Coastal Ocean Modeling Core Proposal

Transcription

1 Coastal Ocean Modeling Core Proposal PROJECT SUMMARY The Coastal Ocean Modeling Core will provide coastal ocean model predictions to the Center s three R01 studies in the San Diego South Bay region. The Core addresses the Center s common theme of the effects of marine pollution discharges on the coastal ocean, biological communities, and their subsequent impact on human health. Specifically, the Core will support the R01 research projects by providing hindcasts or forecasts of contaminant, sediment or phytoplankton transport and fate. The evaluation of point source pollution impacts in coastal waters requires resolving the various multi-scale space/time ocean physics (from estuaries to the inner-shelf) of the receiving waters that control the fate and transport of the discharge. For example, estuaries are primarily tidal driven, the surfzone (region near the shoreline) is driven by breaking waves, and the inner-shelf is driven by winds, tides, stratification, and mesoscale processes. Each of these forcing mechanisms have different time- and length-scales, which the coastal ocean modeling system must resolve. After river-released constituent or contaminant leaves the estuary it enters the surfzone. Constituents leaving the surfzone or released from a submerged Publicly Operated Treatment Works experience inner-shelf processes. Many contaminants bind to sediments, and therefore understanding the transport and settling of sediment released from the estuary is also critical. Furthermore, the Tijuana River Estuary is a source of elevated nutrient loading of the coastal ocean, resulting in chronically elevated phytoplankton concentrations exposed to toxic contaminants. The task (and challenge) for the proposed Core is to provide physical ocean state and transport conditions at the appropriate scales to the three R01s. The Center s Coastal Ocean Modeling Core will develop a framework for coupling open-source community-developed wave (SWAN), estuarine circulation (Delft3D) and nested (surfzone to inner-shelf) coastal ocean circulation models (ROMS). This framework will include assimilation of the real-time ocean surface currents measured in the region. In conjunction, the NCSTM sediment transport model and a planktonic ecosystem model will be integrated. The skill in modeling the regional coastal ocean will be evaluated against over a decade s worth of ocean observations in the San Diego South Bay region, and leverage previous modeling developments efforts by the Core PIs which focused on establishing skill to forecast particular ocean processes (surfzone transport, internal waves, wind driven circulation, tidal flows). This framework will be applied to the San Diego South Bay region to provide hindcasts, exposure kernels, and forecasts of the transport and fate of marine pollutants, sediment, and phytoplankton. The result will be estimates of plume transport and fate (dilution) of pollution source (used by all R01 projects), of the toxic, contaminant-laden sediment deposition within this region (R01-1 and R01-3), and bulk phytoplankton concentrations (R01-2) in the San Diego South Bay region. PHS 398/2590 (Rev. 06/09) Page 1 Continuation Format Page

2 Coastal Ocean Modeling Core Proposal SPECIFIC AIMS Statement of Need: The ocean transports and dilutes human generated pollution, sediments that contaminants bind to, and phytoplankton generated toxins. Knowledge of such transport and fate of contaminants and toxins allows estimates of bio-accumulation in consumed shell-fish or direct exposure to humans. As part of the Center for Marine Toxins and Health, this Coastal Ocean Modeling Core will develop a modeling system for pollutant transport and fate in the San Diego South Bay Region. Coastal Ocean Modeling Core Specific Aims: The overall goals of the Core are to develop a modeling system for pollutant, sediment, and phytoplankton transport and fate for the San Diego South Bay coastal region that can be used in a hindcast, nowcast, or forecast mode. The model will cover the very different dynamical regimes of the well-mixed shallow estuary, to the surfzone, and onto the inner shelf. The specific aims for the Coastal Ocean Modeling Core are: Aim 1: Set up and couple the coastal ocean circulation model ROMS, the wave model SWAN, the NCSTM sediment transport model, and the planktonic ecosystem model. Aim 2: Test the modeling system against available oceanographic observations of waves, currents, and temperature. Aim 3: Develop