Hydrologic Measurements in the Sierra Nevada:...

Sarah MartinGraduate Student ResearcherUniversity of California, Merced

Hydrologic Measurements in the Sierra Nevada: SNAMP and Beyond

Sierra Nevada Adaptive Management Projecthttp://snamp.cnr.berkeley.edu/

Overview

Science directions and questionsWhat do we expect to see?

Infrastructure and data collectionWhat are we collecting and how are we collecting it?

Research HighlightsWhat is the data showing?What can we learn from it?

Future plansWhat are our next steps?

Expanded viewHow does SNAMP fit into the broader picture?What similar studies are being conducted?


Research Questions

Where and when is water stored and how is it routed through the catchments?

What effects do forest treatments have on water quality, quantity, storage and routing through the catchments?

What is the transferability of 1 km2 watersheds to fireshed response?


Hypothesis 1

Fuels treatments will reduce LAI

As Leaf Area Index (LAI) decreases, snow accumulation on the ground will increase, while evapotranspiration (ET) and snow retention in late spring will decrease.


What is LAI?

Leaf Area Index“the ratio of total upper leaf surface of vegetation divided by the

surface area of the land on which the vegetation grows”“the one sided green leaf area per unit ground area”“the amount of leaf material in an ecosystem”

LAI ~ canopy cover

http://en.wikipedia.org/wiki/Leaf_Area_Index

http://www.uni-giessen.de/~gh1461/plapada/lai/lai.html

http://gosic.org/ios/MATRICES/ECV/TERRESTRIAL/ECV-GCOS

-TERRESTRIAL-LAI.htm

http://en.wikipedia.org/wiki/Leaf_Area_Index

http://www.uni-giessen.de/~gh1461/plapada/lai/lai.html

http://gosic.org/ios/MATRICES/ECV/TERRESTRIAL/ECV-GCOS-TERRESTRIAL-LAI.htm

http://gosic.org/ios/MATRICES/ECV/TERRESTRIAL/ECV-GCOS-TERRESTRIAL-LAI.htm

How do we measure LAI?An Introduction to Lidar

Lidar = Light Detection and RangingWe contracted with the National Center for Airborne Laser Mapping (NCALM)We have acquired lidar data for both study areas.The type of Lidar we used picks up multiple returns giving us canopy structure data

Image modified from Lefsky et al. 2004 with tree graphic from globalforestscience.org.


Hypothesis 1

Fuels treatments will reduce LAI

As Leaf Area Index (LAI) decreases, snow accumulation on the ground will increase, while evapotranspiration (ET) and snow retention in late spring will decrease.

Fuels treatments lower LAI less interception and more solar radiation

Size and spacing of gaps will also control snow accumulation and melt timing

Hypotheses 2A change in snow

accumulation will be seen in the magnitude of peak stream flow.

Changes in snow retention, will be observed in the recession limb of the hydrograph and the soil moisture curves.

Changes in ET will affect both the timing and the magnitude of late season base stream flow.


Hypothesis 3

Changes in water chemistry will be a function of changes in discharge.

Increased turbidity will be a function of stream discharge as opposed to hillslope erosion.

Data from King’s River Experimental Watershed

In-stream sources appear to be most significant contribution to sediment budget

Headcut Erosion vs. Bank Erosion

0

5

10

15

20

25

P301 P303 P304 D102

Watershed

Erod

ed V

olum

e (c

u. m

)

Headcut ErosionBank Erosion

Current Sediment Work

Hypothesis 4Using hydrologic models,

physiographic and hydroclimatic thresholds can be defined linking area treated with aquatic effects and impacts on forest water cycle.

Hydrologic models will allow us to scale up responses to the larger watershed and fireshed levels.

What’s important?

