The Dep. of Computational Hydrosystems (CHS) presents:
- Samaniego L., R. Kumar, S. Attinger (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46,W05523, doi:10.1029/2008WR007327.
- Kumar, R., L. Samaniego, and S. Attinger (2013): Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations, Water Resour. Res., 49, doi:10.1029/2012WR012195.
Cite the code:
- Luis Samaniego et al. (2017), mesoscale Hydrologic Model, doi:10.5281/zenodo.1069202.
In the course of 2018, we are planning to migrate our development repository from the SVN to the GitLab. For the time being, please develop your code in the SVN repository. Code developments in the Git environments will not be incorporated into the SVN repository. Access to the SVN repository can be granted through the registration form. Our repository on GibHub.com will be always a mirror of the current release at GitLab.
Developers that contribute to the code will be incorporated into the list of authors and will appear in the DOI of the next mHM version.
Git environments allow now to report bugs or issues publicly. Use for example the issue tracking system on GitHub.com.
As a member of the mHM community, you will have access to the SVN repository and the current release of mHM.
Publications using mHM
The mesoscale hydrologic model (mHM) developed by our group is a spatially explicit distributed hydrologic model that uses grid cells as a primary hydrologic unit, and accounts for the following processes: canopy interception, snow accumulation and melting, soil moisture dynamics, infiltration and surface runoff, evapotranspiration, subsurface storage and discharge generation, deep percolation and baseflow and discharge attenuation and flood routing.
The model is driven by hourly or daily meteorological forcings (e.g., precipitation, temperature), and it utilizes observable basin physical characteristics (e.g., soil textural, vegetation, and geological properties) to infer the spatial variability of the required parameters. To date, the model has been successfully applied and tested in more than 300 Pan EU basins, as well as India, and USA, ranging in size from 4 to 550,000 km2 at spatial resolutions (or grid size) varied between 1 km and 100 km. Shown below is the model performance for stream flow simulations over the EU basins.