Estimating Economic Benefits from NOAA PORTS®

 Information:

A Case Study of Tampa Bay 

July 2005 

TAMPA BAY 

HARBOR SAFETY & SECURITY COMMITTEE

Estimating Economic Benefits from NOAA PORTS®

 Information: 

A Case Study of Tampa Bay 

Report prepared for the Tampa Bay Harbor Safety Committee by Dr. Hauke KitePowell of the Woods Hole Oceanographic Institute Marine Policy Center. Funding for 

the report was provided by the National Oceanic and Atmospheric Administration 

(NOAA). The report utilizes a PORTS® economic assessment methodology developed 

by Dr. Kite-Powell for NOAA and published under separate cover as a tool to estimate 

the economic benefits provided by an existing or proposed PORTS®.

Hauke Kite-Powell 

July 2005 

TAMPA BAY 

HARBOR SAFETY & SECURITY COMMITTEE 

Sal Litrico 

Chairperson
 

 ii

NOTICE

Mention of a commercial company or product does not constitute an 

endorsement by NOAA. Use for publicity or advertising purposes of 

information from this publication concerning proprietary products or the 

tests of such products is not authorized. 
 

 iii

Table of Contents 

Summary............................................................................................................................. v 

INTRODUCTION .............................................................................................................. 1 

ECONOMICS OF INFORMATION.................................................................................. 3 

Quantifying Economic Value ......................................................................................... 3 

SOURCES OF ECONOMIC BENEFIT FROM PORTS®................................................. 5 

ECONOMIC BENEFITS FROM TAMPA BAY PORTS® ............................................... 7 

Background: Tampa Bay PORTS®................................................................................. 7 

General Notes on Value of Tampa Bay PORTS®........................................................... 8 

Safety .............................................................................................................................. 8 

Avoided Groundings, Commercial Vessels................................................................ 8 

Reduced distress cases, recreational vessels............................................................. 12 

Efficiency...................................................................................................................... 12 

Increased cargo carried per transit ............................................................................ 12 

Reduced delays ......................................................................................................... 13 

Improved SAR performance..................................................................................... 14 

Environmental Protection: improved spill response..................................................... 14 

Enhanced Value of Recreation Activities..................................................................... 15 

Boating...................................................................................................................... 15

Fishing....................................................................................................................... 15 

Beach Visits .............................................................................................................. 16 

Enhanced Weather Forecasts ........................................................................................ 16 

General Weather and Coastal Marine Forecasts....................................................... 16 

Storm Surge Forecasts .............................................................................................. 16 

Qualitative Effects and Values...................................................................................... 17 

Educational use of PORTS® ..................................................................................... 17 

Scientific Research/Water quality management ....................................................... 17 

ACKNOWLEDGEMENTS.............................................................................................. 19 

BIBLIOGRAPHY............................................................................................................. 19 
 

 iv
 

 v

Summary 

This report estimates the economic benefits derived from the Physical Oceanographic 

Real-Time System® (PORTS®) installation at Tampa Bay. We estimate benefits in dollar 

terms to the extent possible, and also describe non-quantifiable benefits. 

Sources of economic benefit from Tampa Bay PORTS® information include: 

• Greater draft allowance/increased cargo capacity and reduced transit delays for 

commercial maritime transportation (water level information) 

• Reduced risk of groundings/allisions for maritime traffic (currents and wind 

information) 

• Enhanced recreational use of Tampa Bay by boaters, windsurfers, etc. (winds, 

weather forecasts, and other information) 

• Improved environmental/ecological planning and analysis, including hazardous 

material spill response 

In Table 1 on the following page, we summarize estimates of the annual economic 

benefit to a range of activities. We divide these estimates into three categories: those 

estimates for which there is direct evidence and in which we can have a high degree of 

confidence; those that are likely to be realized at present but for which direct evidence is 

lacking and/or significant assumptions are required; and those that are more speculative 

or potential, and could be realized with the full utilization of Tampa Bay PORTS® data 

by all potential users. 

Our estimates suggest that $2.4 to $4.8 million in direct annual economic benefits can be 

attributed to PORTS® data in the Tampa Bay area with a reasonable degree of 

confidence. Another $2.2 million in annual benefits are less easily traced but may be 

linked to PORTS; and an additional $2.2 million could potentially be realized with the 

full utilization of PORTS® data. Thus, our best estimate of the presently realized 

quantifiable benefit from Tampa Bay PORTS® data is $4.4 to $7.0 million. This estimate 

is best interpreted as a lower bound on total benefits flowing from PORTS® data, since 

not all uses of PORTS® data can be quantified. 

Most of these benefits are in the nature of avoided costs (increased producer surplus, or 

profit) for commercial operations and avoided costs or increased consumer surplus, 

including non-market benefits, for recreational users of the Bay. 
 

 vi

Table 1: Summary of Estimated Annual Benefits from Tampa Bay PORTS®

confidence level Source of benefit Nature of 

benefit 

approx. annual 

value (2005 $) 

avoided groundings, 

commercial vessels 

avoided costs 

(surplus) 

1,100,000 – 

2,800,000 

increased draft, cargo 

loading 

efficiency 

(surplus) 

1,100,000 

reduced delays, 

commercial vessels 

avoided costs 

(surplus) 

10,000 

High confidence 

reasonably good 

confidence and/or direct 

evidence for benefits 

improved spill response 

(present practice) 

avoided costs 

(surplus) 

200,000 – 

900,000 

 Subtotal – high confidence benefits $2.4 – 4.8 million 

reduced distress cases, 

recreational boats 

avoided costs 

(surplus, 

value of life) 