a data assimilation capability for the modeling system Aim 4: Develop a pollution transport and dilution module for each of the land-based (Tijuana River and Punta Bandera) and outfall based (South Bay and Point Loma Ocean Outfalls) sources of pollution in the Southern San Diego region. Aim 5: Develop hindcast and forecast capabilities for the modeling system, particularly the pollution plume transport and fate component, including uncertainties. Provide these estimates to the 3 R01 projects. Make these predictions available as a web application to stakeholders (see letters). Impact: The model results from the Coastal Ocean Modeling Core will be used by the three R01 projects (see the Center diagram in the Center proposal). For example, spatial and time-dependent exposure histories to endocrine disrupting compounds will be developed for R01-3 project Genetic analysis of endocrine disruption in coastal waters. However, this Core can also be considered an intellectual and human-health impacts stand-alone project. New insight about the transport and exchange between well-mixed shallow estuaries, the surfzone, and the inner-shelf will be gained. Almost exclusively, these systems are studied in isolation. Furthermore, predictions of pollutant plumes also will have stand-alone benefit to the coastal communities in the region that are significantly impacted by marine pollution (see support letters). The modeling system is physics-based and thus will be applicable to any coastal region, not just Southern California, and can be used to analyze and forecast exposure to hazards beyond those identified in the Center s R01 projects. These software tools and/or forecasts will be made publicly available to groups responsible for evaluating the risks to human health from discharges and natural hazards. An example of this application is to the San Diego Point Loma outfall, which is controversial for its Advanced Primary level of treatment. The costs of upgrading to Secondary treatment are huge, and so the expected results of such treatment decisions should be quantifiable with verified error estimates to aid in the cost-benefit analysis. PHS 398/2590 (Rev. 06/09) Page 2 Continuation Format Page

3 Coastal Ocean Modeling Core (a) Significance A serious limitation to previous efforts to study the effect of anthropogenic (chemical contaminants) or natural marine toxins on human health is the lack of knowledge regarding the physical context (currents, mixing) and the transport and fate of such contaminants. For example, the amount of contaminant bio-accumulation in a mussel depends on the organism s exposure to the contaminant plume. In the San Diego South Bay region there are distinct coastal ocean pollution sources in an estuary, surfzone, and on the inner-shelf, which each have their own dynamical regime. The pollution plume from each can cross from one regime to another. Pollutants often enter the ocean at the surfzone (e.g., Tijuana river mouth) and are transported along the shoreline. Outfall pollution also can be transported to the shoreline [Kim et al., 2009]. Both of these mechanisms can deliver pollutants to recreational beach users. The effects of transport in the surfzone have been neglected in exposure modeling [i.e., Kim et al., 2009]. Thus, a modeling system that can accurately estimate pollution transport and fate over all three regions is critical to deepening our understanding of the human health impacts of pollution exposure through either direct contact or via the food web. Commonly used shoreline water quality models are completely statistical and tailored for a particular shoreline region [e.g., Frick et al., 2008]. For an example, see Virtual Beach ( These models lack connection to physical transport and dilution and biological mortality processes, These models are tuned to a particular location, poorly handle episodic events, cannot be directly used in other regions without re-tuning, and the causes of model failure are difficult to diagnose. Hydrodynamic and tracer transport models are slowly being adopted both to understand detailed mechanisms of surfzone and nearshore tracer transport and dilution [Clark et al., 2011] and to model nearshore water quality [Zhu et al., 2011]. The former uses a complicated, high spatial- and temporal-resolution model that highly-resolves surfzone mixing and dispersion processes. However, such a model is computationally expensive and does not allow for the inclusion of inner-shelf processes. The latter [Zhu et al., 2011] is a relatively