This repository contains code for a simple hydrology, sediment and phosphorus model, named SimplyP, written using Python. The Python version is slow, and the model has recently been recoded into C++ using the MOBIUS model building framework. This new system offers a number of benefits compared to the Python version, including: (1) super-quick run times, (2) easy to modify model equations, (3) a GUI for exploring and changing model parameters and visualising results, (4) a Python wrapper for interacting with the compiled model (without requiring any C++ knowledge), and (5) a number of optimisation and MCMC algorithms, via the Python wrapper.
The Mobius version of SimplyP is hosted here, and user-friendly instructions to get you started using the GUI and the Python wrapper will be coming very shortly.
The Python version of SimplyP in this repository is fully functional, but for most practical applications we recommend using the Mobius version (you do not need to be familiar with C++).
The model is dynamic, working on a daily time step, and is spatially semi-distributed i.e. there is the ability to differentiate between hydrology, sediment and phosphorus processes, and between land use types and sub-catchments (with associated stream reaches). An application of the model is described in this paper:
Jackson-Blake LA, Sample JE, Wade AJ, Helliwell RC, Skeffington RA. 2017. Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P. Water Resources Research, 53, 5382–5399. doi:10.1002/2016WR020132
and full details of version 0.1 of the model are provided in the Supplementary Information. Several changes have been made to the model since then, and are detailed in the change log.
The hydrology model used by SimplyP builds upon the one described here (see especially notebook 5). The remainder was developed by Leah Jackson-Blake and forms part of her PhD thesis. The work was funded by the RESAS, the Rural and Environment Science and Analytical Services Division of the Scottish Government and by NIVA (the Norwegian Institute for Water Research).
The current release version of the model is v0-2A. There are a number of known issues with the model (see 'Issues'); feel free to add to these. Known bugs will be corrected as soon as possible.
Please report any bugs or errors either by submitting a pull request via GitHub or by emailing Leah Jackson-Blake (ljb@niva.no).
If you don't have an up-to-date Python installation, a good option is the Anaconda Python distribution. Model development was carried out using Python 2.7, but should now be run with Python 3.6 as Python 2.7 is being phased out.
From the Anaconda prompt, create a new clean conda environment for SimplyP (you can replace 'simplyp' with a name of your choice)
conda create -n simplyp python=3.6
Activate the new environment
activate simplyp
Install dependencies
conda install jupyter=1.0.0 notebook=5.7.4 matplotlib=2.0.2 pandas=0.24.1 seaborn=0.9.0 numpy=1.15.4 scipy=1.2.0 xlrd=1.2.0
Download the SimplyP repository and unzip it to a location on your system. The folder Current_Release/vx-xx contains the main model code you will need to set up and run the model (vx-xx refers to the version number, which will change as development continues; e.g. v0-2A). The folder 'Example_Data' includes data to get you started with a model application using data from the Tarland catchment in Scotland.
From the Anaconda command prompt, change directories to the 'Current_Release/vx-xx' folder (which contains 'setup.py'), replacing the x-xx with the appropriate version number for the current release. To change directories, type cd followed by a space and then the filepath (e.g. cd C:\SimplyP\Current_Release\v0-2A). Then run
python setup.py install A simple example illustrating how the model can be used is here. To run this example:
From the Anaconda prompt, activate your SimplyP environment
activate simplyp
Change to the directory containing 'Run_SimplyP_vx-xx.ipynb' within the 'SimplyP/Current_Release/vx-xx' folder and run
jupyter notebook
then click the link to open 'Run_SimplyP_vx-xx_LongExample.ipynb'. You should now be able to work through the notebook, running the code cells interactively. More instructions are given within the notebook itself.
When you have finished working with the model, click 'File > Close and Halt' (remember to save any changes first, if desired), then close the browser tab. Close the 'Home' tab too, then CTRL + C' twice at the Anaconda prompt to shut down any active Python kernels.
A description of the input data required by the model is given here, and will be updated periodically. This file also describes the output data that may optionally be saved to file.