# Presentation: 388228

## Overland and Channel Routing in the Distributed Model 

- Lecture 4a

- Yu Zhang

## Outline

- Conceptual model
- Parameter estimation
- Connectivity
- Slopes
- Channel hydraulic properties
- Local customization steps

## Routing Model

- Real HRAP
- Cell

- Hillslope
- model

- Cell-to-cell channel routing

## Separate Treatment of Fast and Slow Runoff

## HRAP Cell-to-cell Connectivity Examples

- ABRFC ~33,000 cells

- MARFC ~14,000 cells

-  OHD delivers baseline HRAP resolution connectivity, channel slope, and hillslope slope grids for each CONUS RFC
-  HRAP cell-to-cell connectivity and slope grids are derived from higher resolution DEM data.

**Notes:**
Strategy – pre-derive separate complex pre-processing schemes from hydrologic simulation.  Simple framework.
Using the same resolution grid as the available rainfall grids makes sense.  

Would like to work from the most accurate DEM hydro derivatives available.  

## Representative Slopes Are Extracted from Higher Resolution DEMS

- (North Fork of the American River (850 km2))

- Slopes from 30-m DEM

- Hillslope Slope (1/2 HRAP Resolution)
- Average = 0.15
*Slopes of all DEM cells within the HRAP pixel are averaged.*

- Main Channel Slope (1/2 HRAP Resolution)
- Average = 0.06
*Channel slopes are assigned based on a representative channel with the closest drainage area.*

- Local Channel Slope (1/2 HRAP Resolution)
- Average = 0.11

- Slope (m/m)

## Main Channel Slope vs. Local Channel Slope

- Slopes of each stream segment are calculated from the DEM

- (2)  Model cell slopes are assigned from representative segments that most closely match either the cell’s cumulative or local drainage area.  In this case, the slope of segment A is taken as the ‘main’ channel slope and slope of segment B is taken as the ‘local’ channel slope.

- Segment Slopes (m/m)

**Notes:**
Note that these algorithms are used to preprocess data delivered with HL-RDHM.  The algorithms themselves are not yet ‘delivered’ as either LAD or AWIPS partly because they rely on Arc/Info Grid software. 

## Channel Routing Model

- Uses implicit finite difference solution technique
- Solution requires a unique, single-valued relationship between cross-sectional area (A) and flow (Q) in each grid cell (Q=q0Aqm)
- Distributed values for the parameters *q0* and *qm* in this relationship are derived by using
-  USGS flow measurement data at selected points
-  Connectivity/slope data
-  Geomorphologic relationships
- Training on techniques to derive spatially distributed parameter grids is provided in this workshop

## Kinematic Wave Equations Solved by HL-RDHM:

- Hillslope Flow
- Koren et al. (2004)

- q = discharge per unit area of hillslope
- h = average overland flow depth
- Rs = fast runoff from water balance
- Sh = hillslope slope
- nh = hillslope roughness
- D = drainage density
- Lh = hillslope length

- (continuity)

- (momentum)

- Conceptual
- Hillslopes
*(higher D = more hillslopes and faster response)*

**Notes:**
1-d Equations assume that the spatial variations in velocity across the channel and with : a suitable assumption for many practical applications.  
Newton’s second law:  Sum of the forces is equal to the time rate of change of momentum

This version neglects numerous terms in the momentum equation (e.g. momentum from lateral inflow, wind shear, eddy losses, etc)

## Kinematic Wave Equations Solved by HL-RDHM:

- Channel Flow
- Koren et al. (2004)

- ‘Kinematic’ wave solution assumes slope dominates all other forces (e.g. inertial (rapid changes), pressure, wind, tides)

- (continuity)

- (momentum)

- Q = channel discharge
- A = channel cross-sectional area
- qLh = overland flow rate at the hillslope outlet
- Rg = slow runoff component from the water balance
- Fc = grid cell area
- Lc = channel length within a cell

**Notes:**
1-d Equations assume that the spatial variations in velocity across the channel and with : a suitable assumption for many practical applications.  
Newton’s second law:  Sum of the forces is equal to the time rate of change of momentum

This version neglects numerous terms in the momentum equation (e.g. momentum from lateral inflow, wind shear, eddy losses, etc)

## Kinematic Wave vs. Unit Hydrograph 

-   If (qm != 1), channel velocity will vary with flow level (linear superposition does not apply).
-   Typically qm > 1, resulting in faster flood propagation at high flows.
- If qm == 1, channel flow behavior would be similar to a unit hydrograph in the case of uniform runoff (overland flow velocity can still be flow dependent).