– Inputs (precipitation)– Outputs (stream flow,

evaporation/sublimation, ET)

– Storage (snowpack, soil moisture)

– Energy (temp, solar radiation, wind)

– Physical parameters (slope, aspect, elevation, vegetation)

If we want to understand the water cycle, what do we need to measure?

http://www.solcomhouse.com/hydrologiccycle.htm

Sierra Nevada

boundary

Sugar Pine

Last Chance

Meteorological StationMonitored WatershedStudy Area

Last Chance

Sugar Pine


Sampling Design

BACI designFinal Criteria:

• ~1 km2 headwater catchments • perennial stream reach• nested within fireshed of 40-200 km2

• Similar vegetation, slope, stream length, aspect • Near rain-snow transition


Challenges to measurements

Continuous measurementsRemote locations

• Access• Power

Complex terrainLots of variability


Meteorological Stations

4 Stations• northern and southern

sites• lower and higher

elevationOpen areas on ridge topsWeather measurements

Meteorological Data

Wind speed and direction

Air temperatureRelative humiditySolar radiationPrecipitation

Barometric pressure

For hydrologic modeling

For stream flow calculations

http://www.campbellsci.com/documents/manuals/nr-lite.pdf

http://www.licor.com/env/Products/Sensors/200/li200_description.jsp

Incoming and net radiation affects how fast snow melts and soil dries

http://www.juddcom.com/ds2manual.pdf http://www.derm.qld.gov.au/

Ultrasonic depth sensors and tipping bucket gages measure warm and cold season precipitation


Hillslope Instruments

Snow depth and soil moisture instrument nodes

On north and south facing slopes adjacent to met stations and stream instruments

Sensors at multiple depths

Continuous Water Quality Data

Multi-parameter SondeTemperatureConductivityOptical turbidityOptical dissolved

oxygenStage


Water Samples

Automated sampler• Tied to turbidity to

catch storm eventsGrab samples

• In-depth lab analysis• Quality control for

continuous sensors

Sediment

Erosion PinsTurbidity Suspended sedimentScour Pans

Discharge

Pressure transducers + rating curves

Weir/Stilling wells

The challenge is to measure both peak and base flows in streams with a wide range of discharges and a significant subsurface component


Measurements

Met stationsWind speed/directionAir temperatureRelative humidityIncoming solar radiationNet solar radiationPrecipitation (rain)Snow depth

Hill slopesSnow depthSoil moisture

Stream stationsStage dischargeWater temperatureConductivityDissolved oxygenTurbidityAutomated and manual grab samples

• Sediment (suspended)• Stable isotopes• Major cations and anions

pHAlkalinitySediment (bedload)

A total of ~270 instruments…..

Stream Rating Curves

Data through WY 2010 (from YSI sondes)

y=2762x2.67

r2=0.952

y=1033x2.19

r2=0.948

y=373.8x6.23

r2=0.733

y=8298x4.15

r2=0.991


Discharge Data – WY 2010

Speckerman Stream Chemistry WY 2010

WY 2009 Snow Data

0

5

10

15

20

25

3/1/2009 3/8/2009 3/15/2009 3/22/2009 3/29/2009 4/5/2009 4/12/2009 4/19/2009 4/26/2009 5/3/2009 5/10/2009 5/17/2009 5/24/2009

Time (hourly)

Sno

w D

epth

(m

eter

)

-20

-10

0

10

20

30

Tem

pera

ture

(d

eg C

)

WY 2008 Snow Data

0

5

10

15

20

25

3/1/2008 3/8/2008 3/15/2008 3/22/2008 3/29/2008 4/5/2008 4/12/2008 4/19/2008 4/26/2008 5/3/2008 5/10/2008 5/17/2008 5/24/2008

Time (hourly)

Sno

w D

epth

(met

er)

-20

-10

0

10

20

30

Tem

pera

ture

(d

eg C

)

Snow Storms Cold Front

Snow Storms

Spring Snowmelt Data – Big Sandy Met

WY 2008

WY 2009

Storm-Melt Sequence

Increase in Depth

Turbidity Spike?

Fronts

Snow Storm Rain

StormSnow?


How do we use this data?

We measure at points…. How do we get to the landscape scale?

Hydrologic Modeling

Between watersheds Within watershed

Fine scale

Modeling contextMulti-scale heterogeneity in controlling processes, e.g. snow accumulation & melt is problematic to represent at a regional scale using a strictly empirical approach Christina Tague, UCSB

open

under canopy

drip edge

Scaling up and modeling change

Computer models allow us to better represent heterogeneity across a broad area

Also to change parameters and see effects

drought vs. wet years

increase in temperature

Slope Aspect

Next stepsFinal installations

Big Sandy wierCulvert weirsScour pansAutomatic water samplers

Continued data analysis

ModelingResultsCalibration

Large scale version of drop-box weir at Reynolds Creek Experimental Watershed

Bonita and Pierson, 2003

SNAMP sites are part of a larger transect that includes sites throughout the Sierra

Beyond SNAMP

Last Chance

American River

Tioga Pass Road

Sugar Pine

KREW - CZO

Wolverton

Snowpack loss & water storage: 30-yr horizon

Likely loss of ~3.5 MAF of snowpack storage in next 1-3 decades

Sacramento Valley storage San Joaquin Valley storage

snowpack annual storage

MAF: million acre feet Data from DWR

Influence of +3ºC on Snow vs Rain

Bales et al., 2006

Historical, 0 to -3oC

More rain, less snow Earlier snowmelt More winter floods

The water cycle in California’s mountains is undergoing long-term shifts.

