benefits valuation study - in.gov...bighead (asian) carp are considered a nuisance species and are...

Benefits Valuation Study: Alcoa Warrick Power Plant Prepared for: Alcoa Corporation Prepared by: Matthew F. Bingham Jason C. Kinnell Sara G. Hickman Dawn M. Woodard Victoria L. MacPherson Donna Clark January 2018

Office: 919.677.8787 Economic Consulting Fax: 919.677.8331 VeritasEconomics.com

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Benefit Valuation Study: Alcoa Warrick Power Plant January 2018

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Table of Contents Section Page 1. Overview and Results ....................................................................................................... 1

1.1 § 122.21(r)(11)(i): Incremental Changes in Fish and Shellfish .................................... 1 1.2 § 122.21(r)(11)(ii): Description of Changes in Stock or Harvest Levels ...................... 5 1.3 § 122.21(r)(11)(iii): Description of Monetized Values of Commercial,

Recreational, and Forage Species ............................................................................ 13 1.3.1 Recreational Benefits .................................................................................... 13 1.3.2 Commercial Benefits ..................................................................................... 18 1.3.3 Nonuse Benefits ............................................................................................ 18

1.4 §122.21(r)(11)(iv): Discussion of Previous Mitigation Efforts .................................... 19 1.5 §122.21(r)(11)(v): Discussion of Benefits to the Environment and

Local Communities ...................................................... Error! Bookmark not defined. 1.6 §122.21(r)(11)(vi): Discussion of Thermal Discharge Benefits .. Error! Bookmark not

defined. 1.7 Summary of Benefits ................................................................................................. 21 1.8 Report Organization .................................................................................................. 24

2. Methodological Overview ............................................................................................... 25

2.1 Effects Studied .......................................................................................................... 25 2.2 Methods .................................................................................................................... 25 2.3 Recreational Benefits ................................................................................................ 28 2.4 Commercial Benefits ................................................................................................. 32 2.5 Nonuse Benefits ....................................................................................................... 32

2.5.1 Non-Economic Methods ................................................................................ 33 2.5.2 Rule-of-Thumb Method ................................................................................. 34 2.5.3 Hypothetical Scenario Survey Methods ......................................................... 34 2.5.4 Considering Quantitative Methods for Estimating Nonuse Benefits for

Entrainment Reduction at Warrick ................................................................. 39 2.5.5 Qualitative Evaluation of Nonuse Benefits for Entrainment Reduction at

Warrick .......................................................................................................... 40 3. Baseline Fishing Conditions .......................................................................................... 42

3.1 Characterizations of Stock Dynamics ........................................................................ 42 3.2 Baseline Fishing Conditions ...................................................................................... 43

3.2.1 Baseline Recreational Fishing Conditions ..................................................... 43 3.2.2 Angler Preferences ........................................................................................ 43 3.2.3 Angler Participation: Population Size and Annual Fishing Trips .................... 45 3.2.4 Angling Sites ................................................................................................. 45 3.2.5 Calibrated Baseline Trips and Expected Catch .............................................. 48

3.3 Commercial Fishery .................................................................................................. 49 3.4 Future Baseline Fishing Participation, Trips, and Site Quality ................................... 49

4. Modeling Yield Impacts .................................................................................................. 51


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4.1 Direct Changes in Yield ............................................................................................ 51 4.2 Indirect Changes in Yield .......................................................................................... 51

5. Valuing Changes in Recreational and Commercial Yield ............................................. 53

5.1 Valuing Changes in Recreational Yield ..................................................................... 53 5.2 Valuing Changes in Commercial Yield ...................................................................... 56

6. References ...................................................................................................................... 58

Appendix A Commercial Fishery Benefits Theoretical Overview ........................................ 66

Appendix B Substitute Fishing Sites and Characteristics of Sites ..................................... 79


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List of Figures

Figure Page

Figure 1.1: Direct Changes in the Ohio River’s Commercial and Recreational Fish Stocks with Elimination of AWPP’s Entrainment ........................................................................ 6

Figure 1.2: Direct Changes in Forage Stock Biomass (Pounds) with Elimination of AWPP’s Entrainment ............................................................................................................ 7

Figure 1.3: Trophic Transfer Based Changes in Pounds of Catfish Biomass with Elimination of AWPP’s Entrainment .............................................................................................. 9

Figure 1.4: Total (Direct and Indirect) Changes in Recreational Yield with Elimination of AWPP’s Entrainment ............................................................................................ 10

Figure 1.5: Total (Direct and Indirect) Changes in Commercial Yield with Elimination of AWPP’s Entrainment ............................................................................................ 12

Figure 1.6: Location of Sites with Affected Catch Rates, Location of Substitute Sites, and the Concentration of the Affected Angling Population ................................................. 14

Figure 1.7: Change in Expected Catch per Trip by Species at Affected Sites with Elimination of AWPP’s Entrainment ........................................................................................ 16

Figure 1.8: Estimated Trip Change with Elimination of AWPP’s Entrainment ......................... 17

Figure 1.9: Change in Welfare with Elimination of AWPP’s Entrainment ................................ 17

Figure 1.10: Change in Commercial Value with Elimination of AWPP’s Entrainment................ 18

Figure 2.1: Overview of Methodology for Estimating the Benefits of Entrainment Reductions 27

Figure 2.3: Example of the Choice Question Format in the Stated-Preference Survey ........... 37

Figure 3.1: Angling Population and Fishing Sites Included in the Entrainment Reduction Benefits Study ...................................................................................................... 46

Figure 5.1: The Site Demand Curve and Consumer Surplus .................................................. 54

Figure 5.2: Increase in Consumer Surplus from Increase in Catch Rates ............................... 55

Figure A.1: With-Entrainment Variable Costs.......................................................................... 69

Figure A.2: Vessel Supply Curve with Improved Catch Rates and Constant Prices ................ 70

Figure A.3: Commercial Fish Market (with a Quota) ............................................................... 71

Figure A.4: Commercial Fish Market with Open Access ......................................................... 73

Figure A.5: Case 3: Most Complicated Case—Effort and Price Changes .............................. 74

Figure A.6: Summary of the Benefits of Reduced Entrainment ............................................... 75


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List of Tables

Table Page

Table 1.1 Alcoa Warrick Power Plant: Total Impingement Equivalent Adults .............................. 2

Table 1.2 Alcoa Warrick Power Plant: Total Entrainment Year 1 (June 2015–May 2016) ........... 3

Table 1.3 Alcoa Warrick Power Plant: Total Entrainment Year 2 (June 2016–May 2017) ........... 4

Table 1.5 Timing Specified for Feasible Technologies at AWPP ............................................... 21

Table 1.6 Summary of Recreational and Commercial Social Benefits of Entrainment Reduction Alternatives at AWPP ........................................................................................... 23

Table 3.1 Coefficients from the Bingham et al. (2011) Model .................................................... 44

Table 3.2 Fishing Reported in Indiana and Adjoining States during 2011 .................................. 45

Table 3.3 Conditions of Affected Sites ...................................................................................... 48

Table B.1 Recreational Freshwater Fishing Sites within 100 miles of AWPP ............................ 80


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1. Overview and Results The U.S. Environmental Protection Agency’s (USEPA’s) 2014 316(b) Rule (79 Fed. Reg.

158, 48300–48439) (2014 Rule) requires that applicants submit studies of technologies or

operational measures that can reduce entrainment. The studies must discuss cost, feasibility,

impact, and social cost/benefit of technologies including cooling towers, 2 mm or smaller screens,

and water reuse or alternative water sources (§ 122.21(r)(10)(i–iii) and § 122.21(r)(11)(i-vi)). The

Benefits Valuation Study presents the benefits of each technology and must include the following

elements as defined in 79 Fed. Reg. 158, 48428 (r)(11):

(i) Incremental changes in the numbers of individual fish and shellfish lost due to impingement mortality and entrainment as defined in 40 CFR 125.92, for all life stages of each exposed species

(ii) Description of basis for any estimates of changes in the stock sizes or harvest levels of commercial and recreational fish or shellfish species or forage fish species

(iii) Description of basis for any monetized values assigned to changes in the stock size or harvest levels of commercial and recreational fish or shellfish species, forage fish, and to any other ecosystem or nonuse benefits

(iv) A discussion of mitigation efforts completed prior to October 14, 2014 including how long they have been in effect and how effective they have been

(v) Discussion, with quantification and monetization, where possible, of any other benefits expected to accrue to the environment and local communities, including but not limited to improvements for mammals, birds, and other organisms and aquatic habitats

(vi) Discussion, with quantification and monetization, where possible, of any benefits expected to result from any reductions in thermal discharges from entrainment technologies.

The following subsections summarize the data, methods, and results for each

§122.21(r)(11) requirement.

§ 122.21(r)(11)(i): Incremental Changes in Fish and Shellfish Table 1.1 provides the reduction in impingement mortality of all species and life stages of

fish and shellfish that will occur with elimination of impingement mortality at the Alcoa Warrick

Power Plant (AWPP). The data presented in Table 1.1 are impinged equivalent adults estimated

using the impingement data collected at AWPP from 2005-2006 (EA, Engineering, Science and

Technology, 2007). No threatened or endangered species were collected during impingement

sampling.



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Table 1.1 Alcoa Warrick Power Plant: Total Impingement Equivalent Adults

Impingement Year Species Classification

Species 2005–2006 Forage Commercial Recreational Threatened or Endangered

Blue catfish 1 ● ●

Bluegill 17 ●

Channel catfish 16 ● ●

Crayfish 28 ●

Emerald shiner 5 ●

Flathead catfish 4 ● ●

Freshwater drum 2,115 ● ●

Gizzard shad 9,241 ●

Largemouth bass 1 ●

Longear sunfish 2 ●

Northern madtoma 1 ● a

River carpsucker 2 ●

Sauger 6 ●

Silver chub 1 ●

Skipjack herring 73 ●

Striped bass 7 ●

Threadfin shad 13 ●

Unidentified carpiodes 3 ● ●

Unidentified dorosoma 123 ●

Unidentified ictiobinae 17 ●

Unidentified morone 121 ●

Unionoid mussel 42 ●

White bass 17 ●

White perch 3 ●

Yellow bass 1 ●

Total 11,860

a Northern madtoms are species of special concern in Indiana. Sources: Burns and McDonnell (2017a); Indiana Department of Natural Resources (2017a); Indiana General Assembly (2015);

Kentucky Waterways Alliance (2014)

Tables 1.2 and 1.3 present the reduction in entrainment of all taxa that will occur with a

complete entrainment reduction at AWPP. Entrainment sampling was conducted biweekly (twice

per month) during the biologically productive period (March to October) over a 2-year period from

June 2015 to May 2017. The first year of sampling (Year 1) started in June 2015 with sampling

occurring from June through October 2015 and then March to May 2016.



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Table 1.2 Alcoa Warrick Power Plant: Total Entrainment Year 1 (June 2015–May 2016)

Classification Species Eggs Yolk Sac Larvae Post Yolk Sac Larvae Juvenile Species Total Forage Com Rec Nuisanced T or E

Bighead carp 0 1,619,891.0 915,766.9 0.0 2,535,657.8 ●

Carpsucker/buffalo 0 0.0 52,139,416.7 0.0 52,139,416.7 ●

Catfishes 0 0.0 3,587,433.7 0.0 3,587,433.7 ● ●

Channel catfish 0 0.0 1,854,886.3 111,093.3 1,965,979.6 ● ●

Flathead catfish 0 0.0 0.0 54,829.0 54,829.0 ● ●

Freshwater drum 0 5,836,249.5 162,736,694.3 5,628,195.3 174,201,139.1 ● ●

Gars 0 0.0 401,591.0 0.0 401,591.0 ●

Gizzard shad 0 0.0 3,588,307.8 13,125,619.9 16,713,927.7 ●

Herrings 0 0.0 33,454,973.7 12,271,838.7 45,726,812.4 ●

Madtomsa 0 0.0 459,602.4 0.0 459,602.4 ●

Minnows 0 5,875,979.1 4,161,490.7 74,038.0 10,111,507.8 ● ●

Paddlefish 0 0.0 3,553,713.4 0.0 3,553,713.4 ● ●

Pallid/shovelnose sturgeon 0 0.0 404,972.7 0.0 404,972.7 ●

Sauger 0 0.0 1,119,344.1 0.0 1,119,344.1 ●

Shinersb 0 0.0 4,593,206.1 2,805,683.8 7,398,889.8 ●

Skipjack herring 0 0.0 0.0 5,004,680.8 5,004,680.8 ●

Striped bass 0 0.0 0.0 887,784.3 887,784.3 ●

Temperate bass 0 0.0 0.0 54,829.0 54,829.0 ●

Unidentified eggc 1,789,092 0.0 0.0 0.0 1,789,091.7 ● ●

Walleye/sauger 0 0.0 7,333,762.5 0.0 7,333,762.5 ●

Total 1,789,092 13,332,119.6 280,305,162.3 40,018,591.9 335,444,965.5

Notes a Northern madtoms are species of special concern in Indiana. b Pallid shiners are endangered in Indiana. Pugnose and bigmouth shiners are species of special concern in Indiana. c Unidentified eggs are most likely freshwater drum. d Bighead (Asian) Carp are considered a nuisance species and are excluded from the bioeconomic-based benefits evaluation.

Sources: Burns & McDonnell (2017a); Indiana Department of Natural Resources (2017a); Indiana General Assembly (2015); Kentucky Waterways Alliance (2014)



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Table 1.3 Alcoa Warrick Power Plant: Total Entrainment Year 2 (June 2016–May 2017)

Yolk Sac/Post

Yolk Sac Larvae Post Yolk Sac

Larvae

Classification

Species Eggs Yolk Sac Larvae Juvenile Species Total Forage Com Rec Nuisanceb T or E

Bighead carp 0 2,206,979.1 42,303,240.1 83,966,014.3 0.0 128,476,233.5 ●

Carpsucker/buffalo 0 998,968.7 1,322,397.6 1,982,508.0 0.0 4,303,874.3 ●

Catfishes 0 0.0 0.0 303,551.0 0.0 303,551.0 ● ●

Common carp 0 0.0 0.0 139,404.7 0.0 139,404.7 ● ●

Cypriniformes 0 0.0 18,137,279.0 0.0 0.0 18,137,279.0 ●

Emerald shiner 0 0.0 0.0 0.0 36,822.1 36,822.1 ●

Freshwater drum 5,651,596 0.0 0.0 152,354,462.4 372,437.2 158,378,495.2 ● ●

Gars 0 0.0 0.0 69,456.9 0.0 69,456.9 ●

Gizzard shad 0 0.0 0.0 285,880.6 0.0 285,880.6 ●

Herrings 0 0.0 0.0 5,430,133.6 0.0 5,430,133.6 ●

Minnows 0 0.0 0.0 1,916,457.2 583,003.3 2,499,460.5 ● ●

Paddlefish 0 0.0 0.0 5,951,190.9 0.0 5,951,190.9 ● ●

Perches 0 0.0 0.0 78,526.1 0.0 78,526.1 ●

Shads 0 0.0 0.0 187,763.9 0.0 187,763.9 ●

Shads/herring 0 0.0 167,736.1 0.0 0.0 167,736.1 ●

Skipjack herring 0 0.0 0.0 1,114,532.6 116,587.6 1,231,120.2 ●

Suckers 0 151,644.7 0.0 120,396.5 40,960.3 313,001.5 ● ●

Sunfish/bluegill 0 0.0 0.0 0.0 42,473.4 42,473.4 ●

Sunfishes 0 0.0 0.0 64,604.0 0.0 64,604.0 ●

Temperate bass 0 0.0 0.0 239,705.2 0.0 239,705.2 ●

Unidentified egga 3,755,192 0.0 0.0 0.0 0.0 3,755,192.3 ● ●

Walleye/sauger 0 0.0 0.0 1,357,370.5 0.0 1,357,370.5 ●

Total 9,406,788 3,357,592.5 61,930,652.8 255,561,958.6 1,192,284. 331,449,275.6

Notes a Unidentified eggs are most likely freshwater drum. d Bighead (Asian) Carp are considered a nuisance species and are excluded from the bioeconomic-based benefits evaluation.

Sources: Indiana Department of Natural Resources (2017a); Indiana General Assembly (2015); Kentucky Waterways Alliance (2014)



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The second year of sampling (Year 2) started in June 2016 with sampling occurring from

June through October 2016 and then March to May 2017. Annual entrainment estimates were

calculated by multiplying the entrainment densities by the intake flow. To be conservative, the

design intake flow rate of 567 million gallons per day (MGD) was used and 100 percent mortality

of entrained ichthyoplankton was assumed. No threatened or endangered species were collected

during entrainment sampling (Burns & McDonnell 2017a).

§ 122.21(r)(11)(ii): Description of Changes in Stock or Harvest Levels Differences between With-Entrainment (baseline) and Without-Entrainment conditions are

used to quantify the benefits of entrainment reductions. Simulation models of fish species were

developed to represent the changes to stocks affected by entrainment reduction technologies.

