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Isotopic Evolution of Snowmelt. Vicky Roberts Paul Abood Watershed Biogeochemistry 2/20/06. Isotopes in Hydrograph Separation. Used to separate stream discharge into a small number of sources

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isotopic evolution of snowmelt

Isotopic Evolution of Snowmelt

Vicky Roberts

Paul Abood

Watershed Biogeochemistry

2/20/06

isotopes in hydrograph separation
Isotopes in Hydrograph Separation
  • Used to separate stream discharge into a small number of sources
  • Oxygen and hydrogen isotopes are widely used because they are components of water and are conservative over short time scales
problem
Problem
  • For hydrograph separations involving snowmelt runoff
    • Some studies assume snowmelt to have a constant d18O value equal to the average d18O of the snowpack
    • d18O in snowmelt ≠ d18O snowpack
snowmelt isotopes
Snowmelt Isotopes
  • Snowmelt
    • Depleted in d18O early in melting season
    • Enriched in d18O later in melting season
  • Why?
    • Isotopic exchange between liquid water and solid ice as water percolates down the snow column
physical process
Physical Process
  • At equilibrium, the d18O of water is less than the d18O of ice; initial snowmelt has lower d18O than the snowpack
  • Snowpack becomes enriched in d18O ; melt from the enriched pack is itself enriched (d18O )
papers
Papers
  • Theory
    • Feng, X., Taylor, S., and Renshaw, C.E. 2002.
  • Lab
    • Taylor, S., Feng, X., and Renshaw, C.E. 2002.
  • Field
    • Taylor, S., Feng, X., Williams, M., and McNamara, J. 2002.
feng theoretical model quantitatively indicating isotope exchange

Feng: Theoretical model quantitatively indicating isotope exchange

Varied two parameters:

Effectiveness of isotopic exchange (Ψ)

Ice-liquid ratio (γ)

isotopic exchange
Isotopic exchange
  • Rliq controlled by advection, dispersion and ice-water isotopic exchange
  • Rice controlled by ice-water exchange
  • Rate of isotopic exchange dependent on:

Fraction of ice involved in exchange, f

    • Dependent on size and surface roughness of ice grains
    • Accessibility of ice surface to infiltrating water
    • Extent of diffusion within ice
    • Amount of melting and refreezing at ice surface

Ice-liquid ratio quantified by: γ = bf

a + bf

where a = mass of water

b = mass of ice

per unit volume of snow i.e. ratio of liquid to ice

effectiveness of exchange
Effectiveness of exchange:

Ψ= krZ

u*

  • Kr is a constant
  • Z = snow depth
  • U* = flow velocity

Ψ and γ dependent on melt rate and snow properties e.g. grain size, permeability

results
Results:
  • Effect of varying ψ (effectiveness of isotope exchange)
  • Relative to original bulk snow (d18O=0)
  • Where Ψ is large = curved trend (a)
    • Base of snowpack is 18O depleted as substantial exchange occurs
    • Low melt rate so slower percolation velocity
  • Where Ψ is small = linear trend (e)
    • Constant 3‰ difference between liquid and ice
slide11
Effect of varying γ (and therefore f):
  • Relative to original bulk snow (δ18O=0)
  • Low γ = curved trend (e)
    • Slow melt rate
    • Lower liquid: ice ratio as lower water content
  • High γ = linear trend (a)
    • Fast melt rate
    • Higher water content so more recrystallization

Therefore constant difference in 18O of snowmelt and bulk snow

conclusions
Conclusions:
  • High melt rate = effective exchange and high liquid: ice ratio. Higher percolation velocity so constant difference in 18O. Increased water content triggers recrystallisation, a mechanism of isotope exchange.
    • linear trend
  • Low melt rate = Large difference in 18O initially due to substantial exchange
    • Only a small proportion of ice is involved in isotopic exchange therefore insignificant change in 18O of bulk ice
    • 18O of liquid and ice reach steady state resulting in curved trend as equilibrium is reached
assumptions
Assumptions:
  • Snow melted from the surface at constant rate
  • Dispersion is insignificant
  • 18O exchange occurs between percolating water and ice
implications
Implications:
  • Variation in d18O between snowmelt and bulk snow causes errors in hydrograph separation if bulk snow values are used
taylor laboratory experiment to determine k r
Taylor: Laboratory experiment to determine kr
  • Determination of kr to allow implementation of model in the field
  • Controlled melting experiments:
    • Melted 3 snow columns of different heights at different rates
    • 18O content of snowmelt relative to snow column substituted into model equation to obtain kr
      • Kr = Ψu*

