The Routing Application for Parallel computatIon of Discharge (RAPID) is a river network routing model. Given surface and groundwater inflow to rivers, this model can compute flow and volume of water everywhere in river networks made out of many thousands of reaches.
For further information on RAPID including peer-reviewed publications, tutorials, sample input/output data, sample processing scripts and animations of model results, please go to: http://rapid-hub.org/.
Installing RAPID is by far the easiest with Docker. This document was written and tested using Docker Community Edition which is available for free and can be installed on a wide variety of operating systems. To install it, follow the instructions in the link provided above.
Note that the experienced users may find more up-to-date installation instructions in Dockerfile.
Downloading RAPID with Docker can be done using:
$ docker pull chdavid/rapid
The images for RAPID on Docker Hub support CPU architectures for both AMD64 and ARM64!
The beauty of Docker is that there is no need to install anymore packages. RAPID is ready to go! To run it, just use:
$ docker run --rm --name rapid -it chdavid/rapid
Testing scripts are currently under development.
Note that the experienced users may find more up-to-date testing instructions in docker.test.yml.
This document was written and tested on a machine with a clean image of Debian 11.7.0 ARM64 installed, i.e. no update was performed, and no upgrade either. Similar steps may be applicable for Ubuntu.
Note that the experienced users may find more up-to-date installation instructions in github_actions_CI.yml.
First, make sure that git is installed:
$ sudo apt-get install -y --no-install-recommends git
Then download RAPID:
$ git clone https://github.com/c-h-david/rapid
Finally, enter the rapid directory:
$ cd rapid/
Software packages for the Advanced Packaging Tool (APT) are summarized in
requirements.apt
and can be installed with apt-get. All packages can be installed at once using:
$ sudo apt-get install -y --no-install-recommends $(grep -v -E '(^#|^$)' requirements.apt)
Alternatively, one may install the APT packages listed in requirements.apt one by one, for example:
$ sudo apt-get install -y --no-install-recommends gfortran
The Network Common Data Form (NetCDF) was already installed with apt-get.
However, the environment should be updated using:
$ export NETCDF_LIB='-L /usr/lib -lnetcdff'
$ export NETCDF_INCLUDE='-I /usr/include'
Note that these four lines can also be added in
~/.bash_aliasesso that the environment variables persist.
The Portable, Extensible Toolkit for Scientific Computation (PETSc) can be installed using:
$ mkdir $HOME/installz
$ cd $HOME/installz
$ wget "https://ftp.mcs.anl.gov/pub/petsc/release-snapshots/petsc-3.13.6.tar.gz"
$ tar -xzf petsc-3.13.6.tar.gz
$ cd petsc-3.13.6
$ python3 ./configure PETSC_DIR=$PWD PETSC_ARCH=linux-gcc-c --download-fblaslapack=1 --download-mpich=1 --with-cc=gcc --with-fc=gfortran --with-clanguage=c --with-debugging=0
$ make PETSC_DIR=$PWD PETSC_ARCH=linux-gcc-c all > all.log
$ make PETSC_DIR=$PWD PETSC_ARCH=linux-gcc-c check > check.log
Note that the following can be used as a replacement for the above code block:
$ mkdir $HOME/installz $ ./rapid_install_prereqs.sh --installz=$HOME/installz
Then, the environment should be updated using:
$ export PETSC_DIR=$HOME/installz/petsc-3.13.6
$ export PETSC_ARCH=linux-gcc-c
$ export PATH=$PATH:$PETSC_DIR/$PETSC_ARCH/bin
Note that these three lines can also be added in
~/.bash_aliasesso that the environment variables persist.
$ cd rapid/
$ cd src/
$ make rapid
Testing scripts are currently under development.
$ cd rapid/
$ cd tst/
$ gfortran -o tst_run_comp tst_run_comp.f90 $NETCDF_INCLUDE $NETCDF_LIB
$ gfortran -o tst_run_cerr tst_run_cerr.f90 $NETCDF_INCLUDE $NETCDF_LIB
$ gfortran -o tst_run_conv_Qinit tst_run_conv_Qinit.f90 $NETCDF_INCLUDE $NETCDF_LIB
Note that the experienced users may find more up-to-date testing instructions in github_actions_CI.yml.