the significance of model structure in one- dimensional stream solute transport models with multiple...

The Significance of Model Structure in One- Dimensional Stream Solute Transport Models with Multiple Transient Storage Zones Masters Defense of: Patrick Corbitt Kerr Advisor: Michael Gooseff 1 Committee Members: Peggy Johnson 1 Diogo Bolster 2 1 Department of Civil and Environmental Engineering, The Pennsylvania State University, State College, PA, USA 2 Department of Civil Engineering and Geological Sciences, University of Notre Dame, IN, USA 1

Motivation Low-order streams are at the head of the river continuum and are the primary interface between the river network and its drainage basin. These streams feature a strong connectivity with the riparian ecosystem due to channel complexity and stream gradient. 2 Vannote. R.L., G. W. Minshall, K. W. Cummins, J. R. Sedell, and C. E. Cushing. 1980. The river continuum concept. Can. J. Fish. Aquat. Sci. 37: 130-137 1 1

Motivation The hydraulic characteristics and biogeochemical conditions of low-order streams are different than for high-order streams. Biogeochemical processing is dependent on hydrodynamic transport. Residence Time Travel Path Residence Conditions 3 Stream Corridor Restoration: Principles, Processes, and Practices. 1998. Federal Interagency Stream Restoration Working Group. 2 2

Motivation We seek to understand hydrodynamic and biogeochemical processes, so we try to model it. Simulation of hydrodynamic transport requires conceptual models to approximate the complex geometry and physics. Tracer experiments are used to populate parameters in the solute transport model as well as verify model physics. 4

Motivation These models can provide insight into areas of the stream difficult to observe. Interpretation of models can also lead to metrics, a means to quantify biogeochemical and hydraulic characteristics. These metrics can used at the local, reach, or watershed scale to investigate processes such as nutrient cycling. 5 Preston, S.D., Alexander, R.B., Woodside, M.D., and Hamilton, P.A., 2009, SPARROW MODELINGEnhancing Understanding of the Nations Water Quality: U.S. Geological Survey Fact Sheet 20093019, 6 p. 3 3

Transient Storage Model 6 Thackston, E. L., and K. B. Schnelle, J. (1970). "Predicting effects of dead zones on stream mixing." J. Sanit. Eng. Div. Am. Soc. Civ. Eng., 96(SA2), 319-331. Hays, J. R., Krenkel, P. A., and K. B. Schnelle, J. (1966). Mass transport mechanisms in open-channel flow, Vanderbilt Univer., Nashville, Tenn. 4 5 4 5

Previous Work Bencala, K. E., and Walters, R. A. (1983). "Simulation of solute transport in a mountain pool-and-riffle stream: a transient storage model." Water Resources Research, 19(3), 718-724. Stream_Solute_Workshop. (1990). "Concepts and methods for assessing solute dynamics in stream ecosystems." Journal of the North American Benthological Society, 9, 95-119. Runkel, R. L., and Broshears, R. E. (1991). "One dimensional transport with inflow and storage (OTIS): A solute transport model for small streams ", Center for Adv. Decision Support for Water Environ. Syst., ed., Tech Rep. 91-01. D'Angelo, D. J., Webster, J. R., Gregory, S. V., and Meyer, J. L. (1993). "Transient storage in Appalachian and Cascade mountain streams as related to hydraulic characteristics." Journal of the North American Benthological Society, 12(3), 223-235. Choi, J., Harvey, J. W., and Conklin, M. H. (2000). "Characterizing multiple timescales of stream and storage zone interaction that affect solute fate and transport in streams." Water Resources Research, 36(6), 1511-1518. Harvey, J. W., Saiers, J. E., and Newlin, J. T. (2005). "Solute transport and storage mechanisms in wetlands of the Everglades, south Florida." Water Resources Research, W05009, doi:10.1029/2004WR003507. Gooseff, M. N., McKnight, D. M., Runkel, R. L., and Duff, J. H. (2004). "Denitrification and hydrologic transient storage in a glacial meltwater stream, McMurdo Dry Valleys, Antarctica." Limnology and Oceanography, 49(5), 1884-1895. Ensign, S. H., and Doyle, M. W. (2005). "In-channel transient storage and associated nutrient retention: Evidence from experimental manipulations " Limnology and Oceanography. Lautz, L. K., and Siegel, D. I. (2007). "The effect of transient storage on nitrate uptake lengths in streams: an inter-site comparison." Hydrological Processes, 21(26), 3533-3548. Briggs, M. A., Gooseff, M. N., Arp, C. D., and Baker, M. A. (2008). "Informing a stream transient storage model with two-storage zones to discriminate in-channel dead zone and hyporheic exchange." Water Resources Research, Vol. 45. 7