simple depth-averaged model that neglects many relevant processes to pollutant transport include including vertical structure, stratification, and wave forcing. Although perhaps appropriate for shallow, unstratified regions within Biscane Bay, Miami FL, it is not applicable for general coastline regions. In the surfzone, breaking waves are the dominant mechanisms forcing currents and dilution. Obliquely incident breaking waves can drive strong alongshore currents and eddies within the surfzone, The circulation of the inner shelf is driven by tides, local atmospheric forcing (winds, heat, freshwater), and the effects of remote forcing as carried by eddies and coastally-trapped waves. The effect of wind waves is much weaker on the inner-shelf than in the surfzone. The San Diego South Bay region is particularly complicated, due to relatively weak winds and complicated coastline and bathymetry, so no one mechanism dominates. Many existing models, including several in use at SIO, have been shown to work well for other shelf regions. Under most river flow conditions, the TJ River Estuary is classified as vertically mixed, with a barotropic tidal pressure-gradient driven circulation and strong boundary layer mixing. An important modeling challenge is to combine an estuary model, surfzone model (largely driven by waves), and an inner-shelf model, either by nesting the finer surf-zone grid inside the coarser inner shelf model or by using methods that allow for varying grid resolution or via unstructured grids. The proposed modeling system includes estuary, surfzone, and inner-shelf regions. Such a modeling system spanning a diverse dynamical regime has just begun to be explored in any region in the world. Such a modeling system would have stand-along intellectual benefit, revealing significant insights into the transport and connection pathways between these three regions. Fine-scale modeling of coastal ocean waves, currents, and pollutant plume transport and fate across these regimes will be used to provide hindcast and forecast estimates of ocean and pollution state that will provide guidance on exposure risks, exposure pathways, and targeted ocean sampling for the three R01 projects. This Coastal Ocean Modeling system will also be applicable to any coastal region, not just San Diego. The Core PHS 398/2590 (Rev. 06/09) Page 3 Continuation Format Page

4 modeling system also will have stand-alone human health benefits through the public availability of pollutant exposure forecasts to coastal communities, beyond those identified in the Center s R01 project. (b) Innovation We plan to develop a unique and innovative coastal ocean and estuary modeling system for currents, stratification, waves, sediment transport, pollutant transport and dilution, and a planktonic ecosystem model in the San Diego South Bay region. Integrated modeling system for the coastal region within 5-10 km of the shoreline, that includes the inner-shelf, the surfzone, estuary, and transition regions does not yet exist. This modeling system will be tested with observations and used to both hindcast and forecast pollutant plume exposure, sediment transport and deposition, and phytoplankton estimates to the three R01 projects. In addition, model predictions will be made available as a web application for stakeholders, and software will also be made publicly available. The Coastal Ocean Model System, to be developed in Aim 1, tested in Aim 2, and utilized in Aims 3 and 4, will be based on existing open-source community models. The coastal ocean circulation model will be based on ROMS - Regional Ocean Modeling System [Shchepetkin and McWilliams, 2005; Haidvogel et al., 2008]. ROMS is a three-dimensional, free surface, topography-following, hydrostatic, primitive equation model for currents, temperature, and salinity. The model implements both SMP and distributed parallelism and allows for model nesting. Recently, both vortex-force [Uchiyama et al., 2010] and radiation stress [Kumar et al., 2011] wave forcing mechanisms have been included in ROMS, allowing for surfzone application. ROMS is in use to make hindcasts, nowcasts, and forecasts of ocean conditions in a number of more offshore environments. Most relevant to the Coastal Ocean Modeling Core, ROMS is currently used at NASA/JPL to give real-time predictions at 1 km resolution of currents (including tides) and ocean temperature in the Southern California Bight as part of the Southern California Coastal Ocean Observing System (SCCOOS). The wave model that