This is accomplished by creating age-structured transition (i.e., Leslie) matrices (Leslie 1945,

1948; Caswell 2001) that characterize the modeled stocks. The Leslie matrix model is frequently

used in fisheries management and has long been an important component of professional

judgment (PJ) 316(b) assessments under 1977 draft guidance (Akçakaya, Burgman, and

Ginzburg 2002; Public Service Electric and Gas Company [PSEG] 1999; USEPA 2002). These

dynamic matrix models are populated with survival rates and weights at age from EPRI (2012a)

and simulated forward to identify changes in fish stocks that are associated with each evaluated

technology.

Tables 1.2 and 1.3 indicate whether each entrained organism is a forage species or a

recreationally and/or commercially harvested species. As Tables 1.2 and 1.3 show, the entrained

species that have commercial or recreational value include common carp, carpsuckers, catfish,

freshwater drum, gar, minnows, paddlefish, perches, sturgeon, striped bass, suckers, sunfish,

temperate bass, and walleye/sauger. Figure 1.1 depicts the estimated changes in fish stocks for

each species with elimination of entrainment at AWPP. The unidentified eggs presented in Tables

1.2 and 1.3 are assigned to freshwater drum. Panel A presents the results using the 2015

entrainment data, and Panel B presents the results using the 2016 entrainment data.

In assessments of entrainment impacts, it is conventional to monetize impacts to forage

species by converting them to recreational and commercial species via the “trophic transfer”

method. As typically applied, this approach multiplies adult equivalent forage biomass by some

factor (often 10%) to identify changes in higher trophic level species that are recreationally and

commercially valuable. Adult equivalent forage biomass is identified using methods described in

Section 4 for the higher trophic level species to identify numbers and then multiplying by weight

at age to calculate biomass. Figure 1.2 depicts the adult equivalent forage biomass for the



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Figure 1.1: Direct Changes in the Ohio River’s Commercial and Recreational Fish

Stocks with Elimination of AWPP’s Entrainment

Commercial and Recreational Species

Panel A: 2015

Panel B: 2016



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Figure 1.2: Direct Changes in Forage Stock Biomass (Pounds) with Elimination of

AWPP’s Entrainment

Forage Species

Panel A: 2015

Panel B: 2016



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entrained species. Panel A presents the results for the 2015 data, and Panel B presents the

results for the 2016 data.

The approach of directly converting this biomass into gamefish biomass has had some

important advantages in the historical 316(b) regulatory context. These include that it allows

“accounting for” all entrained species, and it is straightforward to implement because it does not

account for the complex and changeable predator-prey relationships of actual food webs.

However, under the 2014 Rule’s peer-review requirement, it is important that the deficiencies of

this approach not be ignored. Primarily, the trophic transfer approach interprets observed

average biomasses at different trophic levels (e.g., 10-to-1 forage to predator) as causal without

meaningful foundations for doing so and in the face of extensive information that indicates

otherwise (Pauly and Christensen, 1995; Zhao, Kocovsky; Madenjian, 2013; Madenjian et al.

1996). Perhaps the most glaring problem with this approach is its inconsistency with the estimates

developed for recreational and commercial species. In particular, it is specified that higher trophic

level species are under fishing pressure from above (humans), rendering them unlikely to be

constrained by forage availability. Moreover, if forage constraints do limit populations of higher

trophic levels, consistency would require considering that some or all of the increased stocks

implied by the reduced entrainment such as those depicted in Figure 1.1 would consume the

increase in forage biomass. Unlike complex, food-web based considerations this concern about

the trophic transfer approach is a simple one of consistency and the avoidance of double counting

within a benefits analysis.

With these deficiencies recognized, the trophic transfer approach is applied. The selected

predator is catfish. Figure 1.3 depicts trophic transfer based changes to the catfish stock as a

result of the changes in forage biomass (in pounds).



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Figure 1.3: Trophic Transfer Based Changes in Pounds of Catfish Biomass with

Elimination of AWPP’s Entrainment

To identify the yield changes associated with changes in stocks, harvest rates are applied

to stock changes. When possible, these harvest rates are based on stock assessments. When

stock-specific recreational harvest rates are not available, these are developed using professional

judgment. Figure 1.4 presents the increase in recreational yield with the elimination of

entrainment at AWPP. Panel A presents the results using the 2015 entrainment data, and Panel

B presents the results using the 2016 data. The results include both the direct changes in

recreational yield from the entrainment reductions and the indirect yield changes from the

reductions in forage species using the results of the production foregone evaluation.

Catfish Biomass from Forage Species (pounds)



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Figure 1.4: Total (Direct and Indirect) Changes in Recreational Yield with


Recreational Yield

Panel A: 2015

Panel B: 2016



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In addition to recreational yield changes, the analysis also considers commercial yield

changes. As Tables 1.2 and 1.3 illustrate, AWPP’s entrained species of common carp,

carpsuckers, catfish, freshwater drum, minnows, paddlefish, shovelnose sturgeon, and suckers

are identified as potentially having commercial value. This identification is based on the

evaluation of the 2012 commercial harvest data which identifies approximately 1,678,651 pounds

of commercially harvested species (Kentucky Waterways Alliance 2014). The 2012 data are the

most recent published data of commercial landings reported for the Indiana, Illinois, and Kentucky

waters of the Ohio River (although not reported by river pool). Commercial anglers from Indiana

primarily seek catfish and paddlefish (Indiana General Assembly 2015).

Based on the entrainment rates of these species and commercial fishing conditions, the

analysis evaluates changes in commercial yield for the species entrained at AWPP that are

commercially harvested in the Ohio River and expected to have a change in commercial yield

with a reduction of AWPP’s entrainment. Figure 1.5 depicts the estimated changes (both direct

and indirect) in pounds of these commercially harvested taxa if entrainment at AWPP was

eliminated. Panel A presents the results using the 2015 entrainment data, and Panel B presents

the results using the 2016 data



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Figure 1.5: Total (Direct and Indirect) Changes in Commercial Yield with


Commercial Yield

Panel A: 2015

Panel B: 2016



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§ 122.21(r)(11)(iii): Description of Monetized Values of Commercial, Recreational, and Forage Species Estimating the benefits of entrainment reduction requires assessing the relationship

between entrainment, fishery changes, and the impact that fishery changes have on people. For

recreational values this includes understanding how AWPP’s entrainment affects recreational

fishing catch rates and how those changed catch rates affect angler well-being.

The methodology uses a site-choice simulation to evaluate the effect that entrainment has

on recreational fisheries. To evaluate the effect of entrainment, the analysis modifies site catch

estimates to generate recreational catch that could occur with entrainment reductions. The

methodology determines the economic value of the estimated catch changes by linking them to

models of recreational angling demand presented in Bingham et al. (2011).

The models used to generate age-structured changes in stock use survival parameters

are from EPRI (2012a). These are linked to the site-choice simulation model through fishery-

specific catch and effort rates. This forms a bio-economic equilibrium (i.e., yield, trips, and

expected catch are integrated) for the With-Entrainment representation of the Ohio River fishery

expected to be affected by AWPP’s entrainment. These integrated partial equilibrium models are

used to simulate conditions under With-Entrainment (baseline) and Without-Entrainment

conditions, and the monetized welfare differences between these two conditions determine the

benefits of entrainment reductions. As described in EPA’s Guidelines for Preparing Economic

Analysis, equilibrium modeling using the With- and Without-Impact approach is central to all

sound benefit estimation processes and regulatory impact analysis (USEPA 2010).

1.3.1 Recreational Benefits Changes in yield could occur at recreational sites throughout the Ohio River and are

specified to occur at the set of aggregated sites presented in Figure 1.6. Figure 1.6 also shows

the location of alternative, substitute sites where anglers can fish that are not affected by AWPP’s

entrainment and the angling population that is most likely affected by changes in AWPP’s

entrainment. The affected angling population is specified to be anglers residing in the ZIP Codes

located in the counties that within 50 miles of AWPP. The shading illustrates the number of

anglers residing in each ZIP Code contained in the counties.



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Figure 1.6: Location of Sites with Affected Catch Rates, Location of Substitute

Sites, and the Concentration of the Affected Angling Population

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The analysis apportions the estimated yield changes over the affected sites according to

angling pressure. This approach results in similar changes in per-trip expected catch across sites.

Figure 1.7 presents the per-trip change in bluegill, catfish, common carp, freshwater drum,

paddlefish, perches, striped and temperate bass, suckers, sunfish, and walleye/sauger expected

catch at each of the affected sites. Panel A presents the 2015 data, and Panel B presents the

2016 data.

Based on these expected catch changes, equations from welfare economics are used to

identify annual changes in trips and economic benefits (based on changes in expected catch for

all affected species). As detailed in Section 5, changes in consumer surplus that arise from

changes in site demand is the metric for economic benefits. This methodology is consistent with

economic theory and adheres to rule discussion with respect to considering the “the availability

of alternative competing water resources for recreational usage [alternative substitute sites], and

the resulting estimated change in demand for use and value of the affected water resources”

(USEPA, 2014, p. 48,371). Figure 1.8 depicts the total change in trips at the three sites where

catch changes are specified to occur based on the elimination of AWPP’s entrainment. Figure

1.9 depicts the annual change in dollar-valued welfare associated with the estimated trip changes

from the complete elimination of AWPP’s entrainment.



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Figure 1.7: Change in Expected Catch per Trip by Species at Affected Sites with


Expected Catch

Panel A: 2015

Panel B: 2016



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Figure 1.8: Estimated Trip Change with Elimination of AWPP’s Entrainment

Figure 1.9: Change in Welfare with Elimination of AWPP’s Entrainment

Affected Sites Change in Trips

Welfare Difference in US Dollars



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1.3.2 Commercial Benefits To assess the commercial fishing benefits, the analysis applies the price per pound from the

National Marine Fisheries Service’s 2012 data of annual landings in Midwestern states (National

Oceanic and Atmospheric Administration [NOAA] Office of Science and Technology 2017; Wildlife

Management Institute 2015) to the changes in commercial yield estimated to result from elimination

of AWPP’s entrainment. The analysis specifies that all of the additional harvest will be sold at 2012

prices, the most recent year for which complete price data is available. Figure 1.10 presents the

results of the evaluation using both the 2015 and 2016 entrainment data.

Figure 1.10: Change in Commercial Value with Elimination of AWPP’s Entrainment

1.3.3 Nonuse Benefits The final category of benefits that could be monetized is nonuse benefits. Krutilla (1967)

presented the original philosophical underpinning for nonuse values, arguing that individuals do not

have to be active consumers of unique, irreplaceable resources in order to derive value from the

continuing existence of such resources. He wrote that “when the existence of a grand scenic wonder

or a unique and fragile ecosystem is involved, its preservation and continued availability are a

significant part of the real income of many individuals” (p. 779).

Change in Commercial Value in US Dollars



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Important components of Krutilla’s original concept are that nonuse values are related to the

continuing existence of unique resources. Under this framework, common resources suffering from

limited injury do not generate significant nonuse values. The economic literature emphasizes the

relationship between nonuse values and both the uniqueness of the resource in question and the

irreversibility of the loss or injury (Freeman 1993). Freeman summarizes this relationship as

follows:

…economists have suggested that there are important nonuse values in …preventing the global or local extinction of species and the destruction of unique ecological communities. In contrast, resources such as ordinary streams and lakes or a subpopulation of a widely dispersed wildlife species are not likely to generate significant nonuse values because of the availability of close substitutes (p. 156).

As Freeman’s text indicates, common resources (i.e., resources that are not unique) that do not

experience irreversible losses are not likely to generate significant nonuse value.

The impacts at AWPP have been occurring over a number of years. The entrainment

samples at AWPP do not indicate that any threatened or endangered species are being entrained.

These resources and impacts also exhibit low levels of awareness as quantified in the 2012

Environmental Impacts Awareness Study (Veritas Economics 2012).

Thus, although the described quantified outcomes could conceivably be associated with

nonuse benefits (e.g., changes in entrainment, changes in stock), the magnitude of nonuse values

for entrainment reductions at AWPP has not been quantitatively evaluated as part of this effort.

However, based on the precepts of nonuse values, we expect that the nonuse benefits of reducing

entrainment at AWPP to be low. This position is described further in Section 2, which also

discusses that a quantitative implication of the qualitatively “low” estimate for nonuse values at

AWPP is that nonuse values should have little impact on a cost to benefit-based Best Technology

Available (BTA) determination. Specifically, given the estimated entrainment reduction costs and

benefits, correctly measured nonuse benefits would not impact a BTA determination that

considers benefits and costs based on any historically applied criteria.

§122.21(r)(11)(iv): Discussion of Previous Mitigation Efforts There have been no previous entrainment mitigation efforts at AWPP.

§122.21(r)(11)(v): Discussion of Benefits to the Environment and Local Communities This section of the rule requires a “discussion, with quantification and monetization, where

possible, of any other benefits expected to accrue to the environment and local communities,



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including but not limited to improvements for mammals, birds, and other organisms and aquatic

habitats.” Reductions in AWPP’s entrainment have the potential to affect the number of fish

species in the Ohio River. The analysis specifies what those levels would be using available life-

history and stock information. Quantifying “benefits expected to accrue to the environment or

local communities” would require analysis of increasing levels of complexity of food web dynamics

and has not been included in this analysis. In lieu of quantified benefits, the following discussion

has been provided.

In theory, positive impacts on local fisheries may generate an improvement in the

population levels and diversity of mammals, birds, and other organisms and aquatic habitat.

species. However, limited, if any, other direct or indirect benefits to mammals, birds, other

organisms and aquatic habitats are anticipated to occur at AWPP by implementing an entrainment

reduction technology. Based on the very low number of biomass lost to the ecosystem, and the

amount of biomass in the Ohio River that will continue to be available (i.e., not entrained), benefits

to mammals, birds, and other organisms are anticipated to be limited. No aquatic mammals or

commercially or recreationally important aquatic invertebrates inhabit the Ohio River in the vicinity

of AWPP; therefore, no direct or indirect benefits to mammals or other aquatic invertebrates are

anticipated. No benefits to aquatic habitats are anticipated because an increase in fish biomass

from implementing an entrainment reduction technology does not improve the overall physical

conditions of the habitat. Improvements to habitats such as wetlands, backwater embayments,

and sand bars or habitat formers typically occur from the restoration or enhancement of water

quality, sediment quality, structure (water depth, water velocity) and/or native vegetation.

§122.21(r)(11)(vi): Discussion of Thermal Discharge Benefits This section of the rule requests a “discussion, with quantification and monetization, where

possible, of any benefits expected to result from any reductions in thermal discharges from

entrainment technologies.” Under the existing conditions, AWPP discharges its thermal effluent

into the Ohio River. With closed-cycle cooling, the thermal discharge would no longer occur. In

some cases, thermal plumes can create attractive environments for fish and birds during colder,

winter months.

AWPP has a thermal variance and a 316(a) Variance Demonstration Study was conducted

in 2017 by Burns & McDonnell. Before a thermal variance under Section 316(a) can be granted,

“40 C.F.R. §§ 125.72 and 125.73 require the permittee to demonstrate that the otherwise

applicable thermal discharge effluent limit is more stringent than necessary to assure the

protection and propagation of the waterbody’s balanced, indigenous community of shellfish, fish

and wildlife.” To support a proposed alternative thermal limit, “the discharger must demonstrate



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that the alternative limit will assure protection of the BIP, considering the “cumulative impact of its

thermal discharge together with all other significant impacts on the species affected.”

The results of the biological community characterization in this 2017 study demonstrate

that the AWPP thermal discharge has not caused prior appreciable harm to the aquatic

community and does not prevent the protection and propagation of a balanced indigenous

community. Therefore, the reduction of the thermal discharge is not expected to have measurable

changes in benefits to the balanced, indigenous community. Given that AWPP’s discharge is not

causing measurable changes in the Ohio River’s balanced indigenous population of shellfish, fish,

and wildlife, the analysis does not quantify changes in ecological or economic conditions from

thermal effluent reductions.

Summary of Benefits The results presented throughout this section have shown the effects of each step to

develop the benefits of eliminating entrainment at AWPP. In addition to a 100-percent reduction,

the analysis also considers the benefits that would result from the entrainment reduction

alternatives that have been evaluated at AWPP. Table 1.5 presents the timing specifications for

each of the feasible technologies.

Table 1.5 Timing Specified for Feasible Technologies at AWPP

Entrainment Reducing Technology

Regulatory Documents Submitted

Permitting, Design, Construction &

Installation O&M Costs

Begin Years of

Operation

Closed-Cycle Retrofit 2018 2018-2021 2022 20

0.5-mm Fine Mesh Traveling Screens (FMS) 2018 2018-2020 2021 20

1.0-mm Fine Mesh Traveling Screens 2018 2018-2020 2021 20

2.0-mm Fine Mesh Traveling Screens 2018 2018-2020 2021 20

0.5-mm Cylindrical Wedgewire Screens (CWS) 2018 2018-2020 2021 20

1.0-mm Cylindrical Wedgewire Screens 2018 2018-2020 2021 20

2.0-mm Cylindrical Wedgewire Screens 2018 2018-2020 2021 20

Table 1.6 presents the recreational and commercial benefits for each entrainment

reduction technology evaluated. The table presents both the present and annual value of benefits

using both sample years of AWPP’s entrainment data and separates the benefits into commercial



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and recreational. To develop the present value estimates, the benefits estimated for each feasible

alternative are discounted at 3 and 7 percent annually and summed over the specified time period

used in the analysis.

