# Presentation: 694615

## Where to Apply Distributed Models

- DHM/HL-RDHM Workshop
- ABRFC
- June 7, 2007

- Mike Smith
- OHD/HL
- Hydrologic Science and Modeling Branch

## Where to Apply Distributed Models

- 1.  Use *with*, not *instead of* lumped model
- 2.  Use when need high resolution information and forecasts
- Customer requests for products
- Land use changes
- 3.  Use to improve outlet forecasts:
- Account for
- Spatial variability in basin features
- Spatial variability in forcings
- Basin shape
- Basin response

**Notes:**
For item 3, lets also consider one other very valuable thing....

## Where to Apply Distributed Models

***Use your experience and judgment ***
***as a forecaster!!!***

## Model Application SpectrumHypothetical Use within WGRFC Operations

- Lumped

- DHM

**Influencing factors**

- model ensemble tool?

**basin type**
**basin response**
**basin shape**
**rainfall distribution**
**flow volume**

- Source: Paul McKee WGRFC; DSST presentation Feb., 2006

**headwater**
**fast**
**irregular**
**non-uniform **
**small**

**mainstem**
**slow**
**regular**
**uniform **
**large**

## Basin Shape:   Case 1

**Notes:**
These figures illustrate the processes performed on each grid:
Upper Left:  Each cell has its own unique parameters
 Upper Right:  Each cell has its own precipitation input
 Lower Left:  Each cell generates runoff
 Lower Right:  Runoff flows from cell to cell to the outlet.

## Use with, not 

**Hydrograph at Location A**

**Hydrograph at Location B**

**Hydrographs at Basin Outlet**

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**Flow (CMS)**

***B***

***A***

- Distributed
- Lumped
- Observed

- Flow (CMS)

- Use *with*, not
*instead *of lumped
- model

- Basin Shape:   Case 1

**Notes:**
Title of talk mentions ‘improved river forecasting’  This slide illustrates two types of  improvements.

A distributed model can be used to simulate processes at points inside the basin. The lumped model is only able to give a simulation at the basin outlet. 
In this example, very little rain fell on the upper part of the basin.  There is no streamflow response at point A.  Small amounts of rain fell in the middle of the basin, so the streamflow does show a small response at point B.
The heaviest rain fell in the lower part of the basin. The lumped simulation shows the effects of averaging over the whole basin.  It underestimates the peak and is delayed.   The distributed model is able to capture the spatial variability of the precipitation and produce a more reasonable simulation. 

## Basin Shape: Case 2 - XDMS Plots of Radar Rainfall

- July 1, 1999 event.  Rain fall on 6/30/99 hours 10,11,12, and 13

**T=10**

**T=12**

**T=11**

**T=13**

**Notes:**
XDMS is a tool you can use now!!!

## Basin Shape:   Case 2

- observed

- lumped

- distributed

## Preliminary Study ConclusionsBenefits of DHM at WGRFC

- Timing of rising limbs well-simulated (variety of DAs and spatially distributed QPE)
- Outperforms lumped model for ***irregularly shaped basins***
- Full utilization of gridded QPE

- Source   Paul McKee, DSST  presentation February, 2006

## Model Application SpectrumHypothetical Use within WGRFC Operations

- Lumped

- DHM

**Influencing factors**

- model ensemble tool?

**basin type**
**basin response**
**basin shape**
**rainfall distribution**
**flow volume**

- Source: Paul McKee WGRFC; DSST presentation Feb., 2006

**headwater**
**fast**
**irregular**
**non-uniform **
**small**

**mainstem**
**slow**
**regular**
**uniform **
**large**

## Basin Response 1: Scaled QME Plots

- Blue River: flashy, less base flow

**Notes:**
Recall that this is a recommended step when calibrating a forecast group: find the basins that are the most similar in hydrograph shape. These should have similar parameters. 

## Basin Response 2: Unit Hydrographs

- Basin Response 2: Unit Hydrographs

- 	“Perhaps the most striking feature in the UH’s shown in Fig. 3 is that they do not, in general, fit very well widely used functional approximations for UH....an indication that some basins studied in this work may not be appropriate for lumped modeling.” (DJ Seo)

## Basin Response 2: Unit Hydrograph derived by using AB-OPT

- Basin Response 2: Unit Hydrograph derived by using AB-OPT

**Notes:**
Trying to fit the observed streamflow using MAP, MAPX data can lead to non sensible answers in some cases.

## Model Application SpectrumHypothetical use within WGRFC operations

- Lumped

- DHM

**Influencing factors**

- model ensemble tool?

**basin type**
**basin response**
**basin shape**
**rainfall distribution**
**flow volume**

*headwater*
*fast*
*irregular*
*non-uniform*
*small*

*mainstem*
*slow*
*regular*
*uniform*
*large*

- Source: Paul McKee, DSST presentation Feb., 2006

## Goal:  diagnostic indicators of basin behavior 

- make inferences on the efficacy of distributed model use

- -**Hypothesis**: basins characterized by 1) spatial variability of precipitation and 2) less smoothing of the rainfall signal will be amenable to distributed modeling.

