Extremely dry and hot summers will become more frequent in Switzerland and will change water availability, so a better understanding of soil moisture patterns is needed. The project SMURF aims to improve soil moisture mapping and monitoring, which is crucial for understanding climate and ecosystem dynamics in Swiss forests. SMURF will focus on grassland-forest transitions and reveal microclimatic soil moisture patterns. It will fill gaps in existing climate grids by integrating in-situ observations, vegetation structure, and novel radiative transfer modeling. The project addresses the lack of microclimate mapping for soil moisture and aims to provide comprehensive monthly soil moisture maps at a 5-meter resolution. These maps will improve drought monitoring and inform climate resilience strategies. The successful candidate will help coordinating a soil moisture measurement campaign and combine these measurements with spatial predictor variables to develop and apply a predictive model for soil moisture.
You hold a PhD in meteorology, hydrology, environmental sciences, or a related field. Further, you have a strong background in spatial mapping using, amongst others, machine learning methods and excellent programming skills in R or Phyton. Additionally, you are experienced in handling and interpreting environmental datasets such as soil moisture measurements. Good skills in scientific writing are essential. You are committed, accustomed to working independently with a high standard of structure and attention to detail, and you possess a high level of self-motivation and strong team spirit.