The total maximum benefit of eliminating entrainment at AWPP ranges from $1.2 to $2.8M

using the 3 percent discount rate and $0.6 to $1.4M using the 7 percent discount rate. For the

closed-cycle retrofit, a present value estimate ranged from $0.6M to $2.7M. Using 2015

entrainment data, the majority of the benefits come from the improvements to the recreational

fishery. Using 2016 entrainment data, the majority of the benefits come from improvements to the

commercial fishery. Annualizing these results over the specified 20-year time period results in

annual benefits ranging from over $29,000 to over $0.1M. Table 1.6 also presents the benefits

of three fine mesh traveling screens (0.5-mm, 1.0mm, and 2.0mm) and three cylindrical

wedgewire screens (0.5-mm, 1.0-mm, and 2.0-mm).



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Table 1.6 Summary of Recreational and Commercial Social Benefits of Entrainment Reduction Alternatives at AWPP

2015 Entrainment Data 2016 Entrainment Data

Discount Rate

Entrainment Reductiona

Present Value Annual Value Present Value Annual Value Technology Rec Com Total Rec Com Total Rec Com Total Rec Com Total

3% 100% Reduction 100% $2.2M $0.7M $2.8M $107.8k $33.7k $141.5k $0.2M $1.0M $1.2M $11.6k $48.8k $60.4k

Closed-Cycle Retrofit 94.6% $2.1M $0.6M $2.7M $102.7k $31.9k $134.6k $0.2M $0.9M $1.1M $11.0k $46.2k $57.2k

0.5-mm FMS 0% - 80% $0.8M $0.1M $0.8M $38.1k $3.4k $41.5k $0.03M $0.02M $0.04M $1.4k $0.8k $2.2k



0.5-mm CWS 96% - 100% $2.2M $0.7M $2.9M $110.1k $33.7k $143.9k $0.2M $1.0M $1.2M $11.6k $48.5k $60.2k



7% 100% Reduction 100% $1.1M $0.3M $1.4M $53.0k $16.8k $69.8k $0.1M $0.5M $0.6M $6.0k $25.1k $31.0k

Closed-Cycle Retrofit 94.6% $1.0M $0.3M $1.3M $50.5k $15.9k $66.4k $0.1M $0.5M $0.6M $5.7k $23.7k $29.4k







Notes: Total may not sum due to rounding. a Entrainment reduction effectiveness ranges based on reduction by life stage (Burns & McDonnell, 2017b).



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Report Organization The following sections present more detailed discussions of the data, methods, and results

presented above. Section 2 presents a more detailed discussion on the methods used to assess

the commercial, recreational, and nonuse values associated with entrainment reduction

alternatives. Section 3 then provides a characterization of the baseline fishery (i.e., the state of

the fishery with AWPP’s current rates of entrainment). Section 4 describes the entrainment

estimates on which the fishery yield change and fishery benefit estimates are based, and the

approach used to estimate the direct and indirect fishery impacts resulting from AWPP’s

entrainment. Section 5 concludes by presenting the methods for evaluating the recreational and

commercial benefits resulting from the changes in yield.



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2. Methodological Overview The U.S. Environmental Protection Agency’s (USEPA’s) 2014 316(b) Rule (79 Fed. Reg.

158, 48300–48439) requires that applicants submit studies of technologies or operational

measures that can reduce entrainment. This section presents an overview of the methods for

estimating the fishing benefits associated with entrainment reductions at AWPP as required by

§ 122.21(r)(11)(i-iii)).

AWPP is located at 4700 Darlington Rd, Newburgh, Indiana. In the course of its normal

operation, AWPP withdraws water from the Ohio River through a cooling water intake structure

(CWIS). As this water is withdrawn, entrainment occurs. Because aquatic systems are

interrelated, AWPP’s operations could potentially affect any of the species found in the Ohio River.

Effects Studied Although any of the species residing in the Ohio River could potentially be affected by

AWPP’s entrainment, for practical reasons it is useful to limit the evaluation to effects most likely

to have meaningful magnitudes. Accordingly, this assessment was limited to species that are

most affected by AWPP’s entrainment, as indicated by 2015–2016 entrainment estimates (Burns

& McDonnell 2017a) and the effects on important commercial and recreational fisheries in the

Ohio River.

The Ohio River provides a recreational fishery for residents and visitors. Anglers catch

black bass, bluegill, carp, catfish, crappie, freshwater drum, sauger, temperate bass, and other

sportfish in the Ohio River. Anglers have access to the Ohio River through at least 23 boat ramps,

11 marinas, and many shore access points within 100 miles of AWPP (ORSANCO 2015).

Stock-level effects could be experienced as changes in catch rates by people hoping to

catch the affected species in the Ohio River. Commercial and recreational anglers that were

modeled as potentially being affected include those fishing the Ohio River from Warrick County

and neighboring counties.

Methods Cooling water intake structures are regulated under Section 316(b) of the Clean Water Act

(CWA). Under the 2014 316(b) Rule (79 Fed. Reg. 158, 48300–48439), social benefits and social

costs of entrainment-control remedies as identified in peer-reviewed studies play a key role in

establishing case-by-case Best Technology Available (BTA) entrainment mortality reduction

standards (§ 125.98(f)). Social benefits must be assessed by the facility owner and included in



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the plant’s permit application submissions. An important part of this evaluation is the identification

of fishery impacts from entrainment. These impacts are uncertain and could result in no effect.1

Estimating the benefits of entrainment reductions requires assessing the relationship

between entrainment, its corresponding changes to the relevant fishery, and the impact that

fishery changes have on people. For example, properly assessing recreational values requires

understanding how AWPP’s entrainment affects recreational fishing catch rates and how those

changed catch rates affect the well-being of anglers located in the plant’s relevant vicinity.

Properly assessing commercial values requires understanding how entrainment affects

commercial catch rates, the profitability of commercial harvesters, and the prices consumers pay

for commercially harvested fish.

The methodology uses a resource-economic simulation to evaluate the effects that

entrainment has on recreational and commercial fisheries. To evaluate the effect of entrainment,

site catch estimates are modified to generate recreational and commercial catch that could occur

without the plant’s entrainment. The methodology determines the economic value of the

estimated catch changes by linking them to a model of recreational angling demand and

evaluations of the relevant commercial fishing markets.

The methodology extends the most relevant fishery and resource-economic studies

published in the peer reviewed literature. Important modeling features include linking yield

equivalence, expected catch, and choice-based behavioral fishing models. These integrated

partial equilibrium models are used to simulate conditions under With-Entrainment (baseline) and

Without-Entrainment conditions, and the differences between these two states of the world

determine the benefits of entrainment reductions. As described in EPA’s Guidelines for Preparing

Economic Analysis, equilibrium modeling using the With- and Without-Impact approach is central

to all sound benefit estimation processes and regulatory impact analysis (USEPA 2010).

Figure 2.1 provides an overview of the methodology for evaluating the economic benefits

of reducing entrainment at AWPP. The shading in the bottom portion of the figure denotes that

the evaluation is separated into two parts: a Baseline (With-Entrainment) evaluation (top white

portion) and a Without-Entrainment evaluation (bottom shaded portion). The calculated difference

in recreational and commercial yield, catch rates, trips, angler welfare, and commercial profits

represent the benefits of entrainment reductions. The approach begins by specifying the baseline

yield for each evaluated species and dividing that into recreational (R) and commercial yield (C).

1 Barnthouse (2013) notes that the available peer-reviewed literature does not support a conclusion that entrainment

reductions will produce measurable improvements in recreational or commercial fish populations.



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Figure 2.1: Overview of Methodology for Estimating the Benefits of Entrainment

Reductions

The model then relates that yield to expected catch rates for the affected waterbody under

the baseline, With-Entrainment, conditions. For brevity, Figure 2.1 illustrates this process for

estimating recreational fishing benefits. Those catch rates are apportioned over the estimated

number of trips that are occurring at affected sites.

Under the Without-Entrainment conditions, the reduction in entrainment and the change

in recreational and commercial yield that would accompany the entrainment reduction are

identified. The new recreational yield is incorporated into changes in expected catch rates and

the corresponding changes in trips that would accompany increase catch rates are estimated. To

calculate recreational fishing benefits the model evaluates the differences between the two states

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Bas

elin

e

R Yield

Stock

Stock C Yield

Expected Catch

Trips

Consumer Surplus Differential

Red

uced

E

Stock Differential

Stock + Adult Equivalents

R Yield + R Yield Equivalents

Stock C Yield + C Yield Equivalents

Expected Catch

Trips

Yield Differential

Trip Differential

Expected Catch Differential



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of the world, including yield, expected catch, and trips. The box around the expected catch and

trip differentials identifies that these result in the recreational fishing benefits measured as the

consumer surplus differential. Consumer surplus is the appropriate economic estimate of value:

the difference between what an angler has to pay for a fishing trip and what the angler would be

willing to pay.

Simulating the linked models produces equilibrium-based changes in stock, yield, trips

and expected catch under Without-Entrainment conditions. Equations from welfare and market-

based economics are used to identify changes in consumer and producer surplus which are then

discounted to calculate present values. The following subsections provide additional detail on the

recreational, commercial, and nonuse value components of the model.

Recreational Benefits Correctly calculating recreational benefits requires a significant amount of information and

calculations. As the 2014 Rule describes,

“…assessing recreational use benefits involves estimating the improvements in recreational fishing opportunities resulting from reduced impingement mortality and entrainment, and assigning a value to these improvements. The value assignment is based on the estimated population profile—in particular, number and proximity to affected water resources—of recreational users, the availability of alternative competing water resources for recreational usage [alternative substitute sites], and the resulting estimated change in demand for use and value of the affected water resources based on reduced impingement mortality and entrainment and increased recreational fishing performance (USEPA, 2014, p. 48,371).”

To account for all this information, the methodology for estimating recreational angler benefits is

based on simulating angler behavior and changes in social welfare resulting from reductions in

entrainment and the associated increases in expected catch. To do this, a mathematical

representation of angler demand (recreational angling demand model) for the population

expected to be affected by reductions in AWPP’s entrainment was developed. The recreational

angling demand model identifies angler behavior across site characteristics that occur in both the

Baseline and With-Out Entrainment conditions. Important modeling features include fusing an

existing, behavioral (choice-based) preference function to spatially represented population data.

This fusing process produces integrated partial equilibrium models that are used to simulate

conditions under Baseline and Without-Entrainment conditions. The differences between these

two conditions determine the social welfare changes associated with the entrainment reductions

resulting from an individual entrainment control technology.



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Important factors accounted for in the recreation angling demand model include angler

preferences; attributes associated with the fishing sites they have to choose from; the number,

quality, and availability of substitute fishing sites; the geographic range of impacted species; the

number of trips with improved catch rates; and the number of anglers associated with those trips.

Preference functions are used to identify how anglers tradeoff the characteristics of

alternative fishing sites when they choose how and where to participate in recreational fishing.

When anglers take a trip, they have a choice of which site to visit. The sites from which they can

choose have numerous characteristics such as the distance from their home, catch rates, facility

amenities (e.g., presence of a boat launch), and water-body characteristics and surroundings

(e.g., fresh versus saltwater, level of crowding, and remoteness of the surroundings).

Preference functions include the (nonmarket) price of fishing as the costs anglers incur in

traveling from their homes to recreation sites. These “prices” vary according to angler locations.

When existing fishing sites have their features changed, such as a change in catch rates that

could occur with entrainment reductions at a power plant, the preference function allows

interpreting the value of the quality change in terms of travel costs. Anglers respond to catch rate

changes by reallocating their trips so as to maximize the value of their fishing experience. For

example, if entrainment rates are reduced and catch rates increase, an angler who typically visits

a site farther away with a higher catch rate under Baseline conditions, would not have to travel as

far to achieve a similar fishing experience under Without-Entrainment conditions. This angler

would incur lower travel and time costs and experience welfare improvement because the same

fishing experience costs the angler less in avoided travel and time costs.

Random utility analysis is the best method for evaluating angler preferences and valuing

entrainment reductions on recreational fishing.2 However, conducting an original random utility

maximization (RUM) study can require extensive primary data collection. Developing a recreation

demand model using a site-calibrated transfer of a preference function from an existing RUM

study can capture important behavioral responses (i.e., changes in trip-taking behavior as a result

of changes to a fishery) without requiring survey-data collection. The accuracy of this

methodology is limited only by the analyst’s ability to calibrate an already estimated preference

2 Random Utility Maximization (RUM) models are recognized in the Department of the Interior (DOI) regulations (43

CFR §11.83) as an appropriate method for quantifying recreation service losses in natural resource damage claims. Currently, the RUM is the most widely used model for quantifying and valuing natural resource services. RUMs are also widely accepted in other areas of the economics profession. RUMs have been used in transportation (Beggs, Cardell, and Hausman 1981; Hensher 1991), housing (McFadden 1997), and electricity demand estimation (Cameron 1985), as well as more recently in environmental and resource economics.



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function to a different population using appropriate economic methodologies (Smith, van Houtven,

and Pattanayak 2002).

Economists have long used the preference functions from random utility models (RUMs)

to estimate demand curves (Bingham et. al 2011; Kinnell et al. 2006; Bockstael, McConnell, and

Strand 1991; Morey, Shaw, and Rowe 1991; Bockstael, Hanemann, and Kling 1987; Bockstael,

Hanemann, and Strand 1986; Caulkins, Bishop, and Bouwes 1986; Feenberg and Mills 1980).

The USEPA endorsed the use of RUMs for 316(b) applications in the now remanded rule (USEPA,

2004, p. 41,658). The RUM is based on welfare theory and posits that individuals make choices

that maximize their utility, subject to constraints.

RUMs divide fishing areas into discrete sites, each site being a plausible destination for

fishing. In this framework, anglers choose which sites to visit, based on costs and fishing

opportunities at the sites. Because anglers trade off factors, such as the cost of getting to the site

against the quality of the fishing opportunity, this approach can evaluate the relative influence of

these variables as revealed by anglers’ decisions. Incorporating the relevant alternative,

substitute sites allows evaluating the importance of site characteristics at each of these sites to

identify the site-demand curves. These form the foundation for appropriately estimated economic

benefits of changes in site attributes such as catch rate improvements.

The focus on site characteristics, such as catch rates, allows for the isolation of benefits

to recreational fishing due to entrainment reductions. All other site characteristics are held

constant. The better the characteristics of a site are, the higher the probability that an angler will

choose that site, which is reflected in a higher value for the site. RUMs can be used to estimate

both the distribution of trips among various sites and the total satisfaction received from a given

set of fishing opportunities.

The analysis uses four main steps to develop the recreational angling demand model and

estimate the benefits associated with reductions in AWPP’s entrainment. The first step involves

selecting the angling preference function from the best available RUM study. The next step

identifies the appropriate geographic scope for substitute sites and selects a representative

sample of substitute sites. We use available information on recreation in the area and typical

travel distances to develop an appropriate area of alternative, substitute sites to include in the

model, generally within 100–200 miles of the affected site. Most RUMs based on original data

use studies providing high-quality data. We employ several substitute sites that are

representative and reasonable and provide a similar fishing experience for anglers who potentially



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fish near AWPP. By capturing substitution among sites, the simulation adds a critical level of

realism relative to approaches that ignore substitution possibilities.

The third step in the analysis entails fusing the preference function to the affected

population and calibrating the model’s prediction of the population’s trips. For this analysis, we

allow the affected anglers to include any angler located in the counties that are adjacent to the

Ohio River near AWPP. Because distance-based travel cost is an important variable in the

recreational angling demand model, anglers closer to the site have a higher predicted likelihood

of visiting the site than those farther away. For the sites affected by AWPP’s entrainment, we fix

the number of trips to correspond to the best available information on current visitation. Within

these constraints, the remaining trips are distributed among the substitute sites in an appropriate

manner, also based on available visitation information.

The distance traveled to a site is one of the most important site characteristics in a RUM.

