Mehdi’s research interests are in the field of remote sensing and hydrological modelling.
He is particularly interested in using different hydro-meteorological variables (e.g., precipitation, soil moisture) in a combination with remote sensing and crop models to analyse the interactions between climate variability and vegetation conditions.
Mehdi’s current research aims to study the plant responses to changing temperatures and in particular investigate how different genotypes may be differentially affected by climate change.
Within this framework, he validates existing crop prediction approaches that can adequately capture yields based on historic datasets.
Mehdi uses the state-of-the-art software, ApSim, with the canola model to run through historical weather data and evaluate how well this crop model matches available yield data.
Moreover, based on the goal of his ongoing research, he works on developing strategies for capturing how genotypes (initially, different FLC combinations) can influence the process-based module outputs.
Within this scope, Mehdi generates artificial data from the FLC model and compute the vernalization requirement and flowering. Consequently, he use the optimised ApSim model to study the causes of current yield instability in the important crop Brassica napus (canola, rapeseed) and analyse the short- and long-term impacts of expected changes in climate on the European winter rapeseed crop.