200,000 

improved weather forecasts non-market 

consumer 

surplus 

1,500,000 

Lower confidence 

more significant 

assumptions required to 

estimate benefits; less 

direct evidence 

improved storm surge 

forecasts 

avoided costs 

(surplus) 

500,000 

 Subtotal – lower confidence benefits $2.2 million 

improved spill response 

(with add’l models & 

infrastructure) 

avoided costs 

(potential; not 

realized at 

present) 

900,000 

enhanced recreational 

boating 

non-market 

consumer 

surplus 

1,000,000 

enhanced recreational 

fishing 

non-market 

consumer 

surplus 

(potential; not 

realized at 

present) 

100,000 

Potential or speculative

these benefits could be 

realized with additional 

investment or a higher 

level of utilization of 

PORTS® data 

enhanced beach recreation non-market 

consumer 

surplus 

200,000 

 Subtotal – potential or speculative benefits $2.2 million 

Non-quantified benefits Educational use non-market N/A 

Scientific research non-market N/A 
 

 1

INTRODUCTION 

NOAA Physical Oceanographic Real-Time Systems® (PORTS®) are near-shore ocean 

observing systems now operating in a dozen locations around the United States (http://coops.nos.noaa.gov/d_ports.html). PORTS® installations provide near-real time 

information and, in some cases, forecasts about water levels and currents at specific 

points in a coastal water body. In some instances, they also provide information on wind 

speed and direction, and on water temperature. In addition, co-located sensors (i.e., 

possibly operated by other parties and not part of the official NOAA PORTS®

installation) may provide information on wave height, visibility, air gaps an bridges, and 

other parameters, as well as digital still or video images of portions of the waterbody. 

The information made available by PORTS® results in economic benefits because it is 

used by decision makers to make choices that affect economic well-being. To estimate 

the benefits that may accrue from a PORTS® installation, it is necessary to compare the 

outcome of these choices under two scenarios: the PORTS® scenario, in which the 

PORTS® data are available to decision makers; and a non-PORTS® scenario, in which 

these data are not available. The data and products enabled or affected by the PORTS®

installation influence decisions made in industry, recreation, the research community, and 

public administration, changing the economic outcome from these activities, and thereby 

affecting economic well-being. The difference in outcome under the two scenarios is the 

benefit derived from the investment in PORTS®. 

The most accurate measure of this benefit is the marginal increase in what economists 

call consumer and producer surplus. Consumer surplus is the difference between what 

consumers are willing to pay and what they actually pay. Producer surplus is the 

difference between the price received for a good or service sold and the costs of 

producing that good or service. Because this surplus is often difficult to estimate, 

economists also use other measures of benefit, such as the change in value added 

(contribution to GDP), or reduction in cost to achieve the same level of output. These 

measures typically are less precise estimates of true social surplus. Usually, these 

measures are estimated as annual values at the level of a firm or other economic unit, and 

then aggregated over geographic regions and industries to estimate total annual benefits. 

Benefits represent only one side of the investment decision. To estimate net benefits, or 

rates of return, it is necessary to have information on costs as well. In the case of 

PORTS®, there are two main categories of costs: the cost of data collection, processing, 

and archiving; and the cost of generating from these data the products that decision 

makers ultimately use. In the case of PORTS®, the first component (the direct capital and 

operating cost of the PORTS® installation) is usually well understood. The second 

component generally includes activities carried out by both public and private sector 

organizations, and these costs are likely to be more difficult to specify. The analysis of 

costs associated with the generation and use of PORTS® data is outside the scope of this 

report. 
 

 2
 

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ECONOMICS OF INFORMATION 

A product, such as a real-time water level report for a harbor, represents information 

about the ocean environment. This information has value when it can be used by an 

individual or an organization to make a better decision – that is, a decision that results in 

an outcome that is economically superior. The standard economic approach to valuing 

information requires: 

• A description of the information being valued and of the state of knowledge about 

the phenomena or conditions it describes. Typically, information is useful 

because it reduces uncertainty about the present or future state of nature in a 

particular context – for example, the location of a particular depth contour, or the 

exact water level in a dredged channel. 

• A model of how this information is used to make decisions. Most decisions are 

made in the face of imperfect information, or uncertainty about how conditions 

will in fact develop and what the exact outcome will be. For example, PORTS®

data may be used in decisions involving the navigation of commercial or 

recreational vessels. Here, the critical information concerns water depth, current 

speed and direction, wind speed and direction, or other information needed for the 

safe and efficient operation of a vessel. 

• A model of how these decisions affect physical outcomes. Modeling the 

difference in outcome with and without the product in question usually requires 

making assumptions about how the decision makers will respond to the lack of 

the product in question. 

• A model of how physical outcomes can be translated into economic outcomes. 

The value of a product is the difference between the expected value of the 

outcome of decisions using that product, and the expected value of the outcome 

without the product. 

Quantifying Economic Value 

The most appropriate measure of economic value of information resulting from a change 

in user decisions or behavior is the change in what economists refer to as “social 

surplus.” Social surplus has two components: producer surplus and consumer surplus. 

Producer surplus in this case is generally a reduction in costs to businesses. Consumer 

surplus, as in the case of the surfer, is the difference between what one would be willing 

to pay and what one actually pays for, for example, a recreational experience. “Social 

surplus” is the sum of producer and consumer surplus. It is the appropriate measurement 

because it assures that only the value in excess of costs is counted, making it a unique 

measure that avoid the artificial inflation of values by double counting. 

