Reducing risk and uncertainty in water quality trading

We need to use every possible approach to improve water quality across the US. The great news is that many facilities are investing in onsite upgrades to comply with nutrient limits. But in places where achieving necessary reductions become very expensive, water quality trading (WQT) can help get there cost-effectively. It’s a relatively new environmental market, with less of a track record than wetland mitigation banking, conservation banking and carbon credits.

How does it work? Forest Trends likens it to “cap-and-trade for waterbodies”:

WQT works by establishing a scientifically-determined “cap” on the amounts of fertilizer or other pollutants that a lake, bay, or stream can handle, and then letting water utilities and other pollution emitters “trade” their allowances to find the most efficient ways of meeting the cap.  

Trading programs had been adopted in eleven states in 2014 (thirteen, if you count Kentucky and Indiana for their participation in the Ohio River Basin Interstate WQT Project), growing to 21 states with programs—or permitting trading—in 2016. Despite this growth in new program popularity, the actual volume of trades is relatively low. Water quality trading’s limited application begs the question, why is it not more widespread?

Over the past couple of years, a few analyses have dug into this question of why water quality trading has not taken off as much as some other environmental markets. An October 2017 report by the US Government Accountability Office points out that a key factor in generating water quality trading demand is the existence of discharge limits. That is, a cap on the quantity of nutrients such as phosphorus and nitrogen that a source or facility can legally emit.

The GAO report further highlights that nonpoint nutrient credit generators (typically, agricultural operations) have a hard time quantifying their nutrient reduction amounts with certainty. They can use models to measure credit generation, but regulators require additional measures to account for uncertainty in the models. Those additional measures can be cost-prohibitive, which leads to a lack of participation. Credit measurement shortcomings translate to market uncertainty for buyers, too. Buyers fear that credits might be invalidated by regulators because they do not meet standards for nutrient reduction.[1]Buyers don’t want to jump into a market when they don’t have confidence in what they’re buying.

This seems like a case of letting the perfect be the enemy of the good. Models and estimates of nutrient benefits might be sufficiently accurate to build effective programs for the long-term. We just need to build a culture of trust around the use of models and technology. Otherwise, nonpoint nutrient credit trading won’t get off the ground.  

EPA’s February 2019 memo, which strengthens federal support for water quality trading and encourages states and tribes to implement trading programs, suggests stakeholders “consider allowing credits to be generated and verified based on scientifically defensible estimates of pollutant reductions from applicable technologies and land-based practices.” This means that utilities and farms could rely on models to predict nutrient runoff reductions. So long as regulators can agree with these modelling standards, the threat of buyers being out of compliance should fall by the wayside. Further, programs should allow for adaptive management to iterate and improve credit development standards while assuring market predictability.

Even more recommendations come from an October 2018 report, spearheaded by Willamette Partnership and Forest Trends’ Ecosystem Marketplace, that offers an extensive list of approaches for accelerating the uptake of water quality trading in the US, for audiences including municipalities, utilities, nonprofits, and the EPA. These ‘priority actions’ are based upon a series of interviews and research into barriers that have hampered trading. They include things like (1) simplifying trading programs, (2) addressing staffing and funding shortages at state regulatory agencies, and (3) addressing risks that scare off potential credit buyers.

To dig into WQT at a local level, I spoke with people involved in managing WQT for Idaho and the Lower Boise Watershed. Idaho has its own WQT guidance, which means trades can happen any time. Trading in the state isn’t widespread, but there is a history of trading among trout farms. What might prove invaluable in the future is that the trading infrastructure and guidance is already established; it will be there when it’s needed. Once facilities complete upgrades to meet their TMDLs, they will likely have some final reductions that can be cost-effectively achieved via trading. For instance, some small municipalities recognize that even after their upgrades are completed, meeting their TMDLs could come with high chemical treatment costs. If they can avoid those through trading, they will save money while still complying with overall reduction requirements.

Idaho also uses a unique approach to watershed management: a statewide network of Watershed Advisory Groups (WAGs) that design WQT frameworks on a watershed basis. The Lower Boise group in particular meets regularly, hears presentations from visiting experts, and works through key barriers to trading.

With a little work, WQT could happen on a large scale in the next few years.  It’s a great tool for achieving nutrient reductions and improving water quality. In order to make it work for more participants, regulators such as EPA and especially states must do more in order to address market uncertainty by establishing more protocols to model offset values and policies that create regulatory certainty for credits; WQT guidance should also develop ways in which to transfer risk to the credit developer, rather than the buyer; and, programs like the NSF Seed Fund should invest in technology and innovation to more accurately calculate offset value over time so programs can improve.


[1] One analysis offers a very compelling example: “in the early days of California’s carbon market, participants were uncertain about what would be considered a violation and what it would take for the Air Resources Board to invalidate offsets. Project developers worried that regulators would retroactively invalidate some credits, forcing the credit owners to replace them at their own cost. When a 2014 investigation resulted in Air Resources Board invalidating a large number of offsets, those fears were confirmed and trading of offsets in the California market dropped substantially as a result (Goldstein, 2015).”

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