Master thesis - High resolution quantification of seasonal water deficits
Image from OpenET data
Background
Seasonal water deficits, caused by the imbalance of water from the land surface through evapotranspiration and runoff and the gain through precipitation, are an important driver of agricultural productivity and forest growth. Recent research by our group (Stocker et al., 2023) has revealed large spatial heterogeneity of seasonal water deficits across the globe at 5 km resolution - interpreted as a reflection of (otherwise unobservable) rooting zone water storage capacity across the soil and bedrock and of plant access to the groundwater, and as a reflection of water use in cropland areas.
Aim
Novel data resources now provide analysis-ready data at field-scale resolution. This provides an opportunity to extend the analysis of Stocker et al. (2023) to the hillslope-scale. You will develop a workflow to access cloud-hosted Earth Observation data and perform analyses for deriving cumulative water deficits. This will generate crucial insights for a better understanding of the role of terrain in shaping plant water availability and for informing land managers about the sustainability of water resource use.
Requirements
- Most important: High motivation to work on questions related to land-atmosphere exchange and the carbon cycle - everything else can be learned!
- Confidence to work with large datasets of the terrestrial biosphere.
- Experience working with R or other data science tools are an advantage.
- The student writes the thesis in English.
Supervision
- Prof. Benjamin Stocker
