Pancras-G/Hydrosense-Kenya

A project for monitoring irrigation using weather data, soil sensor data and crop data # HydroSense-Kenya **ICS 2207 Scientific Computing | Capstone Project** A Python scientific-computing system for smart irrigation, water balance simulation, and climate-aware decision support in a Kenyan smallholder farm context. --- ## Project Overview HydroSense-Kenya models the discrete soil water balance: ``` S(t+1) = S_t + R_t + I_t - ET_t - D_t ``` It answers the central scientific question: *How can we model water availability, estimate water deficit, simulate future soil moisture, and recommend an efficient irrigation plan that minimises water use without exposing crops to moisture stress?* --- ## Folder Structure ``` HydroSense-Kenya/ ├── data/ │ ├── raw/ │ │ ├── weather_daily.csv │ │ ├── soil_sensor_data.csv │ │ └── crop_zone_parameters.csv │ └── processed/ │ └── cleaned_irrigation_dataset.csv ├── notebooks/ │ ├── Level_1_Problem_Framing.ipynb │ ├── Level_2_Vectorization_and_Error.ipynb │ ├── Level_3_Numerical_Methods.ipynb │ ├── Level_4_Data_Analysis_and_Visualization.ipynb │ ├── Level_5_Simulation_and_Optimization.ipynb │ └── Level_6_Final_Integration.ipynb ├── src/ │ ├── __init__.py │ ├── data_cleaning.py │ ├── numerical_methods.py │ ├── simulation.py │ ├── optimization.py │ └── visualization.py ├── tests/ │ ├── test_root_finding.py │ ├── test_integration.py │ ├── test_linear_systems.py │ └── test_simulation.py ├── reports/ │ └── (plots and final report) ├── AI_USE_LOG.md ├── README.md └── requirements.txt ``` --- ## Installation and Setup ```bash # Clone or download the repository cd HydroSense-Kenya # Install dependencies pip install -r requirements.txt # Run all tests python -m pytest tests/ -v # Launch notebooks jupyter notebook notebooks/ ``` --- ## Running the Project Execute the notebooks in order (Level 1 → 6). Each level is self-contained but builds on outputs from previous levels. | Level | Notebook | Key Output | |---|---|---| | 1 | Level_1_Problem_Framing | Data dict …