README.md

geoBAM

bamr Logo

Overview

An update to the bamr R package (built by Mark Hagemann while at UMass) that uses more geomorphologically-informed prior knowledge for discharge inversion.

From bamr: "The bamr package facilitates Bayesian AMHG + Manning discharge estimation using stream slope, width, and partial cross-section area. It includes functions to preprocess and visualize data, perform Bayesian inference using Hamiltonian Monte Carlo (via models pre-written in the Stan language), and analyze the results."

geoBAM expands upon this project by incorporating more realistic river physics and geomorphology into the prior generation models used within bamr. This process includes a classification procedure which assigns intial prior estimates using 'river types' defined by fluvial and landscape geomorphology. Classes are assigned purely using remotely-sensed river widths and thus can be used for both Manning's or AMHG forms of BAM.

Installation

First, you need to have installed rstan from source on your local machine. To do that, follow the directions at this link verbatim. Otherwise, an error will be thrown during package installation. This only needs to be done the first time you wish to install geoBAM.

Following that, you can install geoBAM:

 #First get devtools package
if (!require("devtools")) {
  install.packages("devtools")
  library("devtools")
}

#Then install from github
devtools:: install_github("craigbrinkerhoff/geoBAM", force=TRUE)

Usage

The best way to get started is to follow the examples in the included vignettes, now located at the bamr website

Notes

1) The Sacramento test case in the bamr package is not included with geoBAM.

2) If both bamr and geoBAM are installed, make sure to explictly call functions by package as they have the same names. Otherwise, chaotic confusion will ensue!

For example:

geoBAM:: bam_estimate()
bamr:: bam_estimate()

Contact

For any questions regarding this package, I am reachable at cbrinkerhoff@umass.edu



craigbrinkerhoff/geoBAM documentation built on Dec. 25, 2019, 3:18 a.m.