Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors
This repository mainly contains a juypter notebook as well as the required data to reproduce the results of a manuscript submitted to Hydrology and Earth System Sciences. The manuscript is entitled "Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors" and documents the very first analysis of observations collected by the Cosmic Sense research consortium in a campaign in summer 2019 which features a dense network of CRNS sensors (see Fersch et al. 2020).
The jupyter notebook jfc1-analsis.ipynb contains the analysis code as well as the code to reproduce the manuscript figures. The directory data contains the required data to run the code. A directory figures needs to be created where the figures will be stored that are generated by the notebook. The file jfc1table.csv contains a set of metadata for the CRNS sensors, the file calibration_summary.csv contains some sensor-specific study results.
The main dependencies required to run the notebook are numpy, scipy, matplotlib, pandas, wradlib, and the cosmicsense package. We recommend conda for dependency management.