The VIC Model
Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. VIC (Liang et al., 1994) is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as being applied globally.
VIC shares several basic features with the other land surface models (LSMs) that are commonly coupled to global circulation models (GCMs):
- The land surface is modelled as a grid of large (>1km), flat, uniform cells Sub-grid heterogeneity (e.g. elevation, land cover) is handled via statistical distributions.
- Inputs are time series of daily or sub-daily meteorological drivers (e.g. precipitation, air temperature, wind speed)
- Land-atmosphere fluxes, and the water and energy balances at the land surface, are simulated at a daily or sub-daily time step
- Water can only enter a grid cell via the atmosphere
- Non-channel flow between grid cells is ignored
- The portions of surface and subsurface runoff that reach the local channel network within a grid cell are assumed to be >> the portions that cross grid cell boundaries into neighboring cells
- Once water reaches the channel network, it is assumed to stay in the channel (it cannot flow back into the soil)
- Non-channel flow between grid cells is ignored
The VIC model is distributed under the GNU GPL v2.0 license. If you make use of this model, please acknowledge the appropriate references listed on the references page. Development and maintenance of the current official version of the VIC model is conducted at the University of Washington, Department of Civil and Environmental Engineering, under the direction of Bart Nijssen. Every new application addresses new problems and conditions which the model may not currently be able to handle, and as such the model is always under development. The VIC model is an open source develment project, contributions from outside the University of Washington Land Surface Hydrology Group are welcome. Archived, current, beta, and development versions of the model are available via the group's GitHub repository.
Ocean-Land-Atmosphere Model (OLAM)
OLAM is a global nonhydrostatic weather and climate prediction model that has been developed since 2001. It is an outgrowth of the Regional Atmospheric Modeling System (RAMS), which was developed for investigating meso- and cloud-scale phenomena. OLAM incorporates all of the physics schemes from RAMS, and is thus equipped for atmospheric simulations at very high resolution. The major improvement over RAMS is OLAM's dynamic core and computational grid that accommodates the entire globe while enabling local refinement in targeted regions of interest or significance. Thus, OLAM combines the advantages of global models and high resolution regional models into a single fully-interactive framework.
OLAM employs an unstructured mesh of either hexagonal or triangular grid cells based on refinement of the icosahedron, thus avoiding the polar singularities of the more traditional latitude-longitude grid. More importantly, this mesh configuration provides a natural adaptibility for local mesh refinement that is completely seamless, requiring no special grid nesting algorithm. Local mesh refinement in OLAM is gradual, with less than 25% reduction in size from one grid cell to the next. This reduces reflections that can occur in conventional grid nesting schemes where resolution changes suddenly. OLAM uses a finite volume discretization of the fully compressible Navier-Stokes equations, and does not make the shallow-atmosphere approximation. Topography is represented using a form of the volume-fraction or cut grid cell method in which model levels are strictly horizontal, rather than terrain-following, and therefore intersect topography. This topographic configuration eliminates well-known problems of terrain-following coordinates with complex topography.
Nebraska’s progressive administration of water resources NRDs lack of a system that:
- Allow users to expedite data uploading and access, and allow them to produce more informed decisions
- Integrate data and information across NRDs and with DNR
The WaFIS project is has the goal to integrate water and crop data collected from small-to-big farmers with climate data publicly available to develop a system that provides standardized information to farmers in their NRDs, and mechanisms for data and information exchange.
Interoperability is the ability of two or more systems or components of software to exchange and use information.
Data collection system
Benefit farmers within an NRD, INTEGRATING farmer-to-regional data and information
- Development of manual and web questionnaires to obtain NRDs’ requirements of water, crop, and climate data and information
- Characterization of data and their uploading mechanisms
- Format, frequency, and coverage
- Digitalization, mobile application, webpage uploading
Data standardization and storage
Enable farmers, agencies, and academicians to DIAGNOSE water- and agriculture-resources and CREATE more informed decisions
- Design and develop software mechanisms to filter and consolidate databases
- Characterization of extracted databases to select metadata standards from OCG
- Design and develop software to drive store-operation mechanisms in the system
- Cataloging and storing water- and agriculture-resources databases
Development of data and information exchange software
Provide easy-access to multiple sources of information, SUPPORTING research, teaching, decision-making, and policy-making
Design and development of software including:
- An interface to access datasets by user
- Mechanisms to communicate external and internal data requests (in automatic and manual forms)
- Techniques to display information enabling the interaction user-database and with interfaces for the (requested) data visualization