PhD : Assimilation of satellite images of soil moisture in a pesticide transfer model in a small agr

Location
France
Posted
Mar 20, 2019
Closes
Mar 20, 2019
Ref
106365
Organization Type
University and College
Hours
Full Time
This thesis topic is placed in the context of improving water quality in small agricultural catchments, through the implementation of buffer zones and landscape adaptation to limit pesticide transfers to the river. The thesis aims to develop a rigorous evaluation framework for an existing model, PeshMelba (PESticides and Hydrology: Scale Modelling of the BAssin Versant, developed in the Poldif team), by developing data assimilation methods to evaluate and reduce its uncertainty on pesticide flows within the watershed. PeshMelba is a modular tool for simulating water and pesticide flows at the scale of the catchment area, according to the different features, and the connections between them. This model is particularly interesting because, due to its modularity and simplified representations, it will eventually make it possible to develop management scenarios with stakeholders to limit surface water pollution by adapting the simulations to each basin studied. However, determining and reducing the uncertainty associated with PeshMelba's results is essential for this type of operational tool. To this end, the combination of the model with in situ observations or images will make it possible to integrate field reality into a physico-conceptual model and to reduce its uncertainty optimally in each context in which it will be used.

The first major part of the thesis will focus on research and methodological development of soil moisture image assimilation (satellite and EM measurements), which is an original and very recent problem in data assimilation. The second part will evaluate this method, and gradually integrate in situ data (pesticide concentrations at the outlet or at certain points in the basin), until the optimal quantity and distribution of these measurements are determined to reasonably reduce model uncertainty. The methods will be tested on the Morcille watershed, on which the team has a very rich database in hydrology and water quality, and which will make it possible to test many hypotheses, in particular on the spatial and temporal availability of the in situ data to be assimilated. However, the thesis will focus on developing a framework for PeshMelba with the condition that it must be applicable and easily adaptable to any change: new watershed, new data, new landscape elements or processes.

Eligibility Criteria
  • Applicants must have a Masters degree or equivalent qualification when the contract is signed.
  • The doctoral student will have an engineering or university degree in applied mathematics and/or environmental sciences, with strong programming skills (Python, R and/or Fortran).
  • Experience and/or sensitivity to environmental protection will be appreciated.