Skip to main content
SLU:s publikationsdatabas (SLUpub)

Sammanfattning

This python code estimates ecohydrological parameters that best fit empirical soil saturation probability density functions through Bayesian inference using a stochastic soil water balance framework. For methods description see: Bassiouni, M., C.W. Higgins, C.J. Still, and S.P. Good (2018), Probabilistic inference of ecohydrological parameters using observations from point to satellite scales. Hydrology and Earth System Sciences, 22(6), pp.3229-3243. https://doi.org/10.5194/hess-22-3229-2018. For results from a global application see: Bassiouni, M., S.P. Good, C.J. Still, and C.W. Higgins (2020), Plant water uptake thresholds inferred from satellite soil moisture. Geophysical Research Letters. 47(7), e2020GL087077. https://doi.org/10.1029/2020GL087077 Global dataset of ecohydrological parameters inferred from satellite observations (2020) https://doi.org/10.5281/zenodo.3351622

Publicerad i

Utgivare: Zenodo

SLU författare

  • Bassiouni, Maoya

    • Oregon State University

UKÄ forskningsämne

Oceanografi, hydrologi, vattenresurser

Publikationens identifierare

  • DOI: https://doi.org/10.5281/zenodo.1257718

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/105936