Table of Contents



Physical Science Team (PST) Cover Letter to PMC (click here)


PST Review of the Implementation of  FATHOM in Florida Bay (click here)


FATHOM Modeling Group’s Response to PST Review (click here)


PST Review of the Implementation of RMA10 in Florida Bay (click here)






























TO:             Interagency PMC for the Florida Bay and Adjacent Marine Systems Science Program

FROM:        Tom Lee, Peter Ortner, and DawnMarie Welcher, Physical Science Team


SUBJECT:     Review of ongoing Florida Bay physical modeling projects


Attached please find the final reports the PST developed, at the specific request of the PMC, on FATHOM and RMA10.  Initially, both modeling groups (FATHOM and RMA10) were asked to furnish the PST copies of their final reports.  While the FATHOM group had to generate this report, the ACoE folks furnished one that was dated last October.  Regardless, PST members were asked to provide substantive reviews of one or the other of these reports or both. 


A number of PST members responded and summaries of their responses were created and, along with the individual reviews, sent back to all the PST members to obtain any additional input.  The revised summaries and the individual reviews were then sent to both modeling groups to give them an opportunity, should they wish to avail themselves, to provide the PST a 1-2 page response or comment we could additionally attach to the summary report that would be given to the PMC.  The FATHOM group did so (also attached), but the WESLAB group (ACoE) did not.






























Review of the Implementation of FATHOM in Florida Bay


for the Florida Bay and Adjacent Marine Systems Science Program

by Members of the Physical Science Team




Everglades National Park (ENP) has supported the development of FATHOM, a dynamic mass-balance model, for use in modeling salinity in Florida Bay.  Results of this work are described in the technical report, " FATHOM: Model Description and Initial Application to Florida Bay," (undated).  Copies of these reports were furnished to the Physical Science Team by the authors of the model (B.J Cosby, W.K. Nuttle and J.W. Fourqurean) for review.  This report describes the model at an intermediate stage of development.  A final product is expected by the end of 1999.


The primary purpose of this review is to assist the FATHOM modeling group by providing critical comments and insights of physical scientists with experience working in Florida Bay.  Our intent is to provide a critique of model formulation and application in order to evaluate the model's potential and to suggest model improvements that will eventually lead toward scientifically defensible model predictions. These comments also provide the modelers with an opportunity to inform the PMC of their recent efforts towards these goals.  The comments and the response from the modeling team will be compiled into a single report that will form part of  the PMC's documentation of the overall modeling program in Florida Bay.


The main body of this report consists of a brief report on the status and description of  the FATHOM model and a summary of comments received from six reviewers followed by the complete text of each individual reviewer.


Status of FATHOM (February 1999)


Sponsor:  Everglades National Park


Function:  FATHOM is primarily a mass-balance, i.e. box, model that is currently capable of simulating the spatial and temporal variation in salinity in inner Florida Bay. 


Status:  Implementation and testing of the mass-balance solution code is complete.  Results of an investigation into the influence of variation in net freshwater supply on salinity are reported in a manuscript submitted for publication.  Results of sensitivity studies with FATHOM are reported in the Year-1 report submitted to Everglades National Park.


Objectives:  Work for year-2 will improve the calibration of the model, with attention to the period 1989 through 1995, and perform simulations to estimate residence times in each of the basins in Florida Bay. The PMC is requesting simulated salinity output from a series of management scenarios for discussion at the next Florida Bay Science Conference.

Description of FATHOM


FATHOM simulates variation in salinity in Florida Bay based on hydrologic inputs for the period 1965 through 1995.  Refinement and verification of the solution routine were completed in FY98.  Preliminary simulation results and comparison to Robblee’s historical salinity database were delivered to ENP in September.  The annual report for FY98 includes results of a model sensitivity study.  A manuscript describing these results is in preparation for publication, tentatively planned for the Journal of Coastal Research.


Work planned for FY99 will investigate the Bay-wide response of salinity to different hydrologic scenarios, which will reflect the anticipated changes in Everglades hydrology due to restoration.  Further work also will include refinements in the bathymetry and salinity input data.  The bathymetry GIS data have been analyzed to provide an objective measure of bank widths.  This information parameterizes the hydraulic solution for tidal mixing in the model.  For work completed in FY98, this information was input manually.  Also, FATHOM will be modified to accept a time-varying salinity boundary condition along the Keys and the western boundary with the Gulf of Mexico.  Results of work in FY98 suggest that this is a significant source of variation in salinity in Florida Bay.


Summary of PST comments


Several reviewers feel the FATHOM approach could serve as a useful tool to examine long-term (greater than monthly) changes in Florida Bay salinity and mass (water) balance.  However, one reviewer thinks it’s too early to evaluate the model performance and another adopts a "wait and see" attitude.  Two reviewers question the long-term usefulness of the model and another has serious concerns and lists a number of fundamental weaknesses in the model formulation which are believed to limit FATHOM as a predictive salinity or hydrodynamic model for Florida Bay.  This reviewer also feels that the FATHOM Report should include a set of clearly stated objectives, proven model capabilities, and performance evaluation criteria.


All reviewers feel that the model is insufficiently calibrated and not ready for examining management alternatives. Two reviewers feel that the physics in the model are too simplified for a complex region such as Florida Bay.  A deficiency expressed by several reviewers is the models inability to simulate the effect of direct wind stress on the water surface for water movement and sea level set-up or set-down.  There is also concern expressed regarding the return factor formulation as being inappropriate and fundamentally flawed. More explanation of the model time step is needed. Several reviewers feel that the Key West sea levels cannot be applied to all boundaries to account for storm effects.  The situation seems to be further exacerbated by the use of monthly values. There is concern that Manning’s n should be further adjusted (fudged) in order to calibrate the model.  In some areas of Florida Bay, salinity is controlled mainly by runoff, rainfall, and evaporation.  Advection in these areas may be of little importance because they are basically basins isolated by banks.  In these areas FATHOM can be expected to simulate salinity better than in areas where advection is important. Some reviewers are concerned that the procedure for specifying boundary tides is not clear. Also a minimum to maximum tidal variation is known as a tidal range not an amplitude as presented in the report.


Comments of Reviewer 1


I have reviewed the draft report of the application of the FATHOM model to Florida Bay and provide herewith some comments. In general I feel that this approach is quite useful for examining the long-term salinity data set for the region. In particular, the approach should be very helpful to park managers in considering different methods of water delivery to Florida Bay. I am impressed by some of the initial results and the rapid progress that has been made. It is obvious that considerable effort has gone into the project. But as pointed out in the report the model application is far from complete and there is much more to do following the “next steps” listed on page 57, which seem quite appropriate.


At this stage it is really too early to judge the model in terms of how well it reproduces the salinity magnitude and temporal and spatial variability in different parts of the Bay for there are many refinements yet to be made both to the data and the model. But one can say that results look promising and that the approach should work. One particular strength of the approach is that it provides a method for estimating exchange rates between different basins of the Bay and their residence times. However to do this requires that the model be calibrated to the available data, which has not been done yet and that all the available data be utilized, both within the basins and at the boundaries to reproduce observed variations. This also has not been completed. In this regard it is important to introduce a realistic time varying salinity for the Gulf boundary. Recent observations from Un. Miami and FIU large-scale surveys shows that holding the Gulf salinity constant at 35 psu is inappropriate and will tend to damp variations in the western regions of the Bay.


The model when calibrated will essentially provide a “best fit” to the available data from which exchange rates can be estimated. This should help account for the poor spatial resolution and the assumption that each basin is well-mixed and that there may be some “short-circuiting” of exchange between basins. I think the residence times computed in this manner will be considerably longer than those given in the report.


Specific Comments:


Tidal amplitudes listed in Table 2.2 appear to be too small for the northern Gulf and too large for Biscayne Bay. The table lists “tidal amplitudes” as (cm, maximum to minimum). By definition this is not a tidal amplitude but rather the tidal range. As such the tidal range for the northern Gulf should be closer to 2.0 m for spring tides. Increasing the tidal forcing at this boundary should help increase the salinity variability there to be closer to observed. Also the mean tidal range at  the Biscayne Bay boundary (which is really the southern part of Barnes Sound) should be closer to 16 cm as I remember.


