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- 1 September 24 , 2010 

### Appendix K

Allocation Methodology to R e late Relative Impact to N eeded C ontrols



### Introduction

The nutrient allocation procedures agreed to by 5 of the 7 Bay watershed partners and followed by EPA are de scribed in section 6.9 of the main document. The re ader should be familiar with section 6.9 before reading this appendix. The goal of this appendix is to expand the options that were considered before selection of the final procedures and to provide rationale for the final

decisions. The information pres ented in this appendix is the same information that was used to inform the decisions in the spring and summer of 2009. The watershed model was version 5.2 which had known limitations. Many of the values given in this appendix will be different from

the f inal version as these decisions were not revisited with version 5.3 of the watershed model.



### Relative Effectiveness Options

Section 6.9.2.1 of the main document is a discussion of the relative effectiveness of major basins in improving dissolved oxygen in t he critical areas of the tidal waters of the Chesapeake.

Relative effectiveness is a combination of riverine effectiveness , also known as a delivery factor

, which is expressed as pounds of reduction reaching tidal waters pounds of reduction to the lo cal river

and estuarine effectiveness, which is expressed as improvement in dissolved oxyg en

. pounds of reduction reaching tidal waters

Multiplying the two together gives improvement in dissolved oxyg en

. pounds of reduction to the local river



### Riverine Effectiveness Options

No options were considered in calculating riverine delivery factors. The principles of calculating delivery factors in the Chesapeake Bay Program watershed models are long

- standing and have been approved several times in workgroups and subcommittees and have been reviewed in independent STAC review of the watershed model in 2007 and 2009. Nitrogen delivery factors are calculated for each river segment. Nitrogen levels are lowered naturally in river systems

thro ugh denitrification, providing a long

- run removal of nitrogen. Phosphorus and sediment do not undergo a similar process to denitrification and do not have long

- run removal mechanisms other than delivery through the river system and burial. Burial is offs et by scour, both of which are episodic in nature. This does not hold true in reservoir systems, where burial is much more significant and is not offset by scour to a great degree. Due to the lack of spatially and temporally detailed phosphorus and sedim ent data that would be needed to precisely calibrateDraft Appendix K

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- 2 September 24 , 2010 scour and burial on the segment scale, the calculation of delivery factors for phosphorus and

sediment is closed aroun d reservoirs rather than segment by segment. That is, all segments upstream of a res ervoir or an entrance to the tidal system and downstream of other reservoirs receive the same riverine delivery factor.



### Geographic Grouping of Estuarine Effectiveness

The estuarine effectiveness is calculated by comparing the dissolved oxygen simulated in the Bay of the calibration run to the dissolved oxygen simulated in the Bay when a given watershed area has reduced loads relative to the calibration loads. The effectiveness for that given area is then calculated by dividing the improvement in dissolved oxygen by the reduction in loads. A choice has to be made regarding the geographic areas to test.

Each area along the estuary would theoretically have a different estuarine effectiveness, but there are limitations to what can be effectively calculated. If the area tested has a low total load and therefore a small change in going to a reduced load, the estuarine model may not be able to resolve the change in dissolved oxygen. Tested areas must be aggregated up to a reasonably large load to be able to rec ord the change. Also the estuarine model takes a few days to complete a run and it would be time prohibitive to make more 100 or so runs.

There is no difference in estuarine effectiveness between loads in the same non

- tidal watershed. Loads from areas j ust west of Washington DC would have the same estuarine effectiveness as loads from West Virginia since then enter the tidal waters at the same point, although they would

have different overall effectiveness scores because of the riverine effectiveness. T herefore the head of tide of large river systems is a natural place to define a discrete watershed. The estuarine portion of major river systems like the Potomac and Rappahannock would have significantly

different effects on the critical area for dissolve d oxygen and also have large enough loads to resolve these differences so these are another reasonable place to lump geographically. The Eastern Shore is not amenable to simple rules like this as there are no large non

- tidal river systems with large estua rine river systems. There is, however significant differences in estuarine effectiveness between the northernmost and southernmost portions of the Eastern Shore. The

Eastern Shore was therefore divided in to four sections.

The final geographic breakout, as a balance between the desire to calculate a different effectiveness where a distinction exists and the limiting factors of computer run time and the ability of the estuarine model to resolve the oxygen effect of small differences in loading are:

Susq uehanna

West Shore

Patuxent Above Fall Line

Patuxent Below Fall Line

Potomac Above Fall Line

Potomac Below Fall Line Rapp Above Fall Line Rapp Below Fall Line

York Above Fall Line

York Below Fall Line

James Above Fall Line

James Below Fall Line Upper East Shore

Middle East Shore

Lower East Shore

East Shore VA

To be clear, the allocation calculations are split between these geographic areas within jurisdictions, resulting in 30 different spatial units. The allocations, however, are expressed onDraft Appendix K

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- 3 September 24 , 2010 the jurisdi ction and basin scale. That is, there is a calculation of Maryland Potomac above and below the fall line, but the allocation is expressed only as Maryland Potomac.