will be used to propagate waves across the shelf and model their breaking is the opensource third-generation wave model SWAN (Simulating WAves Nearshore). It computes random, short-crested wind-generated waves in coastal regions and inland waters. This spectral model that allows for an realistic incident wave field, wave propagation in time and space, shoaling, refraction due to current and depth, currentinduced frequency shifting, whitecapping, bottom friction and depth-induced breaking. The ROMS model can include the National Community Sediment-Transport Model (NCSTM), a sophisticated sediment transport model Warner et al. [2008]. The NCSTM model can solve for the evolution of a multi-layer sediment bed morphology, allowing for both cohesive and non-cohesive sediments. Both kinds of sediments may have as many custom size classes as are needed, meaning specification of grain size, density, settling velocity, critical shear stress for erosion, and erodibility. Sediment is moved by the model currents and redistributed, evolving the sediment bed structure as part of the model. This capability of the model will be very important for the credible calculation of the fate of contaminated sediments, and it has been extensively tested by the Woods Hole USGS. A planktonic ecosystem model also will be embedded within the Coastal Ocean Modeling System. The ROMS model comes with several ecosystem models, including that of Franks et al. [1986]. In addition, the NEMURO ecosystem model [Kishi et al., 2007] has been carefully re-parameterized for the California Current System and Southern California Bight ecosystems based on data collected during the NSF-funded California Current Ecosystem Long-Term Ecological Research program (CCE-LTER). This ecosystem model will provide the larger context for interpreting the dynamics of the target dinoflagellate species. (c) Approach Background: The PIs have unique expertise in developing ocean model hindcast/nowcast/forecast systems. Previously, for the region near Huntington Beach CA, Feddersen developed a real time wave and alongshore current system that accurately reproduced wave height and surfzone alongshore current conditions over 2 months PHS 398/2590 (Rev. 06/09) Page 4 Continuation Format Page

5 Figure 1: Time series of observed (blue) and modeled (red) breaking significant wave height H s (top) and surfzoneaveraged (cross-shore averaged) mean alongshore current (bottom) at Huntington Beach CA from the HB06 experiment. during the SCCOOS-funded HB06 experiment (Figure 1). Because the Huntington Beach region was alongshore uniform and because pollutant transport was not explicitly modeled, the HB06 surfzone model is simpler than the proposed ROMS surfzone model. The San Diego South Bay region has significant alongshore non-uniformities near the Tijuana River mouth and in the region north towards Coronado necessitating use of the more complex ROMS model. PI Cornuelle is the leader of the Consortium on the Ocean s Role in Climate (CORC) modeling component at SIO. The goal of CORC modeling is to provide dynamically consistent state estimates of ocean circulation and density structure - together with surface momentum and buoyancy fluxes, using the MITgcm model. The focus region is the California Current - the equator-ward flowing region within 500 km of the North American West Coast. Cornuelle is also engaged in tide-resolving modeling of the San Diego region and is part of a forecasting project for the Loop Current in the Gulf of Mexico. co-pi Terrill is leading efforts at collecting realtime observations in the San Diego South Bay region and at developing an observation based plume tracking model. Aim 1, Coastal Ocean Model System Setup: The wave (SWAN), circulation (ROMS), sediment transport (NC- STMS), estuary (Delft3D), and planktonic ecosystem models must first be set up for the region and coupled together. Coastal Ocean Circulation Model: The San Diego South Bay regional circulation model will be based on ROMS. It will include three nested components, 1. A San Diego regional component spanning from North of Point Loma to Rosarito Beach Mexico and from within a few 100 m of shore to the 400 m depth at a grid resolution of 400 m. This component will be denoted the outer component. This component will use the SCCOOS Southern California ROMS 1 km grid spacing ocean estimate as an outer boundary condition. 2. A San Diego South bay region component that covers from Mission Beach to the Coronado Islands, from 10 m depth to 200 m depth. This region includes the Point Loma and South Bay Ocean Outfalls and the San Diego Bay. It will be nested within component 1) and will have grid resolution of 150 m. 3. A near-shore surfzone component that covers the region within about 300 m from the shoreline from Punta Bandera to Coronado (30 km), the region dominated by wave forcing effects, This component will be nested PHS 398/2590 (Rev. 06/09) Page 5 Continuation Format Page