Page 32 mentions the use of Key West sea level data to establish the monthly pattern of water surface elevations. These data should be useful for the seasonal patterns of temperature and shifts in the Bermuda high, but probably not appropriate for the passage of storms since sea level response at Key West to wind forcing will be different than along the western boundary of Florida Bay due to topographic constraints and changing coastline orientations. A careful analysis of sea level responses at Naples, Key West, Flamingo and Long Key CMAN is needed to find the proper sea level responses along the western boundary. New bottom pressure data collected near the western boundary of the Bay as part of our circulation study could also be used for this purpose.


On page 33 a 0.1 value for Mannings friction coefficient seems high.  Maybe this coefficient should be adjusted in the process of obtaining a best fit to the data.


The model-simulated salinity is compared to observed in Table 2.3. The east region is almost 5 psu less than observed. This is a large difference and suggests that part of the problem may be due to poor estimation of the fresh water input both in magnitude and distribution. Test cases should be run for times when the fresh water input was well resolved. In the Central, South and West regions the mean salinity was larger than observed, suggesting again that realistic salinity values are needed at the western boundary and these should be allowed to vary as observed. The fact that observed standard deviations were significantly greater in the South, Central and West regions than simulated also indicates that holding the Gulf salinity constant is not appropriate. The only region where the simulated standard deviations were close to observations was in the East, where one assumes that variability is more related to P-E+R and less to exchange with adjacent areas. The finding that the average salinity for all regions agree with the simulation should not be considered a significant result for it is merely a non-physical result from combining the overestimation of salinity in some regions with the underestimations in other regions. The actual comparison was not particularly strong for any region. The differences in simulated values and observed appears to be explainable in terms of data input and how the model was used and is not the result of a random process as suggested in the report.


The salinity comparisons for the 9-year period and the 31-year period are very similar, which gives one confidence in the data and use thereof in the model.


Page 48 and 49: I’m not sure that the comparison of simulated mean velocities through the Atlantic boundary (Keys tidal channels) with Ned Smiths results is meaningful since Smiths observations and the simulations were for different time periods.


The turnover times given in Table 2.5 are much shorter than I would have expected. Is this because it is assumed that the tidal flux is completely mixed within each basin? And what fraction of the tidal flux is “new water” i.e., water that had not entered the basin previously.


The conclusion section suggests that the model is now ready to examine sensitivity to different management scenarios. I would agree if the use was restricted to investigation of model sensitivity only. However, I would caution the investigators that the refinements to data and the model listed on page 57 should be made before extending much effort on the management scenarios. Also the model should be adjusted until a “best-fit” with the data is obtained and then this “calibrated model” could be used to estimate exchange rates and residence times for the various basins.


The example of a management scenario given on page 56 indicates that the simulations are quite responsive to freshwater delivery. The results listed in Table 2.6 also suggest that the exchange rates are weak between the basins for there was little dilution of salinity in the South and Central basins compared to the large variation in the East.


Comments of Reviewer 2


I got only to page 35 (the description of the salinity simulations). That seemed like a logical cut-off point, because the simulations should not be looked at too critically before the model has been calibrated carefully.


The authors provide a pretty good critique of the model themselves, offering both pros and cons.  I like that kind of candor.  In general, the report is well written, and it reads easily.


My thoughts will be primarily in the form of questions, because in reading the text quickly I may have missed some of the points that you did in fact make.  I don't expect answers, but you may want to take these questions into account in revising the text at some point.


Am I correct in thinking that by ignoring direct wind stress effects the model will not allow for the wind-induced set-up or set-down of water level within the bay?  As I read it, wind forcing can raise or lower water level along the boundaries, but the only response within the bay would be for water to drain in (if coastal sea level is rising) or drain out.  The additional set-up and set-down of water levels within the bay (relative to the boundary) could involve substantial amounts of water, and thus reduce flushing times.  I guess this is one of the trade-offs mentioned early in the report.


I'm sure you noticed that a citation is missing in the middle of page 9 of section 1.


The return factor you describe on page 1-9 makes sense when water is moving back and forth with the ebb and flood of the tide between two sub-basins.  But what happens in the near-tideless northeast corner of the bay, where wind forcing makes the ebb and flood of the tide highly asymmetrical, and occasionally the flow persists in one direction for days at a time?  It seems that the return factor would be inhibiting the inflow of dissolved and suspended material when little if any of the arriving water is, in fact, "returning."  Over these longer time scales, mixing within the giving and receiving basins may be virtually complete.  A time-dependent return factor may be another compromise.


I don't find a definition for the capital phi symbol in the right hand side of equation 1.2.


The time step noted at the middle of page 1-10 varies from 1 to 10 minutes.  I would be interested to know what guides the choice of, e.g., 1 minute, as opposed to 10 minutes.


Of course, the tidal forcing section was of particular interest. Again, I realize the model is in an early stage, but with so much water level data from the bay itself, and with such complex tidal patterns within the bay, what is the rationale for using Miami tides?  Perhaps by chance Miami's harmonic constants are a close approximation of those found at some place(s) in the bay (I was once surprised to learn that Hampton Roads tides are a very close approximation of tides along the seaward side of Lee Stocking Island, Exuma Cays, Bahamas), but it would certainly make a better impression on the reader if you used the information that is available from the study area itself.  The spring-neap sequence you refer to is only part of the tide story.  The tropic-equatorial sequence arising from the interaction of diurnal tidal constituents are important along the west side of the bay.  Parenthetically, if Table 2.2 includes "maximum to minimum" tide levels, these would be tidal ranges, rather than "amplitudes."


On the middle of page 31, there is a typo.  The exchanges with Biscayne Bay would occur in the northEAST corner of Florida Bay.  Also, if you want to define a better boundary condition here, harmonic constants are available from Jewfish Creek that would be better than an extrapolation of Miami tides.


Finally, on line 3 of page 31 you refer to a "baroclinic" set-up of water levels.  I believe this should be "barotropic," unless you are in fact referring to an increase in water level due to changes in density (which I suspect would be pretty small).


I wish I had more time to go through this.  I have the impression this is definitely a viable alternative to RMA-10.  The real proof will come with the validation of the model, of course, and I look forward to seeing how that turns out.


Comments of Reviewer 3


Although not stated as an explicit objective, the reported work appears to be an attempt at determining the effects on Florida Bay (FB) of restoring runoff towards historical levels, pages 1-1 to 1-2.  It is never clearly stated what implications of such restoration are considered.  At least three parameter spaces could be directly affected: salinity patterns and timing (P1), transport magnitudes and timing (P2), and water quality other than salinity (P3).  The authors seem to focus on P1 although residence times relevant to P2 are also considered.


This review will consider 4 broad areas given major attention in the report: modeling approach, FATHOM, model application and data synthesis, and future directions.




Authors expound on their view of a number of modeling issues, page 1-2 and scattered in the text.  A caution is noted against "complex, many-parameter, physically-based models", which leads them to the selection of a simplified, physics-based model using an empirical (Manning) approach for simulating friction flow.


Unfortunately authors's views are subjective, controversial, and vague, for example (my comments in parens) 1: simplified methods are strictly empirical (In fact, there are many simplified physics-based methods);  2: complex models are difficult and slow to implement (depends on what type of model, who does the modeling, and how much effort is put into it.  Accuracy of results also come into play);  3: "complex, many-parameter, physically-based models" have more model parameters than can be constrained by data (I don't know of any such model, can the authors give an example?. The models in wide use have very few if any free parameters, bottom friction is generally not a free parameter, it is a function of bottom roughness, which is a physical characteristic just like depth which must be known or estimated); 4: There is no cause and effect in empirical models (So this would be true for the empirical Manning eq.? Then what causal behavior can be expected in a hybrid model which uses Manning eq.?).


My sense is that authors feel hard pressed to justify their approach, but don't have really strong arguments and therefore are compelled to suggest rather vague or incoherent reasons.  They don't even follow their own advice as explained above and below.


It would have been useful to have: A clear set of objectives; A list of model capabilities and major incapabilities (sorry); A set of performance or evaluation criteria.




The authors claims that FATHOM is rapid, efficient, and accurate, while including responses to rainfall, runoff, evaporation, sea level, tides and wind (P 1-2 last paragraph).  Some of these claims are not supported by the reported work.  Before addressing this in detail some general comments about the modeling approach may be helpful.


The model is very similar to the link-node type models developed 25 - 30 years ago.  The features are very similar except FATHOM uses a simplified and specialized momentum equation for banks.  FATHOM therefore also suffers from the same known problems of this type of model: subjectivity in schematization, inability to handle local wind stress, excessive numerical diffusion, and lack of convergence to 2-D flow.  In addition, FATHOM employs an untested dynamic formulation for flow over banks.


