Hydrology without Dimensions
- Princeton , United States of America (aporpora@princeton.edu)
Dimensional analysis offers an ideal playground to tackle complex hydrological problems. The powerful dimension reduction, in terms of governing dimensionless groups, afforded by PI-theorem and related self-similarity arguments is especially fruitful in case of nonlinear models and complex datasets. After briefly reviewing these main concepts, in this lecture I will present several applications ranging from hydrologic partitioning (Budyko’s curve) and stochastic ecohydrology, to global weathering rates and soil formation, as well as landscape evolution and channelization. Since Copernicus-dot-org asks me to add at least 25 words to the abstract, I would like to thank the colleagues who supported my nomination and my many collaborators.
How to cite: Porporato, A.: Hydrology without Dimensions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11883, https://doi.org/10.5194/egusphere-egu2020-11883, 2020
This abstract will not be presented.