The problem with social surplus and both of its elements is that they can only be 

measured using exacting, time-consuming, and costly techniques. Other measures of 

economic activity (broadly termed “economic impacts”) such as the value of sales at the 
 

 4

wholesale or retail level, or value added (the most common example of which is the 

Gross Domestic Product, or GDP), are widely available, but measure social surplus in a 

rather imperfect manner. 

In other situations, estimates of social surplus may be available but data to support an 

explicit model of how PORTS® information is used in economic decisions are lacking. 

In such cases, an order-of-magnitude estimate of potential value of PORTS® data may be 

obtained by applying a rule of thumb developed by Nordhaus (1996) and others: the 

value of weather and climate forecasts to economic activities that are sensitive to 

weather/climate tends to be on the order of one percent of the economic activity in 

question. 

Studies of economic values from investments such as PORTS® thus often face a dilemma 

due to data constraints. The most appropriate measure is the least available, while the 

most available measures are the least appropriate. This is a major reason why these 

estimates of economic benefits often must be considered approximate. 
 

 5

SOURCES OF ECONOMIC BENEFIT FROM PORTS®

PORTS® data, and products derived from PORTS® data, are used by a wide range of 

industrial, recreational, and public sector organizations and individuals. They include 

maritime shipping interests, recreational boaters and fishers, and marine resource and 

environmental managers. 

For the purpose of this analysis, we use the following classification of benefits from 

PORTS® installations: 

• Improved Safety of Shipping and Boating 

o Avoided groundings, commercial vessels 

o Avoided distress cases, recreational vessels 

• Improved Efficiency of Marine Operations 

o Increased cargo carried per ship call (greater loaded draft) 

o Reduced delays (less allowance for error/margin in piloting decisions) 

o Improved SAR performance (surface currents) 

• Improved Environmental Protection and Planning 

o Improved hazardous material spill response 

o Improved environmental restoration/conservation activities 

• Improved Recreational Experiences 

o Enhanced value from boating decisions (power, sail, windsurfing, 

kayaking, etc.) 

o Enhanced value from fishing decisions 

o Enhanced value from beach visit decisions 

• Improved Weather and Coastal Marine Conditions Products 

o Improved general weather forecasts 

o Improved coastal marine weather forecasts 

o Improved storm surge forecasts 

• Science and Education 

o Use of PORTS® data in scientific research 

o Use of PORTS® data in secondary education 

While this list is not exhaustive, it captures to the best of our knowledge all of the major 

benefits generated by PORTS® data. 

In each of the benefit categories discussed above, it is possible to estimate the potential 

value of PORTS® data by assuming that all potential users of the information in fact 

make use of it as described. This potential value is an upper bound of sorts on what is 

likely to be the value actually realized during a given year, since the number of actual 

users is likely to be less than 100% of potential users, 100% of the time. Potential value 
 

 6

is often easier to estimate than actual value because estimating potential value does not 

require data on how many users actually use the PORTS® data, and how often. 

In situations where data or model limitations do not permit the application of the benefit 

frameworks described above, it may be possible to estimate at least the general scale of 

potential benefit by applying a “one percent proxy rule.” Formulated by Nordhaus 

(1986) and other economists on the basis of experience with a number of 

forecast/nowcast value of information studies of industries and activities sensitive to 

weather, this rule suggest that the value of weather nowcast/forecast information to 

economic activity sensitive to weather conditions is generally on the order of one percent 

of the economic value generated by the economic activity. There is, of course, no 

guarantee that this rule will hold in all cases; but where no better estimate can be 

constructed, it provides an order of magnitude estimate of value that is likely to be 

reasonable. 
 

 7

ECONOMIC BENEFITS FROM TAMPA BAY PORTS®

Background: Tampa Bay PORTS®

The Tampa Bay Physical Oceanographic Real-Time System® (PORTS®) is a public 

information acquisition and dissemination technology developed by the National Ocean 

Service (NOS) in cooperation with the Greater Tampa Bay Marine Advisory Council. It 

was deployed in Tampa Bay in 1990-91, and is managed, operated, and maintained by 

the Greater Tampa Bay Marine Advisory Council-PORTS® under a cooperative 

agreement with NOS and the University of South Florida.1

 

Tampa Bay PORTS® provides information in near-real-time on currents, water levels, 

winds, air and water temperatures, and barometric pressure at multiple locations with a 

data dissemination system that includes telephone voice response, modem dial-up, 

dedicated modem displays, and World Wide Web/Internet sites (http://coops.nos.noaa.gov/tbports/tbports.html; 1-866-827-6787 (1-866-TBPORTS)). Tampa Bay 

PORTS® infrastructure includes four acoustic Doppler current profilers (ADCPs), four 

water level gages, six anemometers (wind sensors), an atmospheric temperature and 

barometric pressure sensor, packet radio transmission equipment, a data acquisition 

system, and an information dissemination system. Data are taken at six-minute intervals 

at eight locations in Tampa Bay, as follows in Table 2. Data on wave height and 

direction (a directional wave gauge), and visibility, as well as web cameras providing 

visual images of portions of Tampa Bay, are co-located with certain PORTS® sensors and 

operated by other parties, such as the University of South Florida 

(http://ompl.marine.usf.edu/PORTS/PORTS.brochure.html). 

 water 

level 

current wind wave height/ 

direction* 

visibility*

Old Port Tampa X X X 

Port Manatee X X 

Manatee Channel Entrance X X 

Port of Tampa X 

St. Petersburg X X 

Sunshine Skyway X X X 

Egmont Channel X X X X 

Table 2 

*wave and visibility parameters are not part of the NOAA PORTS® installation and are 

operated by other parties 

 

1

 Information in this section is based on the description of Tampa Bay PORTS® on the system web sites, 

http://co-ops.nos.noaa.gov/tbports/tbports.html, http://ompl.marine.usf.edu/PORTS/, and related web pages. 
 

