Technical Papers
Oct 25, 2018

Applications of Linked and Nonlinked Complex Models for TMDL Development: Approaches and Challenges

Publication: Journal of Hydrologic Engineering
Volume 24, Issue 1

Abstract

The choice of a model for total maximum daily load (TMDL) development for impaired water bodies depends mainly on the modeling objectives and system complexity. System complexity and modeling objectives, in turn, determine the required model complexity. Nonlinked or stand-alone complex models or linked models are generally selected for complex systems that consist of large watersheds with urban and rural areas and with a network of flow-controlled water impoundments (e.g., lakes and reservoirs) and estuaries. As an example, we present herein three case studies to demonstrate the role that complex nonlinked and linked models play in the development of complex TMDL studies. Case 1 is the Cannon River watershed, which uses a nonlinked complex model known as Hydrological Simulation Program—FORTRAN (HSPF), which is the core watershed model of the Better Assessment Science Integrating Point and Non-Point Sources (BASINS). Case 2 is the Chesapeake Bay watershed, which uses linked models: air-shed, watershed loading, and estuary models. Note that Case 2 uses the Chesapeake Bay Phase 5.3 Community Watershed Model, which is a version of the HSPF model. Case 3 is the Sougahatchee Creek watershed, which uses three linked models: Loading Simulation Program in C++ (LSPC), Water Quality Simulation Program (WASP), and Environmental Fluid Dynamics Code (EFDC). The results obtained from the case study reports show an absence of quantitative model performance metrics for Case 3 and limited performance results for Cases 1 and 2. For Case 2—a linked model case—model performance is only available for the loading model but not for the other linked models. The use of complex nonlinked models or linked models is not a guarantee of a good modeling practice by itself unless the models are supported by performance metrics, such as Nash–Sutcliffe efficiency (NSE) values that are greater than or equal to 0.65. Only Case 2 reported simulated water quality constituent NSE values for the watershed loading model, and reported values were less than zero. The low predictive performances gleaned from the case study reports can be attributed to inadequate system representation, model structure uncertainty, and poor data quality. Unless complex stand-alone and linked models are supported by accurate system representation and good quality input data, their application for TMDL development may not be scientifically defensible.

Get full access to this article

View all available purchase options and get full access to this article.

