|Vflo provides high-resolution, physics-based distributed hydrologic modeling for managing water from catchment to river basin scale. Improved hydrologic modeling capitalizes on access to high-resolution quantitative precipitation estimates from model forecasts, radar, satellite, rain gauges, or combinations of multi sensor products. Worldwide digital data sets offer tantalizing detail, which Vflo utilizes directly at any resolution.
The advantage of physics-based models is that they can be setup with minimal historical data and still obtain meaningful results. Distributed models better represent the spatial variability of factors that control runoff, and therefore, are more accurate. Finite element solution to the kinematic wave equations is the most efficient solution allowing large systems to be solved quickly on a desktop computer. Days of simulation can be accomplished in just minutes or seconds for large river basins.
||Model input consists of rain-rate maps at any time interval from radar or multi sensor sources. Data input for this model, besides the rainfall input, is derived from various commonly available sources of digital data. Parameters include topography and drainage networks derived from a digital elevation model (DEM), infiltration derived from soils, and hydraulic roughness derived from land use/cover (Landsat). These parameters may be input manually or via ArcView grids.
Radar rainfall and Vflo modeled runoff at the same time step over an 8000 square kilometer area may be viewed at the following link:
DISTRIBUTED RAINFALL AND DISTRIBUTED RUNOFF:
Remnants of Tropical Storm Allison.
Predicting flow rate and depth at any location in a watershed is accomplished by the distributed hydrologic model Vflo. Event reconstruction is used to calibrate the model for real-time operation. Radar rainfall, geospatial data, and hydraulic channel characteristics are used to create a powerful tool for continuous flood forecasting, drainage design, hydropower, and water management.
Using the same hydrologic model output, flood-risk in Greenville, NC is shown below.
- Extendable to ungagued rivers
- Parameter input using GIS data sets
- Efficient simulation (days in seconds)
- Finite elements based on digital terrain
- Meaningful prediction without calibration
- Radar, rain gauge, satellite or multi sensor rainfall input
- Forecast flooding using detected and forecasted precipitation
- Scalable from upland watershed to river basin using the same drainage network
- Soils map
- Channel Cross-sections
- Rainfall (Radar, Rain Gauge, Satellite)