Introducing echor

I primarily use ECHO to obtain discharge monitoring records for wastewater and industrial discharges. Until recently, my workflow was to call or email the state environmental agency and ask for all the available permit numbers in the watershed. Some states maintain and provide a GIS file with spatial locations (this was preffered, but finding out when that file was last updated was can be difficult). Once I obtained the permit numbers, I log onto ECHO and type the permits numbers in, and individually retrieve disharge records for each facility. This requires quite a bit of clicking and typing, and is prone to error. Furthermore, there is no way to verify the records I received are correct. If I mistyped a number or received a wrong record from the agency, I have little way of catching the error.

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Binomial Test for Water Quality Compliance

In the previous post, I used a geometric mean to assess water quality compliance. According to EPA guidance, this is appropriate for assessing bacteria levels in water bodies. For other conventional parameters, we can determine compliance when a standards violation is unlikely to occur more than 10% of the time.

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Date-based rolling functions

States are responsible for water quality assessments that ensure waterbodies comply with designated uses under Section 305(b) of the Clean Water Act. Waterbodies that do not meet applicable standards are listed on the Section 303(d) list, which requires state establish a Total Maximum Daily Load (TMDL) for pollutants responsible for impairement.

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txwater retweets

Let's find out the retweet relationships for txwater twitter users.

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Retrieve EPA ECHO Data in R

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Time-series decomposition and trend analysis in Python

There are a number of methods to accomplish time-series decompositions in R, including the `decompose` and `STL` commands. I haven't come across a seasonal decomposition method in Python comparable to R's `STL`.

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