Evolving issues in land surface hydrology at continental to global

scalesDennis P. Lettenmaier

Department of Civil and Environmental Engineering

University of Washington

for presentation at

Department of Atmospheric SciencesClouds and Precipitation Seminar

November 2, 2006

Outline this talk

• Motivation for this talk – potential synergisms across campus?

• Macroscale hydrology modeling construct• U.S. Drought reconstruction• North American Monsoon• Western U.S. snowpack and runoff trends• Anthropogenic impacts on continental surface

water fluxes• Applications:

– Westwide forecast system– Climate impact assessment

• Challenges to the field

Macroscale hydrology modeling construct

Investigation of forest canopy effects on snow accumulation and melt

Measurement of Canopy Processes via two 25 m2 weighing lysimeters (shown here) and additional lysimeters in an adjacent clear-cut.

Direct measurement of snow interception

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50

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350

11/1/96 12/1/96 1/1/97 2/1/97 3/1/97 4/1/97 5/1/97

SW

E (

mm

)ObservedPredicted

Below-canopy

Shelterwood

Tmin = 0.4 C Zo shelterwood = 7 mmTmax = 0.5 C Zo below-canopy = 20 cm

Albedo based onexponential decaywith age; fitted tospot observationsof albedo

Calibration of an energy balance model of canopy effects on snow accumulation and melt to the weighing lysimeter data. (Model was tested against two additional years of data)

Summer 1994 - Mean Diurnal Cycle

Point Evaluation of a Surface Hydrology Model for BOREAS

Flu

x (W

/m2)

-100

100

300 Rnet

-50

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150

250

H

0

60

120LE

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SSA Mature Black Spruce

Rnet

H

LE

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SSA Mature Jack Pine

Rnet

H

LE

0 3 6 9 12 15 18 21 24

Local time (hours)

NSA Mature Black Spruce

Observed Fluxes

Simulated Fluxes

Rnet Net Radiation

H Sensible Heat Flux

LE Latent Heat Flux

Range in Snow Cover ExtentObserved and Simulated

Eurasia North America

J F M A M J J A S O N D JMonth

Observed Simulated

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sno

w c

ove

r ex

ten

t (1

06 km

2 )

J F M A M J J A S O N D JMonth

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June 18th-July 20th, 1997

UPPER LAYER SOIL MOISTURE

0.40

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SO

IL M

OIS

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(%

)

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TOPLATS regionalESTAR distributed

TOPLATS distributed

11:00 CST JULY 12 1997

ESTAR TOPLATS

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ESTAR TOPLATS

10

50

11:00 CST JUNE 20, 1997

Illinois soil moisture comparison

Cold Season Parameterization -- Frozen Soils

Key

Observed

Simulated

5-100 cm layer

0-5 cm layer

Macroscale modeling approach (“top down”)

1 Northwest 5 Rio Grande 10 Upper Mississippi2 California 6 Missouri 11 Lower Mississippi3 Great Basin 7 Arkansas-Red 12 Ohio4 Colorado 8 Gulf 13 East Coast

9 Great Lakes

U.S. Drought Reconstruction (1916-2003)

Key aspects of the approach

• Spatially and temporally continuous dataset of hydro-climatological variables (one-half degree lat-long, daily)

• Drought event identification using spatio-temporal clustering

• Severity estimated for each drought event for different durations and spatial extents

• Results used to construct Severity-Area-Duration (SAD) curves

Defining drought extent

Evolution of droughts over time

U.S. drought history (1915-2003)

• Droughts of 1930s and 1950s most intense and longest respectively (also, largest spatial extent)

• 2000s western U.S. drought among the worse droughts

• Long dry spells during the 2000s drought hindered recovery in terms of runoff

• Other significant droughts included 1988, 1977 (W U.S.), mid-1960s (NE U.S.)

Model Runoff Annual Trends

• 1925-2003 period selected to account for model initialization effects

• Positive trends dominate (~28% of model domain vs ~1% negative trends)

Positive +

Negative

HCN Streamflow Trends• Trend direction and significance in streamflow

data from HCN have general agreement with model-based trends

Subset of stations was used (period 1925-2003)

Positive (Negative) trend at 109 (19) stations

Soil Moisture Annual Trends

• Positive trends for ~45% of CONUS (1482 grid cells)

• Negative trends for ~3% of model domain (99 grid cells)

Positive +

Negative

Trends in soil moisture drought duration

Severe Drought (10%) Extreme Drought (20%)

Intense Drought (30%) Moderate Drought (40%)

Soil Moisture Drought Spatial Extent

Severe Drought (10%)

Extreme Drought (20%)

Intense Drought (30%)

Trend for the drought spatial extent is negative (95% significance) for all threshold levels (10-50%)

Soil Moisture Drought Intensity● Droughts events identified using spatio-

temporal clustering and threshold of 20th percentile

● Intensity time series constructed from the maximum average intensity

• Mann-Kendall test for trend showed a statistically significant (98%) upward trend in “individual event” drought intensity

North American Monsoon teleconnection analysis

North American Monsoon System (NAMS)

North American monsoon is experienced as a pronounced increase in rainfall from extremely dry May to rainy June.

North American Monsoon Experiment (NAME): Tier 1,2,3. (http://www.cpc.ncep.noaa.gov/products/precip/monsoon/NAME.html)( Comrie & Glenn, 1998 )

The NAMS concept --- thermal contrast between land and adjacent

oceanic regions

( http://www.ifm.uni-kiel.de )

Question: how is the strength of the monsoon (in terms of precipitation) related to antecedent land surface conditions?

