Reservoirs - A library for modeling Bolin & Rodhe reservoirs.

Bolin & Rodhe (1973) describe methods for characterizing the turnover rate of mass accumulating in a reservoir. The distribution of ages of particles in the reservoir constrain the possible input and output rates that could produce the observed record. The functions in this crate allow the user to compare synthetic accumulation records to observed records using the K-S and Kuiper statistics, to determine the best-fitting input/output pair for an observed record.

In my research at Oregon State University, I estimate the transit times of stream sediments moving through headwater valleys of the Coast Range by fitting reservoir models to a record of charcoal ages sampled from stream bank deposits. Inherited age refers to the age of charcoal when it enters a stream deposit. If we do not account for inherited age in the model, then transit times become artificially inflated. I have added an inherited age capacity to reservoirs, and while this is not a traditional feature of Bolin & Rodhe reservoirs, it is useful for dealing with charcoal ages.

This library includes the full code base used to estimate transit times for my ongoing dissertation, published here in the interest of academic transparency.

To use reservoirs, add it to your Cargo.toml toml [dependencies] reservoirs = "^0.1.1"

Let's load the stream bank charcoal data from the Oregon Coast that I use in my research. Many of the functions serve to compare a synthetic distribution against an observed record, and stream bank charcoal makes a handy foil.

```rust use reservoirs::prelude::*;

fn main() -> Result<(), ResError>{ // mean expected deposit age and inherited age by facies let dep = Sample::read("https://crumplecup.github.io/reservoirs/examples/dep.csv")?; let iat = Sample::read("https://crumplecup.github.io/reservoirs/examples/iat.csv")?;

// subset mean ages of debris flows let df: Vec = dep.iter().filter(|x| x.facies == "DF").map(|x| x.age).collect(); // subset inherited ages let ia: Vec = iat.iter().map(|x| x.age).collect();

let res = Reservoir::new().input(&0.78)?.output(&0.78)?.inherit(&ia);
let eg = res.stereotype(&30000.0, 1000, 200);
plot::comp_cdf(eg, df, "https://crumplecup.github.io/reservoirs/examples/df_cdf.png");

Ok(())

}

```