A Knowledge-Based Engineering System for the Planning of Networked Rainwater Harvesting and Distribution Systems

Rainwater harvesting attracts growing interest from the field of municipal planning. When considering a rainwater system as design object, questions include whether is designed for single property or local water network serving multiple properties, what allows inclusion buffer tanks and resource balancing among participants in network, how to size tanks, robust face changing demands. Knowledge-based engineering provides methods tool set such planning objects. For this article, authors applied techniques based on model-based resource-based configuration Bayesian decision networks propose knowledge-based residential, networked distribution systems. This enables designers investigate effects different catchment areas, adjust minimize storage tank sizes grid evaluate their effect individual harvest exchange with central buffer, demands within neighborhood detailed consumer model also over time, test sensitivities sinks sources grid. urban planners, offers possibility, example, make obligations housing construction refurbishment settlements.