6 within 2). It will have cross-shore grid resolution gradually increasing from 2 or 3 meters near the shore to 50 m at the outer edge, and alongshore resolution of 50 m. Wave Model: The SWAN wave model for the San Diego South Bay region will run on a single grid and be used primarily as input for the inner-most nearshore ROMS nest. Initially, coupling to ROMS will be one-way, but eventually two-way coupling will be explored. The SWAN wave model will be initialized on the outer model boundary using Coastal Data Information Program (CDIP) wave model output. Sediment Transport Model: The NCSTM sediment transport model will be coupled to the inner two nests of ROMS. The model will be initialized using the real-time flow rate measurements from the Tijuana River estuary. Observations of sediment size distribution in the estuary will be used to constrain the sediment flux into the ocean. Estuary Model: The Delft3D model will be used in Estuary mode. Tidal forcing and ocean temperatures will be used as estuary mouth boundary conditions. The main channel of the estuary is morphologically stable, and existing bathymetry from the the Tijuana Estuary Research Reserve will be used. Planktonic Ecosystem Model: Both ROMS and the NEMORO planktonic ecosystem models will be embedded within the Coastal Ocean Modeling system to estimate nutrient fluxes and phytoplankton blooms. Both models will be evaluated against historical Chlorophyll and phytoplankton data in the region. This model will be in all ROMS nests. Plume Model: A three-dimensional plume (advection and diffusion) plume model will be developed for the various San Diego South Bay pollution sources. Source input for the Tijuana River Estuary will be based on real-time river flow estimates and the tides. The results of the plume model will give a higher degree of pollutant concentration information than a coarse particle plume model (e.g., Figure 2). Additional Components: High resolution ocean bathymetry is available for the region from SCCOOS. Additional input necessary for the model is the wind field. Modeled WRF or COAMPS winds from regional modeling centers will be used as model input for the San Diego South Bay Coastal Ocean Model. Aim 2, Comparison to Observations: The models will be tested and improved by comparison to observations. A significant number of previous oceanographic observations already have been collected in the San Diego South Bay region, where the land and outfall pollution sources are located. This Core effort will leverage existing San Diego ocean monitoring observations and infrastructure. For example, there are surface current maps generated by high-frequency (HF) radar that provide a 1 km resolution product is available from an array of 5 radars deployed in the U.S.-Mexico border region. Data within the 1 2 km range cell adjacent to the coastline does not represent the transport within the surfzone where the pollution sources and the dominant transport occurs (e.g., Figure 2 of Center Proposal). These surface currents are presently used for estimating the location of plumes offshore the surfzone, but have significant uncertainty in the surfzone and nearshore waters that are not covered. This array is maintained by the Coastal Ocean Research and Development Center (CORDC) at SIO led by co-pi Terrill. HF radar has growing coverage across U.S. coastal waters, with approximately 140 radars now operating across the Gulf, west, and east coasts. In addition, a multi-year record of stratification and currents directly above the South Bay Ocean Outfall and (a shorter record) at the end of the Imperial Beach Pier are available for model validation. PD Feddersen was PI on the IB09 experiment which obtained detailed surfzone and inner shelf waves, currents and water-quality observations during the fall of 2009 in Imperial Beach, CA. Upwelling, including internal tide surges to surf, are one potential contributor to phytoplankton blooms. SCCOOS maintains a HAB surveillance program which can be used to test the planktonic ecosystem model. Long term measurements of internal waves and Chlorophyll have been made off of the SIO pier which also can be used to test the NPZ model. Additional observations collected by USGS and the San Diego Sanitation District will also be utilized to test and constrain the model, as well as any future observations. PHS 398/2590 (Rev. 06/09) Page 6 Continuation Format Page

