Using Heat as a Tracer to Estimate Spatially Distributed ... · given advection and dispersion...
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Ramon C. Naranjo 1 , Greg Pohll 2 , Richard G. Niswonger 1 , Mark Stone 3 , and Alan Mckay 1 1 Nevada Water Science Center, U.S. Geological Survey, Carson City, NV 2 Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 3 Department of Civil Engineering, University of New Mexico, Albuquerque, NM INTRODUCTION Support for the first author was provided by the US EPA Landscape Ecology Branch, Las Vegas NV. Support for the third author was provided by the U.S. Geological Survey's (USGS) Groundwater Resources Program through the Office of Groundwater. Special thanks to the Pyramid Lake Paiute Tribe for permission to access the study site. CONCLUSIONS ACKNOWLEDGEMENTS The biogeochemical changes that occur in the hyporheic zone are highly dependent on the time solutes are in contact with riverbed sediments. To gain a better understanding of physical controls on nitrogen reactions, a two- dimensional longitudinal flow and solute transport model was developed to estimate the spatial distribution of mean residence time (MRT) in the hyporheic zone along a riffle-pool sequence. A physically distributed flow and transport model was necessary to estimate spatially distributed mean residence times. The approach used in this investigation accounts for the mixing of hyporheic water of different ages given advection and dispersion (Goode, 1996). Uncertainty of flow and transport parameters was evaluated using standard Monte-Carlo (MC) analysis and the generalized likelihood uncertainty estimation (GLUE) method. METHODS Truckee River riffle-pool sequence STUDY AREA 2013 AGU : H33F-1452 RESULTS RESULTS (continued) Using Heat as a Tracer to Estimate Spatially Distributed Mean Residence Times in the Hyporheic Zone Hot spots/ hot moments of nitrate and dissolved oxygen Longitudinal flow typically dominate hyporheic flow paths in riffle-pool sequences and variations in bedform slope and changes in flow depth are the primary drivers for exchange into the riverbed. As a consequence, the vertical influx of dissolved oxygen into the hyporheic zone will limit the extent of denitrification along a flow path. Therefore, it is important to account for the mixing of flow paths, both vertical and horizontal, in estimating MRT to understand the fate of nitrogen in the hyporheic zone. PURPOSE OF INVESTIGATION Likelihood measures for shallow and deep horizontal and vertical hydraulic conductivity given GLUE uncertainty weights of M =1 and 6 given 1000 realizations. MRT (days) from the optimal model MRT (days) based on GLUE (M = 6) Comparison of results based on the (a,b) mean and (c,d) standard deviation (Stdev) of MRT estimated by the optimal flow parameters, standard MC realizations from a range in hydraulic conductivity (MC K), porosity (MC porosity), dispersivity (MC dispersivity) and the GLUE method (M=1, M=6). Comparison of mean residence time [days] for different conceptual models , (a) anisotropic three- zone model, (b) anisotropic two-zone model without the low-permeable zone, (c) anisotropic single- zone model (K z /K x = 0.44), and (d) isotropic single-layer model (K z /K x = 1.0). Using the flow and solute transport model VS2DT with the age-mass approach (Goode, 1996), we estimate the spatially distributed mean and standard deviation residence times using a calibrated model (Naranjo et al., 2012) based on temperature and pressure with fixed transport parameters and compared results to: 1) uncertain flow parameters using the GLUE method (Beven and Binley, 1992) with fixed-transport parameters, and 2) fixed-flow parameters and uncertain-transport parameters using standard MC sampling. The GLUE method adopts the concept of equifinality, where multiple sets of model inputs considered likely are included in the analysis of uncertainty. We use the shape factor M, to apply weights to better performing models. Different conceptual models were also evaluated to better understand anisotropy effects on longitudinal hyporheic flow and MRT, assuming that typical fluvial processes results in layered sediment structure and strongly anisotropic hydraulic conductivity. Study area and diagram of the longitudinal two-dimensional VS2DT steady state solute transport model