 8

General Notes on Value of Tampa Bay PORTS®

To maximize the value generated by data from PORTS®, it is necessary to ensure that the 

information reaches all potential users in a timely manner and user-friendly format. A 

single, common, graphic, web-based interface for data is particularly well suited for the 

widely dispersed recreational user community. It is also important to leverage the actual 

observations, which of necessity will be limited to a relatively small number of 

geographic locations, through the use of models that interpolate between and extrapolate 

or forecast from these observations to provide more complete geographic and temporal 

coverage. The NOAA PORTS® web pages for Tampa Bay (http://coops.nos.noaa.gov/tbports/tbpicsgif.html) provide a view of what is presently available; 

projects such as the Tampa Bay Interactive Mapping System (part of the USGS 

Integrated Science Project, http://gulfsci.usgs.gov/tbay_ims/index.html) plan in the future 

to present an integrated view of circulation model output and other data. 

There is little hard data on the utilization of PORTS® data by specific user categories. 

Apart from some general statistics on the number of “hits” on the Tampa PORTS® web 

page, no survey has been undertaken to determine how many users from each user group 

utilize Tampa Bay PORTS® information, how often they do so, and how they utilize the 

information. Anecdotal data gathered in the course of research for this report suggests 

that PORTS® data are used extensively by the maritime operations and safety 

communities, but utilization and even awareness among recreational users is quite low. 

This leads to our classification (see Executive Summary) of many recreational benefit 

estimates as more speculative or potential. To achieve a higher degree of confidence in 

these estimates, it will be necessary to carry out specific surveys of these users. 

Safety 

Avoided Groundings, Commercial Vessels 

PORTS® data have been available to maritime operations in Tampa Bay since the early 

1990s, and since the late 1990s, Tampa Bay pilots have carried laptop computers with 

electronic chart software, GPS, and wireless PORTS® link onto the ships they guide 

through the Bay. Although they do not prove causality, historical data on grounding rates 

for commercial transits of Tampa Bay suggest a reduction in grounding risk accompanied 

the introduction of PORTS® in the early 1990s. 

Data on commercial vessels grounding are drawn from the USCG’s accident databases 

known as CASMAIN (1981-90) and MSIS (1992-95). Data for 1991 are sparse and 

evidently incomplete in each dataset; here, we have replaced the 1991 counts by averages 

of the surrounding years for purposes of analysis. From the USCG data we selected for 

inclusion in this study only accidental, navigational groundings, and ignored those 

identified as intentional or due to mechanical failure or other, clearly non-navigational 

cause. 

Transit data are based on ACE Waterborne Commerce Statistics annual summaries, 

1981-1995 (see USACE, various years). For our purposes, a “transit” is a vessel 

movement, so that a port call usually consists of two transits: one into and one out of the 
 

 9

port. To avoid double counting, we based our transit count on data for only one 

“waterway” as defined by USACE; in this case: waterways code 2021 (Tampa Harbor). 

Average annual transit counts during 1981-95 were 3,700 self-propelled ships and about 

3,000 barge trains. For 2003, the USACE reports about 4,300 self-propelled ship transits 

and 2,500 barge train movements. 

Grounding Rates, Self-propelled Ships, Tampa Bay

0.00

0.50

1.00

1.50

2.00

2.50

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

groundings/1000 transits (5-pt moving average)

Figure 1 

Grounding Rates, Barge Trains, Tampa Bay

0.00

0.50

1.00

1.50

2.00

2.50

3.00

1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

groundings/1000 transits (5-pt moving average)

Figure 2 
 

 10

Figures 1 and 2 show resulting time series of grounding rates in Tampa Bay for selfpropelled ships and barge trains, respectively. Our focus here is on the self-propelled 

vessels, most of which are piloted and likely to have made use of PORTS® data. The 

data show a distinct decline in grounding rates in the early 1990s, during the time when 

PORTS® data first became available. This correlation does not establish causality; other 

factors may well have contributed to this apparent decline in grounding risk. However, it 

is plausible that the availability of PORTS® data materially contributed to this 

development. 

The availability of PORTS® data was perhaps the most significant change in the maritime 

operating environment of Tampa Bay during the early 1990s (M. Farley, p.c. 2005); a 

related significant change came with the introduction of PORTS®-linked portable 

computers used by pilots onboard vessels in the Bay as of 1998. Tampa Bay maritime 

safety officials confirm that grounding risk has remained around 0.5 groundings per 

1,000 deep-draft transit since these measures were introduced (M. Farley, p.c. 2005). 

Given this these developments, a plausible range for the decrease in grounding risk for 

Tampa Bay self-propelled ship transits attributable to PORTS® data is from 20 to 50% 

from the long-term baseline level of about 1.5 grounding per 1,000 transits. This implies 

that PORTS® data prevent between 1.3 and 3.2 deep-draft groundings per year in Tampa 

Bay. 

The economic loss associated with a grounding is the sum of all costs associated with the 

accident. Costs are classified as either internal or external. Internal costs are those 

arising from the vessel involved in the accident and other parts of the marine 

transportation system; they include damage to the vessel, loss of cargo, injury or death of 

crew members, cleanup costs, and delays due to blockage of the route, among others. 

External costs are those incurred outside the transportation system, including 

environmental degradation, human health risks, lost fishery revenues, and lost 

recreational benefits, among others. Both external and internal costs will vary with the 

severity of the accident; the size of the vessel(s) involved, their construction, and their 

cargo; and other factors. External costs will also vary greatly with the environmental and 

human health sensitivity of the location. 

