# Presentation: 882520

## 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

- Conceptual Config

- Cell-to-cell channel routing

- hillslope

**channel**

## Separate Treatment of Fast and Slow Runoff

**HRAP Cell**

## 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 on the basis of 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 on the DEM grid

- (2)  Model pixel slopes are assigned from representative segments (DEM cell) that most closely match either the cell’s cumulative or local drainage area.

- Segment Slopes (m/m)

- Cell slope -> pixel-wise local slopec

- Cell slope -> pixel-wise main slopec

**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. 

## Hillslope and Channel Routing

- Conceptual Framework
- Parameters needed
- How to assign the parameters
- Training provided in workshop 2

## Hillslope Routing

- 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

- Momentum:

- Conceptual
-    Hillslope

- x

- Continuity:

- Kinematic Wave
- Koren et al. (2004)
- Independent routing for each hillslope element
- Only routes fast runoff

**Grid Pixel**

**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)

## Channel Routing

- Momentum:

- x

- Continuity:

- Kinematic Wave
- Koren et al. (2004)
- Routes
- fast runoff from hillslope
- Slow runoff

**Grid Pixel**

- 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 

- Typically qm > 1: faster flood propagation at high flows.
- If qm == 1, channel flow similar to a unit hydrograph with uniform runoff

- Smaller flood delayed

- Larger flood accelerated

- Treating KW 25.4 like UG

- Same q0,qm

- Runoff = 50.8 mm

- Runoff = 12.7 mm

**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

## Parameters Needed

- Hillslope Routing
- Hillslope  (rutpix_SLOPH)
- Roughness (rutpix_ROUGH)
- Drainage Density (rutpix_DS)
- Channel Routing
- Need q0 and qm in Q=q0Aqm
- Two Channel-Flood Plain Models provided
- Rating Curve
- Channel Shape
- Both produced good results in our applications.

## ‘Rating Curve’ Model

- Direct estimation of  *q0* and *qm*
-  at a USGS gauge using measurement data
- Use geomorphologic relationships to derive spatially variable values (see Koren, 2004 for details)
- Parameters
- rutpix_Q0CHN (q0)
- rutpix_QMCHN (qm)

## ‘Channel Shape’ Model

- Assume expoential relationship between top width (B) and depth (H)
- Estimate  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)
- Required parameters
- Rutpix_SLOPC (channel slope)
- Rutpix_ROUGC (channel roughness)
- Rutpix_BETAC (beta factor in                  )
- Rutpix_ALPHC (alpha factor ...)

-  = 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 

## Assign Distributed Routing Parameters

-   Information needed
- Parameters estimated at an outlet pixel
- Drainage area
- Connectivity
- Geomorphologic relationships.  .

*q0*

*qm*

**Extrapolate**

**Estimate**** **

## Validation

**Derive q0 and qm**

- Validate against
- locally derived values

**Extrapolate upstream**

## Validation

**WTTO2**

**TALO2**

- WTTO2 (1645 km2)

- Predicted values **(p)** based on estimates
- for TALO2 (2484 km2) compared with local fits (l)

## Validation

**KNSO2**

**TALO2**

- Predicted values **(p)** based on estimates
- for TALO2 (2484 km2) compared with local fits (l)

- KNSO2 (285 km2)

## Validation

**CAVES**

**TALO2**

- Predicted values **(p)** based on estimates
- for TALO2 (2484 km2) compared with local fits (l)

- CAVES (90 km2)

## Validation

**SPRIN**

**TALO2**

- Predicted values **(p)** based on estimates
- for TALO2 (2484 km2) compared with local fits (l)

- SPRIN(37 km2)

## Customization Procedures (User Manual Chapter 9)

- Determine outlet pixel
- XDMS
- Update Connectivity to incorporate this outlet
- Adjust cell areas to match USGS drainage area
*cellarea*
- Download USGS flow measurement
- Derive routing parameters for a given outlet
- Interactively using a R script
- Distribute values to upstream grids
- genpar

## Determine Outlet pixel 

- Connectivity on grid scale can be inaccurate
- Can not rely on proximity between USGS outlet coordinate and HRAP location itself
- Visual inspection is needed
- Finer resolution grid helps improve accuracy

## 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

## Adjust Cell Areas

- 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.**

## Add Outlet to Connectivity

- Change this number when adding outlets

- User defined header lines

## Obtain USGS Flow Measurements

- Several times a year, USGS provides measurements of
- Discharge
- Cross-sectional Area (wetted)
- Width
- Depth

## 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"**

## R Scripts Provided to Assist with Flow Measurement Analysis

**Notes:**
This replaces rmsmaster.xls

## R Scripts for Deriving Routing Parameters

-   Outletmeas_manual.R
- Reads USGS measurements
- Assigns weighting factors according to discharge
- To better match the results at high flows during regression
- Perform weighted regression for
- Rating Curve method (Q ~A)
- Channel Shape method (A~B)
- Generate plots
- Enable user to make adjustments
- Derived parameters are saved to a file for later use

**Notes:**
This replaces rmsmaster.xls

## Distribute Parameters Upstream using Genpar

- Features of Genpar
- Needs a base grid
- Modifies the entire area upstream of an outlet
- Able to handle multiple outlets

- Assign values to entire upstream area

- Overwrite values for sub-basins

**Notes:**
This replaces rmsmaster.xls

## 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