7 Aim 3, Data Assimilation: After the models have been successful in statistical tests against the observations, data assimilation (or state estimation) will be used to synchronize the model with the observations for hindcasts and forecasts. The primary assimilation method implemented in ROMS is four-dimensional variational optimization (4DVAR). The 4DVAR method uses the adjoint and tangent-linear versions of the ROMS model to optimize the model controls (initial conditions, boundary conditions, and forcing) so that a free forward integration of the model with the altered controls matches the observations to within the expected error during assimilation time window. For relatively short windows, as are envisioned here, the balance and smoothing constraints that are now available as part of ROMS must be employed. The nowcasts and forecasts will be run starting in 2009, but can extend back to 2007 if necessary for better testing, since the HF radar surface current observations and other SCCOOS observations are available. The model will be run in a series of non-overlapping update cycles. In each cycle, the final state from the previous cycle will be run forward using forcing and boundary conditions from Southern California Bight ROMS. The model will be sampled at the space-time locations of the observations, and the differences will be back-projected using the adjoint model to produce adjusted controls. This adjustment cycle will continue until the cost function (which penalizes both model-data misfits and control adjustments) is no longer decreasing. The optimized controls will be used to run the model forward through the assimilation window and onward to forecast out for as long as skill is seen, probably up to a week. The forecast will use forecasts of atmospheric forcing and ocean boundary conditions when and where they are available, and use climatology otherwise. The hindcasts and forecasts will be compared to observations to assess skill and improve the implementation. Once the system works well on existing observations, it will be implemented using the current observations to make near-real-time forecasts for dissemination to the related projects and to the public. Aim 4, Hindcasts, Exposure Kernels, and Forecasts: The Core will provide the R01 projects with specific hindcasts of the ocean/estuary state during periods of interest to provide specific guidance for water sampling or ocean state estimates during and prior to water sampling. Time-exposure histories for various sampling regions will be provided. For example, exposure of R01-1 mussel outplants to plume water or turbot (flat-fish with a limited range) to contaminant-laden sediment will be estimated. In addition, model-based fine-grained exposure kernels (analogous to Figure 3) for water quality degradation at various locations will be developed. In and of itself this will have significant human-health impacts, but will also be useful to the R01-1 and R01-3 projects in mussel or fish outplant sampling. A real-time forecast capability for the Coastal Ocean Modeling system will be developed using assimilated observations and predicted waves and winds. The existing observations will be used to test the skill of the forecast capability for currents and temperature at predictions of one, three, and five days. Model predictions of plume transport and fate will be made available on the web, which will be of great use to stakeholders (see support letters). The Core will interface with the R01 projects providing them with pollution/sediment/phytoplankton transport and fate forecasts. Timeline: YEAR 1: Tasks include: Set up (construct grids and supply forcing and boundary conditions) for SWAN and the three ROMS models at various resolutions. Each model is first set up and run stand-alone in order to test and refine each component before coupling the grids together. Set up SWAN grid with CDIP outer boundary conditions. Test against CDIP model predictions and 2009 wave-buoy observations. Set up surfzone model grid with simple wave stress forcing, compare to surfzone observations from 2009 IB09 experiment and USGS study. Gather atmospheric forcing and JPL ROMS boundary conditions and start test runs for comparison with HF radar, buoy and other regional observations. (Aims 1 & 2) YEAR 2: Tasks include: Implement ROMS nesting. Initially implement one-way nesting from outer-grid to the inner grid. Integrate the NCSTS sediment transport model into the ROMS nests. Develop the plume model for the TJ River Estuary, Punta Bandera, and South Bay Ocean Outfall pollution sources. Begin developing assimilation capabilities. (Aims 1, 2, 3, & 4) PHS 398/2590 (Rev. 06/09) Page 7 Continuation Format Page