We use here an estimate of the cost of groundings that is based on the approach taken in 

the Coast Guard’s Port Needs Study (PNS) (USCG 1991), taking into account relevant 

parameters such as vessel size, nature of cargo, and nature of the transit area. The PNS 

study included in its loss estimation each of the following categories of losses (see 

Schwenk 1991): 

 - loss of human life and personal injuries, 

 - vessel hull damage, 

 - cargo loss and damage, 

 - economic cost of the vessel being out of service, 

 - spill clean up costs, 

 - losses in tourism and recreation, 

 - losses in commercial fish species, 
 

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 - impacts on marine birds and mammals, 

 - losses due to LPG/LNG fires and explosions, and 

 - bridge and navigational aids damage. 

Not included in the estimation procedure are damages to on-shore facilities and water 

supplies, legal fees for litigation over vessel casualties, cumulative effects of consecutive 

spills, effects of chemical releases into the air, and non-use values. 

A summary of the PNS loss estimation procedure is provided by Schwenk (1991). In 

addition to its own procedures, PNS draws on several sources for damage estimation 

models. These include the Natural Resource Damage Assessment Model (see below); 

several models developed by A.T. Kearney (1990) for losses in tourism, property values, 

and subsistence households; and models by ERG (1990) for losses due to cleanup costs 

and to vessel damage and repair. The PNS data, which reflect inputs from all of these 

models, are used to estimate the losses associated with one accident involving various 

vessel types (tanker, dry cargo, tug/barge) and sizes in each study area. 

Perhaps the most volatile element in the PNS loss estimation procedure is the model used 

to calculate natural resource damages. These damages -- loss of fish, birds, marine 

plants, and other species -- account for between 10 and 40 percent of total damages, 

depending on the location and nature of the accident. The PNS results are based on a 

version of the Department of the Interior's Natural Resource Damage Assessment Model 

for Coastal and Marine Environments (NRDAM/CME) which has since been replaced by 

a new version of NRDAM/CME (see Federal Register 59(5):1062-1189). The new 

version includes a new model of restoration costs and makes use of updated biological, 

chemical, and economic data. Preliminary analysis of the new model's parameters 

suggests that there is no consistent way to scale results from the previous version to 

reflect the likely new model results. The cost estimation algorithm we have used here 

therefore includes natural resource damage estimates based on an "old" version of the 

NRDAM/CME. 

Based on the PNS data, the average economic loss associated with self-propelled ship 

grounding in Tampa Bay is $1.25 million for tankers and $0.5 million for dry cargo 

vessels (in current 2005 dollars). These averages take into account the distribution of 

vessel size and cargo for each port, and also reflect seasonal averages for environmental 

losses. They also reflect the relatively “forgiving” nature of the seabed in Tampa Bay, 

which does not have the hard rock bottom of other US harbors. Fortunately, most Tampa 

Bay groundings to not result in major damage to vessels or in spills of fuel or cargo. In 

fact, there has not been a significant grounding-related spill in Tampa Bay in many years. 

Tankers account for 2,200 Tampa Bay transits per year, or roughly half of the selfpropelled total. Using the assumptions described above, the 20-50% reduction in 

grounding risk due to PORTS® translates into a conservative estimate of $1.1 million to 

$2.8 million in avoided costs per year. 
 

 12

Anecdotal evidence supports the claim that PORTS® data help prevent groundings in 

Tampa Bay. For example, the entrance to Port Manatee Channel requires a sharp turn 

across the flow of the tide, and must be negotiated at slack tide by many vessels. A 1996 

tanker grounding at this location has been attributed in part to reliance on tide tables only 

to estimate slack water time during that transit; PORTS® data are now routinely used for 

this purpose. 

Reduced distress cases, recreational vessels 

The USCG (2004) reports 752 significant recreational boating accidents in Florida waters 

during 2003, leading to 64 fatalities, 487 injuries, and $9.7 million in property damage. 

Nationally, hazardous water and weather are a causal factor in about 10% of recreational 

boating accidents (data specific to Florida waters have not been identified). 

Of the 940,000 boats registered in Florida in 2003 (USCG 2004), about 110,000 are 

registered in Manatee, Hillsborough, and Pinellas Counties (Sidman et al. 2004). If we 

assume that recreational boating activity and accident rates in the Tampa Bay area are 

similar to those in other parts of Florida, this suggests about seven significant weatherrelated accidents per year in Tampa Bay, with 0.5 fatalities, 5 injuries, and $100,000 in 

property damage. 

PORTS® data can play a significant role in improving recreational boaters’ weather 

awareness and preventing weather-related accidents. For example, web cameras 

integrated with PORTS® stations can allow boaters to see conditions “first-hand” before 

they set out; and this probably leads to reduced incidence of distress situations, according 

to Coast Guard officials in Tampa (p.c. 2004). Boaters encounter about 30 days of zero 

visibility conditions on the Bay in an average year. 

If we assume a value of life of $4 million, the direct cost associated with weather-related 

recreational boating accidents on Tampa Bay is on the order of $2 million/year. All of 

these could potentially be avoided by scrupulous use of PORTS® and other weather 

information. Observers knowledgeable about the Tampa Bay recreational boating 

community suggest that between 10 and 50 percent of boaters are aware of, and make use 

of PORTS® data today. A conservative estimate of benefits from PORTS® in this 

instance may be 10% of expected losses, or $200,000/year. 