It directly influences the travel cost to each site for each angler. A critical factor for the site-

calibrated benefits transfer is distance from each angler’s residence (ZIP code) to each site

included in the recreational angling demand model. These distances are calculated using the

most recent version of a popular transportation routing software called PC*Miler (ALK

Technologies 2010). Travel costs reflect both direct costs and travel time costs. Direct costs are

calculated by multiplying the round-trip miles by $0.1818 per mile, which is the American

Automobile Association’s (AAA) 2017 per-mile cost of operating a motor vehicle (AAA 2017). The

cost per mile includes gas, maintenance, and tires and is averaged across nine types of vehicles:

small, medium, and large sedans; small and medium SUVs; minivans; crew cab pickups; hybrid

vehicles; and electric vehicles. The average hourly wage of each ZIP code within the model is

calculated by dividing household income from the U.S. Census by 2,000 work hours per year.3

Travel time in minutes is also calculated by PC*Miler. The round-trip time estimate is multiplied

by one-third of the average hourly wage rate to reflect the opportunity cost of time based on the

original research of Cesario (1976) and the more-recent evaluation by Phaneuf and Smith (2004).

In the fourth step, we simulate changes in trip patterns that anglers make in response to

changes in catch rates. For purposes of this assessment, we increase catch at the affected sites

included in the model. The increased catch rate is incorporated into the calibrated RUM while all

other site characteristics for the relevant sites are held constant.

3 While the U.S. Census’ household income data can include income from more categories than just the amount of

earnings for a household’s hourly wages times the number of hours worked in a year, the U.S. Census’ household income by ZIP Code is the best data source available to estimate the modeled population’s opportunity cost of time. The potential effect on benefit estimates from using the U.S. Census income data would be to have an upward bias on benefit estimates.



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Commercial Benefits Commercial benefits from entrainment reductions accrue to commercial anglers as

increased profit attributable to the higher catch per unit effort (CPUE). The CPUE is associated

with increases in fish populations and/or to fish consumers in the form of lower prices. The ability

of commercial anglers to realize sustained increased profits depends on the responsiveness of

market prices to higher CPUE. Market extremes determine the upper and lower bounds on

commercial benefits. In competitive markets, prices adjust instantly and benefits accrue to

consumers. In restricted markets, prices do not change and commercial benefits are maximized

in the form of producer surplus at price times quantity (P * Q). As the rule describes, estimating

the commercial benefits of entrainment reductions involves consideration of the fishery’s relevant

market conditions. Specifically, the 2014 Rule notes that

“…assessing the productivity and value of commercial fisheries involves estimating the expected increases in commercial yield of economically valued species over time as a result of reduced impingement mortality and entrainment, and valuing these at market prices minus any incremental production costs associated with the incremental catch (USEPA, 2014, p. 48,371).”

To assess the commercial fishing benefits, the methodology first characterizes the current

market conditions that exist in the relevant vicinity of AWPP. The methodology characterizes the

operation of the commercial fishery under the With-Entrainment conditions and evaluates the

commercial fishing market conditions. It then uses the information from changes in commercial

yield to determine the effect on commercial catch per unit effort, market prices, producer surplus,

and consumer surplus under Without-Entrainment conditions. Finally, the methodology estimates

the difference in producer surplus and consumer surplus under the With and With-Out

entrainment conditions to determine the commercial fishing benefits.

Nonuse Benefits Recreational and commercial benefits from entrainment reductions arise from changes in

catch rates and therefore accrue to people who use the affected resource. Another benefit

category, nonuse benefits, results from changes in values that people may hold for a resource,

independent of their use of the resource. These can arise for a number of reasons: they may be

happy that other people can use the resource, they may want it to be available for people to use

in the future, or they may believe the resource has some inherent right to exist.

While experts tend to concur on the existence of nonuse values, they are inherently difficult

to observe. As a result, these values are looked upon quite differently from recreational and

commercial values. By comparison with use values, there is less agreement among experts about



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how nonuse values should be measured, and the reliability of measurement techniques

(Barnthouse, Bingham, and Kinnell 2016).

There are a handful of approaches that have been applied to quantify nonuse values both

in the context of entrainment reductions and more generally. These include the non-economic

methods of Habitat Replacement Cost (HRC) and Societal Revealed Preference (SRP), a “rule-

of-thumb” approach called the Fisher-Raucher approximation, and two approaches that require

administering surveys that pose hypothetical questions called Contingent Valuation (CV) and

Discrete Choice Experiments (DCE).4 The following text summarizes these methods as they’ve

been applied for entrainment and evaluates their applicability.

2.5.1 Non-Economic Methods We refer to HRC and SRP as non-economic methods because they do not attempt to

measure economic value. Considering HRC, the costs estimated are the total costs of restoring

habitats so that they produce ecological services equivalent to those expected from technological

alternatives. These are not benefits, and over the course of EPA’s 316(b) rulemaking, numerous

reviewers commented as such. Rather, they are alternative costs for achieving similar objectives.

Mitigation approaches, such as stocking and habitat restoration, may achieve similar waterbody-

level outcomes as entrainment reductions. However, the cost of such alternatives bears no

implicit relationship to the benefits of reducing entrainment.

The underlying reason for this is that measures of economic benefits must be based on

the willingness-to-pay (WTP) principle, and HRC is not based on this principle. In many cases,

the cost of developing a resource can substantially exceed the resource’s value. Although EPA

extensively evaluated HRC during its development of the Phase II Rule, EPA ultimately decided

that the HRC method should not be used as a means of estimating nonuse benefits due to

limitations and uncertainties regarding the application of this methodology (Volume 69, Fed. Reg.,

No. 131, p. 41,625).

The second cost-based methodology considered in EPA rulemaking is called Societal

Revealed Preference (SRP). Rather than using the cost of a hypothetical alternative (as under

HRC), SRP uses historical costs under prior government mandates to measure benefits. Like the

HRC method, this is a cost-based approach that has no foundation in economics. Accordingly, it

is not accepted by economists as a legitimate method of empirical valuation. In fact, the SRP method is a corrupted application of the legitimate revealed preference (RP) method. An essential

4 Both CV and DCE can also appropriately be called “Stated Preference” (SP) techniques as they both rely on stated

rather than revealed (i.e., by taking fishing trips) preferences. Although DCE is often called SP, here we use the more precise term. Also, DCE is often referred to as “conjoint analysis” which is a related, but not identical technique.



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characteristic of RP analysis, that is not part of SRP, is that willingness to pay is revealed by those

who are doing the paying. In contrast, the SRP methodology inappropriately takes the fact that a

program exists as evidence that its benefits exceed costs.

The drawbacks of these methods, with respect to valuation, would seem to indicate that

they should not be used for estimating the nonuse values of entrainment reductions. This position

is, strictly speaking, correct. However, as the following discussions will describe, the methods

that appear at least theoretically capable of quantifying nonuse values are subject to

disagreement regarding their reliability and there remain important questions about bias in nonuse

survey estimates and extrapolation of nonuse survey results. In part because of these difficulties,

Natural Resource Damage Assessments (NRDAs) have effectively abandoned nonuse valuation

and embraced the Habitat and Resource Equivalency Analysis (HEA and REA) methods.

2.5.2 Rule-of-Thumb Method EPA has also considered the Fisher-Raucher or “50 percent” rule. This approach

approximates nonuse values at 50 percent of recreational use values. The approximation is

derived from a comparison of use and nonuse values for water-quality improvements, where the

nonuse values were estimated using the contingent valuation (CV) method (Fisher and Raucher

1984). Applying this “50-percent rule” for entrainment reductions has the great advantage of

being simple. However, it is based on CV studies which are subject to questions about their

reliability. This rule-of-thumb was based on water quality improvements. There is not good

evidence that the ratio of nonuse to use benefits from water-quality improvements is similar to

that same ratio for environmental improvement from reductions in entrainment. In particular, use

values from fish often arise from their consumption whereas use values from water quality are

typically non-consumptive.

2.5.3 Hypothetical Scenario Survey Methods Currently, the only conceptually correct methods (i.e., those applying the WTP concept),

available for estimating nonuse values, are survey-based techniques that ask respondents to

value, or choose natural resource services in a hypothetical context. These are the Contingent

Valuation and Discrete Choice survey methods.

Contingent Valuation The contingent valuation method involves surveying individuals to elicit their willingness

to pay (WTP) for different levels of services.5 For example, the survey may ask respondents a

question such as, “What is the maximum amount you would pay to restore wild salmon runs in

5 See Hausman (1993) and Arrow et al. (1993) for a more detailed critique of CV.



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the Columbia River Basin?”6 The responses are analyzed to determine the average WTP for

preserving wild salmon runs. This method requires that individuals be able to express their value

for changes in the fishery and, furthermore, that their responses to hypothetical questions indicate

their actual valuations of the changes described in the questions.

The CV method attempts to establish, through the course of a survey, a hypothetical

market where environmental changes can be traded like commodities. Ultimately, the goal of the

CV survey is to establish circumstances that represent an exchange of money for the

environmental service. Oral or written descriptions, supplemented by visual aids, are used to

make the survey informative and realistic.

The validity and reliability of CV has been questioned because respondents’ hypothetical

payment for a nonuse service has no behavioral experience to support or test the expressed

value. This lack of a linkage between actual behavior and the hypothetical payment makes CV

estimates particularly sensitive to variations in survey design, implementation, and analysis.

In addition to this sensitivity, the hypothetical nature of CV makes responses subject to

bias. The inclination is for respondents to state that they would pay a higher amount for a good

or service than they would actually pay. This problem was recognized by the National Oceanic

and Atmospheric Administration (NOAA) when it suggested that CV estimates be treated to the

“divide by 2” procedure. That is, to account for hypothetical bias, researchers should divide

estimates of WTP from CV by 2.

NOAA’s “divide by two” rule has no strong empirical basis but it did set economists on the

task of calibrating hypothetical valuations, by comparing them with values derived from real

exchanges, where respondents gave up real money for real goods. Bias from valuation for public

goods (such as fisheries) is especially difficult to investigate, however, because hypothetical

versus real experiments for public goods are difficult to design.

The value estimate from CV data is typically the average WTP from the survey question.

Researchers may model these responses to determine what characteristics of respondents

influence their WTP. An important implication is that, in addition to designing the survey,

researchers must determine the relevant population for the survey. That is, they must determine

“to whom do these results apply?” Identifying this group is important because survey estimated

WTP estimates must be aggregated over the affected population to determine total WTP. A

6 Natural resource economists have used a variety of question formats. This question is an open-ended format.

Alternatives include bidding games, payment cards, and referendum or dichotomous choice. In the dichotomous choice format, respondents are offered a particular payment amount and allowed to accept or reject that amount. See Mitchell and Carson (1989) for a detailed discussion.



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critical and unresolved consideration is that, by its nature, participating in a survey raises

awareness. This is a fundamental difference between the surveyed “aware” population and the

not-surveyed population that is less aware of the impact, but sometimes makes up the vast

majority of the population willingness-to-pay.

A more sophisticated stated preference technique is discrete choice experiments. DCE’s

explicitly recognize that commodities have value because of their attributes. For example, a car

has value because of such specific characteristics as size, color, comfort, body style, handling,

gas mileage, price, etc. A DCE survey asks respondents to choose among a series of different

alternatives with different levels of attributes and different costs. By analyzing the choices made

by respondents, researchers can uncover the underlying preferences for these attributes and

respondents’ WTP for different attributes or attribute bundles such as environmental programs.

Discrete Choice Experiments DCE methods have been applied in the fields of environmental and health economics as

an alternative to the CV method. For example, the DCE technique has been used to value hunting

trips and fishing (Gan and Luzar 1993; Mackenzie 1993; Roe, Boyle, and Teisl 1996), to explain

recreation site-choice selection (Adamowicz, Louviere, and Williams 1994), to determine public

preferences for siting an industrial facility (Opaluch et al. 1993). DCE has also been applied to

measure changes in fishery services (Banzhaf, Johnson, and Mathews 2001).

EPA conducted a DCE to evaluate total (use and nonuse) values for entrainment

reductions (USEPA 2012). EPA selected a total target sample of 2,000 completed surveys across

four regions and a national sample. The EPA allocated these surveys across regions based on

an experimental design which presents a set of three hypothetical choices to each respondent.

Figure 2.2 presents an example of the choice questions.

As Figure 2.2 shows, the choices presented to respondents are profiles that include a

monetary payment and improvement in environmental variables, including reductions in

entrainment, improvements in fish populations, commercial fish populations, and overall aquatic

health. Responses to the choice experiment are modeled for a Northeast, Southeast, Inland

(containing the Great Lakes), Pacific, and National region using the mixed logit econometric

technique. Although many environmental variables are insignificant, in all cases the variable

representing reductions in entrainment is statistically significant. The EPA approximated survey

respondents’ willingness to pay (WTP) for a 1% change in fish saved, from entrainment

reductions, by conducting simulations for alternative uncertainty distributions of resulting

preference coefficients. Ultimately, EPA estimated that WTP for a 1% reduction in the number of

fish impinged and entrained varies between $0.75 and $2.52 per household per year for the four



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Figure 2.3: Example of the Choice Question Format in the Stated-Preference

Survey



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regions surveyed, and averages at $1.13 per household per year for the National region (Exhibit

II-10 in USEPA 2012).7

DCE, such as that conducted by EPA, has advantages over CV. DCE encourages

respondents to explore their preferences for various attribute combinations through a series of

choices. The process of explicitly trading off attributes encourages greater respondent

introspection than is likely to occur in a traditional CV format. The absence of such introspection

has been a major criticism of the validity and reliability of CV estimates (Schkade and Payne

1994). The approach also allows analysts to devise internal consistency checks because

respondents provide answers to multiple questions. Having more information from respondents

on their relative preferences for the scenarios allows analysts to systematically evaluate whether

a respondent’s pattern of answers is plausible and consistent with economic theory used to

construct social values (Johnson and Bingham 2001). These internal consistency checks are a

significant improvement over the rudimentary technique of using general follow-up questions to

assess respondents’ motives for answers to single CV questions.

Because it provides values for individual components of commodities, as well as for

commodities as a whole in a single survey, DCE has general applicability. DCE is frequently used

to evaluate the market potential for new goods or services that are being developed and have not

yet been brought to market or have only recently been introduced to the market. The large

number of such studies that have been done have given the technique substantial credibility in

the area of new product development and forecasting demand for unfamiliar products (Louviere,

Flynn, and Carson 2010).8 Certain of these are for environmental products that have a “nonuse

flavor” such as green electricity (Johnson et al. 1995).

Despite these advantages, DCE has significant drawbacks for calculating nonuse values.

Like CV, it elicits expressed preferences under hypothetical conditions. As a result, the responses

are likewise hypothetical, which implies that respondents do not have to make a real dollar

commitment as they would in a real-market situation. Experimental evidence demonstrating

hypothetical bias in choice experiments has been found by Johansson-Stenman and Svedsäter

(2008). Also, like CV, the question of the affected population is critical. DCE offers higher

potential for connecting WTP to personal characteristics (EPRI 2012b). However, there is

currently no solution to the fact that, by nature of them having taken the survey, the surveyed

population is fundamentally different from the not surveyed population (EPRI 2012b). Although

7 “National” refers to the survey administered to a national sample and is referred to as a region for convenience. 8 Discrete choice experiments are a subset of conjoint analysis and stated preference techniques. The technical

distinction is well-explained in “Discrete Choice Experiments Are Not Conjoint Analysis” (Louviere, Flynn, and Carson 2010).



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there is no study of nonuse values in which these obstacles have been surmounted, recent efforts

have proposed novel extensions of typical DCE surveys that propose methods for minimizing bias

and extrapolating to the not surveyed population (Barnthouse, Bingham, and Kinnell 2016).

2.5.4 Considering Quantitative Methods for Estimating Nonuse Benefits for Entrainment Reduction at AWPP As this overview of methods indicates, certain approaches that have been proposed for

evaluating the nonuse value of entrainment impacts are not consistent with willingness-to-pay, the

economic concept of monetary value. Considering the replacement cost and societal revealed

preference approaches, there is the potential to entrain species that are recreationally and

commercially valuable, forage species, and threatened and endangered species.

Forage species are also already valued. Also, lack of stocking of forage species would tend

to indicate these species are not emphasized in the SRP approach. On the other hand, HEA and

REA (techniques that are similar to HRC) are implemented under Natural Resource Damage

Assessment (NOAA 2000), and it is possible to implement a habitat replacement approach for a

reasonable level of effort and these approaches have been applied in entrainment decision-making

(Veritas Economics 2010). However, it is important to bear in mind that these are cost-based and

not-value-based estimates.

The “rule of thumb” approach is straightforward to implement. However, the approach is

based on water quality, as opposed to fishery impacts. Although the approach is based on methods

that are conceptually capable of identifying nonuse values, the reliability of these methods is

questionable. Bias in the underlying nonuse studies is likely. The appropriate amount of adjustment

(following NOAA) is not known. Moreover, the approach is dated. If the approach were applied,

nonuse benefits would simply be half of the estimated recreational benefits.

The EPA DCE study elicits values from users and nonusers and therefore elicits both use

and nonuse values. It is potentially feasible to extract a use/nonuse ratio from this study. However,

this has not been attempted and may not be straightforward—users can experience nonuse values

and it is not clear how to disentangle them. As described in EPRI (2012b) and Barnthouse, Bingham,

and Kinnell (2016), an important consideration with nonuse values is the appropriate population to

extrapolate over. There is no utility theoretic foundation known to EPRI that allows unaware

nonusers to experience welfare increases.