References

ADEM (Alabama Department of Environmental Management). 2008. “Final total maximum daily load nutrients and OE/DO. Pepperell Branch (AL03150110-0201-700; Nutrients) and Sougahatchee Creek Embayment (Yates Reservoir) (AL03150110-0204-101; Nutrients and OE/DO).” Accessed July 12, 2017. http://adem.alabama.gov/programs/water/wquality/tmdls/FinalSougahatcheeCreekWatershedNutrientandOEDOTMDL.pdf.
Ahuja, L. R., J. C. Ascough II, and O. David. 2005. “Developing natural resource models using the object modeling system: Feasibility and challenges.” Adv. Geosci. 4: 29–36. https://doi.org/10.5194/adgeo-4-29-2005.
Ames, D. P., C. Michaelis, A. Anselmo, L. Chen, and H. Dunsford. 2008. “MapWindow GIS. In Encyclopedia of GIS, 633–634. New York: Springer.
Argent, R. M. 2004. “An overview of model integration for environmental applications: Components, frameworks and semantics.” Environ. Modell. Software 19 (3): 219–234. https://doi.org/10.1016/S1364-8152(03)00150-6.
Babendreier, J. E., and K. J. Castleton. 2005. “Investigating uncertainty and sensitivity in integrated, multimedia environmental models: Tools for FRAMES-3MRA.” Environ. Modell. Software 20 (8): 1043–1055. https://doi.org/10.1016/j.envsoft.2004.09.013.
Battin, A. T., R. Kinerson, and M. Lahlou. 1998. “EPA’s better assessment science integrating point and non-point sources (BASINS)—A powerful tool for managing watersheds.” In Proc., GISHydro98, 1998 ESRI User Conf. Washington, DC: US Environmental Protection Agency and Office, Water-Office of Science and Technology.
Bharati, L., C. Rodgers, T. Erdenberger, M. Plotnikova, S. Shumilov, P. Vlek, and N. Martin. 2008. “Integration of economic and hydrologic models: Exploring conjunctive irrigation water use strategies in the Volta Basin.” Agric. Water Manage. 95 (8): 925–936. https://doi.org/10.1016/j.agwat.2008.03.009.
Bicknell, B. R., J. C. Imhoff, J. L. Kittle Jr., T. H. Jobes, A. S. Donigian Jr., and R. Johanson. 2011. Hydrologic simulation program: FORTRAN, HSPF version 12 users manual. Reston, VA: USEPA.
Cerco, C. F., and T. Cole. 1993. “Three-dimensional eutrophication model of Chesapeake Bay.” J. Environ. Eng. 119 (6): 1006–1025. https://doi.org/10.1061/(ASCE)0733-9372(1993)119:6(1006).
Costanza, R., A. Voinov, R. Boumans, T. Maxwell, F. Villa, L. Wainger, and H. Voinov. 2002. “Integrated ecological economic modeling of the Patuxent River watershed, Maryland.” Ecol. Monogr. 72 (2): 203–231. https://doi.org/10.1890/0012-9615(2002)072[0203:IEEMOT]2.0.CO;2.
DiToro, D. 2001. Sediment flux modeling. New York: Wiley.
Dubois, G., M. Schulz, J. Skøien, L. Bastin, and S. Peedell. 2013. “eHabitat, a multi-purpose web processing service for ecological modeling.” Environ. Modell. Software 41 (Mar): 123–133. https://doi.org/10.1016/j.envsoft.2012.11.005.
Geller, G. N., and W. Turner. 2007. “The model Web: A concept for ecological forecasting.” In Proc., Geoscience and Remote Sensing Symp., 2469–2472. Piscataway, NJ: IEEE.
Gregersen, J. B., P. J. A. Gijsbers, and S. J. P. Westen. 2007. “OpenMI: Open modelling interface.” J. Hydroinf. 9 (3): 175–191. https://doi.org/10.2166/hydro.2007.023.
Haith, D. A., and L. L. Shoemaker. 1987. “Generalized watershed loading functions for stream-flow nutrients.” Water Resour. Bull. 23 (3): 471–478. https://doi.org/10.1111/j.1752-1688.1987.tb00825.x.
Johnson, B. H., K. W. Kim, R. E. Heath, B. B. Hsieh, and H. L. Butler. 1993. “Validation of three-dimensional hydrodynamic model of Chesapeake Bay.” J. Hydraul. Eng. 119 (1): 2–20. https://doi.org/10.1061/(ASCE)0733-9429(1993)119:1(2).
Krause, P., D. P. Boyle, and F. Bäse. 2005. “Comparison of different efficiency criteria for hydrological model assessment.” Adv. Geosci. 5 (Dec): 89–97. https://doi.org/10.5194/adgeo-5-89-2005.
Linker, L. C., G. W. Shenk, R. L. Dennis, and J. S. Sweeney. 2000. “Cross-media models of the Chesapeake Bay watershed and airshed.” Water Qual. Ecosyst. Model. 1 (1–4): 91–122. https://doi.org/10.1023/A:1013934632305.
Mohamoud, Y. M. 2007. “Enhancing hydrological simulation program-FORTRAN model channel hydraulic representation.” JAWRA J. Am. Water Resour. Assoc. 43 (5): 1280–1292. https://doi.org/10.1111/j.1752-1688.2007.00113.x.
Mohamoud, Y. M., and L. M. Prieto. 2012. “Effect of temporal and spatial rainfall resolution on HSPF predictive performance and parameter estimation.” J. Hydrol. Eng. 17 (3): 377–388. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000457.
Mohamoud, Y. M., A. C. Sigleo, and R. S. Parmar. 2009. Modeling the impacts of hydromodification on water quantity and quality. Washington, DC: USEPA.
