Computer scientists have a way of conceptualizing automated business processes as the interaction between a data model and a process model (see figure below). In non-geek-speak, you have data (e.g., like accounting data), and then you do something to it (e.g., tally it up), resulting in the achievement of some important business requirement (e.g., profit/loss statement).
If your data is wrong, or if your process is wrong, then you end up failing to meet your requirement.
This blog series has already raised questions about the CAO data model (i.e., speculative claims of de manifestis pollution), but what do the draft CAOs say about process? As a case in point, the wetland CAO relies principally on a process called the "Rational Method" for its buffer size calculations. The authors of the proposed CAO would really like us to believe that this method is a good predictor of pollutant loading, especially when combined with information from the infamous Mayer paper.
The Rational Method was developed in 1851 by Irish engineer Thomas Mulvany. It predicts the amount of stormwater runoff from various surfaces. For example, impervious surfaces like hardpan will have higher runoff than porous sand. That's all the Rational Method calculates: surficial runoff volume. It says nothing about pollution in that runoff. Nothing.
Our County has made the assumption that higher runoff equals higher pollution. Is that a reasonable universal assumption? Personally, I happen to think pollution is related to authentic pollutant sources, not necessarily to runoff volume. What do you think? Is runoff from a cut pasture more polluted than runoff from an uncut pasture, or from a forest? How about runoff from your organic garden versus runoff from native vegetation? Regardless what you may think, that's what our County thinks. "They" assume that flow is equal to pollution because "they" just assume that we are surrounded by ubiquitous perpetually-emitting pollution sources, with harmful toxins ready to be mobilized by the slightest drop of moisture landing anywhere. As explained in an earlier blog post, that logic would lead you to conclude that the Amazon River is the most polluted river in the world because it has the highest flow. By that logic, the wetter a place is, the dirtier it is.
In short, the CAOs start off with the wrong data and then misapply a 160-year old generalized process with very tenuous applicability to the question at hand. The CAOs have been formulated with both the wrong data model and the wrong process model. Garbage in ... garbage out ... GIGO ... CA(GIG)O.