Subjectivity:  The basin/bank schematization is difficult to do objectively and scientifically. In other words establishing a clear set of guidelines for how to carry out the schematization is difficult (impossible) and certainly was not done here. (Think about it: how do you specify where a bank begins and ends, account for it's plan curvature, account for its cross section, etc. etc.). Therefore the results are not reproducible and the model in effect has an infinite number of degrees of freedom.  The schematization then becomes an expression of the authors' opinion about the behavior of the system, which is good if their opinion is right, but bad if they haven't covered all bases.  Because of the many degrees of freedom, calibration may not lead to a model useful for prediction or even diagnosis.


Wind: The effects of wind are presumed, P 1-8, to be local mixing (no advection) and propagation of surges (included by forcing model boundaries).  The assumption that the effect of local wind stress is only to mix waters within a basin conflicts with ENP water level gage data and HBOI current meter work that shows there definitely is locally wind driven transport between basins. Just think winter storms! The issue of wind forced response is important because it is probably the dominant response in a large part of the bay where tides are tiny.


Numerical diffusion:  Because the model instantaneously mixes a basin every time step, non-physical (usually excessive) diffusion is introduced.  Even in the unlikely event that FB is diffusion dominated, maybe giving this type of model a chance, it is near impossible to adjust model diffusion to physical diffusion.   One way of visualizing the problem is to consider the spreading from a source in the middle of a basin under a steady flow situation. In one (6 min) time step the source material is brought into all (because of the return factor even into upstream) neighboring basins in significant quantities. The next time step brings the material into the neighbor basins' neighbors and so on.  Even setting  the return factor to zero causes excessive diffusion.


Synoptic observations of salinity in the bay show that the dominant transport mechanism in most areas is advection.  Without proper modeling of advective and diffusive processes, the FATHOM model cannot describe water quality parameters correctly, and the shorter the time scales the worse the predictions, because shorter time scales are almost certainly dominated by advection whereas diffusion becomes less important.


Convergence: The basin/bank (node/link) models do not converge towards two-dimensional flow patterns.  It is not possible to refine these models to get better approximations to true 2-D flow because of the 1-D flow in links or over banks.  Once a bank is put in place, the flow must occur in a certain direction across it.  This is in conflict with natural flows which can and do vary in direction.  It is therefore not possible to assure that the chosen schematization adequately represents the (known) physical characteristics of the system.


Dynamic formulation: Bank flow formulation is highly simplified and idealized.  No validation is provided which could help demonstrate how well the model simulates a known problem.  For example [1.11] always assumes a 'transition' loss equal to the velocity head, however, for gradual transitions, that is excessive. The Manning formula was obtained for uniform flow in open channels.  It may not describe the boundary layer processes for transitional flows over submerged banks.  Supercritical flow is assumed to occur, page 1-13 middle paragraph.  Yet there is not mention of the ensuing hydraulic jump.  Have these hydraulic phenomena been observed in FB?  The dynamic formula used in FATHOM are concocted by the authors without proper theoretical or empirical support and no references.


After raising these serious issues, one might well ask how some of the FATHOM results can be in reasonable agreement with data.  First, it is not surprising that water levels can be simulated with some accuracy. Water levels result from flow and conservation of mass.  By adjusting flows water levels can usually be fit to data.  However, it has been shown time and again that fitting water levels does not mean that the corresponding flows represent actual flows.  Second, because averaging the salinity observations in space and time is similar to introducing lots of diffusion in the salinity fields, this will favor comparison with a highly diffusive model.  However, more importantly, in some areas the primary forcings of salinity variations are derived from runoff, rainfall, and evaporation.  In areas where these forcings dominate the salinity response, FATHOM can be expected to predict salinity reasonably well. This would be areas receiving runoff, while they receive significant runoff!  And in isolated basins.  This does not mean that FATHOM predicts transports well, in fact it cannot!  Finally, the intimate familiarity and knowledge about the system collectively possessed by the authors likely also played an important role.  This reinforces the desirability of involving modelers with a good familiarity of the system to be modeled.


Additional detailed comments:


The dynamics of the flow in basins is completely ignored.  The distribution of flow to and from the various banks cannot be correct. In some basins (large and shallow) this will be a big error, in others (small and deep) it may be less important.


With a return factor, FR (eq. [1.1]), different from zero, there is unrealistic upstream advection.  With FR = 0.33, the model grossly violates the transportive property (a quantity can only be advected downstream), Roache (1972).


What is the meaning of phi in [1.2].


There does not appear to be a reproducible way of characterizing bank dimensions, locations, and alignments.  The more removed from reality the harder it is to calibrate the model and to use it for prediction.


The model contains adjustment (fudge) factors en masse: bank characteristics, friction coefficients, and return factors.  This is the type of model the authors admonished against in their discussion of modeling approach.


There does not appear to be any channels in the model (Appendix A), only banks.  Channels between banks have been shown to be very important (HBOI data) in conveying water between basins.  Channels should not be modeled with the flow formula presented in the report.




Section 2 of the report examines an initial application of the FATHOM model.  The model evaluation covers a 31-year period and includes other very desirable elements, such as the error analysis.


The "Background" section, page 21, contains some general observations about estuaries, but contains a curious statement: "The patterns of salinity in estuaries result from a dynamic steady state ....".  Salinities are usually dynamic, rarely at steady state, and never dynamic and steady state at the same time.  The authors define FB as a seasonally hypersaline estuary.  While this may be appropriate for some areas of FB it may not properly describe other areas, and a general classification of the bay as a whole is probably not meaningful.


Page 24.  FATHOM simulated hourly values ... Other places in the report, much smaller time steps (6 min) are mentioned.


In preparation for model application and data comparison, historic salinity, rainfall, runoff, and evaporation were assembled, page 25 to 30.  This is potentially very useful information.  Though leaving plenty of room for improvements, this effort is courageous.  It seems the salinity data from the ENP MMN are missing from the compilation? A better, more complete explanation of methods used to derive the temporal and spatial distribution of runoff and rainfall would be helpful. Although they used a spatially weighted average rainfall in model simulation, it appears a spatially variable rainfall distribution was available.  With proper rationale these results could well serve as a baseline against which future improved estimates could be gauged.  The evaporation estimates could probably be significantly improved.  The SFWMD has made estimates for their model simulations based on a more sophisticated analysis.


Effects of wind cannot be included by specifying water elevations at boundaries page 32.  Moreover, monthly sea levels from Key West cannot capture wind effects since they are most energetic at the shorter, 3-10 day, period band.  Was the same sea level applied at all boundaries?  That would distort most remote wind forcing.


The specification of boundary tides, page 31 and Table 2.2 was not clear.  Showing the generating formula would be helpful.  Why is there such a big difference between first high tide in north and south Gulf? The variation in amplitude in the Atlantic seems far greater than in reality.  (Range would be a better term than amplitude).  Are the channels between the keys modeled as banks?


Is 1 year model spin-up sufficient? page 34 top.


The early onset of the wet season in the Central region is possibly due to the excessive diffusion in the model, page 37.


The simulated tidal amplitudes appear reasonable, however, local wind effects are clearly missing.


I had difficulty understanding the comparison of FB-to-Atlantic channel flows.  The text, last parag. page 48, indicates that the model calculated velocity for Channel 2 was used to normalize all results, but, figure 2.23 seem to indicate data was normalized by data average and model was normalized by model average for Channel 2. How did actual magnitudes compare?  Also what period was used for averaging data and model?


Are the results, inflow north and outflow south, shown in figure 2.23 possibly due to the specified (questionable) variation in tidal amplitude in the Atlantic (table 2.2) ?  Were any model adjustments made to achieve the results shown in fig. 2.23?  How did unaveraged model results compare to data?  What were the magnitudes of Chan 2 velocities, model and data?  Comparing velocity is a poor choice, total discharge is the critical measure.


The water budget, exchange patterns, and residual circulation are solely model results and lack validation against data.  As previously pointed out the model has severe shortcomings and lacks direct wind forcing.  Model input, for example sea level and tides,  have similar problems.


The conclusion that "the use of the model to examine system behavior is justified", page 55 1st par., is inappropriate because of lack of model validation and other fundamental shortcomings detailed above.


The inferred residual circulation and simulated turnover times for the interior of FB are entirely unvalidated.  A critical forcing, local wind stress on the surface is completely missing from model and analysis.


