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The following are a few examples of our recent and ongoing research.

1. Watershed Biogeochemical Processes and Large-Scale Hydrologic Modeling: To make the application of process-based models practical for large watersheds in the Great Lakes region and other parts of the world, we recently developed the PAWS (Process-based Adaptive Watershed Simulator) model (Shen and Phanikumar, 2010). The model uses a stable, non-iterative coupling method to link surface and subsurface processes, uses the finite-volume method and combines some of the best available algorithms to speed up computations. The model is suitable for quantifying fluxes of water, nutrients (C,N,P), sediment and bacteria at downstream receiving water bodies such as lakes and oceans to help manage resources and to protect the public from exposure to contaminated waterways (by making timely predictions; see the section on nearshore processes below). Refinement of process descriptions and model testing using new types of data (e.g., satellite products, data from sensor networks) continues to be an area interest in our group.

Key processes simulated by the PAWS model and (right) typical computational grids used

   

Comparison of PAWS with CATHY and ParFlow - models using fully three-dimensional subsurface modules simulating Hortonian and Dunne runoff processes (Shen and Phanikumar, 2010)

   

Map showing the Grand River and Saginaw Bay watersheds - the two largest watersheds (by drainage area) in the state of Michigan. The watersheds drain to lakes Michigan and Huron

Comparison of observed (USGS) and simulated (PAWS) streamflows in the Grand River watershed

   

 

   

Multiple-year-average evapotranspiration (ET) in the Grand River (left) and Saginaw Bay (right) watersheds

   

Relevant Publications:

  • J. Niu and M.S. Phanikumar, Modeling Watershed-Scale Solute Transport Using an Integrated Hydrologic Model with Application to Bacterial Fate and Transport Modeling (2014, in review)
  • J. Niu, C. Shen, S.G. Li and M.S. Phanikumar, Quantifying Water Storage Changes in Regional Great Lakes Watersheds Using GRACE, MODIS Products and Coupled Subsurface - Land Surface Process Models (2013, in review)
  • R.M. Maxwell, M. Putti, S. Meyerhoff, J.-O. Delfs, I.M. Ferguson, V.Y. Ivanov, J. Kim, O. Kolditz, S.J. Kollet, M. Kumar, S. Lopez, J. Niu, C. Paniconi, Y. -J. Park, M.S. Phanikumar, C.P. Shen, E.A. Sudicky and M. Sulis, Surface-Subsurface Model Intercomparison: A First Set of Benchmark Results to Diagnose Integrated Hydrology and Feedbacks. Water Resources Research, vol. 50(2), pp.1531 - 1549, doi: 10.1002 / 2013WR013725 (2014)
  • C. Shen, J. Niu, M.S. Phanikumar, Evaluating Controls on Coupled Hydrologic and Vegetation Dynamics in a Humid Continental Climate Watershed Using a Subsurface - Land Surface Processes Model, Water Resources Research, vol. 49, pp. 2552 - 2572, doi: 10.1002/wrcr.20189 (2013)
  • L.M. Fry, T.S. Hunter, M.S. Phanikumar, V. Fortin and A.D. Gronewold, Identifying Streamgage Networks for Maximizing the Effectiveness of Regional Water Balance Modeling, Water Resources Research, vol. 49, pp. 2689 - 2700, doi: 10.1002/wrcr.20233 (2013)
  • C. Shen and M.S. Phanikumar, A Process-Based, Distributed Hydrologic Model Based on a Large-Scale Method for Surface - Subsurface Coupling, Advances in Water Resources, vol. 33(12), pp. 1524 - 1541, doi: 10.1016 / j.advwatres.2010.09.002 (2010)

2. Nearshore Processes and Biophysical Modeling in the Great Lakes: Coastal water quality is important not only from the point of human health and exposure of beach-goers to contaminated water at our nation's beaches but also because poor water quality negatively impacts local economies. The development and application of predictive models is imporatant to protect the public and to manage coastal resources effectively.

