Source waters, flowpaths, and solute flux in mountain catchments

1. Source waters, flowpaths, and solute flux in mountain catchments Mark Williams

2. Watershed Hydrology

3. SNOWMELT Mountain-Block Recharge (MBR) + Stream Infiltration Mountain-Front Recharge (MFR)

4. HYDROLOGIC UNKNOWNS • Flowpaths • Residence time • Circulation depth • Reservoir sizes • Groundwater fluxes • Fractured rock environment increases difficulty of understanding mountain plumbing Add snowmelt runoff Permafrost

5. APPLICATION IN GREEN LAKES VALLEY: LTER RESEARCH SITE Green Lake 4 • Sample Collection • Stream water - weekly grab samples • Snowmelt - snow lysimeter • Soil water - zero tension lysimeter • Talus water – biweekly to monthly • Sample Analysis • Delta 18O and major solutes

6. Source Waters

7. Mixing Models in Catchment Hydrology

8. MIXING MODEL: 2 COMPONENTS • One Conservative Tracer • Mass Balance Equations for Water and Tracer

9. ASSUMPTIONS FOR MIXING MODEL • Tracers are conservative (no chemical reactions); • All components have significantly different concentrations for at least one tracer; • Tracer concentrations in all components are temporally constant or their variations are known; • Tracer concentrations in all components are spatially constant or treated as different components; • Unmeasured components have same tracer concentrations or don’t contribute significantly.

10. d18O IN SNOW AND STREAMFLOW • d18O fractionation of 4%o in snowmelt; • Cannot use d18O values measured at snow lysimeter directly to the catchment. • Failed assumption

11. Fractionation in Snowpack d18O = -20‰ Snow surface Ground Difference between maximum 18O values and Minimum 18O values about 4 ‰ d18O = -22‰

12. Isotopic Fractionation • Fractionation occurs as melt from surface percolates towards bottom of snowpack • Isotopic exchange between ice and percolating liquid water • d18Osolid > d18Oliquid > d18Ovapour • Molecules of surface meltwater are not the same as the ones at the base of the snowpack

13. ACCOUNTING FOR d18O IN MELTWATER • d18O values are highly correlated with amount of melt (R2 = 0.9, n = 15, p < 0.001); • Snowmelt regime is different at a point from a real catchment; • So, we developed a Monte Carlo procedure to stretch the dates of d18O in snowmelt measured at a point to a catchment scale using the streamflow d18O values.

14. NEW WATER FROM VARIOUS MODELS M1 - Original time-series of snowpack d18O M2 - Date-stretched time-series of snowpack d18O M3 - Original time-series of snowmelt lysimeter d18O M4 - Date-stretched time-series of snowmelt lysimeter d18O

15. NEW WATER AND OLD WATER Old Water = 64% Not Teflon basins!

16. HYDROLOGIC FLOWPATHS

17. MIXING MODEL: 3 COMPONENTS Simultaneous Equations Solutions • Two Conservative Tracers • Mass Balance Equations for Water and Tracers Q - Discharge C - Tracer Concentration Subscripts - # Components Superscripts - # Tracers

18. MIXING MODEL: 3 COMPONENTS(Using Discharge Fractions) Simultaneous Equations Solutions • Two Conservative Tracers • Mass Balance Equations for Water and Tracers f - Discharge Fraction C - Tracer Concentration Subscripts - # Components Superscripts - # Tracers

19. MIXING DIAGRAM: PAIRED TRACERS

20. FLOWPATHS: 2-TRACER 3-COMPONENT MIXING MODEL

21. FLOWPATHS: 2-TRACER 3-COMPONENT MIXING • Did we choose the right end-members? • Did we choose the right tracers? • Is there any way to quantitatively • evaluate our results?

