Hydrologic Measurements in the Sierra Nevada: SNAMP and Beyond. Sarah Martin Graduate Student Researcher University of California, Merced

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1 Hydrologic Measurements in the Sierra Nevada: SNAMP and Beyond Sarah Martin Graduate Student Researcher University of California, Merced

2 Overview Science directions and questions What do we expect to see? Infrastructure and data collection What are we collecting and how are we collecting it? Research Highlights What is the data showing? What can we learn from it? Future plans What are our next steps? Expanded view How does SNAMP fit into the broader picture? What similar studies are being conducted? Sierra Nevada Adaptive Management Project

3 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 km 2 watersheds to fireshed response? Sierra Nevada Adaptive Management Project

4 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. Sierra Nevada Adaptive Management Project

5 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 TERRESTRIAL-LAI.htm Sierra Nevada Adaptive Management Project

6 How do we measure LAI? An Introduction to Lidar Lidar = Light Detection and Ranging We 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 with tree graphic from globalforestscience.org.

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8 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. Sierra Nevada Adaptive Management Project

9 Fuels treatments lower LAI less interception and more solar radiation Size and spacing of gaps will also control snow accumulation and melt timing

10 Hypotheses 2 A 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.

11 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. Sierra Nevada Adaptive Management Project

12 Current Sediment Work Headcut Erosion vs. Bank Erosion 25 Eroded Volume (cu. m) P301 P303 P304 D102 Watershed Headcut Erosion Bank Erosion Data from King s River Experimental Watershed In-stream sources appear to be most significant contribution to sediment budget

13 Hypothesis 4 Using 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.

14 What s important? If we want to understand the water cycle, what do we need to measure? Inputs (precipitation) Outputs (stream flow, evaporation/sublimation, ET) Storage (snowpack, soil moisture) Energy (temp, solar radiation, wind) Physical parameters (slope, aspect, elevation, vegetation)

15 Last Chance Sierra Nevada boundary Last Chance Meteorological Station Monitored Watershed Study Area Sugar Pine Sugar Pine

16 Sampling Design BACI design Final Criteria: ~1 km 2 headwater catchments perennial stream reach nested within fireshed of km 2 Similar vegetation, slope, stream length, aspect Near rain-snow transition Sierra Nevada Adaptive Management Project

17 Challenges to measurements Continuous measurements Remote locations Access Power Complex terrain Lots of variability Sierra Nevada Adaptive Management Project

18 Meteorological Stations 4 Stations northern and southern sites lower and higher elevation Open areas on ridge tops Weather measurements Sierra Nevada Adaptive Management Project

19 Meteorological Data Wind speed and direction Air temperature Relative humidity Solar radiation Precipitation For hydrologic modeling Incoming and net radiation affects how fast snow melts and soil dries Ultrasonic depth sensors and tipping bucket gages measure warm and cold season precipitation Barometric pressure For stream flow calculations /ds2manual.pdf

20 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 Sierra Nevada Adaptive Management Project

21 Continuous Water Quality Data Multi-parameter Sonde Temperature Conductivity Optical turbidity Optical dissolved oxygen Stage

22 Water Samples Automated sampler Tied to turbidity to catch storm events Grab samples In-depth lab analysis Quality control for continuous sensors Sierra Nevada Adaptive Management Project

23 Sediment Erosion Pins Turbidity Suspended sediment Scour Pans

24 Discharge The challenge is to measure both peak and base flows in streams with a wide range of discharges and a significant subsurface component Pressure transducers + rating curves Weir/Stilling wells

25 Measurements Met stations Wind speed/direction Air temperature Relative humidity Incoming solar radiation Net solar radiation Precipitation (rain) Snow depth Hill slopes Snow depth Soil moisture Stream stations Stage discharge Water temperature Conductivity Dissolved oxygen Turbidity Automated and manual grab samples Sediment (suspended) Stable isotopes Major cations and anions ph Alkalinity Sediment (bedload) A total of ~270 instruments.. Sierra Nevada Adaptive Management Project

26 Stream Rating Curves y=2762x 2.67 r 2 =0.952 y=373.8x 6.23 r 2 =0.733 y=1033x 2.19 r 2 =0.948 y=8298x 4.15 r 2 =0.991 Data through WY 2010 (from YSI sondes)

27 Discharge Data WY 2010 Sierra Nevada Adaptive Management Project

28 Speckerman Stream Chemistry WY 2010

29 Spring Snowmelt Data Big Sandy Met Snow Storms Cold Front 25 WY 2008 WY 2008 Snow Data 30 Snow Depth (meter) /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) Temperature (deg C) 25 Snow Storms WY 2009 WY 2009 Snow Data 30 Snow Depth (meter) /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) Temperature (deg C)