- Smaller flood delayed

- Larger flood accelerated

- Treating KW 25.4 like UG

- Same q0,qm

**Notes:**
Although we are initially focused at the HRAP grid cell scale, methods are generally enough to apply to other types of modeling units

23907 cfs

## Two Simple Channel-Flood Plain Models are

- Available in HL-RDHM

-   The ‘Rating Curve’ model estimates the parameters *q0* and *qm* directly for each model cell using hydraulic measurements at an outlet gauging station, cell drainage areas, and geomorphologic relationships.
-   The ‘Channel shape’ method assumes a simple parabolic channel geometry and uses outlet hydraulic measurements, cell drainage areas, slopes, the Chezy-Manning equation, and geomorphologic relationships to estimate *q0* and *qm* for each cell.
-   Both models have produced good results in our applications.

*q0*

*qm*

## ‘Channel Shape’ Model

- Assume simple relationship between top width (B) and depth (H)
- Solve for  and  at a USGS gauge using streamflow measurement data
- Use geomorphologic relationships to derive spatially variable a values (see Koren, 2004 for details)
- Compute q0 and qm as a function of  and , channel slope (Sc) and channel roughness (nc)

-  = 1

-  < 1

-  > 1

-  = 0

**Notes:**
Note: what are the limits on qm using this model
If b = 1, qm = 1.3333
If b=0, qm = 1.6666  -- this is a rectangular channel
Ib b = infinite, qm approaches 1.  This means that for a very wide channel the velocity tends to become insensitive to flow rate 

## ‘Rating Curve’ Model

- Solve for *q0* and *qm* at a USGS gauge using streamflow measurement data
- Use geomorphologic relationships to derive spatially variable a values (see Koren, 2004 for details)

## Model

- WATTS (1645 km2)

- KNSO2 (285 km2)

- CAVESP (90 km2)

- SPRINGT (37 km2)

- Model predicted relationships **(p)** at points upstream from TALO2 (2484 km2) compared with local fits (l)

**Model**
**Validation**

## Routing Parameter Grids

- Default grid values:
- rutpix_ALPHC:  -1 (nodata)
- rutpix_BETAC:  1
- rutpix_DS:  2.5
- rutpix_Q0CHN:  -1 (nodata)
- rutpix_QMCHN:  1.333
- rutpix_ROUGC:  -1 (nodata)
- rutpix_ROUGH:  0.15

- Rutpix7 = ‘channel shape’
- Rutpix9 = ‘rating curve’

## Routing Parameter Customization Procedures (User Manual Chapter 9)

- Determine best HRAP cell to represent basin outlet (XDMS)
- Add outlet to connectivity file header
- Adjust cell areas so the total drainage area matches USGS area (*cellarea* program)
- Download measurement data from USGS NWIS site
- (optional) Use *preprocess.R* to parse USGS flow measurement data for multiple stations into separate files
- Use *outletmeas_manual.R* to analyze station data
- Use *genpar* utility program to generate grids

## Model Resolution and Basin Size Considerations

- HRAP Cell Connectivity

- Percent errors in representing basins with 4 km resolution pixels.
-   Open squares represent errors due to resolution only.
-   Black diamonds represent errors due to resolution and connectivity.
-   **We correct for these errors by adjusting cell areas in the model so that the sum of the model cell areas matches the USGS reported area at the basin outlet.**

## HRAP vs. 1⁄2 HRAP Implementation

- 1

- 2

- 3

- User must choose which cell is the best outlet for this basin.

