Waters of the US

I have long been a supporter of the navigable waters concept. Not because this approach is most protective of our surface waters. Rather, navigable waters is a pragmatic acknowledgment of the States' ability to assess compliance with ambient water quality standards for major surface waters, given their limited financial support for water quality monitoring.

 State water quality monitoring programs to assess compliance with water quality standards typically consist of monthly sampling. This is the time/temporal aspect of compliance assessment. The spatial component of water quality compliance monitoring is determined by state scientists and is spatially spread out on streams/rivers/lakes/reservoirs/estuaries/etc. The net result is that a relatively small space/time grab sample is intended to represent much spatial and temporal variability.

 So with that in mind, consider what expansion of the Waters of the US implies for water quality monitoring.  First, consider this obvious point - if you do not observe something about which you want to draw a conclusion, you have essentially no basis for a meaningful conclusion. So, we can expand the regulatory Waters of the US to the smallest stream, but unless there is corresponding water quality monitoring, this expansion is essentially meaningless for surface water quality protection for that stream. To express this point in everyday terms, consider highway speed monitoring. If a speed limit on a particular road is increased to, say 55 mph, yet there is no police/sheriff enforcement, then drivers are free to speed as they choose. Regulatory enforcement is essential.

 Given that perspective, if the definition of the Waters of the US is expanded, the states must either increase their water quality monitoring budget or discontinue some current monitoring so they can monitor waters newly-designated as in need of regulation. I have spoken with several state agency scientists about this. None of them expected an increase in their water quality monitoring budgets if the definition of Waters of the US is expanded beyond navigable waters.  Further, these scientists expressed reluctance to change/discontinue current water quality monitoring even with this proposed expansion. Right or wrong, their tendency was to continue monitoring at current locations to focus on water quality trends over time.

 Consider what water quality monitoring beyond navigable waters means for protection of US surface waters. For the most part, with exceptions, these non-navigable waters are "smaller" than the navigable waters and have less impact on waterbody use and enjoyment than do the larger navigable waters. I know that individuals will object to this conclusion for a particular waterbody, but this conclusion is hard to reject for all situations. 

 Water quality monitoring for wetlands is essentially distinct from monitoring for other surface water bodies, as wetlands have unique and considerable biological features. As a result, states have established wetlands water quality standards that reflect this biological focus. Regardless, states tend to not monitor wetland water quality for regulatory compliance. For example, the North Carolina Wetlands Program states that "The state does not have a formal. ongoing, wetland monitoring program."

 So what do I recommend for Waters of the US designation, and why. Unless states are willing to expand water quality monitoring budgets, I think that a navigable waters basis for water quality monitoring stations makes the most sense. In general, navigable waters monitoring is more likely to discover water quality standard violations of significance, as larger waterbodies affect more people. 

 I realize that my opinion is not widely held within the environmental community. Yet this group should not ignore the realities of expansions of Waters of the US beyond navigable waters. If, as I believe, the States do not allocate additional funds to expand their surface water monitoring, then States face a choice:

• Continue monitoring the same stations as before Waters of the US designation is expanded. 
  
  
• Expand the spatial extent of water quality monitoring to smaller waterbodies

So what do I recommend as a strategy for the environmental community? The expansion beyond navigable waters should be based on scientific justification for surface water quality standards and hence protection for these waters. Thus it is essential that a compelling case be made to the States to increase their water quality monitoring budgets to expand the spatial extent beyond navigable waters. As someone who is supportive of surface water quality protection, I understand the merits of expanding regulated waters, but only if this is undertaken with an analysis of the implications of this expansion on regulatory monitoring by the States.

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Reasoning in the Face of Uncertainty

 

How might we improve decision making in the face of uncertainty? I’ve thought about this a great deal throughout my career since uncertainty exists, whether acknowledged or not, in all decisions concerning proposed actions to protect water quality.

In past assessments (http://kreckhow.blogspot.com/2014/05/assessment-of-value-of-new-information.html ) of this issue, I have used decision analysis as my prescriptive model for how to consider uncertainty in model forecasts. That led me to focus on the value of new information that might reduce uncertainty.