### Choice of the Critical Designated Uses and Segments for Calculating

Relative Effectiveness

To estimate the estuarine effectiveness, the change in dissolved oxygen must be calculated for a relevant area of the Chesapeake. The most persistent areas of dissolved oxygen violations are in the main stem of the Chesapeake from roughly the route 50 bay bridge south to the mouth of the Potomac and also the lower Potomac region. The deep water and deep channel designated uses are impaired at a higher rate than the open water designates use and also better integrators of bay

- wide rather than local loads.

The deep water and deep channel designated uses of CB3MH, CB4MH, and CB5MH and the deep water designated use of POTMH_MD were selected as the most appropriate grouping to use in calculating estuarine relative effectiveness for the following reasons

1. These segments and designated uses had high levels of impairment

2. They are centrally located

3. The represent a large group of segments and a large volume of the bay.

4. Deep water and deep channel designated uses are good geographic integrators

Further tests of other combinations showed that the estuarine effectiveness was not particularly sensitive to the addition or subtraction of any given designated use.



### Metric for Relative Effectiveness

To estimate the change in dissolved oxygen an appropriate metric of dissolved oxygen must be calculated that is sensitive to load changes across a wide array of segments, designated uses, and impairment levels and is relevant to the assessment of dissolved oxygen criteria. Three metrics were investigated:

1. Percent non

- attainment.

2. Average dissolved oxygen during the summer assessment period

3. 25 th percentile (quartile) of dissolved oxygen during the summer assessment period

Three criteria were applied in determining which of these make the best metric

1. Relevance to attainment of diss olved oxygen standards

2. Broad applicability to designated uses and water quality segments

3. Linearity of response

– does the first pound have the same effect as the last?

Percent non

- attainment is clearly the most relevant metric to standards attainment alth ough other measures of dissolved oxygen are certainly also relevant. The quartile is more relevant than the average in that we are estimating increases in the lower values of oxygen.

Percent non

- attainment is applicable only to areas that are not in atta inment in the calibration and do not come into attainment when simulating a reduction in any single basin, which is a considerable limitation. Average dissolved oxygen is not an appropriate measure for many open water segments. An impaired open water seg ment may have average dissolved oxygen near saturation, but experience large swings between super saturation and low oxygen. A loadDraft Appendix K

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- 4 September 24 , 2010 reduction may not change the average, but improve the water quality by reducing the variability of oxygen levels and the fr equency of low values. The quartile is applicable to all segments and all designated uses.

Linearity of response is a crucial component. If a metric responded much more to the first pound of reduction than to the last, then smaller basins would be estima ted to have a greater pound for pound influence than larger basins. To determine the linearity of the response to the three candidate metrics a run was made with the Susquehanna at half the level of reduction normally

used to calculate estuarine effective ness. In general, across multiple segments and designated uses, the response for all three metrics was mostly linear. There was not a significant difference

between the metrics on this count.

The average was judged to be not suitable due to its limited applicability. The percent non

attainment was judged to be slightly more relevant than the quartile, but the quartile was selected as the appropriate metric due to its universal applicability.



### Level of Effort Options

Section 6.9.2.2 of the main document d escribes the expression of level of effort as between the

two extreme scenarios of no action scenario and E3. Selection of these two scenarios is an expression of the third principle under section 6.9.1 that all previous reductions are credited

toward ach ieving the allocations.



### Atmosp heric deposition

The atmospheric deposition options and rationale for choosing a level for federal targeting in developed in section 6.10.1. The method of incorporation is to hold atmospheric deposition constant through the bookend scenarios of No action and E3, and through all of the prospective management scenarios unless specific actions are called for in state plans that go beyond the federal levels. One example of states going beyond the federal level is that the E3 has atmospheric deposition set to a level that incorporates reduced agricultural emissions and other possible state actions. This allows the jurisdictions to be responsible strictly for the reductions that they can control and not for federal actions on atmo spheric deposition.



### Scenario Options

The E3 scenario was selected as the appropriate lower end of loading rather than other candidate scenarios such as the ‘current programs’, ‘maximum feasible’, or ‘all forest’. Current programs

could be used as the lowe r end and an assessment made of how far efforts had to increase beyond current programs, but this would violate the expression of equity above in that jurisdictions that had already achieved significant reductions would have to do proportionately more than jurisdictions that have not. Maximum Feasible would be a similar expression as E3 and would meet the equity provision, but it was judged to be much more subjective and therefore inferior to E3 as a metric. The all forest scenario would be an expression of anthropogenic, rather than controllable loads. The all forest was used in the 2003 goal setting. Basing the allocation method on E3 recognizes that various sources have different possible levels of reduction. An allocation based on anthropogenic load could require levels of reduction beyond E3. For example, if an allocation required all loads to go 60% of the way toward all forest, certain theoretical land uses that can only achieve a 50% reduction at E3 would not be able to achieveDraft Appendix K

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- 5 September 24 , 2010 the allocations, while waste water treatment plants would be able to achieve much a much larger

than 60% reduction from no action. These distortions would increase at smaller scales as sources become more dominant locally.