Efficiency 

Increased cargo carried per transit 

The major cargos transshipped through Tampa Bay are petroleum imports and phosphate 

exports. Petroleum products arrive from Gulf Coast refineries and from the Hess facility 

on St. Croix in the Caribbean. About 60 percent of petroleum coming into Tampa moves 

in barges, which are generally not draft constrained. Tank ships (product tankers) calling 

on Tampa generally have a fully loaded draft of 35.5 ft; this is also the controlling depth 

in the Sparkman Channel, which leads to many of the port’s fuel depots. (This channel 

cannot be deepend further because of constraints imposed by the City of Tampa sewage 
 

 13

pipe.) Nominal depth at many of the fuel docks is 33.5 ft, but a strong NE wind can push 

water levels at the docks down to 30 ft. 

Phosphate exports are carried from Tampa in self-propelled dry bulk freighters. Most of 

this cargo is bound for destinations in Asia and Australia via the Panama Canal, and 

under present Panama Canal operating rules faces a typical draft limit for Canal transits 

of 39.5 ft. The controlling depth in the main Tampa Bay channels is 39 to 40 ft. 

Phosphate shipments thus face Tampa Bay draft constraints primarily at the docks. PrePORTS® underkeel clearance requirements for Tampa Bay called for 2 ft of clearance; 

with PORTS, pilots now move ships with 6 inches of clearance (USCG, p.c. 2004). 

This suggests that PORTS® data may provide the ability to load some ships to drafts 12 

inches or more above what used to be considered safe prior to PORTS®. The number of 

dry cargo transits out of Tampa Bay with draft of 38 ft or more in 2003 was about 50 

(USACE). Using the assumptions summarized in the Table 3 below, and the approach 

outlined earlier in this report, we estimate the annual potential benefit to phosphate trade 

from PORTS® data (AV) as about $1.1 million. 

AV = (AD ×TPI × NC / AC) × ((RT × SC / KTS) + (DOC + (2AC / LR)) × PC)

Parameter Variable Value 

Additional draft enabled by PORTS® information (inches) AD 12 

Tons per inch immersion TPI 90 

Average cargo per transit without PORTS® (tons) AC 60,000 

Number of transits/year affected by PORTS® data NC 100 

Average round-trip distance (nm) RT 15,000 

Operating cost at sea (incl. fuel) ($/hr) SC 600 

Vessel speed (kts) KTS 15 

Docking and undocking time per transit (hours) DOC 24 

Loading/unloading rate (tons/hr) LR 1,200 

Operating cost in port ($/hr) PC 200 

Table 3 

Reduced delays 

A Tampa Bay traffic protocol governing the movement of certain “vessels of concern,” in 

place since 1995, requires one-way traffic in the Bay when vessels of concern are 

transiting. Cruise ships are included in this category because of their large beam and the 

limited channel width in Tampa Bay; and ammonia carriers are included because of the 

hazardous nature of their cargo. The potential delays associated with these one-way 

restrictions are well understood by users of the Bay and generally built into their 

operating schedules now. Under the Vessel of Concern Traffic Protocol issued by the 

Captain of the Port, vessels of concern must enter Tampa Bay between 0200 and 0400, 

with docking between 0530 and 0730; the departure window runs from 1600 to 1730. 
 

 14

Other Tampa Bay operating constraints have been relaxed due to the availability of 

PORTS® data and the resulting increase in confidence among pilots about conditions they 

will face during transits. Tampa Bay Pilots used to hold draft-constrained ships until 

maximum high tide, or delay vessels until winds died down. Port Manatee traffic was 

restricted to daylight operations only prior to PORTS®. The pre-PORTS® underkeel 

clearance requirement in Tampa Bay was 2 ft, and has since been reduced to 6 inches. 

All of these developments reduce the likelihood and severity of transit delays. 

Hard data on delays are not available for Tampa Bay. If we assume, conservatively, that 

PORTS® data reduces delays in one percent of transits (67 transits/year) by 60 minutes, 

and an average operating cost of $200/hr, this translate to $13,400/year in operating cost 

savings. 

Improved SAR performance 

According to search and rescue officials, PORTS® data are not a significant factor in 

improving SAR performance within Tampa Bay (Farley, p.c. 2004). 

Environmental Protection: improved spill response 

There has not been a major vessel-related spill in Tampa Bay since 1993. The 1993 spill 

involved a collision between a phosphate freighter and two fuel barges; some 330,000 

gallons were spilled. Wind and tide moved most of the spill out to sea, but much of it 

eventually returned to St. Petersburg beaches. PORTS®-related data predicted the spill’s 

trajectory well but played no significant role in spill response efforts. The combination 

of relatively soft seabed, one-way traffic rules, and PORTS® data make for a relatively 

low spill risk in Tampa Bay. 

Facility spills, usually associated with tropical storm events (e.g., 2004 phosphoric acid 

spill in Hillsborough Bay), are at least as much of a concern in Tampa Bay as vessel 

spills. No significant response measures exist to mitigate the effects of phosphate process 

water (phosphoric acid) or ammonia spills. However, models incorporating PORTS®

data can provide information on concentrations of acids and other contaminants after a 

spill event, and together with biological data are used to estimate mortality in biological 

communities in the Bay, for use in damage assessment. Although much of the Bay is 

regularly flushed by tides, residence time of water in the Bay varies, and can be as long 

as two weeks in upper bays. 