The problems of recirculation and different flow paths described in the bottom par. of page 55 are exactly the reasons that FATHOM has no chance of providing the needed answers. An approach properly accounting for advective and diffusive fluxes is required.  To conclude that using FATHOM is the best solution for estimating retention times sadly ignores everything about how this system works.  One should not be misled by salinity simulations for a few very isolated basins where advection and diffusion are of little importance most of the time. That is not the case for the majority of the FB system.


In summary FATHOM may address P1 in some isolated basins or small basins receiving a significant amount of runoff.  P2 is not achievable because of the limiting (bank-basin) model formulation.  P3 is impossible because of missing P2 and unrealistic numerical diffusion.




The authors clearly want to continue their FATHOM modeling, and even indicate so in the report title.  A list of items to do is stated on page 57.  The refinement items 1 to 7 are desirable although the indicated methods may not be the best.  These all involve input data to any FB model and are not specific to FATHOM.  Work in these areas by qualified researchers is strongly endorsed.


The structural changes suggested for FATHOM are futile.  How do you split one large basin into three smaller subbasins hydrodynamically? How do you decide on bank alignment and characteristics?  This is the trip down the non-convergent path mentioned earlier, refinements do not lead toward real behavior.  Even if an objective reproducible method for deriving a "bank width" could be derived, the dynamics of FATHOM are too far removed from reality and would require endless model adjustment.  Worse predictive capability is compromised.


The agreement of FATHOM computed salinities with observations can undoubtedly be improved by tuning the multitude of model parameters, however, fundamental discrepancies will remain, predictive ability is unattainable, and understanding of the underlying processes will be lost. Predictive capabilities will be limited and will not include circulation (P2) or water quality (P3). This situation is likely to get worse as better data become available for forcing and validation.


Roache, P.J., 1972: Computational Fluid Dynamics.  Hermosa, Albuquerque,

New Mexico.


Wang, John D. July 1, 1999

Comments of Reviewer 4


This is a fascinating approach to develop a tool for examining long-term (> monthly) changes in Florida Bay salinity and mass (water) balance.  It extends a strictly empirical approach to include some of the physically-based processes that the authors feel are paramount in Florida Bay  *primarily frictional effects over the shallow banks between basins that are assumed well-mixed).  In general, I have two points to make:


I.  The authors have done a good job of assembling historical data bases for forcing and evaluating (particularly salinity) the model; and


II. While the results of these initial calculations are encouraging, I think the strict structural approach of FATHOM (based on the physiography of the Bay) and the subsequent simplified physical assumptions (*) are going to limit its usefulness in the long run.


Specific comments follow, in order of importance:


1.  The treatment of the "wind-driven" forcing (i.e. low frequency forcing at the boundary as a water level boundary condition) is weak for several reasons.  It allows for no direct wind-driven movement of water in Florida Bay (a large omission) and as it is formulated it does not account

for the important synoptic scale wind forcing (regional space scale and the 2-5 day time scale).


The use of the Key West water level record does not capture the wind-driven set up and set down (what the authors refer to as stochastic passages of storm systems [month-to-month "noise"] on p32 - please note that storm system time scales are not monthly; they are in the synoptic

[2-5 day] band) that a truly coastal station (e.g. Naples) does, although Key West does represent the seasonal steric effects as well as the long term trend.


What are meant by "wind-tides"?  Diurnal sea breeze?


2.  The tidal forcing is oversimplified, as acknowledged.  Both the NOAA (POM) and ACoE (ADCIRC) regional models have demonstrated that they can provide more detailed tidal boundary conditions that represent the mixed tide on the Gulf side and the more pure semidiurnal tide on the NE Atlantic side.


3.  It's worth noting in the salinity results that the model underestimates the variance by about 50%, except in the eastern basin. I would suggest that this may, in part, be due to the lack of true

synoptic wind forcing (#1 above).


I think the model does better in the east, as stated, because this basin is closer to the sources of runoff and further removed from the larger uncertainties of the west and south boundary conditions.  It's possible too that the constraints of well-mixed basins in the west and south are

even less valid there where the basins are larger.  For example, on p37 (Figure 2.13) the authors state that the model reproduces the hypersaline seasonal (average) signal but in fact the model misses this spring event in both amplitude and phase.


4.  On p56, where the runoff is doubled, it's curious that the model is so insensitive to this away from the eastern basin, whereas the historical observed records of runoff (Figure 2.6) and salinity (Figure 2.4) suggest that the central area salinity does respond to changes in runoff.


5.  On p22 it is stated that the lack of density stratification limits the tidally-driven and baroclinic exchanges.  Please note that tidally-driven exchanges in FL Bay are barotropic and that horizontal density stratification in FL Bay can be significant.


6.  Where's basins #'s 1-3?  Is this why, if there are 41 basins, I see #'s 43, 43, and 44?


Comments of Reviewer 5


Florida Bay is morphologically unique when compared to other eastern US estuaries in that is a broad lagoon with diffuse freshwater inputs, has a low input:volume ratio, a high evaporation:input ratio, and is partitioned by shallow carbonate mud banks which restrict and direct flows in the complex basin mosaic. 


The FATHOM model for Florida Bay is, in essence, a simple mass balance box model.  What is different from other estuarine box models (e.g. Officer) is the necessary use of Manning's equation to determine flow over the banks/shoals.  This is a relatively simple extrapolation and obviates the need for a full-blown hydrodynamic model. 


I feel the most important benefit of the FATHOM model (as with other ecological models) is its heuristic performance.  This first run of the model is more valuable in pointing out what important data are missing/not available than in providing useable results and predictions.  I think the authors and users should remain aware of this inherent learning attribute in their future efforts to modify the model and in their recommendations for future monitoring/measurement efforts.



The model relies on certain assumptions on the physical nature of the estuary which I think could be better defined: 


1. The endmember salinities of the Gulf of Mexico and Atlantic Ocean are held constant in the model at 35 (psu).  We know this is not the case from our data from 4 years of quarterly monitoring.  For the 9 stations in the gulf closest to the model boundary: mean salinity was 35, SD = 1.79, min.=26, max.= 39, n = 126. For the offshore/reef Atlantic stations from Tavernier Creek to Seven Mile Bridge: mean salinity = 35.9, SD = 0.05, min. = 33.7, max. = 36.9, n = 145. For the inshore Atlantic stations: mean salinity = 35.9, SD = 0.10 (double the offshore stations), min. = 32.5, max. = 38.4 (hypersaline), n = 141.  I believe this is one of the most important reasons why the model salinities, especially in the western zone, were so far off the mark.  I think it would behoove the authors to run a sensitivity analysis by varying endmember salinities in an effort to determine the magnitude of this effect.


2. Estimated evaporation rate (unmeasured) has a seasonal component but no interannual variability.  The sensitivity analysis showed that the eastern zone was most sensitive to fluctuations in evaporation rate.




1. Differences between observed and predicted salinity are the sum of all errors (precipitation, evaporation, runoff, groundwater, and flux) and cannot be partitioned.  Sensitivity analysis showed that salinity was equally sensitive to precipitation, evaporation, and Manning's n. 


2. Turnover time calculations are confounded by back flow of solute into the basins which had previously been transported out.  In other words, the water at the boundary of each basin is not independent (autocorrelated) of the basin itself.


3. One of the most useful results of the model is the calculation of annual net water movement (Fig. 2.25). This net flux of higher salinity water from the west mixing with freshwater inputs in the northeast and resultant flow out of the estuary towards the southwest is borne out empirically with the data from the SERC monitoring program. 


Comments of Reviewer 6


With respect to the simulation of the temporary inter-basin exchange of water across the mud banks using a specialized momentum equation, there is now modeling technology that can handle this problem. The layer(s) of fluid are considered to exist everywhere but the layer thickness collapses to zero when/where a mud bank emerges.  The model equations remain valid at all grid points but there is no mass flux (V * thickness = 0) in regions where the layer becomes "massless". Later, the layers re-inflate with water and the cross-bank transport is automatically reactivated. (Think of squishing Jello between layers of Saran Wrap using your fist.)


This technology is employed in the Miami ocean model (MICOM) at UM-RSMAS to simulate isopycnic layer "outcropping" at the ocean surface. The key is to use a high-performance advection scheme with low numerical diffusion (like FCT or Smolarkiewicz' MPDATA) which can accurately predict where the mud banks should emerge. (These numerical algorithms also resolve steep gradients and hydraulic jumps.) This allows the natural, realistic flow to dynamically determine when/where the mud banks should surface or submerge. The formulation avoids the problems caused by FATHOM's static mud bank structure (cited by another reviewer).















