Skip to content

Tracking the raindrop from the sky to the summit to the sea...

Summit... model and modify

From the headwaters of the Tar River on the Piedmont plateau to the Pamlico Sound, water quantity and quality will be monitored and predicted using an ensemble of high-resolution models. Each model will create its own unique streamflow simulation dependent on channel characteristics, soil type, the slope of the land, and vegetation patterns. These simulations will be input into CI-FLOW water quality models to provide forecasters multiple solutions regarding timing and river discharge for multiple forecast points in the basin. Improved information on water quantity and quality is critical to Tar River hydrologic hazard mitigation programs.
Ensemble of hydrologic and hydraulic models to simulate streamflows

Goal: Demonstration of CI-FLOW streamflow ensemble, including water quality and quantity information

Existing CI-FLOW ensemble members:

Current Status:

Model Calibration

Once a model is selected, it must be calibrated for a watershed (James and Burges, 1982). Calibration is widely recognized as a critical step in the application of any hydrologic or channel routing model. This year we will focus on the calibration of HL-RMS and FLDWAV. As seen in the purple boxes in Figure 1, the models are major components of the CI-FLOW system. Implicit in the process of calibration is the collection, quality control, and formatting of all data needed for the calibration process.

HL-RMS takes the gridded rainfall observations from QPE-SUMS and converts the rainfall to runoff and streamflow in each grid. Runoff and streamflow from each grid move down hill to the next grid, eventually making their way to the main Tar River channel below Tarboro. For HL-RMS, calibration involves deriving the best values of the model parameters in each of the grid cells in the Tar River basin. Here, initial parameters describing the type of soils, the slope of the land, and the type of vegetation must be specified. HL-RMS assumes each grid cell contains a river, so the size, shape, and flow resistance of the river must be numerically described. In calibration, these initial parameters are adjusted until the computed flows agree with observed flows measured by the US Geological Survey. Calibration of distributed models is an active area of research. In NOAA’s NWS method, traditional methods of hydrologic model calibration (Smith et al., 2003) are combined with emerging techniques to adjust the parameters in each grid cell.

Determine Statistical Biases for HL-RMS

The Hydrometeorology Group of HL will analyze the precipitation input to HL-RMS as necessary during the hydrologic model calibration process. Such an analysis might be necessary to determine if statistical biases in the precipitation fields emerge or change during the calibration period. The analysis will be a thorough comparison with an independent set of reference rain gauge reports.

FLDWAV Connectivity and Calibration

FLDWAV takes all of the runoff and streamflow generated by HL-RMS and routes the combined inflows through the Tar River system which includes the Tar River from Rocky Mount, NC to the head of the Pamlico Sound and all of its major tributaries within the routing reach. Water levels and discharges are generated at all locations in the river system for all times. In addition, the computed river levels can be used to generate flood inundation maps.

In order to calibrate the river system, FLDWAV requires the following information (Sylvestre et al., 2002): the river system defined based on hydraulic conditions; inflows; observed river levels and discharges (if available) at the gage locations; channel roughness represented by Manning; cross section data representing the topography; and a description of any critical hydraulic structures (.e.g., dams, bridges, levees) in the river system. Rivers with significant backwater and/or significant attenuation due to storage will be modeled dynamically, while rivers that simply add to the flow will be modeled as lateral inflow. Topographic information will be obtained from LIDAR-based Digital Elevation Model data. The roughness coefficients will be adjusted until the difference between the computed and observed water level time series has been minimized at each gage location. To ensure the correct volume is maintained in the river system, the relationship between the effective and inactive storage will be adjusted until the difference between the computed and observed discharges is minimized. The FLDWAV parameters will be calibrated for both record high flows and low flows to ensure model stability when running operationally. They will be verified with an independent flood.

Since the hydrologic and hydraulic model calibrations will be done concurrently, discharge and water level data will be obtained from the USGS and NWS archives. After the calibrations have been completed, inflows from HL-RMS will be used. An assessment will be done to determine the best way to represent the gridded inflows in FLDWAV.

Assessments/Case Findings

NWS FY07 H-OSIP
NWS FY08 AHPS
NC/SC Sea Grant
NWS Operational Verificatio

Feedback

Operational
Citizen