1-SZ Inadequacy 1-SZ models lump the stream into only 2- zones, mobile and immobile. Breakthrough Curves in the channel are not uniform. Discrimination of immobile zones can lead to better models. 8 June Slug

Multiple Storage Zones Surface Transient Storage (STS) Light, Aerobic, Particulate, Diurnal Temperature Hyporheic Transient Storage (HTS) Dark, Anaerobic , Dissolved, Temperate 9

Competing Model Structure 10

Nested Model Structure 11 HTS MC STS

Numerical Model Runkels OTIS was converted to Matlab, multiple storage zones and a GUI were added. F.D. (Crank-Nicholson) 12 Runkel, R. L., and Broshears, R. E. (1991). "One dimensional transport with inflow and storage (OTIS): A solute transport model for small streams ", Center for Adv. Decision Support for Water Environ. Syst., ed., Tech Rep. 91-01. 6 6

A :1.8 m A HTS :0.5 m A STS :1 m D :0.006 m/s Q :0.01 m/s STS :0.00005 s -1 HTS :0.000005 s -1 U/S Boundary Condition: 1.0 g/m Step 1-8hr @ 200m U/S 13 Conceptual Comparison of Competing versus Nested Transient Storage Module Structure using Identical Parameters

Study Site Laurel Run: 1 st order stream Study Reach: 460-m Drainage Area is 4.66 km of valley-ridge topography, old-growth deciduous trees and mountain laurel. Chesapeake Bay Watershed 14

Tracer Experiments Conservative Tracer: Cl- 3 Constant Rate Injections: June, July, August High->Low Flow 3 Control Sections: 0m, 75m, 460m Campbell Scientific CR- 1000 data loggers with CS547A Cond/Temp Probes 2 Piezometers with Trutrack WT-HR Capacitance Rods 15

MC/STS Parsing 2-SZ model requires 2 more parameters (A HTS, HTS ) Solution: Second BTC in STS A STS Estimation Velocity Transects A/A STS Ratio 16

Field Results 17 Breakthrough Curves of Solute in Main Channel A) June, B) July, C) August ParameterJuneJulyAugust A/A STS 2.0 2.6 Q (x10-2 m/s) 5.762.900.87 Q lat (x10-6 m/s)6.3818.00.73

Optimization Process Global Optimization Algorithm: SCE-UA (1992) (Shuffled Complex Evolution Method University of Arizona) 18 IndividualPoint1 Family/GroupSimplexN+1 Community/TribeComplexM=2.N+1 PopulationSampleS=P.(2N+1) N = Dimension of Problem M = Size of Complex P = Number of Complexes S = Size of Sample 1-SZ Parameters: D, A, A S, 2-SZ Parameters: D, A, A STS, STS, A HTS, HTS

SCE-UA Optimization Process 19 Duan Q., Sorooshian, S., Gupta, V. K. 1994. Optimal Use of the SCE-UA Global Optimization Method for Calibrating Watershed Models. Journal of Hydrology, Vol. 158, 265-284. 6 6

Parameter Optimization 24 Color Coded Parameter Optimization for July First Iteration - BLUE, Last Iteration - RED 1-SZCompeting 2-SZNested 2-SZ

Optimized Parameters Parameter JuneJulyAugust Conceptual 1-SZC-SZN-SZ1-SZC-SZN-SZ1-SZC-SZN-SZC-SZN-SZ D (m/s)0.8310.9081.080.2010.2260.3200.5030.7450.8620.006 (x10^-5 s -1 )5.4111.63.73 STS (x10-5 s -1 )4385502102401602105.00 HTS (x10-5 s -1 )9.1917.78.2714.94.7811.40.500 A (m)0.6180.4110.4180.4710.3310.3390.1870.1340.1371.80 A S (m)0.3300.1290.125 A STS (m)0.2060.2090.1650.1700.05150.05291.00 A HTS (m)0.5890.6060.1450.1290.1510.1550.500 RMSE0.3060.3510.3530.4490.3510.3540.2760.4400.4635 Q (x10-2 m/s) 5.762.900.871.00 Q lat (x10-6 m/s)6.3818.00.730.00 25

BTC Comparisons 30 June July August

Single Storage Zone Metrics Main channel residence time Storage zone residence time Mean travel time 31

the significance of model structure in one- dimensional stream solute transport models with multiple...

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simulation of solute

transient storage model

riffle stream

dimensional transport

stream mixing

stream difficult

stream gradient

stream ecosystems