However, there is another way to think about uncertainty in decision making, particularly when several management options are being considered. To see this, consider the figure below.

The probability distributions in the figure represent the predicted outcome for two management options affecting the concentration of a key response variable for which lower concentration is better. The peaks of the distributions represent the most likely outcome; this is the only information that would be generated by a deterministic model. Thus, on the basis of a deterministic model prediction alone, the likely decision would be to select management option B, if the management objective is to reduce concentration.

However, note that the prediction for option A has far less uncertainty than that for option B, even though option A is predicted to have a most likely concentration (the peak of the probability distribution) that exceeds the most likely prediction for option B. The uncertainty analysis provides additional information crucial to the decision. To be specific, do we want to select an option that has substantial nonzero probability (represented by the portion of distribution B that exceeds the concentration covered by distribution A) of exceeding the outcome predicted for option A, or do we want to select an option (A) that has a likely predicted higher concentration than option B, but has a lower probability of higher concentrations?

How might uncertainty differences arise between two management options? If these options represent nutrient levels in a lake, for example, option B may represent uncertain nonpoint source controls, while option A may represent more certain point source controls.

Obviously, cost of pollutant control is an essential component of decision making. So, cost of pollutant control may favor either option A or option B, but that does not take away from the fact that uncertainty in the concentration resulting from pollutant control also is useful information. Beyond that, the distribution of costs and benefits to the constituent groups and jurisdictions affected by the decision may be important.

One “take home” message from this hypothetical example is that public sector decision making is complex. To add to this complexity, I am suggesting that the uncertainty in the response to management actions is yet another attribute that should be considered. So, should we ignore prediction uncertainty because the issues are just too complex? Of course not! Public sector decision makers can always choose how to weight the information presented by their support staff. Indeed, they can choose to down weight information on scientific prediction uncertainty. Yet that does not mean that uncertainty no longer exists. As the public, and as decision makers, we lose if decision-relevant information is not available for consideration. Uncertainty in the impact of management decisions should be part of that decision-relevant information.

A Discussion of Watershed-Scale Pollutant Transport and Management

“I’m really concerned about the Neuse River Estuary,” my daughter Sarah announced one evening. “At school today, Norah, Ari, Sienna, and I talked about water pollution and decided that we should do what we can to save the Neuse.”

“Good for you, Sarah,” I said approvingly. “The only difficulty is that we live in Durham and the water quality problems are near the coast, over 100 miles away.”

“Wait a second, Dad. Doesn’t water run downhill?”

“Sure,” I responded, “so what?”

“Well, you once told me that we should be careful with fertilizer and stuff because the pollution from Durham runs into Falls Lake. So, the water that flows out of Falls Lake goes into the Neuse River which, like, carries it to the coast causing algae and dead fish.”

“Okay, it’s basically true that a portion of Durham’s treated wastewater and stormwater runoff ends up in Falls Reservoir, so we do have an impact on Falls Lake.” I agreed. “But, it’s not clear that anything you do in Durham matters very much if you’re concerned about the lower Neuse River and Estuary.”

“Well, does it or doesn’t it?” Sarah demanded. “You’re a water resources professor at Duke University, you should know. Does it matter how much pollution comes from Durham? And what about the people in Raleigh - don’t they pollute the lower Neuse either? What’s the answer?”

“Its not that simple,” I pointed out. “We’re not real certain about the degree of impact from various sources and locations in the Neuse watershed.”

“You’re kidding! You mean to tell me that a Neuse River management plan is being implemented and you don’t really know that it’s going to work?”

“Well, yes and no. We expect water quality to be better in certain regions of the lower Neuse, but the change may not completely satisfy the public’s desire for improvements. It seems likely that refinements to the plan will be necessary.”

Sarah’s dissatisfaction with this response was evident on her face. “How can you approve a plan when you don’t know what it will do?” she asked.

“First of all, I’m a scientist. I don’t approve plans, only elected officials have that right. Second, you’ve got to realize that we always have a plan in operation. We have a plan for the Neuse right now; it just isn’t as stringent as some people might prefer.”