22. END-MEMBER MIXING ANALYSIS (EMMA) • Uses more tracers than components • Decides number of end-members • Quantitatively select end-members • Quantitatively evaluate results of the • mixing model

23. MIXING MODEL: Generalization Using Matrices Simultaneous Equations Where • One tracer for 2 components and two tracers for 3 components • N tracers for N+1 components? -- Yes • However, solutions would be too difficult for more than 3 components • So, matrix operation is necessary Solutions • Note: • Cx-1 is the inverse matrix of Cx • This procedure can be generalized to N tracers for N+1 components

24. This slide is from Hooper, 2001

25. EMMA PROCEDURES • Identification of Conservative Tracers - Bivariate solute-solute plots to screen data; • PCA Performance - Derive eigenvalues and eigenvectors; • Orthogonal Projection - Use eigenvectors to project chemistry of streamflow and end-members; • Screen End-Members - Calculate Euclidean distance of end-members between their original values and S-space projections; • Hydrograph Separation - Use orthogonal projections and generalized equations for mixing model to get solutions! • Validation of Mixing Model - Predict streamflow chemistry using results of hydrograph separation and original end-member concentrations.

26. STEP 1 - MIXING DIAGRAMS • Look familiar? • This is the same diagram used for geometrical definition of mixing model (components changed to end-members); • Generate all plots for all pair-wise combinations of tracers; • The simple rule to identify conservative tracers is to see if streamflow samples can be bound by a polygon formed by potential end-members or scatter around a line defined by two end-members; • Be aware of outliers and curvature which may indicate chemical reactions!

27. STEP 2 - PCA PERFORMANCE • For most cases, if not all, we should use correlation matrix rather than covariance matrix of conservative solutes in streamflow to derive eigenvalues and eigenvectors; • Why? This treats each variable equally important and unitless; • How? Standardize the original data set using a routine software or minus mean and then divided by standard deviation; • To make sure if you are doing right, the mean should be zero and variance should be 1 after standardized!

28. APPLICATION OF EIGENVALUES • Eigenvalues can be used to infer the number of end-members that should be used in EMMA. How? • Sum up all eigenvalues; • Calculate percentage of each eigenvalue in the total eigenvalue; • The percentage should decrease from PCA component 1 to p (remember p is the number of solutes used in PCA); • How many eigenvalues can be added up to 90% (somewhat subjective! No objective criteria for this!)? Let this number be m, which means the number of PCA components should be retained (sometimes called # of mixing spaces); • (m +1) is equal to # of end-members we use in EMMA.

29. PCA PROJECTIONS First 2 eigenvalues are 92% and so 3 end-members appear to be correct!

30. FLOWPATHS: EMMA

31. EMMA VALIDATION: TRACER PREDICTION

32. NITROGEN DEPOSITION

33. NIWOT RIDGE NADP SITE: N-DEP INCREASED > 4x

34. NITROGEN IN STREAMS

35. Potential Sources of Nitrate and Ammonium

36. FLOWPATHS: EMMA

39. EMMA: NITRATE SOURCES • Under-predicts nitrate during snowmelt • Ionic pulse important • Overpredicts nitrate during summer • Denitrification? • 8-ha Martinelli: 30% stream nitrate atmos • 225-ha GL4: 20% stream nitrate atmos

40. Dual isotopic • analysis of • nitrate • d18O (no3) • d15N (no3)

41. Green Lakes Valley: dual isotopes

42. d18O (no3) time series

43. Hysteresis

44. DUAL ISOTOPE: NITRATE SOURCES • 8-ha Martinelli: 60% stream nitrate atmos • Twice EMMA • 225-ha GL4: 20% stream nitrate atmos • Same as EMMA

46. EMMA and NITRATE ISOTOPES • First time used together • 20% atmospheric nitrate in 220-ha stream • EMMA, dual isotopes similar results • 60% atmospheric nitrate in 8-ha stream • EMMA underestimates: unsampled flowpath • Talus nitrate microbial, not atmospheric • Denitrification probably very important

47. 1 1,300 river miles in Colordo 100,000 AMD sites in Western US

48. END OF PIPE TREATMENT STRATEGY • Millions of dollars to install • Expensive to operate • Operate for long-term • Need low-cost alternatives

50. Watershed approach, hydrometric, isotopic, and chemical measurements CHALK CREEK MINE:GROUNDWATER SOURCE CONTROLSDEMONSTRATION PROJECT EPA VIII 104(b)3 Program SUPPLEMENTAL FUNDING REQUEST Assistance Agreement MM998404-02