The results from the 2012 Environmental Impacts Awareness survey provides insight into

the size of the aware population. The survey was administered to a representative sample of

more than 2,000 United States’ residents and asks them about their current awareness of



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environmental impacts, including impacts from power plants (Veritas Economics 2012). The

results of the survey indicate that slightly over 13 percent of the United States population is aware

of aquatic impacts from steam electric plants. These include impacts such as water pollution,

thermal discharge, wastewater impacts, and impacts to fish. No respondents specifically

mentioned impingement and entrainment, only one respondent was aware that fish could be

impacted through cooling water intakes, and fewer than 5 percent of respondents are aware that

fish can be affected by power plant operations (this includes respondents who are aware of fish

impacts resulting from either steam electric or hydroelectric plants).

The final approach would be to apply a survey that elicits in the hypothetical context.

Although a significant amount of work has been done in this area, conducting a site-specific study

would be a significant undertaking and has not been contemplated for this effort.

2.5.5 Qualitative Evaluation of Nonuse Benefits for Entrainment Reduction at AWPP The magnitude of nonuse values for entrainment reductions at AWPP has not been

quantitatively evaluated as part of this effort; rather, nonuse values have been addressed

qualitatively. Given the importance of benefits in site-specific decision-making, it is important to

provide context for this qualitative assessment. Of particular interest is the question of whether

there is any reason to believe that nonuse values could have a magnitude that would have

implications for decision-making. Nonuse values are a component of all benefits, which must be

considered by Directors making Best Technology Available (BTA) determinations. These social

benefits are to be compared against social costs.

With regard to the Clean Water Act (CWA), the idea of weighing costs relative to benefits

appears in Section 304(b)(1)(B) of the CWA, referring to effluent limitation guidelines. The actual

phraseology of “wholly disproportionate” as rendered in the judicial history states that “[t]he

balancing test between total cost and effluent reduction benefits is intended to limit the application

of technology only where the additional degree of effluent reduction is wholly out of proportion to

the costs of achieving such marginal level of reduction for any class or category of sources”

(Kennecott v. United States EPA).

The “wholly disproportionate cost test” was first applied to Section 316(b) during In the

Matter of Public Service Company of New Hampshire 10 ERC 1257 (May and Van Rossum 1995).

In the decision for that case, the sole basis for applying the “wholly disproportionate” cost test

came from the aforementioned legislative history of the CWA. The ruling stated that Section

316(b) did not require implementation of technology whose cost was “wholly disproportionate” to

its environmental benefits. Following the Seabrook II Decision, the “wholly disproportionate” cost



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test has been applied differently in various cases, depending on the specific facts of the case. In

the previously issued Phase III Rule, EPA promulgated national standards only for new offshore

oil and gas extraction facilities, but also prepared a cost-benefit analysis of regulating additional

Phase III facilities (i.e., existing manufacturing facilities that use cooling water). In this analysis,

EPA found a ratio of costs to benefits that ranged from 17-to-1 to 22-to-1 and found this to be

"wholly disproportionate." Ratios as low as two or three to one have also been determined as

wholly disproportionate.

An implication of the qualitatively “low” estimate for nonuse values at AWPP and these

determinations is that nonuse values should have little impact on cost-to-benefit based BTA

determination at AWPP. Specifically, with entrainment reduction costs that are tens to hundreds

of times the level of benefits, correctly measured nonuse benefits will not influence a BTA

determination that considers benefits and costs based on any historically applied criteria.



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3. Baseline Fishing Conditions The analysis relies upon establishing baseline conditions and models that can be

subjected to counterfactual experiments (reductions in entrainment). To accomplish this,

integrated models were developed of baseline stocks, yields, catch per trip, and angler trip-taking

behavior. This section discusses the baseline fishing conditions.

Characterizations of Stock Dynamics Simulation models of fish stocks in dynamic equilibrium were developed to represent the

stocks affected by once-through cooling. This is accomplished by creating age-structured

transition (i.e., Leslie) matrices (Leslie 1945, 1948; Caswell 2001) that characterize the modeled

stocks. The Leslie matrix model is frequently used in fisheries management and has long been

an important component of professional judgment (PJ) 316(b) assessments under 1977 draft

guidance (Akçakaya, Burgman, and Ginzburg 2002; Public Service Electric and Gas Company

[PSEG] 1999; USEPA 2002).

The mathematical representation of the Leslie matrix is:

(1)

This representation consists of a stock vector and a transition matrix. N1...NA is the stock

vector (on the far right of Equation 1). The stock vector represents the age-structured population

of a single stock at time t with N1,t being the number of Age 1s in the stock at time t, N2,t the

number of Age 2s, and so forth through all the ages. Survival rates (S) in the transition matrix

represent the probabilities that a fish in a population will survive to the next life stage. Fecundity

fns is the number of eggs laid annually by each female of a particular age-class. Survival estimates

used for populating the Leslie Matrix were obtained from a recent EPRI fish life history reference

document (EPRI 2012a).

N1,t + 1N2,t + 1

N3,t + 1

•••

NA,t + 1

=

N1,tN2,t

N3,t

•••

NA,t

S0 f1

S1

0•••0

S0 f2

0S2

0

• • •

S0 fA

00•••0

• • •• • •0…

•••

SA–1

Fecundity

Transition MatrixEstimated Population at

Time t + 1

Initial Population at

Time t



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Baseline Fishing Conditions Baseline fishing conditions are the current state of the world with AWPP’s entrainment.

The characterization of baseline fishing conditions considers recreational and commercial fishing,

both current and into the future. To characterize baseline fishing conditions, we assess current

recreational and commercial yield with AWPP’s entrainment, the number of recreational and

commercial anglers potentially affected by the impact that AWPP’s entrainment has on

recreational and commercial yield, the number of fishing trips the anglers take with AWPP’s

entrainment, the sites that those anglers visit, and catch rates. 9

3.2.1 Baseline Recreational Fishing Conditions When anglers take a fishing trip, they have many sites to choose from with varying

attributes. These attributes include how far the site is from the angler’s house, the type and

number of fish the angler can expect to catch at each site, and the level of development at each

site. Angler preferences across varying site attributes are characterized using recreational

angling demand models.

3.2.2 Angler Preferences The most sophisticated angling demand models are econometrically estimated using

random utility models (RUMs). RUMs are the best method for evaluating angler preferences

across these different site attributes (USEPA 2010). The EPA endorsed the use of RUMs for

316(b) applications in the now remanded rule (69 [131] Fed. Reg. 41658 July 9, 2004).10 The

RUM is based on choice theory and posits that individuals make choices that maximize their utility,

subject to constraints. In this framework, anglers choose which sites to visit, based on costs and

fishing opportunities at the sites. Because anglers trade off factors, such as the cost of getting to

the site against the quality of the fishing opportunity, this approach can evaluate the relative

influence of these variables as revealed by anglers’ decisions.

A number of such studies have been conducted. Bingham et al. (2011) covers fishing

sites across New Jersey and explicitly consider various fishing experiences, including ocean,

estuarine, and freshwater sites (.e.g., inland lakes, rivers, and stream). The survey process was

consistent with accepted survey protocols. The study’s response rate is consistent with survey

research standards, and its models are rigorous, perform well, and reveal results that are

consistent with expectations.

9 One Native American tribe resides within the Ohio River Basin, but they do not practice treaty or subsistence fishing

rights in the Ohio River waters of Indiana (Kappen, Allison, and Verhaaren 2012). 10 RUMs are also widely accepted in other areas of the economics profession. RUMs have been used in transportation

(Beggs, Cardell, and Hausman 1981; Hensher 1991), housing (McFadden 1997), and electricity demand estimation (Cameron 1985).



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The statistical model estimated in Bingham et al. (2011) is a nested logit. To delineate

potential differences in angler preferences with respect to fishery type, Bingham et al. (2011) uses

a three level fishing structure. On the first level, anglers choose whether or not they will fish. On

the second level, anglers choose which waterbody type to fish from (freshwater, saltwater, or tidal

sites). Lastly, after selecting a water body type, anglers decide which site to choose.

The model output is a coefficient for each site characteristic. Each coefficient reflects the

importance of that site characteristic to angler welfare. These coefficients play a key role in the

approach used in this assessment. Table 3.1 contains the relevant coefficients and t-statistics

from the Bingham et al. model.

Table 3.1 Coefficients from the Bingham et al. (2011) Model

Characteristic Coefficient t-Statistic

Travel cost -0.024 -9.93

Boat ramp 1.49 19.69 Trout and shad 0.31 7.42

Panfish 0.16 4.72

Freshwater game 0.16 8.67 Other freshwater 0.08 2.71

Other saltwater 0.36 8.86

Saltwater small game 0.16 3.01 Flatfish 0.95 10.70

When considering yield changes, value at the species level is a critical component of

overall value. The Bingham et al. model includes coefficients for catch rates for both freshwater

and saltwater species. Freshwater game species include walleye/sauger. The other freshwater

species group includes species such as bluegill, catfish, common carp, freshwater drum, suckers,

and temperate bass.

Values at the species level are typically identified by coefficients from random utility

models. However, species-level values are notoriously difficult to estimate. For example,

although anglers have different preferences, most models are based on an “average” angler. In

addition, anglers often misidentify catch (Page et al. 2012) and many “species” coefficients are

actually based on species groupings (Lupi et al. 1998).



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3.2.3 Angler Participation: Population Size and Annual Fishing Trips The U.S. Fish and Wildlife Service (USFWS) conducts the National Survey of Fishing,

Hunting, and Wildlife-Associated Recreation every five years. Among other information, the

survey collects data on anglers and the types of fish that they catch. This assessment uses data

from the 2011 survey for Indiana because those are the most recent, complete data on angling

activity. According to the national survey, 11 percent of Indiana residents, 7 percent of Illinois

residents, and 10 percent of Kentucky residents 16 years of age and older fished during 2011

(USFWS 2013a, 2013b, 2013c, 2014).

Table 3.2 summarizes the number of anglers and days spent fishing by Indiana, Illinois,

and Kentucky residents during 2011 (USFWS 2013a, 2013b, 2013c). To develop the baseline

number of annual trips taken by potentially affected anglers, the analysis applies these trip rates

to the anglers located in the specified affected population.

Table 3.2 Fishing Reported in Indiana and Adjoining States during 2011

Category Indiana Illinois Kentucky

Number of anglers 0.720 million 0.955 million 0.451 million

Days spent fishing 21.502 million 15.491 million 10.031 million

Average number of fishing days per angler 30 16 22

Source: USFWS (2013a, 2013b, 2013c)

3.2.4 Angling Sites In addition to using information on angler preferences and participation, the recreational

angling demand model has to contain information on the sites an angler can potentially visit. We

collect information from publicly available sources on the most popular inland river and lake sites.

Figure 3.1 illustrates the fishing sites and angling population used in AWPP’s fishing benefits

model. The red circles represent the sites that the model specifies as being affected by AWPP’s

entrainment. The blue triangles are the alternative, substitute fishing sites that anglers can

potentially visit in addition to the affected sites that are included in the model. Fishing sites include

shore and boat fishing. Appendix B presents the characteristics of the sites included in the model.



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Figure 3.1: Angling Population and Fishing Sites Included in the Entrainment

Reduction Benefits Study

VeritasEconomic Consulting



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The shading represents the number of anglers residing in each Indiana ZIP Code

contained in the model. The number of anglers is derived from using the 2010 U.S. Census

population by ZIP Code and the percent anglers from the 2011 Indiana, Illinois, and Kentucky

FWS Survey of Fishing, Hunting, and Wildlife-Watching (U.S. Census Bureau 2017, USFWS

2013a, 2013b, 2013c). The dark green represents ZIP Codes with up to 1,000 anglers; the lighter

green represents ZIP Codes with 1,001 to 2,000 anglers; the yellow represents ZIP Codes with

2,001 to 3,000 anglers; the orange represents ZIP Codes with 3,001 to 4,000 anglers; and the

red represents ZIP Codes with more than 4,000 anglers.

Anglers can choose among many quality fishing sites within 100 miles of AWPP, including

other locations along the Ohio River. Many substitute fishing sites feature attractive amenities,

such as parks and marinas. Besides the Ohio River, attractive fishing sites include Dogwood

Lake and Patoka Lake, Indiana; Crab Orchard Lake, Illinois; and Lake Barkley, Kentucky. Brief

descriptions of these sites follow.

• Ohio River, Indiana—Anglers can catch largemouth and smallmouth bass, spotted bass, yellow bass, blue catfish, channel catfish, flathead catfish, black crappie, white crappie, tiger muskellunge, northern pike, sauger, and trout. Harvest rates can exceed 1 fish per hour. Anglers rank catfish among the top five most preferred species. Catfish weighing as much as 104 pounds have been caught from the Ohio River (Indiana Fishing Regulation Guide 2017; Indiana Wildlife Federation 2017; Perleberg 2016; Berg 2014; Henley 1995; Jackson 1986).

• Dogwood Lake, Indiana—According to state biologists, “Dogwood is an excellent crappie lake,” rated by Game and Fish magazine as one of the five best crappie waterbodies in the state. Dogwood Lake, located within the 8,060-acre Glendale Fish and Wildlife Area, also provides high catch rates of largemouth bass (Berg 2010; Indiana Department of Natural Resources 2017b).

• Patoka Lake, Indiana—This 8,800-acre lake “is best known for its quality largemouth bass fishing.” Bass tournaments are held on Patoka Lake each year, which “also has good fishing for channel catfish, crappie, white bass, and striped bass.” This lake is part of a 25,800 acre state recreation area located near historic sites. Patoka Lake Marina & Lodging offers floating cabins on the lake (Carnahan 2001, 2008; Indiana Department of Natural Resources 2017c; Patoka Lake Marina & Lodging 2017).

• Crab Orchard Lake, Illinois—This 6,036-acre lake provides good catch rates for largemouth bass and particularly good catch rates for crappie. Fishing tournaments are held routinely at Crab Orchard Lake, which is located within 43,890-acre Crab Orchard National Wildlife Refuge (Illinois Department of Natural Resources 2017; Miller-Ishmael et al. 2001).

• Lake Barkley, Kentucky—“Fishing on Lake Barkley is an angler's dream,” according to Lake Barkley Tourism (2017). The Kentucky Department of Fish & Wildlife Resources Fisheries Division (2017a) forecast the potential for fishing on the 45,600-acre Lake Barkley as excellent for crappie, largemouth bass, and redear sunfish. Potential fishing for blue catfish, bluegill, and white bass was rated good to excellent.



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Fishing tournaments are held routinely on Lake Barkley (Kentucky Department of Fish & Wildlife Resources Fisheries Division 2017a, 2017b, 2017c; Lake Barkley Tourism 2017).

Table 3.3 lists conditions at affected sites in the Ohio River. Catch rates are specified to

be the catch per hour and are listed for six categories. Saltwater small game species are not

available within 100 miles of AWPP.

Table 3.3 Conditions of Affected Sites

Category Cannelton Pool, Ohio River

Angel Mounds Boat Ramp

Smithland Pool, Ohio River

Angler trips 43,279 31,131 16,249

Catch rate:

Trout or shad 0.0000 0.0000 0.0000

Panfish 0.7800 0.7800 0.0000

Freshwater game 0.0800 0.0600 0.2105

Other freshwater fish 0.7800 0.7800 0.5895

Saltwater small game 0.0000 0.0000 0.0000

Other saltwater fish 0.0000 0.0000 0.0000

Flatfish 0.0000 0.0000 0.0000

The distance traveled to a site is one of the most important site characteristics in a

recreational angling demand model. It directly influences the travel cost to each site for each

angler. Thus, a critical factor in the simulation model is distance from each angler’s residence

(ZIP Code) to each site. These distances are calculated using the most recent version of a

popular transportation routing software called PC*Miler (ALK Technologies 2010). Travel costs

reflect both direct costs and travel time costs. Direct costs are calculated by multiplying the round-

trip miles by the standard per mile reimbursement. The average hourly wage of each ZIP Code

is calculated by dividing household income from the U.S. Census by 2,000 work hours per year.

Travel time in minutes is also calculated by PC*Miler. The round-trip time estimate is multiplied

by one-third of the average hourly wage rate to reflect the opportunity cost of time. The travel

cost included in the model is the sum of the direct travel cost and the opportunity cost of time.

3.2.5 Calibrated Baseline Trips and Expected Catch Travel costs and the other site characteristics are combined with the coefficients from the

Bingham et al. (2011) model to allocate the estimated annual trips by the affected angling

population to the affected and substitute sites. Total trips to the affected portion of Ohio River are

calibrated to correspond to the best available visitation information for the affected sites. This



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process results in the distribution of trips to the affected sites listed in Table 3.3. The remaining

trips are distributed among the substitute sites using the best available visitation information.

In the calibrated baseline dynamic recreational fishing model, baseline trips (from above)

and yield (as described in Section 3.1) were combined by dividing recreational catch by trips, to

identify a calibrated baseline expected catch for each affected species.

