1. Plot Scale © Oregon State University Isotope Hydrology Shortcourse Prof. Jeff McDonnell Richardson Chair in Watershed Science Dept. of Forest Engineering Oregon State University Hydrologic Models Isotopes in Hydrological Models

2. Plot Scale © Oregon State University Outline  Day 1 Morning: Introduction, Isotope Geochemistry Basics Afternoon: Isotope Geochemistry Basics ‘cont, Examples  Day 2 Morning: Groundwater Surface Water Interaction, Hydrograph separation basics, time source separations, geographic source separations, practical issues Afternoon: Processes explaining isotope evidence, groundwater ridging, transmissivity feedback, subsurface stormflow, saturation overland flow  Day 3 Morning: Mean residence time computation Afternoon: Stable isotopes in watershed models, mean residence time and model strcutures, two-box models with isotope time series, 3-box models and use of isotope tracers as soft data  Day 4 Field Trip to Hydrohill or nearby research site Catchment Scale Isotope Basics Concluding Statements Hydrologic Models

3. Plot Scale © Oregon State University Example 1 Hydrologic Models

4. Plot Scale © Oregon State University Svartberget Sweden  Isotopes in model validation

5. Plot Scale © Oregon State University Svartberget Sweden  Isotopes in model validation

6. Plot Scale © Oregon State University Example 2 Hydrologic Models

7. Plot Scale © Oregon State University Maimai New Zealand  Isotopes in model calibration

8. Plot Scale © Oregon State University Catchment Scale Maimai Watershed in New Zealand Hydrologic Models

9. Plot Scale © Oregon State University Process Study Findings  Channel stormflow is usually 85-90% old water (Pearce et al., 1986 WRR)  Most subsurface stormflow is via soil pipes at the soil bedrock interface (Mosley, 1979 WRR; McDonnell, 1990 WRR).  Riparian zone, hillslopes and hollows have distinct 18-O (McDonnell et al., 1991 WRR and base cation concentration (Grady et al., in review).  Mean age of baseflow is 3 mo (Stewart and McDonnell, 1991 WRR). …process experimental work at Maimai for past 25 yr Catchment Scale Hydrologic Models

10. Plot Scale © Oregon State University Hillslope Riparian Zone Hollow Catchment Scale Hydrologic Models

11. Plot Scale © Oregon State University A Three Box Model Seibert and McDonnell, 2002 WRR Catchment Scale Hydrologic Models

12. Plot Scale © Oregon State University Na  mol/L) 0 10 20 30 40 50 60 70 80 90 100 K (  mol/L) Stream Rain Riparian Zone Soil-Ridge Soil-Hollow 050100150200250 Riparian Zone Hollow Hillslope Geochemical End Members Catchment Scale Hydrologic Models

13. Plot Scale © Oregon State University McDonnell et al.,1991; WRR) Hillslope Hollow Riparian Cluster Analysis of Deuterium Concentration in Subsurface Water Catchment Scale Hydrologic Models

14. Plot Scale © Oregon State University A Three Box Model Hillslope type discussed earlier… Seibert and McDonnell, 2002 WRR Catchment Scale Hydrologic Models

15. Plot Scale © Oregon State University The hollow box   <0        dZ dS  dZ       Storm Rainfall             Catchment Scale Hydrologic Models

16. Plot Scale © Oregon State University The time series Catchment Scale Hydrologic Models

17. Plot Scale © Oregon State University ….but does it work for the right reasons??? Model efficiency 0.93 Catchment Scale Hydrologic Models

18. Plot Scale © Oregon State University But does this agree with our conceptual picture of the how the watershed works based on our isotope information???? Hydrologic Models

19. Plot Scale © Oregon State University Model performance with hard data calibration Increasing soft data Catchment Scale Hydrologic Models

20. Plot Scale © Oregon State University Soft Data: Qualitative knowledge from the experimentalist that cannot be used directly as exact numbers (e.g. % new water, soil depth, reservoir volume, macropore flow, etc Bypass flow and mixing Pipeflow of old water Rainfall/snow How can we use the process knowledge Soils Catchment Scale Hydrologic Models

21. Plot Scale © Oregon State University Type of soft data  New water contribution to peak runoff  Range of groundwater levels, min/max, fraction of saturated soil  Frequency of groundwater levels above a certain level  Parameter values Fraction of riparian, hillslope, hollow Porosity of riparian, hillslope, hollow Soil depth of riparian, hillslope, hollow Threshold level in hollow zone Catchment Scale Hydrologic Models