Damage assessment model exercise conducted by Knutsen (p.c. 2005) considered a 

hypothetical spill of 328,000 gallons of #6 fuel oil from a vessel near the Skyway Bridge 

on an incoming tide (scenario similar to the 1993 spill, but on a different part of the tide 

cycle). The Florida State formula natural resource damage assessment model estimated 

resulting environmental damages of $460 million. It is not known precisely how the 

availability of PORTS® data would influence spill response efforts in the event of such a 

spill, or how that change in response would affect (reduce) environmental damages. If 

we assume, conservatively, a 1% to 5% reduction in damages due to the use of PORTS®

data in spill response activities, and that such spills will happen in Tampa Bay once every 

25 years, the expected annual benefit is between about $180,000 and $900,000. 
 

 15

According to spill response officials, present technology and practice typically allows for 

the recovery of about 10 percent of spilled oil (Watabayashi, p.c. 2005). Some oil spill 

modelers suggest that greater improvements in cleanup effectiveness will be possible 

once PORTS®-like data are integrated directly with more sophisticated hydrodynamic 

current models and models of hydrocarbon transport and fate. Such models exist today 

and are used in risk assessment exercises, among others for spill events in Tampa Bay 

(see French et al. 1999, French McCay et al. 1999, also Mark Luther’s work at the Ocean 

Modeling and Prediction Laboratory at USF, http://ompl.marine.usf.edu/). These models 

are not at present used directly in guiding “live” spill response activities. If these models 

are combined with appropriate spill response, modelers suggest that it may be possible to 

increase recovery to 20% and target recovery efforts more effectively to minimize 

environmental damage (French McCay p.c. 2005). If this can be achieved, environmental 

damages may be reduced by an additional 5% or so. In Tampa Bay’s case, using the 

above assumptions, that means another $900,000/year in expected avoided losses. 

Enhanced Value of Recreation Activities 

It is estimated that between 10 and 50 percent of the recreational boating community 

around Tampa Bay is aware of and (at least occasionally) making use of PORTS®

(Sherburne, p.c. 2004). About 9% of boaters surveyed in 2003-2004 indicated that they 

would like to have more or better information about weather (tide, wind, lightning, seas); 

and one third of these mentioned the internet as the preferred medium for obtaining this 

information (Sidman et al. 2004). 

Boating 

About 110,000 recreational boats are registered in Manatee, Hillsborough, and Pinellas 

Counties as of 2004 (Sidman et al. 2004). The typical boater makes about 3.5 trips per 

month, averaged over the year – or 43 trips/year. Most are day trips, although there are 

also a substantial number of overnights. About 91 percent of boaters surveyed in 2003 

and 2004 had internet access. 

Assuming that a boating day generates economic surplus equal to about 10 percent of 

actual expenditures (Hushak 1999), we estimate the per day surplus from recreational 

boating at $20/day. If PORTS® data leads to a one percent increase in positive boating 

day experiences in Tampa Bay, this suggests in annual non-market benefit from PORTS®

of $946,000. 

Fishing 

64% of recreational boaters surveyed in Tampa Bay 2003-2004 engaged in fishing 

(Sidman et al. 2004). Recreational fishers and guides/charter operators are interested in 

water temperature and in details of current speed and direction (fish are usually not 

caught during slack water). Estimates of willingness to pay for increased fishing success 

on Florida’s Gulf coast range from $3 to $23 per fishing trip (Haab et al. 2000). 

Using a value of $10 per fishing trip, and assuming that boaters who fish do so on 50% of 

their boating trips, and that PORTS® data leads to improved fishing success on one 
 

 16

percent of fishing trips, we estimate the value of PORTS® data to fishers in Tampa Bay at 

about $150,000/year. We consider this a potential benefit because it is not known how 

many recreational fishers routinely utilize PORTS® data at this time. 

Beach Visits 

Surveys indicate that some 15 million beach visitors spent 177 million beach days in 

Florida in 2000 (Leeworthy and Wiley 2001). Typical expenditures directly associated 

with beach recreation are $25 per beach day, and generate an estimated $15 of consumer 

surplus per beach day (Pendleton 2003). Assuming that one percent of Florida beach 

days take place on beaches around Tampa Bay, and that PORTS® can lead to a one 

percent improvement in economic surplus generated by beach use, this suggest an annual 

benefit of $265,000. We consider this to be a potential benefit because there is no solid 

evidence that beach visitors regularly make use of PORTS® data at this time. 

Enhanced Weather Forecasts 

General Weather and Coastal Marine Forecasts 

PORTS® data are used in the local analysis and prediction system operated by the 

National Weather Service office in Tampa. As such, these data help improve both 

general weather forecasts for the Tampa Bay area and coastal marine weather forecasts. 

The value of improved coastal marine forecasts is reflected in the improved recreational 

boating experience of local boaters, as discussed above. The improved general weather 

forecasts benefit all users of weather forecasts in the Tampa area. 

Data used include water level information (for coastal flooding), wind speed and 

direction, and temperature. The weather service uses PORTS® data to verify marine 

warnings generally, and as a basis for marine warnings issued for Tampa Bay. The 

Weather Service typically issues about 20 severe weather warnings/year, mostly during 

the summer, as well as several coastal flood warnings (see below). Some of these 

warnings are based directly on PORTS® data (C. Paxton, NOAA NWS, p.c. 2004). 

The exact contribution of PORTS® data to improved weather forecasts for the Tampa 

Bay area is not known. Using Lazo and Chestnut’s (2002) estimate of about 

$15/household/year for the value of significant improvements to general weather 

forecasts, assuming that PORTS® data contribute 10 percent of such an improvement, for 

an estimated 1 million affected households, results in an annual benefit from improved 

weather forecasting of $1.5 million. We consider this a lower confidence estimate 

because although the mechanism is clear and the use of PORTS® data in this context is 

well established, the magnitude of the contribution of PORTS® to the weather forecast is 

difficult to quantify. 

