently released open-source version of Aquacrop (Foster et al., 2017), and the Simple Algorithm for Yield prediction, SAFY.
These models will be calibrated and validated over the different case studies areas. The models will be coupled to a hydrological model and remote sensing data assimilation procedures (LAI, LST) will be implemented for sharing pixel soil moisture, biophysical variables retrieved from remote sensing and meteorological data between crop and soil water balance modelling.
The initial appointment in for 1 year but renewable for 1 additional year (or possibly more).
Eligibility and desired competences:
Deadline for application: 10 August 2019.
The interested applicants should get in touch as soon as possible with Prof. Raffaele Casa (firstname.lastname@example.org) to arrange a preliminary informal interview (Skype) sending a CV and motivation letter with contact details of 2 reference persons.
If the interest is confirmed, a formal application should be submitted according to the call published in the University of Tuscia website. Detailed instructions on how to apply will be given directly to the perspective applicants after they get in touch.