LRGV Project

This repository contains the source code and resources for the LRGV (Lower Rio Grande Valley) simulation and optimization project. The focus is on a command-line interface version of the model that accepts decision variables and writes outputs to std-out.

The original reference for the model is Kasprzyk et al. (2009) "Managing population and drought risks using many-objective water portfolio planning under uncertainty", Water Resources Research, https://doi.org/10.1029/2009WR008121 but this model also reflects additions added later.

Structure

• lrgv_src/ — C++ source code for the simulation model
• lrgv_bin/ — Input data, Makefiles, and Python runner script

Python Environment

Create your own virtual environment and install dependencies as follows:

1. Ensure you have Python 3.13.12 or newer installed.
2. (Optional but recommended) Create a virtual environment:

python -m venv venv

3. Activate the virtual environment:

• On Windows (cmd):

  venv\Scripts\activate.bat

• On PowerShell:

  .\venv\Scripts\Activate.ps1

4. Install dependencies (none required except standard library):

pip install -r requirements.txt

For the current Python demo, no external Python packages are required; only the standard library is used. The script was developed and tested with Python 3.13.12.

C++ Build Instructions

To build the C++ code, two Makefiles are provided:

1. On Windows (latest testing):

• Open a terminal in the repository root.
• Run:

  make -f lrgv_bin/Makefile.msvc

• This will build the simulation executable using the MSVC-compatible Makefile. This is the version most recently tested.

2. On Linux/macOS (or with GNU Make):

• Open a terminal in the repository root.
• Run:

  make -f lrgv_bin/MakefileSerial

• This will build the simulation executable using the standard Makefile. This was originally tested when the repo was created in 2015.

Running the Python Demo

• To run the simulation from Python, use:

  python lrgv_bin/run_from_python.py

• This demonstration calls the C++ executable and shows how input decision variables and output objective functions are communicated through console input and output.
• The executable should be compatible with MOEAFramework and other tools that perform simulation-based optimization using standard input and output.

Notes

• Input data files are in lrgv_bin/.
• C++ source code is in lrgv_src/.
• The project uses both C++ and Python for different components.