showing the boundary conditions Beven, K.J. and Binley, A.M., 1992. The future of distributed models: model calibration and uncertainty prediction, Hydrological Processes, 6, p.279–298. Goode, D.J., (1996), Direct Simulation of groundwater age. Water Resour. Res., 32, No. 2, 289-296 Naranjo, R. C., R. G.Niswonger, M.Stone, C.Davis, and A.Mckay (2012), The use of multiobjective calibration and regional sensitivity analysis in simulating hyporheic exchange, Water Resour. Res., 48, W01538, doi:10.1029/2011WR011179. Naranjo, R. C., G. Pohll, R. G. Niswonger, M. Stone, and A. Mckay (2013), Using heat as a tracer to estimate spatially distributed mean residence times in the hyporheic zone of a riffle-pool sequence, Water Resour. Res., 49, 3697–3711, doi:10.1002/wrcr.20306. REFERENCES • Down-gradient of urban area and nutrient inputs • Low gradient system with low variability in discharge • Significant amount of attached algae Riffle-Pool Characteristics Deep (dP) 70-110 cm Shallow (sP) 15-20 cm Piezometer M = 1 M = 6 a) c) d) b) Anisotropic Heterogeneous Model Anisotropic Homogenous Model Isotropic Homogenous Model Temperature observations Anisotropic Heterogeneous Model • Spatially variable MRT beneath a riffle-pool sequence does not conform to simple conceptual models of hyporheic flow. • Mixing behavior between the river and the hyporheic zone controlled by layered heterogeneity is important consideration in estimating MRT. • We have shown the value of combining the use of temperature and pressure for flow model calibration (Naranjo et al. 2012) and here we demonstrate its value in simulating MRT. • MRT were found to be relatively longer than what is typically reported for alluvial sediments (9 - 40 days). • The GLUE method helped reduce uncertainty of simulated MRT compared to standard MC. • Alternative conceptual models demonstrate the importance of including anisotropy and layered heterogeneity in estimating MRT.
Transcript of Using Heat as a Tracer to Estimate Spatially Distributed ... · given advection and dispersion...
Ramon C. Naranjo1, Greg Pohll2, Richard G. Niswonger1, Mark Stone3, and Alan Mckay1
1Nevada Water Science Center, U.S. Geological Survey, Carson City, NV 2Division of Hydrologic Sciences, Desert Research Institute, Reno, NV
3Department of Civil Engineering, University of New Mexico, Albuquerque, NM
INTRODUCTION
Support for the first author was provided by the US EPA Landscape Ecology Branch, Las Vegas NV. Support for the third author was provided by the U.S. Geological Survey's (USGS) Groundwater Resources Program through the Office of Groundwater. Special thanks to the Pyramid Lake Paiute Tribe for permission to access the study site.
CONCLUSIONS
ACKNOWLEDGEMENTS
The biogeochemical changes that occur in the hyporheic zone are highly dependent on the time solutes are in contact with riverbed sediments. To gain a better understanding of physical controls on nitrogen reactions, a two-dimensional longitudinal flow and solute transport model was developed to estimate the spatial distribution of mean residence time (MRT) in the hyporheic zone along a riffle-pool sequence. A physically distributed flow and transport model was necessary to estimate spatially distributed mean residence times. The approach used in this investigation accounts for the mixing of hyporheic water of different ages given advection and dispersion (Goode, 1996). Uncertainty of flow and transport parameters was evaluated using standard Monte-Carlo (MC) analysis and the generalized likelihood uncertainty estimation (GLUE) method.
METHODS
Truckee River riffle-pool sequence
STUDY AREA
2013 AGU : H33F-1452
RESULTS
RESULTS (continued)
Using Heat as a Tracer to Estimate Spatially Distributed Mean Residence Times in the Hyporheic Zone
Hot spots/ hot moments of nitrate and dissolved oxygen
Longitudinal flow typically dominate hyporheic flow paths in riffle-pool sequences and variations in bedform slope and changes in flow depth are the primary drivers for exchange into the riverbed. As a consequence, the vertical influx of dissolved oxygen into the hyporheic zone will limit the extent of denitrification along a flow path. Therefore, it is important to account for the mixing of flow paths, both vertical and horizontal, in estimating MRT to understand the fate of nitrogen in the hyporheic zone.
