Runcheng Precise Urban Irrigation System

Problem Context

Urban green-space irrigation is often based on operator experience, which can lead to overwatering, wasted water, or under-irrigation that stresses plants. Irrigation needs vary widely by climate zone, soil type, season, and daily weather, and manual planning rarely combines temperature, humidity, wind, rainfall, plot area, vehicle routes, and execution records into one auditable workflow.

How the skill works

The skill turns irrigation planning into an inspectable engineering pipeline:

• Input city and site data: Configure the city, climate zone, and soil type in config.json, then import green-space zones, vehicles, and water sources from CSV files.
• Estimate water demand: Use FAO-56 ET₀ evapotranspiration, plant coefficients, and soil correction factors to produce a 15-day daily irrigation plan.
• Apply decision rules: Handle winter shutdown, frost protection, heat-wave increases, high-wind adjustments, and reduced irrigation in wetter regions, with 24 solar-term seasonal guidance.
• Close the execution loop: Optimize each vehicle's route and travel distance, record actual completion, and generate plan-versus-actual comparisons, water savings, and cost reviews.

Boundaries and notes

This skill fits China-based municipal landscaping, urban greening, and maintenance teams, especially those with plot, vehicle, water-source, and weather data. It can be tested with sample data or demo mode, but production planning still requires reliable weather access and local operational records. Local files such as config.local.json that contain API keys should not be committed to public repositories.