fabsies/HydroSense-Kenya

Scientific Computing Capstone Project # HydroSense-Kenya **ICS 2207 Scientific Computing — Capstone Project** Smart Irrigation Decision-Support System for a Kenyan Demonstration Farm --- ## Project Overview HydroSense-Kenya uses 30 days of weather and soil sensor data from a demonstration farm to: - Model daily soil water balance across three crop zones (tomato, kale, maize) - Estimate evapotranspiration using an empirical formula - Implement numerical methods from scratch: root finding, finite differences, numerical integration, and linear system solving - Simulate soil moisture trajectories using Euler and Runge-Kutta (RK4) methods - Quantify irrigation uncertainty using Monte Carlo simulation (1000 scenarios) - Produce an optimised irrigation schedule that minimises water use while preventing crop stress --- ## Project Structure ``` hydrosense-kenya/ ├── README.md ← You are here ├── requirements.txt ← Python dependencies ├── AI_USE_LOG.md ← Documented AI tool usage │ ├── data/ │ ├── raw/ │ │ ├── weather_daily.csv ← 30-day weather records │ │ ├── soil_sensor_data.csv ← Soil sensor readings (3 zones × 30 days) │ │ └── crop_zone_parameters.csv ← Zone crop and soil parameters │ └── processed/ │ ├── weather_clean.csv ← Cleaned weather (generated by Level 4) │ └── soil_clean.csv ← Cleaned soil data (generated by Level 4) │ ├── 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_AI_Testing_Presentation.ipynb │ ├── src/ │ ├── numerical_methods.py ← All numerical methods (from scratch) │ └── simulation.py ← Euler, RK4, Monte Carlo, Optimisation │ ├── tests/ │ ├── test_numerical_methods.py ← 45+ tests for numerical methods │ ├── test_wa …