Response to:  "Review of the Implementation of FATHOM in Florida Bay" by the Members of the Physical Science Team of the Florida Bay and Adjacent Marine Systems Science Program


Prepared by B.J. Cosby and J.W. Fourqurean


The PST review comments reflect a great deal of effort on the part of the reviewers and have been very useful to our group in planning the next steps in the development and application of FATHOM. In addition to these reviews, we have had a number of individual conversations with members of the PST regarding the FATHOM model. Many of the comments have been incisive and have led to changes in the way FATHOM is being applied to Florida Bay. It is also clear from the comments that shortcomings in the data used to drive the model (and to evaluate the model) can be a cause for as much concern/discussion as the model itself, and to that end we have undertaken to obtain better data where needed.  Some (but not all) of these problems with the model and data were recognized by us and pointed out when we prepared the report. We are grateful to the members of the PST who provided ideas toward resolving the problems we knew about as well as the new problems that were raised. This review process has apparently worked - you spoke and we're trying our best to hear. From some of the comments, however, it is evident that some confusion still exists about the model, its conceptual basis, its intended purposes, and its mathematical structure. In some concepts and details, the reviewers have come away from reading the same report with distinctly different impressions of the model, what it is capable of, and what it has been asked to do so far.


Dr. Lee has asked us to respond to the reviews in 1-2 pages, so we will not address here any specific comments of the reviewers. Rather we will: 1) address briefly what we perceive as the need to get FATHOM "on the street" so that its capabilities and shortcomings can be understood and evaluated by potential users, and we can begin working toward a resolution (if possible) of remaining difficulties; and 2) attempt to provide a brief explanation of the approach and philosophy we adopted in developing the model, and what we consider its role to be in ecological and physical investigations in Florida Bay.  With respect to the specific comments and criticisms presented in the reviews, they have been noted and we are working to resolve them.


1) Getting FATHOM "on the street"


There seems to be, at the moment, a problem arising from the fact that FATHOM is currently known only in broad outline. Prior to the presentation to the PST (and the follow-up report) there had been little formal presentation of the model and its capabilities or shortcomings. This resulted from the fact that the funds available for the project have been spent mostly on the development of the model and the data bases needed to implement and evaluate the model. The model (and its appropriate uses in Florida Bay) must be judged on merit (what does it do? and how well does it do it?), and to that end, we are trying to get as much exposure as is possible for the model and its current capabilities and shortcomings.


The way forward for the FATHOM model is to get some simulation results out in front of the appropriate audience so that the strengths and weaknesses of the model can be evaluated. We are firmly of the opinion that as much is learned (if not more) when a model "breaks" as when it "succeeds".  The initial feedback we have received has been gratifying, and we appreciate the time and effort expended on discussion, comments, and suggestions. The model can run on PC's, and we have made a demonstration version of the model available on CD-ROM along with the simulation results from the PMC scenario workshop held in August. We are preparing another report similar to the one reviewed by the PST and are planning two more papers for submission to peer-reviewed journals.  We (in all likelihood) will be calling on some of you in the near future as these activities move forward. Further suggestions on how we can get folks involved in using and criticizing the model are welcome.


While it may be the opinion of some that FATHOM is "not ready for prime time", our opinion is that the current state of the model represents a significant step forward in the development of a tool for examining physical and ecological processes in Florida Bay. It may be that current uses are primarily heuristic (as several reviewers point out) and that the reliability of the model's predictive capabilities has yet to be established. However, if the model is not "exercised", discussed, and dissected, that predictive reliability can never be determined.


2) FATHOM - Approach and Philosophy


There seems to be a general misconception that FATHOM was developed as an alternative to  the RMA-10 model or to hydrodynamic models in general. In fact, that is not the case. FATHOM was intended from the outset as an aggregated mass-balance model designed to utilize the basin/bank arrangement of the bay to define regions within the bay that would be useful in ecological studies requiring information about the movements of water and solutes between individual basins. The comparison of FATHOM simulations to observed salinity was seen as a way to partially "validate" the solute transport results from the model.


The aggregated nature of the model was adopted so that the model could be more easily used in heuristic studies - "What if...? experiments". It was also envisioned that the model, once adequately calibrated and validated, could also be used to provide quantitative estimates of physical properties important to ecological studies (basin residence times, salinity variations, water levels, etc.).  Again, the need for a model that could be readily implemented to derive these estimates was an a priori consideration. Finally, we intended that the model be configured such that it could be used to examine potential effects of changes in freshwater inputs to the bay and thus have heuristic and perhaps predictive utility in management contexts as well as scientific studies.


The expected applications of the model do not require simulation of continuous velocity fields within the bay (rather exchanges between basins is perceived to be the critical process) and so we did not adopt the hydrodynamic approach. To criticize the FATHOM model, therefore, because it is "empirical" and not hydrodynamic misses the point concerning: 1) its intended uses; and 2) its ability to reproduce important behavior in the Bay. FATHOM is a rather successful refinement of a linked-node, mass-balance box model, and not a failed hydrodynamic flow and transport model. The tide-driven flows across banks in FATHOM provide  estimates of exchange fluxes between well-mixed basins in a way that is tightly constrained by the available bathymetric data for the bay.  The simulation outputs from FATHOM have much potential utility for ecological and physical investigations, providing  model reliability  and confidence in the model can be established. Whether or not this latter condition can be satisfied is the focus of large part of our anticipated future activities.


Our approach to building models is to add model complexity in a step-wise fashion and compare model results to data at each step. Using this paradigm, we are better able to discriminate between those factors that influence  variation in bay characteristics (by their contribution to the incremental improvement in model simulation success) and those factors that appear to have little effect. We are well aware that the FATHOM model potentially has a large number of degrees of freedom that can be exploited through an optimization scheme to maximize the model fit to observed data.  However to do so would defeat one of our favorite tactics - "breaking" the model to learn something new. At each step of improvement in model structure or input data, we have learned something about the relative importance of each change on overall model behavior. Therefore, we have so far left the model “uncalibrated” (by purposefully assuming, for example, uniform bottom roughness, when in fact we could assign a different roughness to each bank and possibly improve the simulation results relative to observations).  If reliable observations of variables or processes in the Bay are not currently available, we apply "Occam's razor" and choose the simplest assumption for the missing information, and then evaluate how well or poorly the model performs. We consider that this modelling approach makes the best use of the available data in Florida Bay, especially where existing data may not currently be adequate to support the calibration and validation of a hydrodynamic flow and transport model (for instance there is very little data on tide-driven currents within the bay to use for flow calibration).


As the emphasis of FATHOM applications moves to predictive exercises, it will become increasingly important to have the "best" input data to drive the model and we will implement a calibration of the model to maximize model success in simulating salinity. While the reviewer's are correct in asserting that there is more to be done, it is also correct that progress has been made. We look forward to continuing  this dialogue with the PST and other interested parties.
























Review of the Implementation of RMA10 in Florida Bay


for the Florida Bay and Adjacent Marine Systems Science Program

 by members of the Physical Science Team




The Waterways Experiment Station (WES), U.S. Army Corps of Engineers (ACoE) has calibrated its RMA10 hydrodynamic model for use in Florida Bay.  Results of this work are described in the technical report, “Field and Model Studies in Support of the Evaluation of Impacts of the C-111 Canal on Regional Water Resource, South Florida, Part IV: Florida Bay Hydrodynamic Modeling,” dated October 1998.  The Jacksonville District Office of the ACoE furnished copies of this report to the PMC in December 1998.  The PMC subsequently forwarded the report to its Physical Science Team for review.  A later version of this report which addresses some of the issues raised here may be available, however, this later report was not available for review.


The primary purpose of this review is to assist the WES modeling team by providing critical comments and insights of physical scientists with experience working in Florida Bay.  Our intent is to provide a critique of model formulation and application in order to evaluate the model's potential and to suggest model improvements that will eventually lead toward scientifically defensible model predictions. These comments also provide ACoE with an opportunity to inform the PMC of their recent efforts towards these goals.


This report consists of a brief report on the status of the RMA10 model, a condensed description of the model, a summary of comments received from five reviewers, and the full text of each individual review.