“Okay, that makes sense, but I still want to know about people in Durham and Raleigh - does their pollution affect the lower Neuse?”

“Sarah, that’s a good question. For the Neuse River watershed as well as other large watersheds in the United States, one of the more pressing research priorities is the need to understand pollutant transport and transformation on a watershed scale so that accurate predictions can be made to guide management. Many water pollutants, such as nutrients, synthetic organics, and pathogenic microorganisms may enter a waterbody ten miles to over one hundred miles upstream of a point of concern for possible adverse impact. While it is reasonable to assume that there is some attenuation of these pollutants with distance, the degree of loss or change is currently quite uncertain. The interesting and challenging research task is to develop scientific understanding leading to good predictive models, which are essential for effective and equitable basinwide water quality management.”

“Dad, I’m not one of your students.”  Sarah groaned. “Stop lecturing and tell me what we can do in Durham!”

“Alright, Sarah, it’s reasonable to assume that Durham has some impact on the lower Neuse, even if we can’t quantify it too precisely right now. So, you and your friends might consider a few things that can make a difference, if not in the Neuse, certainly in our nearby Durham streams and in Falls Reservoir.

“One of the most important water pollution factors in residential and urban areas is the stormwater drainage network. Our house is not located near any streams or waterbodies, which at first thought, suggests that we have nothing to be concerned about. However, the storm drains located in the street in front of our house and throughout Durham provide an efficient pathway for fertilizers, lawn chemicals, and general urban debris to be washed from the streets and parking lots directly into our streams.

“This means that in areas with storm drains, location can be a deceiving indicator of impact. Potentially polluting land uses that are located quite remote from a stream or lake may have an impact on surface water quality, because a storm drain efficiently channels the stormwater runoff into the waterbody. So, Sarah, you and your friends can have a positive impact on water quality by urging your classmates and their families to keep polluting substances from washing into storm drains.”

“Thanks, Dad.” Sarah responded, as she dashed off to answer yet another phone call.

Is Chlorophyll a Reliable Indicator of Designated Use in Lakes and Reservoirs?

State water quality standards are established in accordance with Section 303(c) of the Clean Water Act and must include a designated-use statement and one or more water quality criteria. Over the past several years, the USEPA has been assisting the states to adopt/modify nutrient criteria. The criteria serve as measurable surrogates for the narrative designated use; in other words, measurement of the criteria provides an indication of attainment of the designated use. In addition, violation of the criteria is a basis for regulatory enforcement, which typically requires establishment of a TMDL. Thus, good criteria should be easily measurable and good indicators of the attainment of designated use.

Traditionally, the task of setting criteria has involved judgments by government and university scientists concerning the selection of specific water quality characteristics and the levels of those characteristics that are associated with the designated use. For example, consider the North Carolina chlorophyll a criterion of 40 ug/l, which was established in 1979. This criterion applies to Class C waters, which are freshwaters with use designations of secondary recreation, fishing, and aquatic life support. To establish this criterion, the NC Division of Environmental Management examined the scientific literature on eutrophication and then recommended a chlorophyll criterion level of 50 ug/l to a panel of scientists for consideration. After reviewing a study of nutrient enrichment in 69 North Carolina lakes, the panel responded that 40 ug/l reflected a transition to algal, macrophyte, and DO problems and thus represented a better choice. Following public hearings, 40 ug/l was adopted as the chlorophyll water quality criterion. The 40 ug/l criterion was developed from an ad hoc process of science-based expert judgment. In my view, we should be cautious in selecting a criterion level simply because it represents a change/transition point in waterbody response (e.g., transition to algal, macrophyte, and DO problems). For example, a DO level of zero is clearly a major transition point for an aquatic ecosystem, but it is unlikely to make sense as a water quality criterion protective of designated use. The criterion level should also reflect public values on designated use; good water quality criterion selection is not strictly a scientific endeavor.