22. Plot Scale © Oregon State University Dialog between the experimentalist and modeler ExperimentalistModeller Evaluation rules Values for evaluation rules (a i ) a1a1 a2a2 a3a3 a4a4 0 1 Model value or parameter “Degree of acceptability” Catchment Scale Hydrologic Models

23. Plot Scale © Oregon State University Different ways of evaluating model acceptability Acceptability according to:ExampleMeasure A 1 Fit between simulated and Runoff Efficiency observed data A 2 Agreement with process New water Percentage of (qualitative) knowledge contribution peak flow A 3 Reasonability of parameter Spatial extension Fraction of values according to of riparian zone catchment area experimentalist Combined objective function: Seibert and McDonnell, 2002 AGU Monograph Catchment Scale Hydrologic Models

24. Plot Scale © Oregon State University Soft data discussions a1a1 a2a2 a3a3 a4a4 Fuzzy Rules - new water at peak - reservoir volumes, K sat etc - range of gw levels - hollow threshold level 0.03 0.06 0.12 0.15 (30/9/87 event, McDonnell et al. 91; WRR) Catchment Scale Hydrologic Models

25. Plot Scale © Oregon State University Improvement of model performance with soft data Increasing soft data e.g. from Seibert and McDonnell, 2002 WRR Catchment Scale Hydrologic Models

26. Plot Scale © Oregon State University ….but does it work for the right reasons??? Model efficiency 0.93 Catchment Scale Hydrologic Models

27. Plot Scale © Oregon State University Model efficiency 0.92 ….maybe not? Catchment Scale Hydrologic Models

28. Plot Scale © Oregon State University Model efficiency 0.93 ….maybe not???!! Catchment Scale Hydrologic Models

29. Plot Scale © Oregon State University Improvement of model performance with soft data Increasing soft data e.g. from Seibert and McDonnell, 2002 WRR Catchment Scale Hydrologic Models

30. Plot Scale © Oregon State University Example 3 Catchment Scale Hydrologic Models

31. Plot Scale © Oregon State University Brugga Basin, Germany  Isotopes in model structure

32. Plot Scale © Oregon State University Beyond a 1km 2 research watershed  Obtain as much map info as possible  Do synoptic survey of stream flow (if possible, temp, pH, EC etc)  Gauge trib junctions  Measure mean age of water  Dominant runoff generation processes Example Rietholzbach catchment  Translation into model elements Catchment Scale Hydrologic Models

33. Plot Scale © Oregon State University Topography Catchment Scale Hydrologic Models

34. Plot Scale © Oregon State University Soils and Geology Soil Regosol Saure Braunerde Braunerde Kalkbraunerde Verbraunter u. Bunter Gley Fahler gley Catchment Scale Hydrologic Models

35. Plot Scale © Oregon State University Digital Elevation Model Topo Index TopographySlope Curvature Hydrologic Models

36. Plot Scale © Oregon State University Hortonian Overland Flow Saturation Overland Flow Sub- surface Flow Process Identification Catchment Scale Hydrologic Models

37. Plot Scale © Oregon State University Dominant Runoff Processes Horton rarely saturated sometimes saturated Frequently saturated Often saturated Always saturated Subsurface flow Drained areas No runoff Catchment Scale Hydrologic Models

38. Plot Scale © Oregon State University MRT and watershed modeling.... following Uhlenbrook et al. (2002) WRR Discharge Catchment Scale Hydrologic Models

39. Plot Scale © Oregon State University Conceptualization of Runoff Processes.... following Uhlenbrook et al. (2002) WRR Catchment Scale Hydrologic Models

40. Plot Scale © Oregon State University Runoff Generation.... following Uhlenbrook et al. (2002) WRR Catchment Scale Hydrologic Models

41. Plot Scale © Oregon State University Summary  Day 1 Morning: Introduction, Isotope Geochemistry Basics Afternoon: Isotope Geochemistry Basics ‘cont, Examples  Day 2 Morning: Groundwater Surface Water Interaction, Hydrograph separation basics, time source separations, geographic source separations, practical issues Afternoon: Processes explaining isotope evidence, groundwater ridging, transmissivity feedback, subsurface stormflow, saturation overland flow  Day 3 Morning: Mean residence time computation Afternoon: Stable isotopes in watershed models, mean residence time and model strcutures, two-box models with isotope time series, 3-box models and use of isotope tracers as soft data  Day 4 Field Trip to Hydrohill or nearby research site Catchment Scale Isotope Basics Concluding Statements Hydrologic Models