ai-patrick/HydroSense-Kenya

# HydroSense-Kenya **A Scientific Computing System for Smart Irrigation, Water Balance Simulation, and Climate-Aware Decision Support** *ICS 2207 — Scientific Computing Capstone Project, February–May 2026* --- ## Scientific Objective Given daily weather and soil-sensor data from a Kenyan demonstration farm, HydroSense-Kenya answers: > *How can we model water availability, estimate water deficit, simulate future soil moisture under rainfall uncertainty, and recommend an efficient irrigation plan that minimises water use without exposing crops to moisture stress?* The system implements the discrete water balance equation: ``` S(t+1) = S(t) + R(t) + I(t) − ET(t) − D(t) ``` with a simplified evapotranspiration model: ``` ET = max(0, 0.12·T + 0.35·W + 2.4·Solar − 0.025·H) ``` ## Repository Structure ``` HydroSense-Kenya/ ├── data/ │ ├── raw/ # Original sensor datasets │ │ ├── weather_daily.csv │ │ ├── soil_sensor_data.csv │ │ └── crop_zone_parameters.csv │ └── processed/ # Cleaned datasets │ └── cleaned_irrigation_dataset.csv ├── notebooks/ # Six-level analysis progression │ ├── 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/ # Computation engine │ ├── __init__.py │ ├── data_cleaning.py # Validation, imputation, outlier detection │ ├── numerical_methods.py # Root-finding, integration, linear systems │ ├── simulation.py # Water balance ODE, Monte Carlo engine │ ├── optimization.py # Irrigation scheduling optimiser │ └── visualization.py # Publication-quality figures ├── tests/ # pytest-compatible test suite │ ├── test_root_finding.py # 14 tests │ ├── tes …