📄️ Working with BRAT Outputs
The majority of users of BRAT will not actually run BRAT themselves, but instead will download BRAT outputs and summary products for use in beaver-related stream conservation and restoration efforts. In the text and videos tutorials below, we walk through various ways to interact with the BRAT outputs. We cover each of the outputs that BRAT produces, provide lookup tables for investigative purposes, and provide illustrative videos to help access and interrogate the outputs.
📄️ Architecture
BRAT comprises three separate processes that are run in order. Operations that involve data that change infrequently and also don't involve human judegment are broken out into their own process. This avoids unnecessarily performing time consuming processes on data that hasn't changed. Conversely, the third step is designed as a separate process because it requires the selection of hydraulic equations and vegetation suitability, which is subjective and might change over time.
📄️ Database
BRAT uses a lightweight SQLite database to store the information needed to run the model. This page describes the design of this database (referred to as a "schema") and how to work with it to refine the results. This is particularly important for the third and final BRAT Run step that calculates dam capacity etc. All the parameters over which the user has control are stored in the database where they can be changed easily.
📄️ Installation
BRAT is written in Python and exclusively uses open source libraries. You do not need ArcGIS to run the latest version of BRAT. However, the cost of this open source freedom is that some of the open source libraries used can be tricky to install, especially on Microsoft Windows (see the explanation at the bottom of this page as to why this is).
📄️ International
Applying BRAT to settings outside the United States
📄️ CONUS BRAT Parameters
BRAT parameters for the Conterminous United States (CONUS) are stored in the BRAT git repository here. The parameters are stored in a series of plain text CSV files. These files are then used to populate the BRAT SQLite database each time BRAT is run. Be careful to check your git branch to ensure you are looking at the latest parameters.
📄️ Importing Suitability
The following instructions describe how to import vegetation suitability values from old pyBRAT runs. Using the script we have provided, this is a quick way to reuse vegetation suitability values that have already been determined.