No Action was chosen as the upper end to follow the principle of accounting for previous reductions. Using a starting point that incorporated management practices or higher levels of treatment would give a disadvantage to jurisdictions that had implemented these actions.



### Allocation Method Options

Secti on 6.9.2.3 describes the method used to relate relative effectiveness to reduction effort. With this basic outline there an infinite number of ways to define the allocation and still meet water quality standards. The major decisions to be made are the nu mber of lines that represent different source categories and the shapes of those lines. The options were discussed in the WQGIT and the PSC and agreement was reached between the EPA and 5 of the 7 jurisdictional

partners.



### Number of Allocation Lines

During the allocation process, the WQGIT recognized that different source categories had different abilities to make progress toward an E3 level of implementation. Figure K

- 1 is a plot of implementation progress through 2009 plotted on the same vertical axis as the allocation charts, percent of E3 from no action.

Figure K

- 1: 2009 implementation by sector

The 2009 implementation represents the choices that the jurisdictions have made to date, presumably taking into account the same t ypes of criteria that will be used to make decisions on restoration spending in the future.

Note that this does not necessarily mean that more money or effort went to any particular sector, just that using the allocation metric of no action and E3 with th e current definitions the sectors have varying current levels. Figure K

- 1 was created with phase 5.3 output , while the EPA and the WQGIT saw similar information using phase 5.1.Draft Appendix K

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- 6 September 24 , 2010 There is a clear separation between the sources in that jurisdictions have c hosen to set waste water treatment at a level closer to E3, relative to no action, than either agriculture or developed

land. The re is also a separation between agriculture and developed land, but it is not as large as the separation between WWTP and all other sources. With this information, the decision was made to use 2 lines, one for WWTP and one or all other sources.



### Shape of the Allocation Lines

Several allocation line shapes were discussed with the three main shapes being:

1. Straight: This is the mos t straightforward expression of the allocation principle stated under section 6.9.1 that areas with a greater pound for pound effect on water quality

should do more

2. Hockey Stick: It was recognized that a natural maximum existed for some sources, particula rly with waste water treatment where a given technology could reach a concentration that could be expressed as a percentage from no action to E3. A hockey

stick line has a maximum for watershed areas in the range of relative effectiveness and slopes down for lower levels of relative effectiveness.

3. Z

- curve: similar to the hockey stick, but also recognizing that a natural minimum also may exist. Again related to waste water treatment plants, a given technology producing a known concentration may be seen as a minimum technology that should be implemented.

As reported in more detail in section 6.9.2.3 the wastewater line was set first in a ‘hockey stick’ shape such that the upper 50% of the relative effectiveness values were at a maximum attainment

percentag e, based on a given concentration and the rest sloped off to a minimum value also based on a concentration. The straight line for all other sources was set such that a zero relative effectiveness would have a 20% lower value on the percent controllable ax is than the area with the maximum relative effectiveness value. The intercept for the all other sources was set such that the water quality standards were attained. Figure K

- 2, which is also figure 6

- 7 in the main document is the implementation of this m ethod for Nitrogen.Draft Appendix K

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- 7 September 24 , 2010 Figure K

- 2. Allocation methodology example showing the “hockey stick” and straight line reductions approaches, respectively, to wastewater (red line) and all other sources (blue line).

To make the above decision, the partnership was presented with several options for constructing

the lines. Basin

-

jurisdiction loads were calculated for each option.

Table K

- 1 : Initial options presented to the WQGIT on 9/30/2009Draft Appendix K

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- 8 September 24 , 2010 Table K

- 1 is a sample of options that were e xplored. Several more options were generated

before the final decision was made.



### Calculation of Equivalent Allocation Option s
For any given level of water quality there is an infinite number of lines that can be drawn on the allocation plots like figure K

- 2. To calculate an equivalent line to an existing line, it is necessary

to meet the condition of:

or the sum of all delivered loads for each state/basin/fall

- line combination times its estuarine delivery factor must equal a constant for the family of lines that meets the same water quality.

Expanding the delivered load term to create an equation between relative effectiveness and delivered load gives:

where:

X i is the relative effectiveness

E3 i and NoBMP i are the loads for that state/basin/fall

- line/sector for the two scenarios

m and b are the slope and intercept of the line and the only unknowns

Given a slope or an intercept the above equation can be solved numerically for the other parameter of the line. This equation was implemented in ex cel for multiple lines with enforced

maximum and minimum to accommodate the decisions above.