 
Computational grids for the Great Lakes
 

We use field experiments and numerical models to understand the relative importance of different processes in the nearshore region of large lakes such as Lake Michigan and Lake Huron and to improve our descriptions of complex biological and physical processes in mathematical models. We are planning to combine watershed models such as PAWS (described above) to provide loading / boundary conditions for lake circulation and transport models. We are also refining the descriptions of physical and biological processes in our models (e.g., sediment resuspension, nearshore transport in the presence of currents and waves) and using new data (e.g., data from Lagrangian drifters and remote sensing of nearshore processes) to improve models. The ultimate goal of this research is to make predictive modeling an attractive alternative to more traditional approaches based on observation for managing coastal resources. In summer 2008, we deployed five bottom-mounted Doppler profilers, conducted a dye release study and measured the levels of indicator bacteria such as Escherichia coli in several beaches in Southern Lake Michigan.

A 1200 kHz Sentinel ADCP and frame ready for deployment (2008)

Observed and simulated horizontal currents (vertically-averaged) in S. Lake Michigan (Indiana beaches, 2006)

 

A 2000 kHz Aquadopp profiler being deployed in Lake Michigan (2008)

Observed and simulated profiles of vertical currents in S. Lake Michigan (Indiana beaches, 2006)

 

Observed and simulated E. coli levels near Indiana beaches (2004)

 

Insights gained from these (and other similar) studies are being used to develop better models to address questions related to coastal water quality.

Relevant Publications:

  • T.D. Nguyen, P. Thupaki, E.J. Anderson and M.S. Phanikumar, Summer Circulation and Exchange in the Saginaw Bay - Lake Huron System, J. Geophys. Res. Oceans (2013, in review)
  • P. Thupaki, M.S. Phanikumar, D.J. Schwab, M.B. Nevers and R.L. Whitman, Evaluating the Role of Sediment-Bacteria Interactions on Escherichia coli Concentrations at Beaches in Southern Lake Michigan, J. Geophys. Res. Oceans, vol. 118(12), pp. 7049-7065, doi: 10.1002 / jgrc.20481 (2013)
  • P. Thupaki, M.S. Phanikumar and R.L. Whitman, Solute Dispersion in the Coastal Boundary Layer of Southern Lake Michigan, J. Geophys. Res. Oceans, vol. 118(3), pp. 1606-1617, doi: 10.1002/jgrc.20136 (2013)
  • Z. Ge, R.L. Whitman, M.B. Nevers, M.S. Phanikumar and M.N. Byappanahalli, Nearshore Hydrodynamics as Loading and Forcing Factors for Escherichia coli Contamination at an Embayed Beach, Limnology and Oceanography, Vol. 57(1), pp. 362-381, doi:10.4319/lo.2012.57.1.0362 (2012)
  • Z. Ge, R.L. Whitman, M.B. Nevers and M.S. Phanikumar, Wave-induced Mass Transport Affects Daily Escherichia coli Fluctuations in Nearshore Water, Environmental Science & Technology, Vol. 46, doi: 10.1021 / es203847n (2012)
  • P. Thupaki, M.S. Phanikumar, D. Beletsky, D.J. Schwab, M.B. Nevers and R.L. Whitman, Budget Analysis of Escherichia coli at a Southern Lake Michigan Beach, Environmental Science & Technology, vol. 44, no. 3, pp. 1010-1016, doi: 10.1021/es0902232a (2010)
  • M. Wong, L. Kumar, T.M. Jenkins, I. Xagoraraki, M.S. Phanikumar, and J. B. Rose, Evaluation of Public Health Risks at Recreational Beaches in Lake Michigan via Detection of Enteric Viruses and a Human-Specific Bacteriological Marker, Water Research, 43(4), p. 1137-1149, doi: 10.1016/j.watres.2008.11.051 (2009)
  • L. Liu, M.S. Phanikumar, S.L. Molloy, R.L. Whitman, M.B. Nevers, D.A. Shively, D.J. Schwab, J.B. Rose, Modeling the Transport and Inactivation of E. coli and Enterococci in the Nearshore Region of Lake Michigan, Environmental Science & Technology , Vol. 40, No. 16, pp. 5022-5028, doi: 10.1021/es060438k (2006)

