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
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
Plot Scale © Oregon State University Example 1 Hydrologic Models
Plot Scale © Oregon State University Svartberget Sweden Isotopes in model validation
Plot Scale © Oregon State University Svartberget Sweden Isotopes in model validation
Plot Scale © Oregon State University Example 2 Hydrologic Models
Plot Scale © Oregon State University Maimai New Zealand Isotopes in model calibration
Plot Scale © Oregon State University Catchment Scale Maimai Watershed in New Zealand Hydrologic Models
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
Plot Scale © Oregon State University Hillslope Riparian Zone Hollow Catchment Scale Hydrologic Models
Plot Scale © Oregon State University A Three Box Model Seibert and McDonnell, 2002 WRR Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Na mol/L) K ( mol/L) Stream Rain Riparian Zone Soil-Ridge Soil-Hollow Riparian Zone Hollow Hillslope Geochemical End Members Catchment Scale Hydrologic Models
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
Plot Scale © Oregon State University A Three Box Model Hillslope type discussed earlier… Seibert and McDonnell, 2002 WRR Catchment Scale Hydrologic Models
Plot Scale © Oregon State University The hollow box <0 dZ dS dZ Storm Rainfall Catchment Scale Hydrologic Models
Plot Scale © Oregon State University The time series Catchment Scale Hydrologic Models
Plot Scale © Oregon State University ….but does it work for the right reasons??? Model efficiency 0.93 Catchment Scale Hydrologic Models
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
Plot Scale © Oregon State University Model performance with hard data calibration Increasing soft data Catchment Scale Hydrologic Models
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
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
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
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
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 (30/9/87 event, McDonnell et al. 91; WRR) Catchment Scale Hydrologic Models
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
Plot Scale © Oregon State University ….but does it work for the right reasons??? Model efficiency 0.93 Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Model efficiency 0.92 ….maybe not? Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Model efficiency 0.93 ….maybe not???!! Catchment Scale Hydrologic Models
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
Plot Scale © Oregon State University Example 3 Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Brugga Basin, Germany Isotopes in model structure
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
Plot Scale © Oregon State University Topography Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Soils and Geology Soil Regosol Saure Braunerde Braunerde Kalkbraunerde Verbraunter u. Bunter Gley Fahler gley Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Digital Elevation Model Topo Index TopographySlope Curvature Hydrologic Models
Plot Scale © Oregon State University Hortonian Overland Flow Saturation Overland Flow Sub- surface Flow Process Identification Catchment Scale Hydrologic Models
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
Plot Scale © Oregon State University MRT and watershed modeling.... following Uhlenbrook et al. (2002) WRR Discharge Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Conceptualization of Runoff Processes.... following Uhlenbrook et al. (2002) WRR Catchment Scale Hydrologic Models
Plot Scale © Oregon State University Runoff Generation.... following Uhlenbrook et al. (2002) WRR Catchment Scale Hydrologic Models
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