dr. CCE (Cynthia) van Leeuwen

dr. CCE (Cynthia) van Leeuwen

Postdoctoral researcher

Current research

Cynthia is a postdoctoral researcher on the ReGeNL project. ReGeNL is a collaboration of more than 50 organisations working together to transform the Dutch agricultural sector into a regenerative, sustainable, and future-proof industry. ReGeNL aims to develop feasible regenerative business models with a group of pioneering farms by 2030, and facilitate the transition to regenerative agriculture for at least 1,000 farmers across five regions within the Netherlands. Additionally, ReGeNL seeks to implement educational innovations focused on regenerative agriculture, ensuring that at least 10,000 (future) farmers, advisors, and employees of the supply chain and regional organizations are trained by 2030.

Within ReGeNL, Cynthia researches how different regenerative practices impact soil, hydrology, nutrient cycling and biodiversity on a field, farm and regional level. Field data, unmanned aerial vehicles (UAV) and satellite imagery will be used to quantify the effects.

Past

Cynthia has completed the master Earth Sciences at the University of Amsterdam, following the research track Geo-Ecological Dynamics. She did her MSc thesis in collaboration with the University of Basel, where she has looked into the physical properties of wind erosion, i.e. the threshold friction velocity for PM10 dust emission, while comparing two instruments; a traditional straight-line wind tunnel and a new device, the Portable In-Situ Wind Erosion Lab (PI-SWERL).

Cynthia has completed her PhD thesis, titled ‘Statistical modelling of analytical and spectral soil measurement errors’, in 2024 at ISRIC and Wageningen University. In this thesis, analytical and spectral measurement errors in soil data were quantified, emphasizing the importance of informing data users about these errors before calibrating and validating models. Measurement errors propagate through soil models and can drastically reduce model performance and prediction uncertainty. In this thesis, the sensitivity of widely employed models within the soil science community to analytical and spectral measurement errors was studied.