- Gauge Name

- Area (km2)

- ID

- 4 km resolution does not allow accurate selection of an outlet for this subbasin because

- 2 km resolution allows more accurate delineation

## Connectivity File Example

- Change this number when adding outlets

- User defined header lines

## Outletmeas_manual.R:  Additional Plots

- Q vs. A for Two Methods

## R Scripts Provided to Assist with Flow Measurement Analysis

-   Outletmeas_manual.R automatically generates several plots and computes reqressions
-   User can specify plotting and regression weight options
-   Derived parameters are saved to a file for later use

**Notes:**
This replaces rmsmaster.xls

## Outletmeas_manual.R User Options

- #---(1)--- input file name
- file.list<-"/fs/hsmb5/hydro/users/sreed/flow_measurements/dmip2/talo2meas3_29_07.d"
- #---(2)--- user specified weight exponent for regression
- Qwt.qa<-1  # for Q-A
- Qwt.ab<-1  # for A-B
- Qwt.n <-1  # for Manning's n
- #---(3)--- User specified relative weights for each of the USGS data quality flags
- ws<-c(1,1,1,1,1)
- #---------------------------------
- # Code  Description
- # ---------------------------------
- # E     Excellent       the data is within 2% (percent) of the actual flow
- # G     Good            the data is within 5% (percent) of the actual flow
- # F     Fair            the data is within 8% (percent) of the actual flow
- # P     Poor            the data are not within 8% (percent) of the actual flow
- # -1    Missing
- # The ws vector is ordered as above c(E,G,F,P,-1)
- #---(4)--- graph options
- plot_quality=T
- new_graphics=T
- #---(5)--- info for the channel shape method
- slope=0.002
- #reread_data=TRUE
- #--- (6)---  output file names
- file.out<-"param.final.d"

## Genpar Input Deck

- #genpar.card
- #enter the connectivity file name
- connectivity = /fs/hsmb5/hydro/users/zhangy/RDHM/Genpar/sequence/abrfc_var_adj.con
- #specify an input location for parameter grids
- input-path   =  /fs/hsmb5/hydro/rms/parameterslx/abrfc
- #specificy an output location
- output-path = /fs/hsmb5/hydro/users/zhangy/RDHM/Genpar/output
- #replace/update the existing grid or output the grid to the output-path, true or false
- #
- overwrite-existing-grid = false
- #
- #create a new grid instead of modify existing grid, the boundary in this
- # case is the boundary of all selected basins, true or false
- create-new-grid = true
- #
- #if the create-new-grid is true, the grid will be created in this window.
- #if this window is not consistent with the window from the connectivity,
- #the windows are combined into a big window that contains both subwindows.
- #window-in-hrap =   480   505  298     306
- #
- # Name of the parameter to be created, available names are:
- # slopc   rougc   betac  alphc  sloph   ds   rough   Q0CHN   QMCHM
- # They are case insensitive
- #genpar-id = slopc
- #genpar-id = rougc
- #genpar-id = alphc
- #the next line specifies the parameter for which values will be generated
- genpar-id = q0chn
- #genpar-id = qmchn
- #next line is an example input information for q0chn grid generation
- genpar-data = TALO2 0.31  1.2

- Table 9.3 tells you what to put here

## Required Arguments for Grid Generation

| No. | genpar-id | Arguments | Comments |
| --- | --- | --- | --- |
| 1 | SLOPC | 0.178 1.23 | Use defaults |
| 2 | ROUGC | no 0.272 -0.00011 | The user should specify the first argument and use defaults for arguments 2 and 3.  |
| 3 | BETAC                       | Betac |  |
| 4 | ALPHC                       | -1   Ao  alphac | Enter -1 for the first argument since it is no longer used.  Ao is a representative cross sectional area at the outlet. |
| 5 | SLOPH                        | constant | Typically, this option is not needed since reasonable values of SLOPH can be derived from the DEM. |
| 6 | DS                                | Constant |  |
| 7 | ROUGH                       | Constant |  |
| 8 | Q0CHN | q0chn  qmchn |  |
| 9 | QMCHN | qmchn |  |

**Condensed Table 9.3**