Winter Precipitation - Monsoon Rainfall feedback hypothesis

Higher (lower) winter precipitation & spring snowpack

More (less) spring & early summer soil moisture

Weak (strong) monsoon Lower (higher) spring & early summer surface temperature

Possible mechanism:

Winter Precipitation – Monsoon Onset

15-year Moving Average Correlation of PI versus monsoon onset

Correlation of JFM Precip and Monsoon Onset Date

Late

Early

Late Early

JFM Precipitation in extreme monsoon years

May Soil moisture in extreme monsoon years

May Sm in extreme monsoon years

May Ts in extreme monsoon years

Late Early

Late Early

Correlation:May first layer Sm & May Ts

Correlation:May Ts & monsoon onset

May soil moisture plays some role in pre-monsoon seasonal surface thermal condition

Western U.S. snowpack trend analysis

1916-2003

Trend %/yr

DJF

avg

T (

C)

1925-1946with1977-2003

Trend %/yr

DJF

avg

T (

C)

DJF

avg

T (

C)

1947-2003

Decadal Variability Doesn’t Explain the Temperature Related Effects to Snowpack

b) Max Accum. c) 90 % Melt a) 10 % Accum.

DJF

Tem

p (C

)

Change in Date

Change in Date

DJF

Tem

p (C

)

Change in Date

Change in Date

DJF

Tem

p (C

)

Change in Date

Change in Date

Trends in the Date of Snow Accumulation and Melt

1916-2003

Anthropogenic impacts on continental surface water fluxes

Introduction - Outline

• Background– Irrigation:

• 60-70 % of global water withdrawals (Shiklomanov, 1996, 1997)

– Reservoirs (ICOLD): • 35 % of large dams built for

irrigation purpose alone– Freshwater scarcity: one of the most

important environmental issues of the 21st century (UNEP, 1999)

• Approach– VIC macroscale hydrologic model

• Irrigation scheme• Reservoir model

• Results• Conclusions• Future research

Irrigated areas

Siebert, S., Döll, P., Hoogeveen, J., 2002. Global map of irrigated areas version 2.1, Center for Environmental Systems

Research, University of Kassel, Germany/Food and Agriculture Organization of the United Nations, Rome, Italy

•Irrigated areas, globally: • 2.5*106 km2

• 1.7 % of global land area

•Location of irrigated areas:• Asia: 68 %• America: 16%• India, China, USA: 47 %

Irrigation water requirements

Reservoirs

Main purpose of dam

Irrigation

Flood

Hydro

Fishing

Navigation

Recreation

Water supply

Unknown

ICOLD, 2003. World Register of Dams 2003, International Commission on Large Dams (ICOLD), Paris, France.

Model development: Reservoir model

365365 365

1min1

1

max

,

min

idaydayres

iday idaydayinendi

iini

EQQSS

QS

Qi

107min QQi

RiverNon-irrigated part of grid cellIrrigated part of grid cellReservoirDamWater withdrawal pointWater withdrawn from local riverWater withdrawn from reservoir

1st priority: Irrigation water demand 2nd priority: Flood control3rd priority: Hydropower production

If no flood, no hydropower: Make streamflow as constant as possible

Reservoir model

1st priority: Irrigation water demand 2nd priority: Flood control3rd priority: Hydropower production

If no flood, no hydropower: Make streamflow as constant as possible

Reservoir evaporation: Penman

Model evaluation: 1) Columbia, 2) Colorado, and 3) Missouri River basins

Results: Runoff and evapotranspiration

Results: Evapotranspiration

a) Effects of cropland expansion (1992 – 1700)

b) Effects of cropland expansion and irrigation (1992 – 1700)

c) Effects of irrigation (1992 - 1992)

Results: Streamflow

Colorado River basin

•Irrigation included:•Q: 26.5 mm year-1

•ET: 350 mm year-1

•Naturalized:•Q: 42.3 mm year-1

•ET: 335 mm year-1

Irrigation water

requirements

Evapotranspiration

increase

Changes in sensible heat

fluxes

Changes in surface

temperatures

Changes in latent heat

fluxes

Applications: Westwide hydrologic forecast system

UW Forecast Approach Schematic

NCDC COOP station obs.

up to 3 months from

current

local scale (1/8 degree) weather inputs

soil moisturesnowpack

VIC Hydrologic model spin up

SNOTEL

Update

streamflow, soil moisture, snow water equivalent, runoff

25th Day, Month 01-2 years back

index stn. real-time

met. forcings for spin-up

gap

Hydrologic forecast simulation

Month 12

INITIAL STATE

ObservedSWE

Assimilation

ensemble forecasts ESP traces CPC-based outlook NCEP CFS ensemble NSIPP-1 ensemble

West-wide System

West-wide System

www.hydro.washington.edu/forecast/westwide/

Application: Colorado River basin climate impact assessment

Water Resource Metrics

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A2 Avg.Shortfall

B1 Avg.Shortfall

A2 % of NOSHTG

B1 % of NOSHTG

A2 % ofSHTG 3

B1 % ofSHTG 3

BC

M/y

r

/

Pro

bab

ilit

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BASE

2010-2039

2040-2069

2070-2099

Challenges

• Role of new observation methods

• Scaling and the physically based model paradigm

• Understanding the sensitivity of runoff to long-term dec-cen climate variability and change