🌍 Earth-System-Modelling

This repository contains the simple water balance model (SWBM) used in the Earth System Modelling course.
It is designed to demonstrate the most basic version of the model.

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✨ Features

• 🧹 Preprocessing of input data for the water balance model
• 💧 Simulation of soil moisture, runoff, and evapotranspiration
• ⏱ Easy-to-run time series simulations
• 📈 Plotting of results
• 📊 Correlation analysis between model output and observed data

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🗂 Input Data

The model requires an input CSV file with the following variables:

📅 time: Date or timestamp

🌐 latitude and longitude

☔ tp_[mm]: Precipitation in mm

☀️ snr_[MJ/m2]: Surface net radiation

Optional: (used for correlation with observations):

🌱 sm_[m3/m3]: Soil moisture

🌊 ro_[m]: Runoff

🔥 le_[W/m2]: Latent heat flux

An example file is provided in the data/ folder: 📊 Data_swbm_Germany.csv

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⚙️ Configuration

The model uses a configuration dictionary with these example parameters:

Parameter	Description	Example
c_s	Soil water holding capacity (mm)	420
a	Runoff function shape (α)	4
g	ET function shape (γ)	0.5
b0	Maximum of ET function (β)	0.8

Python example:

config = {
    'c_s': 420,
    'a': 4,
    'g': 0.5,
    'b0': 0.8
}

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🚀 Getting Started on your Local Machine

Follow these steps to set up the environment and run the model.

0. Install Git

If you do not have Git installed on your system, download and install Git for your system:

🌐 Git Downloads

1. Clone the Repository

git clone https://github.com/Motzemoere/Earth-System-Modelling.git
cd Earth-System-Modelling

2. Install Conda

If you do not have Conda installed, download and install Miniforge for your system:

🌐 Miniforge Releases

You should now have access to the Miniforge prompt command terminal

3. Create and Activate the Environment

The easiest way is to just create the environment manually by runnning these commands in the miniforge prompt:

conda create -n esm python pandas numpy matplotlib -y
conda activate esm

Alternatively:

Use the provided environment.yml file to create a Python environment with all dependencies in one go: (this is how its normally done with bigger envs)

Run and confirm this in your miniforge prompt:

cd Earth-System-Modelling
conda env create -f environment.yml
conda activate esm

🏃Running the Model

Open the cloned repository folder in you prefered IDE, select the esm env as your Python interpreter and start playing around.

You can find a complete example workflow, including how to run the SWBM model, plot the results, and compute correlations with observed data, in the following file:

➡️ run_swbm.py

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🚀 Getting Started on Google Colab

1. Open a new Notebook in Google Colab

2. Mount your Google Drive: (run this commands in a new code cell)

from google.colab import drive
drive.mount('/content/drive')
# Follow the instruction to allow access to your google drive

3. Clone the Repository into your Google Drive

Open up a terminal in Google Colab (bottom left corner) and run the following commands:

cd drive/MyDrive
git clone https://github.com/Motzemoere/Earth-System-Modelling.git
cd Earth-System-Modelling

Alternatively you could also just clone the repository to your local machine (see above) and then upload it to Google Drive.

4. Run the SWBM

In the repository, there is a complete example flow for running the SWBM: run_swbm_colab.ipynb. However, to open the script in Colab, you need to go back to Google Drive, navigate to the GitHub repository that you just cloned, and open the script from there using the Open with option, selecting Google Colaboratory.

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📬 Contact

If you have any questions, feel free to reach out:

✉️ mattis.pfenning@email.uni-freiburg.de

Reference

Koster, R. D., and S. P. P. Mahanama, 2012: Land surface controls on hydroclimatic means and variability. J. Hydrometeor., 13, 1604 1620, doi:10.1175/JHM-D-12-050.1.