Status of RMA10 (February 1999)


Sponsor:  U.S. Army Corps of Engineers


Function:  RMA10 is a 3-D hydrodynamic model that has been implemented for Florida Bay in 2-D format for Florida Bay and the near-shore region of the Florida Shelf north to the 10,000 Islands and through the Keys onto the reef tract down to the lower Keys.  RMA10 provides detailed information on tides and currents in response to tides on the boundaries, wind, rainfall, runoff, and evaporation.  RMA10 also has the capability of simulating salinity.


Status:  Initial development and implementation of RMA10 is complete.  The draft final report provides results of salinity simulations for three runoff scenarios.


Objectives:  The PMC is requesting simulated salinity output from a series of management scenarios for discussion at the next Florida Bay Science Conference.

Description of RMA10


(Note:  This section is based on source material from the WES web site and the project report, "Field and Model Studies in Support of the Evaluation of Impacts of the C-111 Canal on Regional Water Resources, South Florida", dated October 1998)


The two-dimensional model includes dynamic coupling between the salinity and hydrodynamic fields.  Model development and verification were accomplished using extensive data sets taken by WES and data supplied by other agencies and organizations, such as the National Park Service, USGS, Harbor Branch Oceanographic Institute, NOAA, and the South Florida Water Management District.


The model verification period is that period for which WES data were taken (March 1996 to April 1997).  The model was initialized using August 1995 salinity distributions from the USGS surveys.  Freshwater inflows from USGS gauged flows into northeast portion of the Bay and net freshwater (rainfall - evaporation) values derived from three WES meteorological stations were included in the model.  Verification (calibration) of the model was attained by adjusting bottom roughness in the model to provide the best match to tides, currents and salinity variation (in that order) over a relatively short period of time (20 days in September 1996 and February 1997).


The first model calculations examined the salinity of the Bay under varying wet season freshwater inflows.  Three flow scenarios were considered.  The base flow is representative of the flow in a wet year.  The NSM (Natural System Model) flow represents a conjectured flow through the everglades before human intervention.  Alternative D represents a proposal for future water usage.  The calculations for Florida Bay based on these three flow scenarios used tides, net rainfall, and winds for the year 1996.  Calculations were made for the three-month period, September through November.  Results of the three inflow calculations show that diverting more freshwater into the northeastern part of the Bay through the Taylor Slough system has these effects:


·       Lowers the salinity of the northeast corner of the Bay in approximate inverse proportion to the increase in freshwater flows;

·       Pushes these salinity changes out to mid Bay;

·       Creates a sharper gradient of salinity in the mid-Bay area.


The model provides flow fields for a WES water quality study of Florida Bay.  To enable the model hydrodynamics to be used in conjunction with a water quality model with different spatial resolution, a unique projection technique was developed through a partnership between WES researchers and the University of Texas at Austin. This projection tool enables two-dimensional hydrodynamic results to be applied to water quality modeling without the two efforts having the same computational mesh, so that the ideal resolution for each portion of the modeling effort can be used.

Summary of PST comments


All five reviewers recommend that further work is needed before the RMA10 model can be accepted as calibrated and verified.  The reviewers recommend using quantitative measures of model performance in future calibration and verification work.  Each expressed frustration with trying to make judgements about model performance from plotted output.  Performing harmonic analysis on the modeled water levels near measurement sites would provide information directly comparable to known values of tidal amplitude and phase angles for 4-5 of the major tidal constituents for the interior of Florida Bay and at selected sites along the boundary.  More attention needs to be paid to how well the model predicts the response of the Bay to sub-tidal (long-term) forcing from winds. This could be evaluated for subtidal sea level changes and water flows at the boundaries and between interior basins at those sites where measurements have been made.  Further work on calibration/verification is needed to build confidence in the capability of the RMA10 model to predict water levels, flows, and transports in Florida Bay and at the boundaries.


The reviewers raised fundamental issues related to the boundary conditions and transport processes in the interior.  Errors in the tide predictions of the ocean model, used to provide the ocean boundary condition, should be estimated and, when known, their propagation into the RMA10 domain should be investigated.  Reviewer 1 raises the issue of whether the coastal ocean model captures the net water slope and distribution of residual flows that are know to occur across the boundaries of the Bay. Wind is expected to drive circulation and mixing in the interior of the Bay; therefore, it is inappropriate to assume a uniform wind field over the Bay without a sensitivity study to determine the errors inherent in this assumption.  Reviewer 4 points out that it is not clear if the sea level boundary conditions at the open ocean boundaries were provided by the NOAA POM model or by ACoE’s ADCIRC model.


Reviewers were confused by several aspects of the simulation runs that were performed to investigate the sensitivity of the model to changing freshwater flow.  In particular, why were simulations initialized in August 1995 but run with inflows from a different year?  Several reviewers pointed out that magnitudes of freshwater inflows appear to be much higher than observed (by a factor of 10 or more) and, as a result, modeled salinity values are too low in the northeast Bay and off Shark River. The general pattern of salinity seemed reasonable but the values were largely different from observations due to the uncertainty of the freshwater inflows. Also, the results of the simulations were difficult to judge without knowing how long the effects of initial conditions persist to influence the calculated salinity field. Tests should be run to determine the spin-up time for the model and effect of initial conditions.


Comments of Reviewer 1


The model verification section was of primary interest to me, and I must say I would like to see this approached with tables rather than with figures.  First, model verification is documented with analog plots for the most part (Plates 1-30).  Model simulation results are plotted along with observations from the same time and place.  I would prefer to see a comparison of harmonic constants.  Given the importance of tidal forcing in the Bay, results of the 20-day simulations could be subjected to the same harmonic analyses used for observations to quantify the amplitudes and phase angles of the 4-5 major tidal constituents.  Actually, only 15 days are needed for this, so the data are probably already available.


Second, the model's ability to reproduce hourly transport along the western boundary is of less importance than the model's ability to reproduce the net inflow and outflow over longer time scales.  Two of the most important features of the regional circulation are the inflow through the northern and central parts of the open western boundary and the outflow through the southern part of the boundary.  Did the model reproduce these features?  From Plates 5-7 we have no idea.  Another major feature of the regional circulation is the long-term net outflow through the major tidal channels of the Middle Keys.  Plate 9 contains data from Long Key Channel, but how do these hourly water levels translate into the long-term average 250-300 m3/s net outflow that has been calculated for this channel?  Similarly, we have values for half-tidal-cycle inflows and outflows for all of the major tidal constituents and for all of the major channels.  How do model results match up?


A really convincing validation would come from a series of co-amplitude and co-phase charts for the major tidal constituents.  Is the model reproducing the negligible tidal conditions in the interior of the Bay?  I don't think anyone is expecting the model results to mirror the observations exactly, but I have no clear picture of how good the simulations are.  If the model is to be used as a management tool, shouldn't we know how good it is?


The report (page 9, bottom) notes that a user-friendly graphical user environment has been developed to facilitate the post-processing of model outputs.  If so, then a closer look at the output should be a relatively easy matter (easy for me to say, anyway).


From the beginning, I have wondered about the decision to use ADCIRC model output for the boundary conditions that will serve as input to the RMA10 model.  Have the ADCIRC-derived boundary conditions been tested against observations to quantify the errors that are being fed into RMA10?


Also, do the ADCIRC boundary conditions include a net transport into Florida Bay?  This would seem to be very important if RMA10 is going to force water out through the tidal channels on the other side of the Bay.


Comments of Reviewer 2


The objectives are succinctly stated, however, no performance criteria are given by which the results can be judged.


The authors' objective (a) can be said to have been achieved, though model calibration and validation is inadequate.  Additional quantitative model verification and sensitivity analyses are needed before an assessment of the model performance can be made.


Fundamental issues related to transport processes, their type and parameterization in the model are not addressed as detailed below.


Chapter 4 of the report attempts to address the second objective, (b).  Without proper model verification little confidence can be attached to the results.  The freshwater inflows seem inappropriately high and, certainly, are far beyond the range of values used previously with the Model.  The results are shown for two times on Nov 28 and 29.


Curiously, these times were chosen only 34 hours apart and the patterns are expectedly virtually identical.  The statements on p. 23, line 10, "Figures 45 and 45 are given to illustrate the fact that the salinities, particularly in the northwest corner of the Bay, are changing very little.  This reflects the nearly constant inflows into the northeast part of the system for this time period" demonstrate a poor understanding of how this system behaves, even accepting that "northwest" is a typo for "northeast".