California has a need for a modern, integrated

water information system

SNRI researchers are building prototype systems

lidar

A new generation of integrated measurements

eddy correlation

satellite snowcover

embedded sensor

networks

sap flow

isotopes & ions

low-cost sensors

sediment

discharge

Decagon EC-TM: 8Campbell CS616: 57Watermark: 9Judd snow depth: 26Met stations: 2Wired & Crossbow radiosRetrieval: manualPeriod: 2005-12 +

Decagon EC-TM: 214Decagon MPS: 113

Judd snow depth: 57Met stations: 2

Wired & Dust Network radiosRetrieval: manual & cell phone

Period: 2007-12 +

Decagon EC-TM: 57 (12)Judd snow depth: 28Met stations: (4)Wired & Alden radiosRetrieval: manualPeriod: 2009-19 +(Scripps sensors in parens)

Southern sierra Critical Zone Observatory

1750-2100 m elevationRain-snow transition zone

Tioga Pass Road

0 4 8 km

Gin FlatMerced Grove

SmokeyQuarry

Providence Creek basin

Wolverton basin

Long Meadow

Panther Meadow

km

2100-2700 m, lies in the snow zone

Elevational transect

Prototype embedded sensor

network

RSSI<-80dBmRSSI>-80dBm

Randomized channel-hopping protocol

Self-assembling redundant mesh

Near 100% transmission w/ RSSI > -73 dBm, i.e. spacing of < 100 m

2008-present

Received signal strength (RSSI), log scale

Pack

et d

eliv

ery

ratio

n

Kings R.

San Joaquin R.

Kaweah R.

Fresno

Flux towers along an elevation gradient, 400-2700 m, extend the core CZO instrument cluster from water-limited to temperature-limited ecosystems

4 towers in place now, 3 more planned under NEON (2 co-located)

Water flux based on soil moisture vs. sap flow

Jan Hopmans, UCD

ET decreasing from 1 to 0.5 mm/d

ET decreasing towards 0.1 mm/d

Soil moisture & sap flux track each other

Decreasing temperatureIncreasing snow fractionDecreasing LAICoarser soils

Mean elevations for 8 catchments across the rain-snow transition

Climatic, physiographic & vegetation controls on water yield

Modeling in progress

Increase in water yield w/ elevation, from rain to snow dominated

C. Hunsaker et al., in preparation

Cumulative Et (mm)

Rnet (W/m2)

Air T (oC)

Little rain, 5/09-10/09

430 mm Et, 5/10-10/10

730 mm Et, 10/08-10/09

Very high annual & summer ET at P301

High summer values depend on deep root extraction of water

Happy elev for trees – T & precip just right

Soils hold snowmelt over summer.How much water can soils hold vs. elev?

Jun 10Sep- 08 Jun 09 Jan 10Jan 09


Where can you find data?

California Data Exchange Center http://cdec.water.ca.gov/

Station CodesBig Sandy Met (BSN)Fresno Dome (FRD)Bear Trap (BTP)Duncan Peak (DUN)

UC Merced Digital Libraryhttps://eng.ucmerced.edu/snsjho

SNAMP Digital Libraryhttps://snamp.ucmerced.edu/

http://cdec.water.ca.gov/

https://eng.ucmerced.edu/snsjho

https://snamp.ucmerced.edu/


Data availability through digital library

Level 2 data from core field measurements made available by water year: snow, soil moisture, temperatures

Level 1 data available by request


Contacts Roger Bales

[email protected](209) 228-4348

Martha [email protected](209) 228-4349

Patrick [email protected]

Sarah [email protected](559) 359-6252

Phil [email protected]

mailto:[email protected]





Hydrologic Measurements in the Sierra Nevada:...

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