In Reckhow et al. (2005), structural equation modeling and expert elicitation were used to quantitatively link candidate water quality criteria with designated use. This technique was applied to Lake Washington, with designated uses that protect, for example, salmon and trout, primary contact recreation, domestic water supply, wildlife habitat, commerce and navigation, boating, and aesthetic values. Dr. Eugene Welch, a Professor Emeritus at the University of Washington, was chosen as the expert for this study. Presented with Lake Washington’s designated-use statement, Dr. Welch identified boating as the most appropriate nutrient-related designated use to address based on his technical expertise. He selected water clarity, the absence of algal scums, odor, and interference from aquatic vegetation as desired properties of a “boatable” lake. In addition, the expert provided a conceptual model that included chlorophyll a, total phosphorus, Secchi depth, total zooplankton, and Daphnia biomass as the key environmental variables for assessing attainment of the designated use. He hypothesized that chlorophyll a would be the water quality variable most closely linked to the desirable properties of a boatable lake.

Consider the approaches of a few other states. In Florida lakes, a numeric chlorophyll criterion has been set to protect designated use associated with “an imbalance in the natural populations of the aquatic flora or fauna.” This is similar to the North Carolina perspective. In addition to the chlorophyll criterion, Florida also established criteria for nitrogen and phosphorus.

In Texas, PBS&J (2003) conducted a thorough and thoughtful analysis of nutrient water quality standards in lakes in the Trinity River Basin. They observed that “the (Trinity River Basin) study reservoirs are heavily used for recreation, water supply, and support healthy aquatic life communities. By that measure, all the reservoirs supported their designated uses.” However, based on the chlorophyll water quality criterion, seven of the nine reservoirs were not in compliance. Despite this inconsistency, PBS&J “determined that chlorophyll a was the parameter most directly related to uses, and that it should be the parameter selected for numerical criteria development.”

While recommending chlorophyll as the best nutrient criterion, PBS&J pointed out the difficulty in selecting the specific concentration of chlorophyll to serve as the compliance/noncompliance cutoff. The figures below from the PBS&J report identify an “optimal range” for the chlorophyll cutoff for the designated uses in the Trinity River Basin lakes. What is most striking about these figures is the size of the optimal range and the insensitivity of designated use to chlorophyll levels within this optimal range.

Why is this so important? This insensitivity of designated use to chlorophyll concentration is of particular concern in situations where attainment of a single-number chlorophyll criterion is expected to be extremely expensive, with little evidence of designated use improvement. In those situations, it is essential that water quality improvements (or, designated use improvements/attainment) justify the costs. This may be the situation in Falls Reservoir (North Carolina) where, despite little evidence of designated use impairment, compliance with the 40ug/l chlorophyll criterion is estimated to cost approximately $1 billion.

For much of my career, I have been a strong supporter of chlorophyll a as the best nutrient criterion for surface waters in the US. Since chlorophyll integrates the effect of nitrogen and phosphorus, it effectively serves as a site specific indicator of eutrophication. However, in my advocacy of chlorophyll as the best nutrient criterion, I neglected the fact that chlorophyll is not highly correlated with many common designated uses over the range of chlorophyll levels found in many US lakes, as demonstrated in the PBS&J figures.

What is the alternative? Dissolved oxygen is often a water quality criterion for nutrient enrichment. However, DO can be quite variable in space and time, so monitoring DO to assess designated use compliance poses challenges. It is an exaggeration but worth noting that a user survey to assess designated use may be more cumbersome than DO monitoring for compliance, but at least the user survey is a direct assessment of what matters most.

Water clarity, typically measured with a Secchi disk (SD), is another plausible alternative, as the SD depth is a good indicator of aesthetic appeal. Perhaps, as in Chesapeake Bay, all three (chlorophyll, DO, and SD) should be nutrient criteria, but I am not sure that this is sufficient. I think that these three criteria need to be accompanied by a direct assessment of designated use attainment in situations, like in Falls Reservoir, where compliance costs are extremely high. This will help ensure that our limited resources for environmental protection are wisely spent.

References

Reckhow, K.H. G.B. Arhonditsis, M.A. Kenney, L. Hauser, J. Tribo, C. Wu, K.J. Elcock, L.J. Steinberg, C.A. Stow, S.J. McBride. 2005. A Predictive Approach to Nutrient Criteria. Environmental Science and Technology. 39:2913-2919.