MPCA (Minnesota Pollution Control Agency). 2015. “Cannon river watershed HSPF model development project. Final report.” Accessed June 18, 2017. https://www.pca.state.mn.us/sites/default/files/wq-ws4-23d.pdf.
OpenMI. 2009. “The Open-MI life project website.” Accessed July 22, 2017. http://www.openmi-life.org/.
Ritter, A., and R. Muñoz-Carpena. 2013. “Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments.” J. Hydrol. 480 (Feb): 33–45. https://doi.org/10.1016/j.jhydrol.2012.12.004.
Rosegrant, M. W., C. Ringler, D. C. McKinney, X. Cai, A. Keller, and G. Donoso. 2000. “Integrated economic-hydrologic water modeling at the basin scale: The Maipo River basin.” Agric. Econ. 24 (1): 33–46. https://doi.org/10.1111/j.1574-0862.2000.tb00091.x.
Ross, M., J. Geurink, A. Aly, P. Tara, K. Trout, and T. Jobes. 2004. Integrated hydrologic model (IHM). Volume 1: Theory manual. Tampa, FL: Water Resources Group, Dept. of Civil Engineering, Univ. of South Florida.
Rossman, L. A. 2010. Storm water management model, user’s manual, version 5. Cincinnati: Water Supply and Water Resources Division and National Risk Management Research Laboratory, USEPA.
Shirmohammadi, A., et al. 2006. “Uncertainty in TMDL models.” Trans. ASABE 49 (4): 1033–1049. https://doi.org/10.13031/2013.21741.
Shoemaker, L., T. Dai, J. Koenig, and M. Hantush. 2005. TMDL model evaluation and research needs. Cincinnati: USEPA and National Risk Management Research Laboratory.
USEPA (US Environmental Protection Agency). 2000. Ambient water quality criteria recommendations, information supporting the development of state and tribal nutrient criteria, rivers and streams in nutrient Ecoregion XI. Washington, DC: USEPA.
USEPA (US Environmental Protection Agency). 2001. Better assessment science integrating point and nonpoint sources BASINS Version 3.0 user’s manual. Washington, DC: USEPA and Office of Water.
USEPA (US Environmental Protection Agency). 2010a. Chesapeake bay phase 5 community watershed model. Section 11: Riverine simulation. Washington, DC: USEPA.
USEPA (US Environmental Protection Agency). 2010b. “Chesapeake bay total maximum daily load for nitrogen, phosphorus and sediment.” Accessed September 9, 2017. https://www.epa.gov/sites/production/files/2014-12/documents/cbay_final_tmdl_exec_sum_section_1_through_3_final_0.pdf.
USEPA (US Environmental Protection Agency). 2011. “Chesapeake bay modeling phase calibration.” Accessed January 23, 2018. ftp://ftp.chesapeakebay.net/Modeling/phase5/calibration_pdfs/p532_2011_05/.
USEPA (US Environmental Protection Agency). 2012. Better assessment science integrating point and nonpoint sources (BASINS version 4.1). Washington, DC: USEPA.
USEPA (US Environmental Protection Agency). 2015. “TMDL modeling toolbox.” Accessed October 30, 2017. https://www.epa.gov/sites/production/files/2015-10/documents/toolbox-overview.pdf.
van Delden, H., J. van Vliet, D. T. Rutledge, and M. J. Kirkby. 2011. “Comparison of scale and scaling issues in integrated land-use models for policy support.” Agric. Ecosyst. Environ. 142 (1): 18–28. https://doi.org/10.1016/j.agee.2011.03.005.
van Evert, F., D. Holzworth, R. Muetzelfeldt, A. Rizzoli, and F. Villa. 2005. “Convergence in integrated modeling frameworks.” In Proc., MODSIM 2005 Int. Congress on Modelling and Simulation, 1539–1545. Canberra, Australia.
Voinov, A., and C. Cerco. 2010. “Model integration and the role of data.” Environ. Modell. Software 25 (8): 965–969. https://doi.org/10.1016/j.envsoft.2010.02.005.
Whittemore, R. C., and J. Beebe. 2000. “EPA’s BASINS model: Good science or serendipitous modeling.” J. Am. Water Resour. Assoc. 36 (3): 493–499. https://doi.org/10.1111/j.1752-1688.2000.tb04281.x.
Wool, T. A., R. B. Ambrose, J. L. Martin, and E. A. Comer. 2003. Water quality analysis simulation program (WASP) version 6.0, Draft user’s manual. Atlanta, GA: US Environmental Protection Agency.

Information & Authors

Information

Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 24Issue 1January 2019

History

Received: Oct 24, 2017
Accepted: Jul 10, 2018
Published online: Oct 25, 2018
Published in print: Jan 1, 2019
Discussion open until: Mar 25, 2019

Permissions

Request permissions for this article.

Authors

Affiliations

Yusuf Mohamoud, Ph.D. [email protected]
P.E.
Director, Natural Resources, Environment, and Technology Institute, Duluth, GA 30096 (corresponding author). Email: [email protected]
Harry Zhang, Ph.D. [email protected]
P.E.
Program Director, Water Research Foundation, 1199 N. Fairfax St., Suite 900, Alexandria, VA 22314. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share