30 Storm-Melt Sequence Fronts Snow Storm Snow? Rain Storm Increase in Depth Turbidity Spike?

31 How do we use this data? We measure at points. How do we get to the landscape scale? Hydrologic Modeling Sierra Nevada Adaptive Management Project

32 Between watersheds Within watershed Modeling context Multi-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 drip edge Fine scale under canopy

33 Scaling up and modeling change Computer models allow us to better represent heterogeneity across a broad area Slope Aspect Also to change parameters and see effects drought vs. wet years increase in temperature

34 Next steps Final installations Big Sandy wier Culvert weirs Scour pans Automatic water samplers Continued data analysis Modeling Results Calibration Large scale version of drop-box weir at Reynolds Creek Experimental Watershed Bonita and Pierson, 2003

35 Beyond SNAMP Last Chance Tioga Pass Road American River SNAMP sites are part of a larger transect that includes sites throughout the Sierra Sugar Pine KREW - CZO Wolverton

36 Snowpack loss & water storage: 30-yr horizon snowpack annual storage Sacramento Valley storage San Joaquin Valley storage Likely loss of ~3.5 MAF of snowpack storage in next 1-3 decades MAF: million acre feet Data from DWR

37 Influence of +3ºC on Snow vs Rain More rain, less snow Earlier snowmelt More winter floods Historical, 0 to -3 o C The water cycle in California s mountains is undergoing long-term shifts. Bales et al., 2006

38 California has a need for a modern, integrated water information system SNRI researchers are building prototype systems

39 A new generation of integrated measurements eddy correlation embedded sensor networks lidar isotopes & ions satellite snowcover low-cost sensors discharge sap flow sediment

40 Tioga Pass Road Merced Grove km Gin Flat Elevational transect Smokey Quarry Decagon EC-TM: 57 (12) Judd snow depth: 28 Met stations: (4) Wired & Alden radios Retrieval: manual Period: (Scripps sensors in parens) Decagon EC-TM: 214 Decagon MPS: 113 Judd snow depth: 57 Met stations: 2 Wired & Dust Network radios Retrieval: manual & cell phone Period: Providence Creek basin Wolverton basin Long Meadow Panther Meadow km Decagon EC-TM: 8 Campbell CS616: 57 Watermark: 9 Judd snow depth: 26 Met stations: 2 Wired & Crossbow radios Retrieval: manual Period: Southern sierra Critical Zone Observatory m elevation Rain-snow transition zone m, lies in the snow zone

41 Prototype embedded sensor network Packet delivery ration RSSI<- 80dBm RSSI>- 80dBm Received signal strength (RSSI), log scale Randomized channelhopping protocol Self-assembling redundant mesh Near 100% transmission w/ RSSI > -73 dbm, i.e. spacing of < 100 m 2008-present

42 San Joaquin R. Kings R. Fresno Kaweah R.

43 Flux towers along an elevation gradient, m, extend the core CZO instrument cluster from water-limited to temperaturelimited ecosystems 4 towers in place now, 3 more planned under NEON (2 co-located)

44 Water flux based on soil moisture vs. sap flow ET decreasing from 1 to 0.5 mm/d ET decreasing towards 0.1 mm/d Soil moisture & sap flux track each other Jan Hopmans, UCD

45 Increase in water yield w/ elevation, from rain to snow dominated Mean elevations for 8 catchments across the rain-snow transition Climatic, physiographic & vegetation controls on water yield Modeling in progress Decreasing temperature Increasing snow fraction Decreasing LAI Coarser soils C. Hunsaker et al., in preparation

46 Very high annual & summer ET at P301 Air T ( o C) Rnet (W/m 2 ) Cumulative Et (mm) 730 mm Et, 10/08-10/09 Little rain, 5/09-10/09 Sep- 08 Jan 09 Jun 09 Jan mm Et, 5/10-10/10 Jun 10 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?

47 Where can you find data? California Data Exchange Center Station Codes Big Sandy Met (BSN) Fresno Dome (FRD) Bear Trap (BTP) Duncan Peak (DUN) UC Merced Digital Library SNAMP Digital Library Sierra Nevada Adaptive Management Project

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51 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 Sierra Nevada Adaptive Management Project

52 Contacts Roger Bales (209) Martha Conklin (209) Patrick Womble Sarah Martin (559) Phil Saksa Sierra Nevada Adaptive Management Project