PBS&J. 2003. Analysis of Use and Nutrient Data on Selected Reservoirs of the Trinity River Basin. Austin, Texas.

Is the TMDL Program Effective for Surface Water Quality Management?

In 2001, I chaired the National Academy of Sciences review of the USEPA TMDL program (Assessing the TMDL Approach to Water Quality Management, NRC 2001). At that time, I was an enthusiastic supporter of TMDLs based on watershed analysis and improvement of surface water quality based on pollutant load reduction. Two issues have caused me to reconsider my perspective:

·         My colleagues’ endorsement of in-lake management strategies, such as artificial aeration and biomanipulation

·         My view that current water quality criteria may not be good indicators of designated use, resulting in unnecessary and exorbitant costs of compliance

In the past few years my colleagues, Dick Osgood and Ken Wagner, have made a compelling case for the ineffectiveness of watershed pollutant load reductions to achieve compliance with surface water quality standards in many water bodies; instead they have proposed that in-lake treatment is often a better management alternative. Their examples are hard to argue against. So what does this mean for the TMDL Program? Should we acknowledge the limitations of watershed pollutant load reduction and embrace in-waterbody treatment processes?

The 1972 Clean Water Act (CWA) was monumental in its positive effect on our Nation’s water quality. At the same time, the environmental euphoria of the CWA has sometimes resulted in well-meaning but non-attainable water quality standards in a number of situations. The result, in the Chesapeake Bay and in my home state of North Carolina, is water quality criteria that are not really reflective of underlying designated use. This is an important point because designated use (e.g., swimmable, recreational fishery) is what we protect with our water quality standards; water quality criteria, such as chlorophyll a and dissolved oxygen, are just easily-measurable (and inexact) surrogates for designated use.

I believe that many surface water quality criteria that have been established by the States are not adequately representative of designated use. Further, I believe that in many situations we have set water quality criteria that have resulted in TMDLs that have associated costs of compliance that are way beyond expected water quality benefits. At the same time, I am not a proponent of in-lake treatment processes as an alternative to watershed pollutant load reduction except in small waterbodies where studies have demonstrated the effectiveness of in-lake techniques. My bottom-line perspective on the two issues that I raise – we should revisit the TMDL program and the underlying surface water quality standards, yet we should not be taken in by the low-cost, but ineffective in-lake treatment technologies (as recently employed in North Carolina at a waste of $2 million) unless there is compelling scientific evidence of their effectiveness. 

EPA’s Approach to Decision Support is in need of a Sea Change

In the past few decades, the USEPA has widely recognized the importance of economic analysis to the EPA mission. As a consequence, EPA has hired environmental economists and supported research on benefits assessment. This has greatly enhanced EPA’s knowledge base for decision support. EPA should now make a further significant improvement to their decision support by establishing prescriptive decision analysis as the best way to present uncertain scientific knowledge for informed decision making.

Decision analysis, based on the normative model of decision theory, is a well-established discipline that is taught in many university public policy and business programs. There are two fundamental elements in a decision analysis:

•      A utility function that characterizes the values, or perhaps net benefits, associated with outcomes of interest that result from a management action,
•    A probability model that quantifies the uncertainty in the outcomes of interest that result from a management action.

The economic analysis that is now embraced by EPA may be used to provide the first element of the decision analysis quantifying value. An uncertainty analysis can provide the second essential element.

Why has EPA recognized the importance of economic benefits assessment to inform decision making, yet seems oblivious to the need to follow the decision analysis model that is so well-established as an academic discipline? I think that a major reason for this situation is that the environmental engineering and ecology programs that have provided the academic training for many scientists in EPA and in state environmental agencies do not include a course in decision analysis, nor do they recommend a curriculum that includes decision analysis taught in another academic department.

Perhaps to better appreciate the role of this decision analytic framework, consider the following example from everyday life. All of us have made decisions on outdoor activities in consideration of the forecast for rain. In deciding whether to hold or postpone an outdoor activity, we typically seek (scientific) information on such things as the probability (reflecting uncertainty) of rain. Further, it is not uncommon  to hear the weather forecast on the evening news, but still defer a final decision on the activity until an updated weather prediction in the morning (in other words, get more sample information).