8 Principal Investigator/Program Director(Last, First, Middle): Figure 2: Snapshot of the Tijuana River (TJR) plume track model (upper panel) and the histogram of the particles within the near-coast cell (lower panel). The hourly released particles at the TJR mouth (black plus mark) are tracked for three days, and the color of particle represents the age of the particle since it was released. Figure 3: Coastal exposure kernels (essentially a probability distribution function) based on the plume tracking model (Figure 2) for the Tijuana River plume in (left) all season, (middle) summer, and (right) winter. YEARS 3-4: Tasks include: furthering the assimilation capabilities of the modeling system. Provide the R01 groups with specific hindcasts of the ocean/estuary state during periods of interest. Provide specific guidance for water sampling. Provide time-exposure histories for various sampling regions. For example, exposure of R01-1 mussel outplants to plume water or Turbot (flat-fish with a limited range) to contaminant-laden sediment. Develop model-based fine-grained exposure kernels (e.g., Figure 3) for water quality degradation at various locations. In and of itself this will have significant human-health impacts, but will also be useful to the projects R01-1,3 projects in mussel or fish outplant sampling. (Aims 3, 4, & 5) YEARS 4-5: Develop the real-time forecast capabilities of the Coastal Ocean Modeling system using assimilated observations and predicted waves and winds. Use the existing observations to test the skill of the forecast capability for currents and temperature at predictions of one, three, and five days. Make model predictions of plume transport and fate available on the web. Continue to interface with the R01 projects providing them with pollution/sediment/phytoplankton transport and dilution estimates. (Aims 4 & 5) PHS 398/2590 (Rev. 06/09) Page 8 Continuation Format Page

9 Literature Cited Clark, D. B., F. Feddersen, and R. T. Guza, Boussinesq modeling of surfzone tracer plumes, part 2: Tracer plumes and cross-shore dispersion, J. Geophys. Res., in press, Franks, P., J. Wroblewski, and G. Flierl, Behavior of a simple plankton model with food-level acclimation by herbivores, Marine Biology, 91(1), , doi: /bf , Frick, W. E., Z. Ge, and R. G. Zepp, Nowcasting and forecasting concentrations of biological contaminants at beaches: A feasibility and case study, Env. Sci. & Tech., 42(13), , doi: /es703185p, Haidvogel, D. B., et al., Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System, J. Computational Physics, 227(7), , doi: /j.jcp , Kim, S. Y., E. J. Terrill, and B. D. Cornuelle, Assessing Coastal Plumes in a Region of Multiple Discharges: The US-Mexico Border, Environmental Science & Technology, 43(19), , doi: /es900775p, Kishi, M. J., et al., NEMURO - a lower trophic level model for the North Pacific marine ecosystem, Ecological Modelling, 202(1-2, SI), 12 25, doi: /j.ecolmodel , 11th PICES Annua Meeting, Qingdao, PEOPLES R CHINA, 2002, Kumar, N., G. Voulgaris, and J. C. Warner, Implementation and modification of a three-dimensional radiation stress formulation for surf zone and rip-current applications, Coastal Eng., 58(12), , doi: /j.coastaleng , Shchepetkin, A., and J. McWilliams, The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model, Ocean Modelling, 9(4), , doi: /j.ocemod , Uchiyama, Y., J. C. McWilliams, and A. F. Shchepetkin, Wave-current interaction in an oceanic circulation model with a vortex-force formalism: Application to the surf zone, Ocean Modelling, 34(1-2), 16 35, doi: /j.ocemod , Warner, J. C., C. R. Sherwood, R. P. Signell, C. K. Harris, and H. G. Arango, Development of a three-dimensional, regional, coupled wave, current, and sediment-transport model, Computers & Geosciences, 34(10), , doi: /j.cageo , Zhu, X., J. D. Wang, H. M. Solo-Gabriele, and L. E. Fleming, A water quality modeling study of non-point sources at recreational marine beaches, Water Research, 45(9), , doi: /j.watres , PHS 398/2590 (Rev. 06/09) Page 9 Continuation Format Page