Commercial Fishery Title 312, Administrative Code 9 governs commercial fishing in Indiana’s waters: 312 IAC

9-8-1 governs general requirements and definitions for commercial fishing, 312 IAC 9-8-2 governs

commercial fishing on inland waters, and 312 IAC 9-8-6 governs commercial fishing on the Ohio

River (Indiana General Assembly 2017). The Ohio River supports commercial fishing in Indiana,

Illinois, and Kentucky, which have reciprocal agreements for commercial fishing. Commercial

fishers harvested about 1,678,651 pounds from the Ohio River during 2012. Harvested species

included catfish (blue, channel, and flathead) as well as carp, carpsuckers, drum, paddlefish (flesh

and eggs), shad, suckers, and sturgeon (flesh and eggs). The majority of the commercial harvest

by weight is catfish. Several commercial fisheries ship their products to Atlanta, Memphis, St.

Louis, Chicago, and New York City (Indiana General Assembly 2015; Illinois Administrative Code

2017; Kentucky Waterways Alliance 2014).

About 354 individuals hold a license for commercial fishing on inland waters of Indiana.

Most of those commercial fishing license holders are recreational anglers who “use commercial

fishing gear to take catfish and other species for personal use (food for relatives and friends) and

for local fish fry events.” Twenty license holders “conduct commercial fishing on the Ohio River,

and 12 of them fish primarily for paddlefish” (Indiana General Assembly 2015).

According to the Kentucky Department of Fish & Wildlife Resources (2014), since the mid-

1990s commercial fishing for catfish in the Ohio River has changed from “primarily a harvest for

flesh to harvesting trophy-sized fish to sell to pay lake owners.” Since about 2000 when Eurasian

sturgeon stocks crashed, commercial fishers have targeted Ohio River paddlefish and sturgeon

for their eggs to be processed as caviar. At least 10,000 pounds of eggs from paddlefish or

sturgeon are harvested annually from Indiana waters of the Ohio River (Stefanavage 2009;

Wildlife Management Institute 2015).

Future Baseline Fishing Participation, Trips, and Site Quality Because the modeling goes out decades into the future, differences from the current state

of fishing could impact results. This means anticipated changes in site quality and availability or



Veritas

changes in economic conditions and fishing preferences should be expressed in the baseline

case going forward.

Although participation in recreational fishing declined nationally years ago, fishing license

sales have rebounded in recent years—dramatically in some states. According to the National

Survey of Fishing, Hunting, and Wildlife-Associated Recreation, the number of anglers rose four

percent from 2006 to 2011. Based on fishing license sales from 2006 to 2011, fishing participation

increased about one percent among Indiana anglers. However, between 2004 and 2015,

Indiana’s fishing license sales actually decreased by nearly 23 percent (U.S. Fish and Wildlife

Service 2017).

Based on this information, the future baseline of fishing participation, trips to sites, and

expected catch was specified consistent with the pre-2012 calibrated baseline estimates

described in Section 3.2.4.



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4. Modeling Yield Impacts Once the baseline fishing conditions have been established, the next step in the analysis

was to model the recreational and commercial yield impacts associated with AWPP’s entrainment.

The model uses two types of yield changes associated with simulating a reduction in AWPP’s

entrainment: direct and indirect yield changes. The direct yield changes are the increases in

recreational and commercial species that would occur as a result of eliminating AWPP’s

entrainment. The indirect yield changes are the increases in recreational and commercial yields

that would occur as a result of eliminating entrainment of forage species.

Direct Changes in Yield To identify the yield effects of AWPP’s entrainment on recreational and commercial

species, the analysis adds the estimates of annual entrained organisms to the corresponding life

stages in the population model. The specification begins with the year that entrainment is reduced

(here 2016) and continues until an expected plant closure.

Indirect Changes in Yield Because commercial and recreational anglers do not target them, forage fish such as

grubby are considered to have indirect economic benefits. In this context, indirect-use benefits

arise from the role forage species play in supporting game fish populations. Indirect-use benefits

can be calculated by evaluating the degree of energy transfer that occurs through the

consumption of grubby and other forage fish by game fish. However, this approach requires

knowing whether and to what degree limited availability of forage species constrains the

populations of commercial and recreational species. There are two general situations:

1. Lack of forage fish does not constrain populations of commercially and recreationally valuable species

2. Lack of forage fish does constrain populations of commercially and recreationally valuable species.

Valuation in the first instance is straightforward. When forage fish availability does not

constrain commercial and recreational populations, impingement and entrainment of forage fish

does not affect game fish populations and indirect use values are zero. When the lack of forage

species availability does constrain commercial and recreational populations, forage losses are

greater than zero, but can potentially be valued using trophic transfer. For purposes of this

assessment, we have assumed that populations of harvested species are constrained and

incorporate them through a trophic transfer methodology.



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We first evaluate the available information on survival and fecundity for the forage species.

Rather than focusing on fishing mortality rates, we evaluate natural mortality rates, which include

consumption by other species.

Literature on trophic transfer rates suggests that a trophic transfer efficiency of 10 percent

across all species is reasonable. For example, Pauly and Christensen (1995) compiled 140

estimates of trophic transfer efficiency from 48 trophic models of aquatic ecosystems. Pauly and

Christensen found that although the range of values was very wide, the mean value was 10

percent and only a few of the values were 20 percent or higher. This finding also is bolstered by

more recent work with bioenergetics models that support a value of 10 percent (PSEG 1999).

Similarly, the EPA used a 10 percent transfer rate in its final rule (USEPA 2014). This approach

assumes that all the lost forage production would have been consumed by harvested species.

However, it is likely that a large portion of the forgone production is consumed by intermediate

predators and then by harvested species and that a lower proportion of forage fish is actually

consumed by predators. Thus, the assumption that harvested species directly consume all forage

biomass likely leads to an overestimate of the harvested gains.

The forage species evaluated for AWPP include those listed in Table 1.2 and 1.3. The

predators of these forage species include the following sportfish:

• Walleye, blue catfish, and flathead catfish prey on emerald shiner (Great Lakes Environmental Research Laboratory 2009).

• Blue catfish, flathead catfish, and striped bass prey on gizzard shad (Great Lakes Environmental Research Laboratory 2009; Meyer 2015).

• Walleye, sauger, blue catfish, and flathead catfish prey on minnows (Meyer 2015).

• Walleye, black bass, blue catfish, and flathead catfish prey on skipjack herring (University of Michigan 2017).

For purposes of this assessment, we assume that all emerald shiner, gizzard shad, minnows, and

skipjack herring are converted to catfish through a ten-percent trophic transfer.



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5. Valuing Changes in Recreational and Commercial Yield After modeling the yield impacts associated with AWPP’s entrainment, the next step in

estimating the economic benefits entails valuing the changes in recreational and commercial

yield. Developing these values requires assessing the relationship between the recreational and

commercial yield changes and the impact that these yield changes have on people. For example,

properly assessing recreational values requires understanding how AWPP’s entrainment affects

recreational fishing catch rates and how those changed catch rates affect the well-being of anglers

located in the plant’s relevant vicinity. Properly assessing commercial values requires

understanding how AWPP’s entrainment affects fishery yields and how those changes in fishery

yields affect commercial catch rates, the profitability of commercial harvesters, and the prices

consumers pay for commercially harvested fish.

Valuing Changes in Recreational Yield For a recreational fishery, the appropriate measure for valuing changes in recreational

yield is the increase in consumer surplus resulting from changes in catch rates attributable to

entrainment reductions. Consumer surplus is measured using demand functions. Demand

functions describe the maximum number of trips a person would be willing to take at each price

over a given time period. For a nonmarket service like recreational fishing, “price” is the cost of

taking a trip to that site. This cost may include transportation costs, the opportunity cost of time,

entrance fees, and other trip-related costs. Differences across demand functions under with and

without entrainment catch rates are used to identify economic benefits.

Figure 5.1 depicts an econometrically estimated demand curve. Here, the (hypothetical)

angler’s round-trip travel cost is $25.11 Consistent with the concept of diminishing marginal utility,

each additional trip is valued somewhat less than the previous trip. The fifth (and higher) trip is

valued at less than travel cost. Therefore, the angler maximizes his utility by taking four trips. In

the figure, the gray area above the per-trip cost and below the demand curve is the difference

between what an angler pays for fishing trips to a site and the value that the angler has for those

trips. This area is called consumer surplus, and it is the dollar measure of the satisfaction received

from trips to the site. It is the difference between what the angler actually has to pay to visit a site

and how much she would be willing to pay to visit the site.

11 Travel cost consists of direct expenditures and the value of time going to and from the site.



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Figure 5.1: The Site Demand Curve and Consumer Surplus

Consumer surplus changes when a site’s catch rates change. Figure 5.2 depicts the

process. In the figure, the red demand curve reflects catch rates with entrainment. The blue

curve depicts demand curve when the site has higher, without-entrainment catch rates. This new

demand curve is to the right of the With-Entrainment curve. For each level of visitation, the trip is

more valuable because of the higher catch rates. Consequently, the angler takes more trips to

the site (five trips rather than four) and these trips have a higher value.

EPRI-0289

Trips

Trav

el C

ost (

$)250

225

200

175

150

125

100

75

50

25

00 1 2 3 4 5 6 7 108 9

Consumer surplus

Number of trips taken at $25 per trip

Trip cost

Demand with I&E



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Figure 5.2: Increase in Consumer Surplus from Increase in Catch Rates

Developing these estimates of demand and changes in consumer surplus requires

estimating changes in angler utility associated with changes in catch rates resulting from

entrainment reductions. In mathematical terms, an individual angler’s utility, Uipwj (the well-being

they receive from a fishing trip), is treated as a random variable composed of a deterministic

component and a random component. The utility associated with a recreational fishing trip to site

j of waterbody type w after making participation decision p by angler i can be expressed as:

(1)

where Vipwj is the deterministic part of the utility function and εipwj represents the random terms,

which are assumed to be jointly distributed according to the generalized extreme value (GEV)

distribution. V is a function of site characteristics, such as how far the site is from the angler’s

house, what type of fish he can catch there, how many fish he might expect to catch there, and

how developed the site is.

For this assessment, the analysis uses the structure from Bingham et al. (2011) to

estimate changes in angler utility resulting from reductions in AWPP’s entrainment. An important

aspect of the Bingham et al. model is that it can be used to estimate changes in consumer surplus

Trips

Trav

el C

ost (

$)250

225

200

175

150

125

100

75

50

25

00 1 2 3 4 5 6 7 108 9

Change in consumer surplus

Number of trips taken at $25 per trip

Trip cost

EPRI-0290

Demand with I&E

Demand without I&E

Uipwj = Vipwj + εipwj



Veritas

attributable to site quality changes, such as improved catch rates resulting from reduced

entrainment, as well as the addition or elimination of a site. For this analysis, to estimate the

changes in demand that would occur if AWPP’s entrainment was not occurring, the analysis uses

the results from Bingham et al. (2011) to determine how changes in catch would change anglers’

trip-taking behavior and utility. The coefficients on expected catch in Bingham et al. (2011) are

used to link the recreational yield changes to the preferences of affected anglers presented

earlier.

After estimating the changes in catch resulting from the reduced entrainment, the analysis

simulates the changes in trip patterns that anglers make in response to changes in catch rates in

the Ohio River. The economic assessment proceeds by developing the estimated changes in

social welfare, in dollars, associated with the changes in trips that result from the changes in catch

and trips. The analysis estimates the monetized benefits by calculating the difference in angler

welfare without and with the increased catch rates and trips associated with reduced entrainment

at AWPP.

Valuing Changes in Commercial Yield Valuing changes in commercial yield entails evaluating the effect of changes in

commercial harvest rates on the economic welfare of both commercial anglers and consumers of

commercially harvested fish. This involves understanding how changes in catch rates affect the

profitability of commercial harvesters and the prices faced by fish consumers. Doing so requires

adding the supply curve to the concepts of demand curves and consumer surplus presented in

Section 5.1 and evaluating supply implications under the current conditions versus the conditions

that would result with reductions in AWPP’s entrainment. Economic benefits from entrainment

reductions could accrue to commercial anglers as increased profit attributable to higher catch per

unit effort (CPUE), as surplus to consumers arising from lower fish prices, or some mixture of

these. The ability of commercial anglers to realize sustained increased profits depends on the

responsiveness of market prices to higher CPUE.

Generally speaking, the nature of commercial fishing benefits resulting from yield

increases or improvements in CPUE depend on the type of fishery as summarized below:

• Case 1: Commercial anglers experience increases in catch rates, but fish prices do not change.

• Case 2: Commercial anglers experience increases in catch rates, and fish prices do change.

• Case 3: Commercial anglers experience increases in catch rates, the commercial fishing market is in short-run equilibrium, and there are no explicit regulatory quotas.



Veritas

Appendix A provides a detailed discussion of these three cases for commercial fisheries. As

Appendix A describes, commercial harvesters consider many factors when making business

decisions about fishing including the fact that catch rates are seasonal and stochastic, fish and

fuel prices vary, vessels often target a variety of species and can switch gear if needed, boats

can sail from and offload at various ports, the number of crewmembers can vary, the weather has

implications for catch and safety, and so on. This complicated supply picture interacts with

consumer demand that is impacted by a number of factors, including quality of catch (i.e.,

freshness), cost of substitutes (other fish and foods), and eating trends. Regulatory actions such

as quota-setting impact both harvest costs and market prices.

Given the commercial yield changes associated with reductions in AWPP’s entrainment, the

analysis specifies that no price changes would occur as a result of reductions in AWPP’s

entrainment. It also species that commercial anglers would be able to sell all their additional harvest

at the unchanged prices. To assess benefits under these specifications, the analysis applies the

price per pound from the National Marine Fisheries Service’s 2012 data of annual landings in

Midwestern states (National Oceanic and Atmospheric Administration [NOAA] Office of Science

and Technology 2017; Wildlife Management Institute 2015) to the changes in commercial yield

estimated to result from reductions in AWPP’s entrainment.



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U.S. Census Bureau. 2017. “American Factfinder: Advanced Search.” Available at https://factfinder.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t. Retrieved on November 1, 2017.

U.S. Environmental Protection Agency. 2002. Economic and Benefits Analysis for the Proposed Section 316(b) Phase II Existing Facilities Rule. Report Number 821-R-02-001. February. Washington, DC: U.S. EPA.

U.S. Environmental Protection Agency. 2004. National Pollutant Discharge Elimination System—Final Regulations to Establish Requirements for Cooling Water Intake Structures at Phase II Existing Facilities: Final Rule. Federal Register Vol. 69, No. 131 (Friday, July 9):41,576–41,693.

U.S. Environmental Protection Agency. 2010. Guidelines for Preparing Economic Analyses. Report Number EPA 240-R-10-001. December. Washington, DC: U.S. EPA. Available at http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0568-50.pdf/$file/EE-0568-50.pdf. Retrieved on June 19, 2013.

U.S. Environmental Protection Agency. 2012. “Survey Support Document in Support of Section 316(b) Stated Preference Survey Notice of Data Availability.” June. Washington, DC: U.S. EPA.

U.S. Environmental Protection Agency. 2014. National Pollutant Discharge Elimination System—Final Regulations to Establish Requirements for Cooling Water Intake Structures at Existing Facilities and Amend Requirements at Phase I Facilities; Final Rule. Federal Register Vol. 79, No. 158 (August 15):48300–48439.

U.S. Fish and Wildlife Service. 2013a. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Indiana. Available at http://www.census.gov/prod/2013pubs/fhw11-in.pdf. Retrieved on August 29, 2013.

U.S. Fish and Wildlife Service. 2013b. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Illinois. Available at http://www.census.gov/prod/2013pubs/fhw11-il.pdf. Retrieved on August 29, 2013.

U.S. Fish and Wildlife Service. 2013c. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Kentucky. Available at http://www.census.gov/prod/2013pubs/fhw11-ky.pdf. Retrieved on August 29, 2013.



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U.S. Fish and Wildlife Service. 2014. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. Available at http://www.census.gov/prod/2012pubs/fhw11-nat.pdf. Retrieved on May 19, 2017.

U.S. Fish and Wildlife Service. 2017. “Historical Fishing License Data.” Available at https://wsfrprograms.fws.gov/Subpages/LicenseInfo/Fishing.htm. Retrieved on May 3, 2017.

Veritas Economic Consulting. 2010. Habitat Offset Cost Estimates. Section 4.6.2 in Agreement No. 47927 Compliance Assistance and Technical Services for the Clean Water Act Section 316(b) Cooling Water Phase II Rule: Technical Assessment and Mitigation Measures. Prepared by Alden Research Laboratory, Inc.; MBC Applied Environmental Sciences; Tenera Environmental, Inc.; Veritas Economics; Bonterra Consulting; URS Corporation for City of Los Angeles Department of Water and Power (LADWP).

