California water, mountain hydrology, & UC Merced

Transcription

1 California water, mountain hydrology, & UC Merced Roger Bales Acting Director, Sierra Nevada Research Institute Professor, School of Engineering University of California, Merced Snowcover & climate Remote sensing Ground-based networks

2 Sierra Nevada Research Institute Foster interdisciplinary research that focuses on the Sierra Nevada eco-region, including the Central Valley & other adjacent areas. Facilitate synergistic links between science, the arts, education & natural resource management.

3 SNRI research within UC Merced Climate & water Ecology & ecosystem science Air pollution & public health Environmental economics, policy & management

4 California s water resources challenges place increasing pressure on mountain resources 1. Changing urban & agricultural water demand 2. Sea level rise 3. Reduction of average annual snowpack 4. Changes in precipitation: timing, intensity, location, amount, variability 5. Long-term changes in watershed vegetation & increased incidence of wildfires 6. Increased water temperatures The foundation for the new knowledge needed to meet these challenges is new measurements DWR, 2006

5 Influence of +3ºC on SNOW vs RAIN About 1/3 of current snow will be rain Also earlier snowmelt -- shorter snow season And large snowstorms will become rainstorms, bringing more flooding Currently about 2/3 of Sierra Nevada precipitation is snow Historical snow, 0 to -3 o C Derived from UW s VIC model daily inputs, Bales et al., 2006

6 Snowpack loss & water storage snowpack annual storage 14 MAF 13.5 MAF 11 MAF Sacramento Valley storage San Joaquin Valley storage Likely loss of 3-5 million acre feet of snowpack storage in coming decades Data from DWR

7 Blending satellite & ground-based data to estimate snow water equivalent (SWE) Mountain Hydrology Research Group

8 Snow covered area (SCA) from MODIS satellite % SCA Tuolumne Merced May 10, 2004 Jeff Dozier, UCSB

9 UCM/UCB snowpack estimates in DWR monthly climate report Merced river basin Snowcover increases with elevation Bob Rice, UCM

10 Snow water equivalent (SWE) estimated from interpolation of ground-based measurements Measurements are sparse, but these are the only measurements of snow depth & snow water equivalent available

11 Big problem: operational, ground-based snow measurements are not representative snow course mean 80 SWE, cm km 2 spatial mean SWE, cm February 2006 Gin Flat data 50 April 1, 2006 Snow pillow & snow course measurements provide limited information on spatial distribution patterns Sites are not representative of the terrain & thus fail to represent basin-wide snow depth or water equivalent

12 60 SWE based on satellite SCA plus degree-day snowmelt Volumne snowmelt, 10 7 m Based on SCA depletion and degree day calculation Tuolumne Cumulative melt also calculated based on interpolated SWE More rapid depletion Interpolation over-estimates below 3,000 m & underestimates above 3,000 m Volumne snowmelt, 10 7 m 3 0 3/1/04 4/1/04 5/1/04 6/1/04 7/1/ Based on interpolated SWE /1/04 4/1/04 5/1/04 6/1/04 7/1/04

13 Sierra Nevada Hydrologic Observatory Tahoe NF Yosemite NP Sierra NF Sequoia NP A new generation of measurements & infrastructure Collaboration: universities, state & federal agencies, water districts Initial instrument clusters near rain-snow transition Measurement strategies rely heavily on satellite remote sensing coupled with new in situ measurements

14 Wolverton, Sequoia NP UCM, UCD, UCLA collaboration

15 Wolverton basin, Sequoia NP (12 km2) stream gage water balance instrumentation met station meadow transects

16 Embedded sensor network for mountain water cycle signal/data to/from other nodes One node Sensors snow depth air temperature relative humidity solar radiation soil moisture soil temperature Pod microcomputer data storage radio battery solar cell signal/data Mother pod microcomputer radio battery solar cell data logger & IP connection via phone, radio or direct network data & control Pod from Sensornet, Inc. signal/data to/from data system

17 Wolverton, Sequoia NP Vertical soil profiles of moisture & temperature, colocated with snow & radiation measurements Wells & piezometers in meadows & riparian areas Met stations across the basin Martha Conklin, UCM

18 Wolverton Creek, Sequoia NP: stream stage Base - flow August 14 - September 7, 2007 Base-flow period, 2150 m elevation stage cm Peter Kirchner, UCM August September 0

19 Wolverton Creek, Sequoia NP: stage & precipitation Base - flow August 14 - September 7, 2007 Base-flow period, 2150 m elevation stage cm precip.001mm As we add measurements and integrate them causal relationships become increasingly clear August September 5 0

20 Wolverton Creek, Sequoia NP: stage, precip & air temperature Base - flow August 14 - September 7, 2007 Base-flow period, 2150 m elevation stage cm air temp C precip.001mm to 6 hour lag between daily low flow and Tmax or daily high flow and Tmin August September 0

21 Wolverton Creek, Sequoia NP: stage, precip, air temp & sap flow Base - flow August 14 - September 7, 2007 Base-flow period, 2150 m elevation stage cm sap-flow C air temp C precip.001mm Peak sapflow occurs at solar noon about 1 hr before Tmax August September 0

22 Southern Sierra Critical Zone Observatory (CZO): Kings River underlying hypothesis: The distribution of soil moisture throughout the catchments controls (bio)geochemical processes, including weathering & the extent of coupling among the carbon & nitrogen cycles.

23 Mixed conifer forest dominates the CZO, which crosses the rainsnow transition (1,500-2,000 m) UCM, UCD, UCB, UCSB, UCLA, UCI, UNR, USFS

24 Rain-snow transition zone undergoes rapid seasonal changes, going from snowcover to wet soil to dry soil over 1-2 months Soil volumetric water content drip edge SWE under canopy March April May 2007 snow depth Snow & SWE depth, cm

25 Steep gradients in temperature & precipitation result in a lag in spring runoff in going from lower to higher elevation 2004

26 What paths does snowmelt take in a basin? overland flow subsurface flow groundwater Groundwater & subsurface flow insensitive to interanual variability in snowpack Martha Conklin & Fengjing Liu

27 Forest adaptive management: water 3 objectives: Measure changes in water quality & water budget in representative areas subjected to Framework/SPLATS treatment Estimate the impact of forest treatments on water quality, water budget & aquatic habitat at three levels: watershed, forest, bioregion Provide basis for continuing operational assessment of how Framework treatments will impact streams, water cycle & forest health Sierra Nevada Adaptive Management Program UCM, UCB, UCD snamp.cnr.berkeley.edu

28 Tahoe NF catchments Hydrology focuses on 3 smaller catchments: treatment control higher elevation, future treatment Same strategy in Sierra NF Martha Conklin Qinghua Guo

29 Concluding thoughts Current ability to quantitatively estimate water fluxes & reservoirs in mountains is woefully inadequate (also ecological & biogeochemical linkages) Economic value of & societal demand for new knowledge & tools for mountain hydrology is very large Advances will require sustained investments in new measurements & infrastructure, including data & information systems (plus research) Measurement strategies will rely heavily on remote sensing plus complimentary, distributed ground-based networks