The comparison between base flow and NSM flows shows that increased inflow of freshwater from Taylor Slough results in lower salinities in eastern Florida Bay. Hardly a surprising result.  However, the reliability of the computed values depends on transport and diffusion processes, whose magnitudes in the model are unknown and untested.


In summary, the best one can say is that the reported work raises many questions but that answers are hard to come by.  Because of the lack of proper calibration and verification, as detailed below, confidence in the reported model or its ability to predict transport and mixing in Florida Bay is low.  In this respect, the data collected for model calibration and validation seems seriously deficient in the interior of Florida Bay. To test the viability and reliability of the model, a set of performance criteria based on a set of relevant objectives and associated data must be developed and the model should be evaluated against these criteria.


Specific questions or comments:


P 2.  The process in which model is iteratively adjusted to fit data is usually called calibration not verification.


P 3, L 11 bot.  These are crucial statements that one would expect support for.  Data in terms of stratification, and either model results or analysis in terms of circulation impacts.

No support is provided.


P 6, L 4 bot.  Circulation in the interior of Florida Bay is controlled by the wind.  Yet all the comparisons focus on tides.   What about wind?


P 9 bot.  It's interesting that the authors reference only two of the four model studies performed simultaneously.  Were they not aware of the two other ones?


P 10, Figs 5 and 6.  There are very abrupt changes in element sizes within the grid.  Does this require extra numerical smoothing to control numerical high wave number noise?


P 10 bot. What is the numerical diffusion? How much eddy viscosity was applied.


P 11.  Using a large-scale tidal model to compute boundary conditions is not a certain solution to a difficult problem.  In the present situation, the proximity of the offshore boundaries to inlets, the complex bottom topography, and the inability of the large-scale model to properly represent these features can cause mismatch.  Therefore, careful validation must be made.  The comparisons, e.g. channel tidal flows, show that there is a serious mismatch.


P 11, Figs 11 to 18 show prescribed tides with no comparison to actual tides.  There is, therefore, no way to verify the model forcing directly.


P 11.  A high degree of correlation does not justify making the wind uniform.  This must be validated or sensitivity should be established.  There are important phase shifts within the domain in the peak energy band for wind.  After all, the major wind systems move through the area.


P 11.  At what height was the wind sensor?  Were wind speeds corrected to standard height?


P 12 bot.  Was salinity zero or was it assumed to be zero?  What is the significance of averaging over three days.  If salinity is not zero, not all discharge would be freshwater.


P 12 - 13.  The explanation of how freshwater discharges were obtained was incomprehensible to me.  How were the estimates mentioned on P. 12, 14 bot. determined?   What are these estimates?


Was a 72-hour average used to drive model?  Where was the Taylor River gage located?  What is the justification for using that to determine discharges at all points?


P 13.  Since net rainfall is highly uncertain, a sensitivity analysis could have been made.


P 14.  The choice of initial salinity condition, August 95, for the so called verification calculations is peculiar since the model simulation starts September 96.  The issue of how long the model needs to be run for results to become independent of the initial conditions is

never addressed.


To test the effect of initial salinity conditions, the model could have been run with different initialization.  It would be very valuable to ascertain that the model can reach a realistic salinity field after sufficient time if started from arbitrary salinity; however, that may take longer runs than have been made so far.


P 15.  The term verification is used to describe model calibration and validation.  Most investigators distinguish between calibration in which model parameters are adjusted and verification (or validation) where model performance is tested for one or more independent data sets not used in the calibration procedure.


P 17.  The comparison of water levels would be more helpful if it addressed at least three areas: boundary condition errors, tidal fluctuations, and subtidal variations.  The reported comparison consisting of time series plots is purely qualitative and very difficult to evaluate.  The water surface comparisons reveals large tidal discrepancies, which are bound to cause major discrepancies in flows that primarily depend on the surface slopes. Equally important is the model's apparent failure to describe the low frequency variations in water level which are apparent in the figures.  It would have been useful to plot low passed water elevation comparisons, especially since these likely would be caused by wind, and wind probably is a major forcing in eastern Florida Bay.


P 18-19.  Velocities.  Again the comparisons are strictly qualitative.  Terms such as "make sense", "compares well", and "agreement is good" are used subjectively. How well does the model describe harmonic constants, direction of subtidal flow, magnitude of subtidal flow?  The importance of subtidal flows seems totally lost as the authors' focus exclusively on tides.  Plates 31 to 36 seem to indicate very different magnitudes and phases between data and model.  The text for Plates 32 and 33 does not seem to agree with what is shown in the figures.  Since tidal flows in the channels result from differences in tides inside Florida Bay and in the Atlantic, the discrepancies in channel flows indicate that model calculated tides in the Bay and/or offshore tides have problems. Similarly, since subtidal water level variations differ significantly from observed values, model calculated wind driven flow is probably unreliable.


P 19-20.  Salinity.  A simulation was made to determine salinity using estimated freshwater inflows.  No mention is made of the magnitude and distribution of these inflow estimates.  The model uses salinity from August 1995 as initial condition, but the model is started Sept 14, 1996. Results are only shown at points near the Atlantic where the salinity remains near 35 to 36 no matter what, or for a point in Joe Bay which remains fresh at all times.  No results are shown for the interior of Florida Bay.  It is interesting that no freshwater was routed into Joe Bay, an almost enclosed bay, yet the salinity there is near zero.  How does Joe Bay become fresh, or is the entire region fresh?


A simulation was also made for Feb. with an 80% reduction in inflow.  The reason for this reduction is not explained.  What was used for initial conditions?  The resulting salinities, only one station shown, appear to be completely different from observed.


Finally, a discussion of longer calculations made with inflows based on USGS data is given without any results shown.  The discussion tests the reader's imaginative power.  A couple of figures would have been helpful even though only qualitative results are given.


The nebulous conclusions of the model verification part of the report aptly represent the results.


Chapter 5.  Summary and Conclusions


Conclusions are too subjective and qualitative.  Some are trivial or so general that no new information is obtained, (e.g. "The results of the calculations were that increasing the flows into the northeast part of the Florida Bay model will result in a freshening of the northeast to mid Bay areas.").


What is wind blow down?  Why was it not mentioned before?


Comments of Reviewer 3


1.     Model Characteristics:


2D vertical average Model - RMA10, finite element includes evaporation, precipitation, salinity, temperature and sediment transports including erosion and deposition.


Evaporation: 27.5" to 30.0" 3/96 - 4/97 with small spatial variation.


Has a Graphical User Environment (GUE) allows user to visualize model results.


Bathymetry based on nautical charts (NOAA #11451 example).


Boundary Conditions (B. C.) - ocean salinity, tide, wind, net rainfall and freshwater inflow.


Tidal - uses global ocean model (Luettich et al., 1991 and 1992) & POM (Aikman).  These models include subtidal wind effects.


Winds -29 km Eta model and CMAN stations.


Winds used for B.C. development are considered as spatially uniform i.e., no variation with longitude.


B.C. are set for two 20-day periods Sept. 96 and Feb. 97.


Fresh water inflows are most problematic, for they consist of complicated inflows from many small creeks that are not well measured.


Quantitative values of fresh water inflows were not available for initial verification so estimates were used for wet (Sept.) and dry (Feb.) seasons.


Compared model data to intensive WES surveys in 9/96 and 2/97.


Also use USGS fresh water inflows: weak in summer and fall 1996.  During high fresh water flows the discharge to Florida Bay is complicated by increased overland sheet flow and multiple ungauged channels.


Taylor River gage showed a net inflow to Bay and it was used to construct inflows from other points, i.e. Shark River Slough system. The Shark River data contain water level only, no flows.


Taylor River flows were observed near the mouth from 8/96 to 2/97

Total range was 0 to 120 cfs (0 to 3.4 m3/s). 

Typical flows ranged from 10 to 50 cfs (.3 to 1.4 m3/s)

Maximum flows were approximately 120 cfs (3.4 m3/s) in mid Oct. 1996

Weak flows of 10 to 30 cfs (.3 to 0.84 m3/s) occurred from Dec 96 to Feb. 97


Rainfall and evaporation are included in the model as a net freshwater input.


Initial salinity set to USGS salinity map of 8/95.


Verification proceeds from tides to velocity to salinity.  Model is adjusted to agree with data at each step by adjusting bed roughness.


2.     Model comparison with data - Results generally similar for Sept. 96 and Feb. 97:




Model tides (sea level) generally greater than observed for ocean tides.


Model tides were much smaller than observed on the Bay side of the Keys.


Poor agreement between model and observed tides in Long Key Channel.