Z

k r u z
Kr = Ψu* Z
  • Range of ψ (effectiveness of isotopic exchange) values obtained by melting a short column rapidly (low ψ) and long column slowly (high ψ)
  • Z = initial snow depth
  • U* = percolation velocity
slide17
Model used to calculate kr as d18O is used to infer Ψ (effectiveness of exchange) so equation

Kr = Ψu* Z can be solved

results1
Results
  • kr = 0.16  0.02 hr-1
  • Small range (0.14 – 0.17 hr-1)
  • Small standard deviation (15%)
  • Successful parameterization of kr indicates that the model captures the physical processes that control the isotopic composition of meltwater
results2
Results
  • Estimate of f is uncertain
    • Test 1: 0.9Tests 2-3: 0.2
    • Uncertainties
      • Snowpack heterogeneity
      • Recrystallization
snowpack heterogeneity
Snowpack Heterogeneity
  • Real snowpacks are not homogeneous in terms of pore size
  • If water content is low, water may only percolate in small pores
  • Reduces surface area where isotopic exchange can occur
recrystallization
Recrystallization
  • Snow metamorphism due to wetting of snow
    • Small ice grains melt completely
      • No isotopic fractionation
    • Water refreezes onto larger ice crystals
      • 18O preferentially enters ice
      • Liquid becomes depleted
recrystallization1
Recrystallization
  • Change to fraction of ice participating in isotope exchange (f) depends on two processes
    • Increase in f
      • High mass of snow involved in melt – freeze
    • Decrease in f
      • Larger mean particle size reduces surface area available for ice – liquid interaction
slide23
Taylor, S., Feng, X., Williams, M., and McNamara, J. 2002.
  • How isotopic fractionation of snowmelt affects hydrograph separation
locations
Locations
  • Central Sierra Snow Laboratory (CA)
    • Warm, maritime snowpack
  • Sleeper River Research Watershed (VT)
    • Temperate, continental snowpack
  • Niwot Ridge (CO)
    • Cold, continental snowpack
  • Imnavit Creek (AK)
    • Arctic snowpack
methods
Methods
  • Sample collection
    • Meltwater collected from a pipe draining a meltpan (CA, VT, CO)
    • Plastic tray inserted into the snowpack at the base of a snow pit (AK)
  • Determination of d18O for meltwater samples
results4
Results
  • At all locations, meltwater had lower d18O values at the beginning of the melt event and increasingly higher values throughout the event (3.5% to 5.6%)
  • Trend holds despite widely different climate conditions
why is this important
Why is this important?
  • Using the average d18O value of pre-melt snowpack leads to errors in the hydrograph separation
error equation
Error Equation

Dx = estimated error in x

x = fraction of new water

d18ONew - d18OOld = isotopic difference between new and old water

Dd18ONew = difference between d18O in average

snowpack and meltwater samples

error equation1
Error Equation
  • Error is proportional to:
    • Fraction of new water in discharge (x)
    • Difference in d18O between snowpack and meltwater (Dd18ONew)
  • Error is inversely proportional to:
    • Isotopic difference between new and old water (d18ONew - d18OOld)
error
Error
  • Large error if meltwater dominates the hydrograph
  • Expected in areas of low infiltration
    • Permafrost
    • Cities
  • Underestimate new water
    • Assume more enriched water is a mixture of new and old water
error1
Error
  • Error magnitude depends on time frame of interest
    • Maximum error at a given instant in time
    • Error is lower if entire melt event is considered
      • d18OMelt ≈ d18OPack during middle of melt season
      • Negative error and positive error cancel out
other factors
Other Factors
  • Additional precipitation events
  • Varying melt rates
  • Meltwater mixing
  • Spatial isotopic heterogeneity
additional applications
Additional Applications
  • Incorporation into other models
    • Mass and energy snowmelt model
      • SNTHERM
  • Glaciers
    • Climate studies involving ice cores