Gordon E. GrantUSDA Forest Service PNW Research Station

M. Safeeq & S.Lewis Oregon State UniversityC.Tague, University of California Santa Barbara

Where’s Water? Forecasting future

streamflow regimes in the Pacific Northwest

J F M A M J J A S O N Dp

reci

pit

atio

n water u

se

The paradox of water in the

West…

• Develop a theoretical model of streamflow sensitivity to warming

• Apply this model to long-term data from basins across western US; examine empirical trends in streamflow

• Explore sensitivity to warming across basins across Oregon

• Compare with downscaled models

Today’s menu

A quick primer on climate change in the Pacific Northwest

– Warmer historic temperatures– Changes in precipitation likely

but uncertain (storminess?)– Snowpack is smaller and melting

earlier– Glaciers are retreating

(Nolin and Daly, 2006)

Snow at risk in a warming climate

22% Oregon Cascades12% Washington Cascades61% Olympic Range<3% Pacific Northwest study area

Red = rain instead of snow in the winter

But….

• It’s not just about snow….• Location (geology) matters too…• So…where, when, and how much

water will be available in the future – and what will its quality be?– Start with summer streamflow

• Filter 1:Timing and Magnitude of Recharge

• Filter 2: Drainage Efficiency

Tague & Grant, 2009

Simple model (from Tague and Grant, 2009)

Qt – streamflow at time t (in days)

Qo – streamflow at beginning of recession

k – recession constant

ktoeQtQ

Treating recharge as a single event, we develop a model for summer baseflow:

Qr – summer streamflow

k - drainage efficiency

tr - days between snowmelt (tpk) and time of interest (tsummer)

pk15-day- snowmelt input (peak reduction in a watershed areal mean of a 15 day running average

Qr pkl 5 daye k tr

pk15-day

tr

k

(Tague & Grant, 2009)

Summer flow sensitivity to changes in snowmelt dynamics (first

derivatives)

Qr pk15day

e k tr

Qr tr

pk15day ke k tr

Magnitude

(pk15-day) Timing

(tr)

Both contain k, drainage efficiency

(Tague & Grant, 2009)

(Tague & Grant, 2009)

unit change in daily streamflow

(mm

/day)

sensitive

Not sensitive

deep/slow shallow/fast

short

long

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10M

ean

uni

t di

scha

rge

(mm

/day

)

0

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14Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

current climate

1.5C warming

current climate

1.5C warmingClear Lake (MC)

Lookout Creek (LOC)

0

2

4

6

8

10M

ean

unit

disc

harg

e (m

m/d

ay)

0

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14Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

current climate

1.5C warming

current climate

1.5C warmingClear Lake (MC)

Lookout Creek (LOC)

less sensitive

more sensitive

Now, how do we go about:

forecasting the sensitivity of watersheds

across the region

0

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10

Mea

n un

it di

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rge

(mm

/day

)

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2

4

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14Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

current climate

1.5C warming

current climate

1.5C warmingClear Lake (MC)

Lookout Creek (LOC)

without modeling everything in sight?

…can we?

It would be nice if we could break the world into four distinct classes:

Rain Slow

SnowSlow

RainFast

SnowFast

Snowmelt dominated

Filter 1: Climate / Precipitation

Filter 2: Drainage Efficienc

y

Rain dominated

Fast draining

Slow draining

Interpreting streamflow trends across western US

81 unregulated basins

Drainage area: 20 to 36,000 km2 (median 550 km2)

Gage elevation:6.5 to 2,245 m(median 431 m)

Time period for analysis: 1950-2010

Extracting metrics from hydrologic records

1. Centroid Timing (CT)

2a. Recession (k)

2b. Base Flow Index (BFI)

Recession Constant (k)Bas

e F

low

Ind

ex (

BF

I)

annual value; mean for period

of record

daily value; mean for period

of record

event value; median for period of record

Interpreting streamflow trends across western US

Early CT = rain-dominated

Intermediate CT = Rain-on-snow / mixed

Late CT = snowmelt-dominated

1. Timing

Interpreting streamflow trends across western US

Low BFI = fast draining

Medium BFI = somewhere in between

High BFI = slow draining

2. Efficiency

Late CT

Snowmelt dominated

Filter 1: Climate / PrecipitationEarly CT

Rain dominated

Filter 2: Drainage Efficiency

Low BFI

Fast draining

High BFI

Slow draining

Late CT

Snowmelt dominated

Filter 1: Climate / PrecipitationEarly CT

Rain dominated

Filter 2: Drainage Efficiency

Low BFI

Fast draining

High BFI

Slow draining

•All trends are negative

Late CT

Snowmelt dominated

Filter 1: Climate / PrecipitationEarly CT

Rain dominated

Filter 2: Drainage Efficiency

Low BFI

Fast draining

High BFI

Slow draining

• Slopes steepen with increasing BFI

Late CT

Snowmelt dominated

Filter 1: Climate / PrecipitationEarly CT

Rain dominated

Filter 2: Drainage Efficiency

Low BFI

Fast draining

High BFI

Slow draining

• Precipitation trends can trump geology

Key initial findings:• Snowpack dynamics and drainage efficiency

(mediated through hydrogeology) are both first-order controls on streamflow response to climate warming

• Simple theory predicts greatest low flow sensitivity to changes in timing of snowmelt are in basins with intermediate snowmelt timing and low drainage efficiencies

• Basins can be categorized in terms of their snowpack dynamics and drainage efficiencies using simple metrics

• Historical trends in streamflow are consistent with model predictions

• Changes in precipitation can trump changes due to warming alone

Extra Slides

www.fsl.orst.edu/wpg