Veritas Economic Consulting. 2012. The Role of Knowledge in Assessing Nonuse Values for Site-Specific 316(b) Determination: Results and Implications from the National Environmental Impacts Awareness Survey. Available at http://www.veritaseconomics.com/publications.asp?p=3. Retrieved on May 3, 2017.

Wildlife Management Institute. 2015. “Paddlefish Stock Assessments Drive Regulation Changes in Tennessee.” Available at https://wildlifemanagement.institute/outdoor-news-bulletin/may-2015/paddlefish-stock-assessments-drive-regulation-changes-tennessee. Retrieved on November 3, 2017.

Zhao, Yingming, Patrick M. Kocovsky, and Charles P. Madenjian. 2013. “Development of a Stock-Recruitment Model and Assessment of Biological Reference Points for the Lake Erie Walleye Fishery.” North American Journal of Fisheries Management 33:956–964.



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Appendix A Commercial Fishery Benefits Theoretical Overview



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Both the supply and demand components of commercial fishing markets are quite

complex and empirical applications that link commercial catch rates to economic benefits are

limited. These limitations vis-a-vis the economic valuation of entrainment reductions were

thoroughly considered by authors of this study and Ted McConnell (resource economist,

University of Maryland) as part of the EPRI Closed-Cycle Cooling Program (EPRI 2011). As

described in the body of this report, the limited change in commercial yield that is projected from

entrainment reductions at AWPP is monetized by specifying that no price changes occur as a

result of reductions in AWPP’s entrainment and that commercial anglers are able to sell all of their

additional catch at these unchanged prices. This approach does not rely on the preferred partial

equilibrium structure and as such produces only economic values with no characterization of

behaviors. This is a result of the lack of study information for performing functional benefits

transfer.

This appendix is intended for reviewers with interest in the rationale for not applying partial

equilibrium modeling and provides a conceptual characterization of commercial fishing

economics. Consistent with relevancy for entrainment reductions the focus is on the supply

side. To provide a behavioral foundation for the concept of the supply curve, this exposition uses

results from a simulation model of vessel behavior. This model simulates optimizing behavior

under various complex changes. It was constructed to understand behaviors in the important and

contentious New England groundfish fleet (Bingham et al. 2010).

To provide a behavioral foundation for the concept of the supply curve, this exposition

uses a model of vessel behavior that is based on the New England groundfish fleet.12 A typical

vessel in this fleet might be a trawler that is 55 to 65 feet in length. Fixed annual costs for owning

such a vessel include dock fees, insurance, and loan repayment.13 For owning the boat to be

profitable, the fixed costs of ownership must be covered by revenues net of operating costs.

Revenues are the dockside value of catch (i.e., pounds landed times price per pound). Boat

owners seek to increase revenues by traveling to fishing grounds with high catch rates. Operating

(or variable) costs include costs for fuel, ice, and the crew. Owners consider these costs when

deciding where to fish.

An optimization model was developed to simulate the behavior of owners of groundfish

trawlers less than 65 feet operating out of New Bedford. The model simulates behavior of a profit-

12 Ultimately analysts are interested in knowing impacts to all commercial fishing. This example considers a single

vessel out of approximately 1,000 similar vessels participating in the New England groundfishery. 13 Typical terms for purchase of a fishing boat might be 25 percent down with a payout over 7–12 years. There might

be a fixed interest rate for the first five years at about 2.5 percent to 2.75 percent over the cost of funds, which is the federal home loan bank rate (Tim Kelleher, TD Bankworth).



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maximizing vessel owner who chooses where and when to fish based on costs and catch rates.

The model is calibrated to produce trip-taking behavior that is like the “average” or “typical”

behavior. Under these conditions, the minimum cost of catching any given quantity of groundfish

is determined, and from that cost one can derive the marginal cost curve depicted in Figure A.1

below.14 This With-Entrainment minimum cost curve is generated by successively simulating the

behavior of a typical groundfishing vessel, where dockside price is fixed and the quantity of catch

is constrained at various (increasing) levels.

The profit-maximizing vessel owner chooses the most profitable opportunities first. As the

artificially imposed catch constraint is loosened, less productive (or equivalently more costly)

alternatives are chosen.

The successive loosening of the total catch constraint produces the rising marginal cost

curve shown below. By implication, the average cost of harvest also increases. Including the

market price for groundfish allows assessing the variable economics of the boat. In the figure, a

market price of $1 per pound is specified.15 With market price at $1 per pound, the owner chooses

to take all trips that are expected to result in an average per-trip harvest cost of less than $1 per

pound. This leads to an annual groundfish harvest of 80,000 pounds for this vessel.16 This is

consistent with a typical vessel in the New England groundfishery from 2003 to 2008. Total

variable costs observed visually as the area under the marginal cost (supply) curve, equals

approximately $40,000 in fuel and ice costs. The remaining $40,000 (the area above the supply

curve and below price) is revenue less non-labor variable costs. Skipper and crew shares

generally are about 50 percent of net returns. This would total about $20,000, leaving $20,000 to

pay for dock fees, insurance, boat loan payments, and maintenance.

14 Optimization is conducted in Analytica 4.2 using mixed integer formulation and Frontline optimizer. 15 This is consistent with average historical dockside price for groundfish in New England. 16 This curve is also known as the boat’s supply curve because it represents the quantity of fish that the boat would

supply at each market price.



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Figure A.1: With-Entrainment Variable Costs

Commercial Fishing Without-Entrainment The difficulty of identifying economic benefits under Without-Entrainment conditions

depends upon a number of factors that are considered in the cases described below.

Case 1: Harvesters experience an increase in catch rates, but fish prices do not change. In this simple case, higher catch rates lead to harvest increases and/or cost decreases.

Depending on the form (i.e., magnitude and location) of catch-rate improvements, the vessel can

either fish as it did under With-Entrainment conditions; adjust its effort in a number of ways,

including changing gear, fishing longer, choosing different locations; or make many other marginal

adjustments short of investment or exit/entry. To simulate this effect in the model of commercial

fishing behavior, catch rates are increased within the optimization model at certain locations and

times. This effect can be seen graphically in the new cost curve depicted below.

Quantity (Thousands)EPRI-0299

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Figure A.2: Vessel Supply Curve with Improved Catch Rates and Constant Prices

With this new cost curve, the financial picture of the boat is improved. If that market price

stays at $1 per pound, the boat increases its harvest to 90,000 pounds and total revenue

increases to $90,000. Now total variable costs are $45,000. Of the $45,000 remaining ($90,000–

$45,000) half goes to the captain and crew. Their economic status is somewhat improved; they

now divide $22,500 compared to the previous $20,000. Furthermore, under these Without-

Entrainment catch rates, there is a return to ownership of the vessel of $2,500 per year.

Ultimately analysts are interested in understanding how economic welfare might change

across all commercial fishing. The fishery regulatory structure most likely to have constant prices

is a fishery regime that restricts harvest. In such markets there is a strict quota on the quantity of

commercial stock sold, which determines the equilibrium price. As shown in Figure A.3, improved

catch rates reduce costs; however, the quantity supplied remains at the quota level and the

corresponding equilibrium price remains at the original (With-Entrainment) price. In this situation,

there would be an increase in producer surplus because costs are lower, but revenues remain

the same.


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With I&E

Without I&E



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Figure A.3: Commercial Fish Market (with a Quota)

In the very simplest of cases, there is no change in fishing behavior, and the change in

producer surplus is equal to the change in catch multiplied by dockside value. In the more general

case when fishing behavior changes, identifying producer surplus changes requires estimating

the area between the two supply curves. Doing so requires a times series of data on the market

of the species as well as sufficient data to estimate the impact of biomass changes. This would

include harvest, effort, price of output, input prices, biomass, and information on the regulatory

structure.

Under these conditions, econometric modeling of the response of commercial harvesters

to changes in biomass falls roughly into one of these categories:

1. Estimating a random utility model of harvester choice among locations, using the idea that improved biomass at some of the locations could then be valued using the same ideas as recreational anglers (for example, Haynie and Layton 2004). This requires trip-level data on expenditures by vessel and expected returns or catch rates by location.

2. Using trip or seasonal-level data by vessel to estimate cost or production function that can be converted to supply functions. These models are estimated at the individual level and typically not aggregated. (See Squires and Kirkley 1991 for an example.)


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3. Estimating models of bioeconomic equilibrium. This approach typically begins by modeling effort, including the biological growth function and then whatever market structure is appropriate. This approach implicitly creates a cost function but it entails an equilibrium bioeconomic model of the species. These models are more appropriate for the long run when both vessels and biomass adjust. See, for example, Homans and Wilen (1997).

4. Estimating each of these models is feasible but far exceeds the time and expense warranted for assessment of the benefits for the typical species affected by entrainment.

Case 2: Harvesters experience an increase in catch rates and fish prices do change. In the previous example, the wholesale price of ground fish has been specified as

remaining constant. This example was motivated at the market level by introducing a quota based

management system. For open-access fisheries, the degree to which prices of commercial fish

are “sticky” (i.e., not responsive to changes in quantity) would depend on a number of factors.

For example, small percentage yield changes would be less likely to lead to price changes.

Species that are marketed from different areas would tend to keep those differences damped by

absorbing supply increases across a broader area. The more general case in which prices

respond to yield changes is depicted at the vessel level in Figure A.4.



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Figure A.4: Commercial Fish Market with Open Access

In this figure, with higher catch rates, the vessel maximizes profit by increasing harvest.

When all harvesters face lower harvest costs, they may compete to sell additional fish by lowering

prices. If the market for fish is small relative to the increased harvest, these individual efforts can

result in lower market prices. This is a natural consequence of a large number of owners

independently maximizing profit. The introduction of the market demand curve in Figure A.5

represents this condition, Case 3.


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Figure A.5: Case 3: Most Complicated Case—Effort and Price Changes

This figure shows a new supply curve generated from the model with more identical

vessels and more output per vessel. Two points on the market demand curve arise from the price

and quantity observed in With-Entrainment, and the price observed in Without-Entrainment

conditions. Solving for profit-maximizing output for each boat at this new market price and

summing returns the total quantity supplied.17 Consumer surplus is the difference between what

consumers are willing to pay (as represented by the demand curve) and market price.

This case has the same intense need for data and modeling as in Case 1. In addition, it

is now necessary to have the correct instruments for identifying both supply and demand curves

because structural econometric modeling of these benefits takes the supply and how it shifts with

increases in biomass, as well as the dockside demand curve. This means the demand function

must be estimated and the market model and data must allow the identification of supply and

demand curves. This would require the estimation of a system such as Hermann and Criddle

(2006) or a bioeconomic model such as Homans and Wilen (1997) with endogenous demand.

17 Here this is greatly simplified by assuming 1,000 identical boats.


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Market PriceChange in Consumer Surplus



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Summary and Implications for Methods Figure A.6 provides a summary of the most complicated case. This figure features a

fishery in short-run equilibrium without explicit regulatory quotas.

Figure A.6: Summary of the Benefits of Reduced Entrainment

As depicted in the figure, catch-rate improvements reduce the cost of harvesting. This

leads to the supply curve shift across With-Entrainment and Without-Entrainment. The dockside

demand is given by the Demand curve. In the figure, landings increase and the price falls. The

change in producer surplus equals the area a+b+c. The change in consumer surplus is d. The

net change in social surplus is the sum: a+b+c+d.

Important to the analysis of benefits to commercial fisheries is that even this admittedly

complicated example is a great simplification of commercial fishing behavior and markets.

Commercial harvesters consider many factors when making business decisions about fishing.

Among these considerations, catch rates are seasonal and stochastic; fish and fuel prices vary;

vessels often target a variety of species and can switch gear if needed; boats can sail from and

offload at various ports; the number of crewmembers can vary; the weather has implications for


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Market Price c d

a

b



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catch and safety, and so on. This complicated supply picture interacts with consumer demand

that is impacted by a number of factors, including quality of catch (i.e., freshness), cost of

substitutes (other fish and foods), and eating trends. Regulatory actions impact both harvest

costs and market prices. Given these complexities, it is useful to assess what approaches are

available and to consider their implications with respect to errors in the estimation of benefits.

In many cases familiarity with the fishery, including processing and downstream

marketing, can help determine whether price changes could be expected for given changes in

landings. Such judgments would help rule out price changes in some cases, but would not provide

empirical support when price would be expected to change. Using data sets such as those

employed by Kirkley (2006) and Bishop and Holt (2002), it would be feasible to estimate aggregate

inverse demand functions.

The flexibility of price with respect to landings separates Case 1 from Case 2. To sort out

the cases, it would be necessary to have estimates of the price flexibility or to estimate the

relationship. Estimating the flexibility of price with respect to landings involves a model with price

as a function of landings and other exogenous variables. This model stems from the notion that

landings are exogenous with respect to contemporaneous price and the fact that the commodity

is perishable, so that supply cannot be provided from storage. Each assumption is true at some

time scale, but the scale differs across species. Increasingly fish are flash frozen as they are

harvested, making supply more endogenous.

There are two basic approaches to estimating this model. One is to assume that the

correct model represents the valuation placed on harvest by consumers and to adopt a flexible

functional form of consumers’ preferences. This is the approach taken by Bishop and Holt (2002)

and others. The other approach is to estimate a model with less structure—basically an aggregate

inverse demand function.

The Holt-Bishop paper provides flexibilities that could be used with entrainment cases on

the Great Lakes. Kirkley (2006) provides estimates for a number of saltwater species. There are

reasons to be concerned with these estimates. First, the preference functions are based on

household’s valuation of exogenous changes in fish. The structure of dockside demand reflects

in part the structure of household demand buyers for households paying posted prices. Fish are

not exogenous to them. Further, there are other outlets for landings so the supply going to

households will be endogenous. For example, landings of species that are traded internationally

will be divided between domestic consumption and export.



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The more low-tech but intuitive approach of Graddy (2006) is perhaps more appropriate

for modeling dockside demand. This model explains the price as a function of landings. This is

an aggregate dockside price model that captures the various influences on price. Structurally it

is an inverse demand function, and so represents the responses of buyers. It provides estimates

of price flexibility that would be ideal for using in entrainment assessments. It recognizes that

price responds to landings, but does not give more structure to the model than that.



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References Bingham, M.F, D.M. Woodard, Z. Li, and G. Crownfield. 2010. “Behavioral and Bioeconomic

Considerations of Catch Share Policies.” Presented at the American Fisheries Society Conference, Pittsburgh, Pennsylvania. September 14.

Bishop, R.C., and M.T. Holt. 2002. “A Semiflexible Normalized Quadratic Inverse Demand System: An Application to the Price Formation of Fish." Empirical Economics 27(1):23–47.

Electric Power Research Institute. 2011. National Benefits of a Closed-Cycle Cooling Retrofit Requirement. Product ID 1023401. Palo Alto, CA: EPRI.

Graddy, K. 2006. “The Fulton Market.” Journal of Economic Perspectives 20(2):207–220.

Haynie, A.C., and D.F. Layton. 2004. “Estimating the Economic Impact of Stellar Sea Lion Conservation Area: Developing and Applying New Methods for Evaluating Spatially Complex Area Closures.” In Proceedings of the International Institute for Fisheries Economics and Trade, Japan.

Hermann, M., and K. Criddle. 2006. “An Econometric Market Model for the Pacific Halibut Fishery.” Marine Resource Economics 21(2):129–158.

Homans, F.R., and J.E. Wilen. 1997. “A Model of Regulated Open Access Use.” Journal of Environmental Economics and Management 32(1):1–21.

Kirkley, J. 2006. Potential Economic Ramifications of Reissuing the Rule to Implement the Fish and Seafood Promotion Act of 1986. Report prepared for NOAA Fisheries, Office of Constituent Services, Silver Spring, MD.

Squires, Dale, and James Kirkley. 1991. “Production Quota in Multiproduct Pacific Fisheries.” Journal of Environmental Economics and Management 21:109–126.



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Appendix B Substitute Fishing Sites and Characteristics of Sites



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Table B.1 lists recreational fishing sites in Indiana that are within 100 miles of AWPP.