- Goal:  diagnostic indicators of basin behavior
- and model improvement

- -“Further investigation is necessary to establish
- hydroclimatic or watershed characteristics that
- may indicate a priori better performance from
- either distributed or lumped models”  (Carpenter and Georgakakos, DMIP Special Issue, 2004)

- Rainfall Distribution / Basin Response

**Notes:**
Amenable: defined here as a basin for which a distributed model will improve over a lumped model.

##  Impact of Precipitation Spatial Variability

- flow

- time

- output

- input

- precipitation at time t

- precipitation at time t +t

- precipitation at time t + 2t

-  Impact of Precipitation Spatial Variability

- ‘filter’

- 16

**Notes:**
Example,
When is the variability of precipitation great enough to overcome the filtering and damping effects of the basin (Obled et al., 1994; Smith et al., 2004) to cause variability in the outlet hydrograph that can’t be modeled well using lumped models?  Base analyses on observed input and output data (not models) to generate diagnostic indicators. 

## Basins Used in Analysis

- Texas

- Oklahoma

- Arkansas

- Missouri

- Kansas

- Radar Locations

- 1. INX

- -

- Inola

- 2. FDR

- –

- Frederick

- 3. FWS

- –

- Ft. Worth

- 4. SGF

- –

- Springfield

- 5. LZK

- –

- N. Little Rock

- 6. SRX

- –

- Ft. Smith

- 7. TLX

- –

- Twin Lakes

- Elk R.

- Illinois River at Watts, OK

- Blue R.

- FWS

- LZK

- SRX

- FDR

- TLX

- INX

- SGF

- North

- of Rainfall Distribution/Basin Response

- Rainfall Distribution / Basin Response

- 17

- Baron Fork

## Select observed rainfall/runoff events: 
WTTO2=23,  ELDO2=25, BLUO2=31
Compute 
Rainfall location index
Rainfall general variability: 
(hly spatial std. dev.)
Compute rainfall/runoff smoothing
Plot location, variability versus smoothing
Compare to DMIP 1 ‘improvement’ results

- WTTO2=23,  ELDO2=25, BLUO2=31
- Compute
- Rainfall location index
- Rainfall general variability:
- (hly spatial std. dev.)
- Compute rainfall/runoff smoothing
- Plot location, variability versus smoothing
- Compare to DMIP 1 ‘improvement’ results

- DMIP Special Issue of the Journal Hydrology, 267-286

- Rainfall Distribution / Basin Response

- Steps

## Location Index for a Storm IL

- Location Index for a Storm IL

- Compute event center-of-mass in relation to basin centroid

| IL | Location of rainfall |
| --- | --- |
| IL > 1.0 | Upper basin |
| IL = 1.0 | Centroid of basin |
| IL  < 1.0 | Lower basin |

## Rainfall Distribution / Basin Response

- time

- time

- Rainfall hyetograph
- (input signal)

- Outlet hydrograph
- (output signal)

- Basin
- (filter)

- smoothed
- response

- depth

- flow

- Compute Basin Smoothing Metric

## Basin Smoothing vs. Rainfall Location Index

**upper basin**

**lower basin**

- DMIP Special Issue of J. Hydrology, pages 267-286

- Rainfall Distribution / Basin Response

**     ****smoothing**

- low

- high

## BLUO2: Blue River 

- Location Index IL

- General Rainfall Variability Imm

- Dampening Ratio Rd

- Dampening Ratio Rd

- 0.5

- 0.6

- 0.7

- 0.8

- 0.9

- 1.0

- 1.1

- 1.2

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- 1.4

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- BLUO2: Blue River
- at Blue, OK.

**   ****smoothing**

**     ****smoothing**

- high

- high

- low

- low

- HL-RDHM Performance vs Spatial Variability & Smoothing

**Notes:**
Check our hypothesis using DMIP 1 results. Rmod used here.  DMIP results seem to support the hypothesis, but more work is needed:
Use gridded rainfall, not MAP
Compute change from one hour to next in rainfall
Use more events

## ELDO2: Baron Fork 

- General Rainfall Variability Imm

- Dampening Ratio Rd

- Dampening Ratio Rd

- 0.9

- 0.95

- 1.0

- 1.05

- 1.1

- 1.15

- 1.2

- 1.25

- 1.3

- 1.35

- 1.4

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- ELDO2: Baron Fork
- at Eldon, OK.

**   ****smoothing**

**   ****smoothing**

- ELDO2

- high

- high

- low

- low

- HL-RDHM Performance vs Spatial Variability & Smoothing

**Notes:**
eldo2

## WTTO2: Illinois River 

- General Rainfall Variability Imm

- Dampening Ratio Rd

- Dampening Ratio Rd

- 0.96

- 0.98

- 1.0

- 1.02

- 1.04

- 1.06

- 1.08

- 1.10

- 0

- 5

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- 30

- 1

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- 0

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- WTTO2: Illinois River
- at Watts, OK

**   ****smoothing**

**   ****smoothing**

- high

- high

- low

- low

**Notes:**
Watts:  conclude that general variability isn’t enough.  Dominant component is in the rainfall structure

## Tools to Use

- XDMS
- ICP Plot TS
- Scaled QME plots
- CAP
- Soils
- Parameters
- AB-OPT: Compute UHG
- Compute event center of mass
- OHD tools
- ABRFC display

- Available now

- Future