PhD opportunities

Uncertainty reduction and risk estimation for landscape evolution models

Thesis proposal

Area of expertiseGéosciences et géoingénierie
Doctoral SchoolGéosciences, Ressources Naturelles et Environnement
Research unitCentre de Géosciences
Keywordsgeomorphology, landscape evolution models, soil erosion, sediment transport, extreme climatic events
AbstractExtreme climatic events such as heavy rainfall or periods of drought can induce changes in the landscape morphology and soil composition. In particular, they can cause mudslides, soil depletion or silting up of watercourses in the absence of suitable facilities, and it thus appears crucial to anticipate and prevent them.
Landscape evolution numerical models can help in the management of these risks. They aim to mimic the primary physical processes at various scales in time and space and can provide predictions for the future dynamics in hydrographic basins. Some of the main difficulties in obtaining reliable predictions are the
complexity of the input parameters, such as spatial variability of soil characteristics, and the uncertainty in the physical laws upon which landscape evolution models are developed. Furthermore, observations available to
characterize these parameters such as rainfall and fluxes can be sparse in space and time. However, only a
handful of studies have explored the fundamental problem of uncertainty for landscape evolution models. The
objective of this PhD is therefore to develop a new efficient and relevant workflow for model calibration on
available data and estimation of the future basin dynamics and associated uncertainties in relation to climatic
hazards. The developed approaches will be based on existing methodologies for sensitivity analysis,
optimization and uncertainty propagation that will be adapted to the context of landscape evolution modeling.
The PhD will focus on the Canche watershed (Hauts-de-France) where there is a notable risk of soil depletion
and mud floods, and a wealth of observations from on-going projects in collaboration with Mines Paris - PSL and IMT Nord Europe.
ProfileUniversity Master degree in Landscape evolution modelling
FundingConcours pour un contrat doctoral