Table B.1 Recreational Freshwater Fishing Sites within 100 miles of AWPP

Location Amenities No. Boat Ramps

Trout, Shad Panfish Freshwater

Game Other

Freshwater Trips Fishing Pressure

Angler Hrs/Acrea

Hours per Trip

Sportfish Caught from Waterbody

Ohio River, Cannelton Pool (boat angler), Newburgh (Warrick County), Indiana

Angel Mounds State Historic Site, Hoosier National Forest, camping, marinas

14 0.0000 0.7800 0.0600 0.7800 43,279 72,276 3.17 1.67 Black bass, bluegill, buffalo, carp, channel catfish, crappie, freshwater drum, sauger, white bass

Blue Grass Pit (boat angler), Warrick County, Indiana

Blue Grass Fish and Wildlife Area

2 0.0000 0.0444 0.7272 0.0084 7,287 24,628 123.10 3.38 Bluegill, channel catfish, crappie, largemouth bass, muskellunge

Dogwood Lake (boat angler), Glendale (Jo Daviess County), Indiana

Glendale Fish and Wildlife Area

3 0.0000 0.0000 0.6467 1.2846 14,183 77,991 55.16 5.50 Bluegill, bullhead, catfish, crappie, largemouth bass, sunfish, warmouth

Hovey Lake (boat angler), Posey County, Indiana

Hovey Lake Fish and Wildlife Area

1 0.0000 0.0000 0.2105 0.5895 600 3,090 2.21 5.15 Buffalo, carp, carpsucker, catfish, crappie, largemouth bass, white bass

Loon Pit (boat angler), Warrick County, Indiana

Blue Grass Fish and Wildlife Area

1 0.0000 0.1385 0.3966 0.0449 4,009 12,475 69.30 3.11 Bluegill, channel catfish, crappie, largemouth bass

McAlpine tailwaters of Ohio River (boat angler), Harrison and Floyd Counties, Indiana

Hiking, paddling 3 0.0000 0.0000 0.0509 0.8491 13,218 49,665 6.63 3.76 Carp; catfish; crappie; freshwater drum; largemouth, smallmouth, and spotted bass; sauger; white bass

Monroe Reservoir (boat angler), Monroe County, Indiana

Adjoins several state recreation areas; hiking, camping, nature center

5 0.0000 0.2350 0.1874 0.1170 32,731 149,692 13.92 4.57 Bluegill, channel catfish, crappie, hybrid striped bass, largemouth bass, walleye, yellow bass

Newburgh Pool, Ohio River (boat angler), Vanderburgh and Warrick Counties, Indiana

Camping, marinas, playground park, water sports


Patoka Lake (boat angler), Crawford, Dubois, and Orange Counties, Indiana

Adjoins several state recreation areas, Patoka Lake Marina & Lodging

11 0.0000 0.2844 0.3062 0.0694 65,860 324,313 36.85 4.00 Bluegill, bullhead, channel and flathead catfish, common carp, largemouth bass, sunfish, striped bass, warmouth



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Table B.1, continued



Game Other


Angler Hrs/Acrea

Hours per Trip


Scales Lake (boat angler), Boonville (Warrick County), Indiana

Scales Lake Park, camping, beach, trails, horseback riding, biking

1 0.0000 0.0268 0.1242 0.5690 1,881 16,032 242.91 8.52 Black crappie, bluegill, channel catfish, largemouth bass, redear sunfish, warmouth

Wabash River (boat angler), Posey County, Indiana

Harmonie State Park, trail system

4 0.0000 0.7800 0.0600 0.7800 3,221 5,379 3.17 1.67 Bluegill, buffalo, catfish, sauger, rock bass, smallmouth bass

West Boggs Creek Reservoir (boat angler), Daviess Couny, Indiana

West Boggs Park, camping

1 0.0000 0.4882 0.0091 1.1962 16,781 67,125 107.92 4.00 Bluegill, bullhead, catfish, crappie, largemouth bass, sunfish

White River and East Fork White River, Sector 1, Sections 1–3 (boat angler), Martin County, Indiana

Martin County State Forest, Hindostan Falls Public Fishing Area, camping, paddling, cabins, guided paddling tours

4 0.0000 0.0123 0.1568 0.7557 29,148 90,359 1,964.32 3.10 Bluegill, buffalo, catfish, crappie, freshwater drum, hybrid striped bass, largemouth and smallmouth bass, sauger, shovelnose sturgeon, spotted bass, striped bass, sunfish, walleye, white bass

White River and East Fork White River, Sector 2, Sections 1–6 (boat angler), Indiana

Camping 4 0.0000 0.0100 0.0238 1.2417 23,525 72,926 959.55 3.10 Bluegill, buffalo, catfish, carp, crappie, freshwater drum, hybrid striped bass, largemouth and smallmouth bass, spotted bass, striped bass, sunfish, walleye, white bass

Crab Orchard Lake (boat angler), Williamson and Jackson Counties, Illinois

Crab Orchard National Wildlife Refuge, Crab Orchard Campground

9 0.0000 0.7316 0.2437 0.9127 23,774 78,453 13.00 3.30 Black and white crappie, bluegill, buffalo, bullhead, carp, channel and flathead catfish, freshwater drum, hybrid striped bass, largemouth bass, smallmouth buffalo, sunfish, warmouth, white bass, yellow bass, yellow perch



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Game Other


Angler Hrs/Acrea

Hours per Trip


Devil's Kitchen Lake (boat angler), Grassy (Williamson County), Illinois

Within Crab Orchard National Wildlife Refuge, camping, near Little Grassy Lake

3 0.0686 0.1609 0.5289 1.7713 5,567 18,928 26.89 3.40 Black and white crappie, bluegill, largemouth bass, rainbow trout, spotted bass, sunfish, warmouth, yellow perch, yellow bass

Dolan Lake (boat angler), Hamilton County, Illinois

Hamilton County State Fish and Wildlife Area, camping, trails

1 0.0000 0.3015 0.0842 0.8802 4,825 12,546 174.25 2.60 Black and white crappie, bluegill, bullhead, catfish, largemouth bass, sunfish, walleye, warmouth, white bass, yellow bass

East Fork Lake (boat angler), Olney (Richland County), Illinois

East Fork Lake Campground, trails

3 0.0000 0.8879 0.4339 1.2117 12,148 64,383 68.86 5.30 Black and white crappie, blue and channel catfish, bluegill, bowfin, largemouth bass, redear sunfish, walleye

Glendale Lake (shore angler), Pope County, Illinois

Shawnee National Forest, Glendale Recreation Area, beach, camping

0 0.0000 0.1838 0.2934 0.7964 2,718 4,893 61.16 1.80 Black crappie, bluegill, bullhead, catfish, grass pickerel, largemouth bass, sunfish, warmouth

Lake McLeansboro (boat angler), McLeansboro (Hamilton County), Illinois

Izaak Walton Park 2 0.0000 1.2681 0.1398 1.1650 2,109 6,539 87.19 3.10 Black and white crappie, bluegill, bullhead, catfish, largemouth bass, sunfish, warmouth, yellow bass, yellow perch

Mermet Lake (boat angler), Massac County, Illinois

Mermet Lake State Conservation Area, hiking, hunting

2 0.0000 0.3080 0.1200 0.5390 6,707 24,146 55.00 3.60 Black and white crappie, blue and channel catfish, bluegill, bullhead, bowfin, carp, largemouth bass, sunfish, spotted gar, warmouth

Newton Lake (boat angler), Jasper County, Illinois

Newton Lake Conservation Area, trails, hunting

3 0.0000 0.0379 0.4684 0.6452 14,009 75,650 43.23 5.40 Black and white crappie, bluegill, bullhead, carp, catfish, bowfin, carp, largemouth bass, sunfish, warmouth, white bass



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Game Other


Angler Hrs/Acrea

Hours per Trip


Red Hills Lake (boat angler), Lawrence County, Illinois

Red Hills State Park, camping, hiking, biking, horseback riding

2 0.0000 0.2602 0.2021 0.8690 3,574 10,722 268.05 3.00 Black and white crappie, bluegill, bowfin, carp, catfish, largemouth and smallmouth bass, sunfish, threadfin shad, warmouth, yellow bullhead

Rend Lake (boat angler), Jefferson County, Illinois

Wayne Fitzgerrell State Recreation Area, camping, hiking, horseback riding, hunting

17 0.0000 0.6320 0.0420 0.3030 33,755 118,142 7.32 3.50 Black and white crappie, bluegill, carp, channel and flathead catfish, freshwater drum, hybrid striped bass, largemouth bass, smallmouth buffalo, sunfish, warmouth, white bass, yellow bass

Cannelton Pool, (shore angler), Owensboro (Daviess County), Kentucky

English Park, Smothers Park, playground and spray park


Kentucky Lake (boat angler), Livingston County, Kentucky

Green Turtle Bay Resort and Marina, other marinas, camping, biking, hiking, wildlife viewing, horseback riding, OHV trails, water parks, golfing

44 0.0000 0.2473 0.3190 0.4808 188,601 841,143 5.25 4.46 Black and white crappie; blue, channel, and flathead catfish; bluegill; bullhead; drum; largemouth, spotted, and smallmouth bass; sauger; skipjack herring; sunfish; temperate bass; warmouth; yellow perch

Lake Barkley (boat angler), Lyon and Trigg Counties, Kentucky

Lake Barkley State Resort Park, camping, lodge, biking, wildlife watching

39 0.0000 0.1704 0.2843 0.7931 89,412 366,341 8.03 4.10 Black and white crappie; blue, channel, and flathead catfish; bluegill; bullhead; largemouth, smallmouth, and spotted bass; sunfish; warmouth

Lake Malone (boat angler), parts of Muhlenberg, Logan, and Todd Counties, Kentucky

Lake Malone State Park, camping, beach, hiking, biking

2 0.0000 0.2165 0.3238 0.5531 13,439 64,130 83.61 4.77 Black bass, including largemouth, black and white crappie, bluegill, catfish, sunfish



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Game Other


Angler Hrs/Acrea

Hours per Trip


Nolin River Lake (boat angler), Edmonson, Grayson, and Hart Counties, Kentucky

Nolin Lake State Park, Moutardier Campground, biking, wildlife viewing

9 0.0000 0.2780 0.5300 0.2093 25,177 152,950 26.37 6.07 Black and white crappie, bluegill, catfish, largemouth and spotted bass, sunfish, walleye

Smithland Pool, Ohio River (boat angler), Crittenden, Livingston, Union Counties, Kentucky

Big Rivers Wildlife Management Area and State Forest, hunting, camping

11 0.0000 0.0000 0.2105 0.5895 16,249 83,684 3.64 5.15 Carp; catfish; crappie; freshwater drum; largemouth, smallmouth, and spotted bass; sauger; white bass

aNote that panfish are crappie and yellow perch in this study. bMultiply number of anglers at shoreline locations times 528 for anglers per mile. cIf river, angler hours per mile unless acres are given. Sources: Cain (2010); Carnahan (2002, 2008); Harper (2010); Henley (1995); Hoffman (2004); Jackson (1986); Kentucky Department of Fish & Wildlife Resources Fisheries Division (2012, 2014, 2016,

2017); King (2010); Kittaka (2005, 2007, 2017); Miller-Ishmael et al. (2001); Schoenung (2001); Stein et al. (2002, 2003, 2004, 2005); U.S. Fish and Wildlife Service (2013)



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References Cain, Michelle L. 2010. “Blue Grass Pit and Loon Pit Angler Creel Survey: Warrick County

2009 Fish Management Report.” Indianapolis, IN: Indiana Department of Natural Resources Division of Fish and Wildlife.

Carnahan, Daniel P. 2002. “Scales Lake Fisheries Survey and Angler Survey Results.” Available at www.state.in.us/dnr/fishwild/files/scales.pdf. Retrieved on October 24, 2017.

Carnahan, Daniel P. 2008. “Patoka Lake: Crawford, Dubois, and Orange Counties 2007 Fish Management Report.” Indianapolis, IN: Indiana Department of Natural Resources Division of Fish and Wildlife.

Harper, Ray. 2010. “Fearsome Foursome Indiana Crappie Hotspots.” Available at http://www.gameandfishmag.com/fishing/fishing_crappies-panfish-fishing_in_aa021804a/. Retrieved on November 1, 2017.

Henley, Douglas T. 1995. “Ohio River Sport Fishery Investigations.” Bulletin No. 95. Available at https://fw.ky.gov/Fish/Documents/FishBulletin095.pdf. Retrieved on October 24, 2017.

Hoffman, Kevin. 2004. “Recreational Use Survey of the East Fork White and White Rivers, 2003.” Indianapolis, IN: Indiana Department of Natural Resources Division of Fish and Wildlife. Available at www.brstats.com/Stats/IN_WhiteRiverE_03.pdf. Retrieved on October 24, 2017.

Jackson, Ralph V. 1986. “Assessment of the Sport Fishery at Meldahl Pool and Tailwater of the Ohio River.” Bulletin No. 80. Available at https://fw.ky.gov/Fish/Documents/FishBulletin080.pdf. Retrieved on October 24, 2017.

Kentucky Department of Fish & Wildlife Resources Fisheries Division. 2012. Annual Performance Report District Fisheries Management Part I. Sport Fish Restoration Grant F-50, Segment 34. Available at https://fw.ky.gov/Fish/Documents/2011lakeandtailwatersurveys.pdf. Retrieved on October 24, 2017.

Kentucky Department of Fish & Wildlife Resources Fisheries Division. 2014. “Fish Consumption Advisories.” Available at https://fw.ky.gov/Fish/Pages/Fish-Consumption-Advisories.aspx. Retrieved on October 30, 2017.

Kentucky Department of Fish & Wildlife Resources Fisheries Division. 2016. Annual Performance Report District Fisheries Management Projects A–C. Sport Fish Restoration Grant F-50, Segment 38. Available at https://fw.ky.gov/Fish/Documents/2015lakeandtailwatersurveys.pdf. Retrieved on October 24, 2017.

Kentucky Department of Fish & Wildlife Resources Fisheries Division. 2017. Annual Performance Report District Fisheries Management Projects A–C. Sport Fish Restoration Grant F-50, Segment 39. Available at https://fw.ky.gov/Fish/Documents/2016lakeandtailwatersurveys.pdf. Retrieved on October 24, 2017.

http://webcache.googleusercontent.com/search?q=cache:fHG9cEutK14J:www.brstats.com/Stats/IN_WhiteRiverE_03.pdf+&cd=96&hl=en&ct=clnk&gl=us



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King, Debra A. 2010. “Angler Survey Results for Kickapoo Lake of Shakamak State Park: Sullivan County 2009 Fish Management Report.” Indianapolis, IN: Indiana Department of Natural Resources Division of Fish and Wildlife.

Kittaka, David S. 2005. “Fishing Pressure, Fish Harvest, and Economic Value of West Boggs Creek Reservoir Fishery.” Available at in.gov/dnr/fishwild/files/Boggs_Creek_rpt_041.pdf. Retrieved on November 2, 2017.

Kittaka, David S. 2007. “Fishing Pressure, Fish Harvest, and Economic Value of Dogwood Lake: Daviess County 2006 Fish Management Report.” Available at www.in.gov/dnr/fishwild/files/Dogwood_crl_rpt_06.pdf. Retrieved on November 1, 2017.

Kittaka, David S. 2017. “Fisheries Management and an Angler Creel Survey at Monroe Reservoir Monroe County 2015.” Presented at the 29th Annual Indiana Lakes Management Conference, Bloomington, Indiana, March 2–3.

Miller-Ishmael, Lynnette, Betty Carroll, Amy B. Osterman, Julie Claussen, Darren M. Benjamin, Robert F. Illyes, and David B. Philipp. 2001. Database Management and Analysis of Fisheries in Illinois. Champaign, IL: Illinois Natural History Survey Center for Aquatic Ecology.

Schoenung, Brian M. 2001. “Fishing Pressure and Fish Harvest at Lake Monroe, 2000.” Available at www.state.in.us/dnr/fishwild/files/monroe.pdf. Retrieved on October 25, 2017.

Stein, Jeffrey A., Robert F. Illyes, Betty Carroll, Lynette Miller Ismael, Julie Claussen, Todd Kassler, John Epifanio, and David P. Philipp. 2002. Database Management and Analysis of Fisheries in Illinois. Submitted to Division of Fisheries, Illinois Department of Natural Resources. Federal Aid Project F-69-R Segments 13–15, Aquatic Ecology Technical Report 02/04. Champaign, IL: University of Illinois at Urbana-Champaign, Illinois Natural History Survey.

Stein, Jeffrey A., Robert F. Illyes, Lynette Miller Ismael, Betty Carroll, Julie Claussen, John Epifanio, and David P. Philipp. 2003. Database Management and Analysis of Fisheries in Illinois. Submitted to Division of Fisheries, Illinois Department of Natural Resources. Federal Aid Project F-69-R Segment 16, Aquatic Ecology Technical Report 03/03. Champaign, IL: University of Illinois at Urbana-Champaign, Illinois Natural History Survey.

Stein, Jeffrey A., Robert F. Illyes, Betty Carroll, Lynette Miller Ismael, Thomasine McNamara, Julie Claussen, John Epifanio, and David P. Philipp. 2004. Database Management and Analysis of Fisheries in Illinois. Submitted to Division of Fisheries, Illinois Department of Natural Resources. Federal Aid Project F-69-R-17 Segment 17. Champaign, IL: University of Illinois at Urbana-Champaign, Illinois Natural History Survey.

Stein, Jeffrey A., Robert F. Illyes, Thomasine McNamara, Lynette Miller Ismael, Betty Carroll, Julie Claussen, John Epifanio, and David P. Philipp. 2005. Database Management and Analysis of Fisheries in Illinois. Submitted to Division of Fisheries, Illinois Department of Natural Resources. Federal Aid Project F-69-R Segments 16–18. Champaign, IL: University of Illinois at Urbana-Champaign, Illinois Natural History Survey.



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U.S. Fish and Wildlife Service. 2013. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Indiana.