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Welcome to our latest SNAMP newsletter! This issue focuses on recent work from the Water Team. To read other newsletters and for more information about the SNAMP project, please visit our project website at: http://snamp.cnr.berkeley.edu.

SNAMP WATER TEAM RESEARCH QUESTIONSThere are three main research questions that the water team is exploring: (1) What are the timing and amount of water storage and routing in forested Sierra Nevada catchments? (2) What effects do forest treatments have on water quality, quantity (yield), storage & routing through the catchments? And (3) What is the transferability of in-formation from four intensively measured headwater streams to a larger area fireshed response?

Pre-treatment water measurements started in October 2007. Instrumentation was installed in phases with five years of meteorological data, four years of distributed snow depth data, and three years of distributed soil mois-ture, stream water quality, and streamflow data. Alto-gether, over 230 sensors are in continuous operation in the northern (Last Chance) and southern (Sugar Pine) sites. The team has collected data during a good range of annual precipitation. The annual precipita-tion measured 70% of average in water years 2008 and 2009, 100% in 2010, and 120% in 2011.

THE WATER TEAM’S HYPOTHESES:1) Forest fuel treatments that reduce tree canopy cover, measured using Leaf Area Index (LAI), will

enhance snow accumulation on the ground, while evapotranspiration (ET) will decrease. Snow re-tention may increase or decrease based on exactly how the treatments open gaps in the forest can-opy, which affects the solar radiation.

A Newsletter from the SNAMP Public Participation Science Team - Volume 6, Number 1, November 2012

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F o r M o r e I n f o r m a t i o n : h t t p : / / s n a m p . c n r . b e r k e l e y . e d u

SNAMP HIGHLIGHT: WATER TEAM

The water team has two leads: Dr. Roger Bales and Dr. Martha Conklin at UC Merced. The water team includes Postdoctoral Researcher Ram Ray, Graduate Students Sarah Martin and Phil Saksa and Staffer Patrick Womble.

theSierra NevadaAdaptive Management Project newsletter

Figure 1. Phil Saska in the field.

2) Treatment effects on snow retention will be observed in the recession limb of the streamflow hy-drograph and soil-moisture-storage measurements. Changes in ET will affect both the timing and the magnitude of late-season streamflow.

3) Changes in water quality, as measured by turbidity and electrical conductivity, will be a function of changes in discharge. Any turbidity increases from treatments would be a function of increased stream discharge effects on in-stream sediment sources as opposed to hillslope erosion.

CONDUCTIVITY Specific conductivity of stream water has been collected by both continuous sampling

and grab samples. In general, snow and rain have lower conductivity, with fewer dissolved salts, than groundwater. Conductivity is typically lowest in late winter and spring when there are significant snow melt inputs. It is highest in summer when the main water source is groundwater and evaporation/ET remove water, leaving salts behind.

WATER CHEMISTRY The team is using isotope and ion analysis to

compare watersheds and identify the sources of the water. Paired streams had similar range of values, but there were distinct differences between the northern and southern sites. Stream water was isotopically lighter at higher elevation in the south, and heavier water at lower elevation in the north. These data fit within larger regional trends.

TURBIDITY Turbidity changes are episodic, and show a fall “first flush”

with the beginning of rains followed by a seasonal depletion of sediment es-pecially following multiple storm events. Individual spikes in turbidity seem not only tied to stream discharge, but also to recent storm event history.

MODELING SCENARIOS AND CALIBRATIONS

The Regional Hydro-Ecologic Simulation System (Rhessys) is used to estimate components of hydrologic cycle, including streamflow, soil moisture, and

evapotranspiration. Our data have been used for simulation and calibration of the RHESSys model using a dynamic vegetation component. Simulated flow is compared to

observed streamflow, and is being used to parameterize the model, along with snow and soil moisture measurements. Originally researchers allowed the model to decide

whether precipitation fell as rain or snow based on the daily average temperature, but they found that manually separating rain and snow inputs vastly improved

model results. They are now specifying in the model the form of precipitation based on information from snow-depth instruments, yielding estimates of twice

as much snow fall as before. Based on NASH efficiency coefficient (0-least and 1 most accurate), model accuracy increased from 0.5 to 0.82, precipita-

tion input vs rain and snow input which is now acceptable for this type of modeling and catchments. After forest treatments are complete, new

vegetation data derived from LiDAR measurements will be incorporated into RHESSys to assess impacts on the hydrologic cycle. Scaling up to larger watersheds is the final step in the modeling process.

For more information on the SNAMP Water Team, please see: http://snamp.cnr.berkeley.edu/teams/water.

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This SNAMP Newsletter created by Anne Lomnbardo, Susie Kocher and Maggi Kelly. This Newsletter ’s images courtesy of the SNAMP

water team , and http://fiesta .bren .ucsb.edu/~rhessys/.

Figure 2. The new weir plate at Big Sandy at the southern site.