Beyond consideration of the scientific assessment in the weather forecast, we also think about how important the activity is to us. Do we really want to participate in the activity, such that a little rain will not greatly reduce our enjoyment? Or, is the activity of only limited value, such that a small probability of rain may be enough so that we choose not participate?

Every day, we make decisions based on an interplay, or mix, of uncertainty in an event (e.g., rain) and value (enjoyment) of an activity. We are used to weighing these considerations in our minds and deciding. These same considerations--getting new information on the weather (which is analogous to supporting new scientific research, as in adaptive management), and deciding how valuable the activity is to us (which is what we determine through cost/benefit analysis)--are key features of decision analysis.

Public sector decisions involving uncertain knowledge and uncertain forecasts should follow this same decision analytic paradigm. Given the consequences of most public sector decisions and the uncertainties in environmental modeling, it is essential that this happen. Failure on the part of EPA to use decision analysis as their prescriptive model for decision support means that many of EPA’s assessments and models will continue to ignore uncertainty in model predictions, resulting in many unexpected management outcomes because stakeholders are unaware of the large uncertainties in predictions from the deterministic models that EPA provides in its decision support. In my view, this situation is inexcusable.

Unattainable Surface Water Quality Standards may Diminish Widespread Public Support for Water Quality Improvements

Many state water quality standards were established in the early years of the Clean Water Act (CWA) when a key goal of the 1972 CWA was “to eliminate pollutant discharge to navigable waters by 1985.” Unfortunately, this admirable goal sometimes has resulted in required pollutant load reductions (e.g., TMDLs) that are based on unattainable water quality standards that reflect the environmental euphoria of the 1970s and 1980s. In my view, it is wise to consider if we should continue to develop water quality management plans focused on achievement of those goals, or if it is better to develop realistic goals and set attainable water quality standards. 

From a pragmatic perspective, working toward unattainable water quality standards diminishes our ability to achieve widespread buy-in on pollutant load controls.  I see this reaction to water pollutant control now in North Carolina, where unattainable standards are leading to a backlash against pollutant reduction, due primarily to extremely high costs of compliance with a TMDL. 

Unfortunately, this perspective may be given further support by long lag times between implementation of nonpoint source controls and observable water quality improvements, leading to skepticism that the required pollutant load reductions will have any effect.

For example, Falls Reservoir in North Carolina has a TMDL mandating a 77% reduction in phosphorus loading to attain the 40 ug/l chlorophyll a water quality criterion. Given the preponderance of nonpoint sources of phosphorus in the Falls Reservoir watershed, a 77% phosphorus load reduction is not feasible; even if it were, the cost of attainment almost certainly will far exceed the benefits derived for designated use. Given that situation, Falls Reservoir is in need of a Use Attainability Analysis (which determines if a designated use is technologically and economically feasible) or new site-specific nutrient criteria.

I believe that realistic and achievable water quality standards, with designated use (e.g., recreational fishing) improvements that is causally-linked to attainment of water quality criteria (e.g., chlorophyll a), are needed to gain widespread support for pollutant controls for water quality improvements. In Falls Reservoir, the backlash against the high cost of phosphorus load reductions has resulted in a state-sponsored plan for in-lake artificial mixing (using SolarBees). This is a waste of money, as whole-lake mixing is not feasible due to the large size of Falls Reservoir, and in-lake mixing will have little effect on nutrient concentrations. While I do not believe that water column mixing in Falls Reservoir is scientifically-defensible, I do understand that local and state elected officials may feel desperate enough to embrace even ineffective “solutions” in the hope of reducing pollutant control costs for their constituents.

It is unfortunate that the laudatory goals of the Clean Water Act are not everywhere attainable. Given that fact, I believe that the most effective way to achieve additional protection of designated uses is to adopt technologically and economically feasible water quality standards. This is likely to result in relaxation of a limited number of current water quality criteria. I wish that we could do better and eliminate pollutant discharges to navigable waters, but that is not going to happen. In my view, recognition of the need to set realistic water quality goals is the best pathway to achieve and maintain meaningful water quality improvements.