PURPOSE OF INVESTIGATION
Likelihood measures for shallow and deep horizontal and vertical hydraulic conductivity given GLUE uncertainty weights
of M =1 and 6 given 1000 realizations.
MRT (days) from the optimal model
MRT (days) based on GLUE (M = 6)
Comparison of results based on the (a,b) mean and (c,d) standard deviation (Stdev) of MRT estimated by the optimal flow parameters, standard MC realizations from a range in hydraulic conductivity (MC K),
porosity (MC porosity), dispersivity (MC dispersivity) and the GLUE method (M=1, M=6).
Comparison of mean residence time [days] for different conceptual models , (a) anisotropic three-zone model, (b) anisotropic two-zone model without the low-permeable zone, (c) anisotropic single-zone model (Kz/Kx = 0.44), and (d) isotropic single-layer model (Kz/Kx = 1.0).
Using the flow and solute transport model VS2DT with the age-mass approach (Goode, 1996), we estimate the spatially distributed mean and standard deviation residence times using a calibrated model (Naranjo et al., 2012) based on temperature and pressure with fixed transport parameters and compared results to: 1) uncertain flow parameters using the GLUE method (Beven and Binley, 1992) with fixed-transport parameters, and 2) fixed-flow parameters and uncertain-transport parameters using standard MC sampling. The GLUE method adopts the concept of equifinality, where multiple sets of model inputs considered likely are included in the analysis of uncertainty. We use the shape factor M, to apply weights to better performing models. Different conceptual models were also evaluated to better understand anisotropy effects on longitudinal hyporheic flow and MRT, assuming that typical fluvial processes results in layered sediment structure and strongly anisotropic hydraulic conductivity.
Study area and diagram of the longitudinal two-dimensional VS2DT steady state solute transport model showing the
boundary conditions
Beven, K.J. and Binley, A.M., 1992. The future of distributed models: model calibration and uncertainty prediction, Hydrological Processes, 6, p.279–298. Goode, D.J., (1996), Direct Simulation of groundwater age. Water Resour. Res., 32, No. 2, 289-296 Naranjo, R. C., R. G.Niswonger, M.Stone, C.Davis, and A.Mckay (2012), The use of multiobjective calibration and regional sensitivity analysis in simulating hyporheic exchange, Water Resour. Res., 48, W01538, doi:10.1029/2011WR011179. Naranjo, R. C., G. Pohll, R. G. Niswonger, M. Stone, and A. Mckay (2013), Using heat as a tracer to estimate spatially distributed mean residence times in the hyporheic zone of a riffle-pool sequence, Water Resour. Res., 49, 3697–3711, doi:10.1002/wrcr.20306.
REFERENCES
• Down-gradient of urban area and nutrient inputs
• Low gradient system with low variability
in discharge
• Significant amount of attached algae
Riffle-Pool Characteristics
Deep (dP) 70-110 cm
Shallow (sP) 15-20 cm
Piezometer
M = 1 M = 6
a)
c) d)
b)
Anisotropic Heterogeneous Model
Anisotropic Homogenous Model Isotropic Homogenous Model
Temperature observations
Anisotropic Heterogeneous Model
• Spatially variable MRT beneath a riffle-pool sequence does not conform to simple conceptual models of hyporheic flow.
• Mixing behavior between the river and the hyporheic zone controlled by layered heterogeneity is important consideration in estimating MRT.
• We have shown the value of combining the use of temperature and pressure for flow model calibration (Naranjo et al. 2012) and here we demonstrate its value in simulating MRT.
• MRT were found to be relatively longer than what is typically reported for alluvial sediments (9 - 40 days).
• The GLUE method helped reduce uncertainty of simulated MRT compared to standard MC.
• Alternative conceptual models demonstrate the importance of including anisotropy and layered heterogeneity in estimating MRT.