Model tides were generally greater than observed inside Florida Bay.


Discharges (volume transports)


In interior channels (Jewfish, Dusenburg Ck. And Grouper Ck.) the model flows led observed flows by approximately 1/2-day.


Whale Harbor Channel: phasing is poor but magnitude OK.


Channel 5: phasing poor but magnitude OK.


Long Key: phasing poor but magnitude OK.




Salinity verification uses two sets of freshwater inflows (historical and later measured);  salinity has 1 to 2 ppt offset after rather brief spin-up period for gages near Keys passages.


Only interior long-term salinity gage is at Joe Bay where the model salinity is 10 to 20 ppt less than observed.


Using USGS inflow data and their 8/95 salinity map as initial conditions, the general pattern of the model salinity field compares reasonably well with the observed.  However, major disagreement occurs in the northeast portion of the Bay and offshore of Shark River where the model salinities are much fresher than observed. Also in the northwest portion of the Bay near East Cape the model buldges the 30 psu isohaline toward the west more than observed.


The results indicate that better freshwater inflow data is needed before quantitative comparisons with observations can be made.


3.     Experimentation:


Three freshwater inflow scenarios derived from coupled surface-ground water model.  The SFWMD 2X2 coupled surface-ground water model provided head values to use in the hydrodynamic model.  The Hydrologic model calculates surface flow values a few miles inland from the coast (due to uncertainties in defining topography in the coastal swamps).


Three scenarios: 1995 (wet year), NSM (Natural System Model, i.e. before man) and Alt-D (proposed for future water usage).


For Taylor Slough the NSM fresh water discharge is about twice the wet year or about equal to Alt-D in the full wet season.


For Shark River discharge all three scenarios are about the same.


Observed fresh water discharges in Taylor Slough range from 0 to 3.4 m3/s


Taylor Slough model discharges


Dry Season: 500 to 1500 cfs (14 to 42 m3/s) which is about a factor of 10 greater than observed.


Wet Season: 2000 to 4000 cfs (56 to 113 m3/s) which is a factor of 40 to 80 times observed.


Shark River model discharges


Dry Season: 1000 to 3000 cfs (28 to 85 m3/s) which is about 5 to 17 times previous estimates.


Wet Season: 6000 to 8000 cfs (170 to 226 m3/s) which is 30 to 40 times larger than previous estimates.


The model calculated salinity in Florida Bay based on these three fresh water input scenarios using tides, net rainfall and winds for the three month period Sept. to Nov 1996.  However, the freshwater inflows were calculated for the year 1995.


The resulting model salinity patterns are much too fresh in northeast Florida Bay and off Shark River because the modeled inflows were 10 to 80 times larger than observed.

4.     Conclusions:


1)  Model not verified as yet.

2)  Model needs to be compared to a wider range observations and quantify results of comparisons.

3)  Need to use correctly modeled inflows of freshwater or observations.

4) Need to run the model for same time period as inflows.

5)  Need to compare model salinity values and field patterns to observations.

6)  Need to compare model time series of transports to observations at boundaries

         and in channels connecting interior basins.

7)  Need to compare model sea level to observations for tidal and subtidal variations.

8)  Need to compare model drifter trajectories to real drifter tracks through western Florida Bay.

9)  Need to compute and quantify differences and errors.

10) Should use the new high-resolution bathymetry data set for Florida Bay.


Comments of Reviewer 4


This report documents the development and use of the 2D RMA10 hydrodynamic model for Florida Bay, wherein the "verified" model system was used to experiment with three different freshwater scenarios to examine the salinity response in the Bay.  In general, I liked the report.  It is written well and presented clearly and I found it to be pretty thorough.  It follows a logical progression from describing the major inputs and the region (FL Bay prototype), to describing the model and its verification, to describing the numerical experiments and results.


However, I do have a few comments.


I.  Boundary Conditions


Water level: The tidal boundary conditions look reasonable (Figures 11-18) although it is not clear which of the two sources (the NOAA's POM or ACoE's ADCIRC) of model-derived water level boundary conditions were actually used in the simulations presented.  Both of these water level sources also include wind effects, which can be substantial, especially in winter on the west FL shelf.  Were the effects of the wind-driven subtidal boundary condition effects evaluated (for example, in terms of set up and set down or in terms of x-FL Bay pressure differences)?


Wind: A spatially uniform wind field is used to drive RMA10, based on combining the three WES interior FL Bay weather stations (Figure 2).  Of course these three stations are well correlated, they're only 10s of kilometers apart!  Why weren't other wind sources considered (e.g.

C-MANs) to look wider afield for correlations?  Assuming the wind over the west FL shelf part of the RMA10 domain to be the same as inside the bay could be erroneous and wind-driven responses on the west FL shelf can propagate into the bay.


Freshwater inputs: Agreed, freshwater inflows are the single most problematic factor.

II. Verification


Calibration of the bed roughness: The process of tuning a model using the bed roughness is described but none of these steps are illustrated for RMA10 applied to Florida Bay?  It would be good to see some of this and understand how much tuning had to be done, vis-a-vis tidal elevations, currents, and salinity.


Tides: The model tides do look pretty good, testament to the RMA10 model itself but more so to the quality of the tidal boundary conditions used.


Subtidal water levels: A northerly wind event is referred to on p18 but no analysis is done.  It is important to examine the subtidal response of the model to wind-driven events.  The tides should be removed (low pass filtering is fine) from both the observed and simulated water levels and the resultant records compared.


Velocities: The tidal velocities look pretty good.  Although the authors do not acknowledge that the N-S component of the model flow at ST1 looks pretty bad (phase and amplitude) after 9/30.


Discharge: It's frustrating to only have ~1/2 day of observed discharge data to compare with the model discharge, although I understand what it takes to get such measurements.  Indeed, the model seems to lead the observed data by ~1/2 day.  Could some of the simulated synoptic time

scale fluctuations (Figures 32 and 33) be related to wind?  Flow through these channels is not always to the south, as stated on p19.


Salinity: Why is the 0-40 ppt range used in all these plots?  Doing this doesn't allow us to see what is happening.  The model doesn't seem to capture events in the observed salinity record at TG1 on ~days 22, 30, and 33.  Overall, given the acknowledged uncertainties in the freshwater

inflows and boundary salinities, a 1-2 ppt difference is reasonable.  However, I would argue that the model does not appear to parallel the observed salinity records, even after the spin up.  Plot these data at a proper scale (not 0-40 ppt) and this will become quite evident.  I think the 10 ppt offset at JBTS speaks for itself and the two records have nothing in common.


III. Experiments & Results


Bay-wide model salinity patterns look qualitatively reasonable; however, the actual salinity values can be way off.


In summary:


1.     RMA10 seems well calibrated for the tides, both elevations and currents;

2.     Subtidal water level fluctuations need to be examined in both the model results and observed data.  There can be considerable barotropic effects in Florida Bay due to wind-driven set up and set down and due to large-scale wind-driven pressure differences across the Bay.  These might explain some of the synoptic time scale changes simulated in the channel discharges (Figures 32 and 33).

3.     The tuning of the model needs to be illustrated and quantified;

4.     The large uncertainties in fresh water inputs and salinity boundary conditions lead to large discrepancies between simulated and observed salinities.  Qualitatively, the large-scale simulated salinity patterns look reasonable.


Comments of Reviewer 5


1.     The reviewers point out that the circulation in the interior of Florida Bay is controlled by the wind, yet a spatially uniform wind field is used. Since surface wind stress forcing is so crucial in setting up water slope and driving currents, especially in shallow water, a wind field which contains realistic horizontal gradients should be used instead.


Even a simple "regime catalog" (sea breeze, hurricane, cold front passage) of wind fields created from analytical textbook equations would be an improvement. The hurricane or frontal gradient could be moved around (similar to what the Storm Surge Unit does at the National Hurricane Center) in model sensitivity tests.


Confusion:  was a high-resolution wind field, constructed from CMAN stations and NCEP's 29 km Eta model, used as boundary conditions?   This should provide adequate horizontal gradients.


2.     Instead of just calibrating the model with real data, the model could be gradually "nudged" to the real data using a Newtonian relaxation scheme. This would be simple to implement [one term in the governing equation for each variable being nudged: dV/dt + ... +  alpha*(V-Vobs) = 0, for example], computationally insignificant, and would help overcome simplifications/deficiencies in the model's physical parameterizations (bottom friction, etc.) and structure (lack of channels/gaps).