Storm Surge Forecasts 

Storm surges are associated with large storm events, such as hurricanes, and can cause 

extensive damage. Much of this damage cannot be avoided by an improved forecast, but 

marginal improvements in response activities (securing boats and structures, evacuating 

areas) may be possible or less costly with a more accurate and timely forecast. 
 

 17

The Tampa Bay area is considered among the most endangered in the country from storm 

surge because of its large population and because the geography of the Bay and 

surrounding areas can “trap” the storm surge and cause it to build up significantly. Storm 

surges that measure a few feet in height at sea can build to more than 15 feet in confined 

shallow water and nearshore areas. Nearshore areas along tidal bays and rivers are 

particularly vulnerable. A large storm surge can submerge much of downtown Tampa. 

Major storm surge events hitting urban areas can cause billions of dollars in damages. 

Assuming a $1 billion storm surge damage from a major storm once every 20 years in the 

Tampa Bay area, we estimate an annualized risk from storm surge of $50 million. The 

precise contribution of PORTS® data to storm surge forecast quality and risk reduction is 

not known. Applying the one percent rule, we estimate an annualized value of $500,000 

from improved storm surge prediction. 

Qualitative Effects and Values 

PORTS® data are used in educational and scientific activities that are valuable but do not 

lend themselves to economic quantification. Examples of these are highlighted below. 

Although we do not attempt to quantify benefits from these activities, they are important 

uses of PORTS® data and suggest that the quantified benefits should be treated as a lower 

bound estimate of total benefits from PORTS®. 

Educational use of PORTS®

PORTS® data are used Pinellas Country’s Environmental Distance Learning project 

(http://www.edlonline.org/). This internet-based system makes use of PORTS® data in a 

variety of learning projects for primary school students. It is used by some 2,500 

teachers and recorded 1.3 million internet hits in 2003, 70 percent of which came from 

within Florida (P. Luther, p.c. 2004). 

Scientific Research/Water quality management 

A Comprehensive Conservation and Management Plan for Tampa Bay (EPA National 

Estuaries Program) was adopted 1996. This plan addresses water and sediments, 

habitats, dredge material disposal, spill prevention and response, and public education 

and access. PORTS® data are used in scientific research that supports work associated 

with this plan and with other water quality initiatives in Tampa Bay. Research activities 

include the development and application of circulation models for Tampa Bay to study 

nutrient level effects associated with phosphate process water spills, atmospheric 

deposition of nitrogen via volatilized ammonia, desalination plants, and diversion of fresh 

water from rivers leading into Tampa Bay. 

One of EPA’s environmental goals is to restore sea grass in Tampa Bay to 1950s levels. 

This requires improved water clarity, which in turn requires a reduction in nitrogen 

(nutrient) levels. Atmospheric deposition historically accounts for 50 percent of nitrogen 

input (as well as mercury and other substances) to the Bay. Atmospheric flux models 

used to develop policies to address this issue are driven by wind speed and direction data, 

provided in part by PORTS®. 
 

 18

Harmful algal blooms occur in late summer in Tampa Bay, driven by water temperature 

and nutrient loads. These blooms can lead to shellfish area closures, beach closures, and 

sometimes restrictions on boating activity. PORTS® data can play a role in predicting 

these blooms and in minimizing their adverse effects. 
 

 19

ACKNOWLEDGEMENTS 

Funding for this work was provided by NOAA CO-OPS under the guidance of Richard 

Edwing and Dave McFarland. Rodney Weiher assisted in the administration of the 

project. 

Many people were helpful in giving me insights into the use of PORTS® data in Tampa 

Bay. In particular, Michael Henderson (NOAA) provided valuable assistance on the 

ground in Tampa, identifying and arranging my interviews with most of the people in the 

following list. Among those who provided information on the use of PORTS® in the 

Tampa Bay area were Michael Bailey (NOAA), John Ballaron (Port Manatee Operations 

Coordinator), Brad Benggio (NOAA HAZMAT), Capt. Mel Berman, Suzanne Cooper 

(Tampa Bay Regional Planning Council), Capt. Steve Cropper (Tampa Bay Pilots), 

David Dale (NOAA), Capt. Mike Farley (USCG), Steve Fidler (Tampa Port Authority), 

Terry Fluke (Citgo Marine), Debbie French McKay (Applied Science Associates), 

Ernest Gerlach (Gulf-East Coast Intermodal), Richard Ghent (CF Industries), Joseph 

Gontarski (Port Manatee), Holly Greening (EPA National Estuaries Program, Tampa 

Bay), Cliff Hearn (USGS Tampa Bay Integrated Science Study), Jim Jeansonne (NOAA 

NOS), Richard Knudsen (Florida Fish and Wildlife Research Institute), Ron Kobosky 

(Mosaic), Eric Lesnett (Hillsborough County Environmental Protection Commission), 

Mark Luther (University of South Florida), Pauline Luther (Pinellas County Schools), 

Capt. Dave Markett, Bill Merlin (USGC ret.), Charlie Paxton (NOAA Weather Service), 

Bob Puccinelli, Arthur Savage (AR Savage), Kevin Sherburne, Bill Simpson (TECO 

Ocean Shipping), Capt. Thompson (Tampa Bay Pilots), Glen Watabayashi (NOAA), and 

Todd Wood; as well as the Tampa Bay Harbor Safety and Security Committee. 

I was struck throughout my time in Tampa with the pleasantly collegial and collaborative 

atmosphere within the Tampa Bay marine community. 

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