3. River Research and Groundwater - Surface Water Interactions: Integrated watershed modeling using models such as PAWS (described above) offers one example of GW-SW interactions at the river basin scale. Several small-scale processes (e.g., interactions with river bed sediments / hyporheic exchange and surface storage zones) control the dynamics of solute transport at the river reach scale. Understanding these small-scale processes is important to accurately describe the transport of conservative (e.g., salt, rhodamine) and reactive (e.g., nutrients) solutes at the river reach scale and to address many questions involving biogeochemical cycles. Research in our group aims to improve our ability to describe solute transport in rivers and streams using improved mathematical models and field observations. As examples, we recently demonstrated that using the shear-flow dispersion theory and data from Doppler current profilers we can estimate the longitudinal dispersion coefficeint in rivers quickly and reliably (Shen et al., 2010). The dispersion coefficient is a parameter that introduces considerable uncertainty into solute transport modeling and traditional methods of estimating this parameter (using tracer-based approaches) are labor-intensive and expensive and the methods are often impractical for large rivers (width:depth ratios > 50). Similarly, using wavelet decomposition of observed high-resolution velocity data in streams, we demosntrated that the sizes of surface storage zones can be estimated (i.e., by separating the stream channel into regions of high- and low velocity, Phanikumar et al., 2007). Separting the contributions of surface and hyporheic storage zones is important to correctly interpret solute transport data and the rates of microbially-mediated reactions (e.g., nutrient uptake rates). Recently, we examined solute transport dynamics in large rivers in an attempt to translate our understanding of small-stream transport to large rivers (Anderson and Phanikumar, 2011) and proposed new approaches for describing transport in large rivers.

Typical velocity data from ADCP transects from rivers in the US Midwest used for estimating the longitudinal dispersion coefficient (below)

   

Comparison of longitudinal dispersion coeffcients for several Midwestern rivers using two methods (a) the traditional tracer-based apprach and (b) the ADCP method based on the shear-flow dispersion theory

   

Relevant Publications:

  • I. Mendoza-Sanchez, M.S. Phanikumar, J. Niu, J.R. Masoner, I. M. Cozzarelli and J.T. McGuire, Quantifying Wetland-Aquifer Interactions in a Humid Subtropical Climate Region: An Integrated Approach, J. Hydrology, vol. 498, pp. 237-253, doi: 10.1016/j.jhydrol.2013.06.022 (2013)
  • H. Zhang, F. Liu, M.S. Phanikumar and M.M. Meerschaert, A Novel Numerical Method for the Time Variable Fractional Order Mobile-Immobile Advection-Dispersion Model, Computers & Mathematics with Applications, doi: http://dx.doi.org/10.1016/j.camwa.2013.01.031 (2013)
  • E.J. Anderson and M.S. Phanikumar, Surface Storage Dynamics in Large Rivers: Comparing Three-Dimensional Particle Transport, 1D Fractional Derivative and Multi-Rate Transient Storage Models, Water Resources Research, Vol. 47, No. 9, W09511, doi: 10.1029/2010WR010228 (2011)
  • C. Shen, J. Niu, E.J. Anderson and M.S. Phanikumar, Estimating Longitudinal Dispersion in Rivers Using Acoustic Doppler Current Profilers, Advances in Water Resources, 33(6), pp. 615-623, doi: 10.1016 / j.advwatres. 2010.02.008 (2010)
  • C. Shen and M.S. Phanikumar, An Efficient Space-Fractional Dispersion Approximation for Stream Solute Transport Modeling, Advances in Water Resources, 32(10), pp. 1482-1494, doi: 10.1016 / j.advwatres. 2009.07.01 (2009)
  • C. Shen, M.S. Phanikumar, T.T. Fong, I. Aslam, S.L. Molloy and J.B. Rose, Evaluating Bacteriophage P22 as a Tracer in a Complex Surface Water System: The Grand River, Michigan, Environmental Science & Technology, Vol. 42, No. 7, pp. 2426 - 2431, doi: 10.1021/es02317t (2008)
  • M.S. Phanikumar, I. Aslam, C. Shen, D.T. Long and T.C. Voice, Separating Surface Storage from Hyporheic Retention in Natural Streams Using Wavelet Decomposition of Acoustic Doppler Current Profiles, Water Resources Research, Vol. 43, No. 5, W05406, doi: 10.1029 / 2006WR005104 (2007)