Sizing Rainwater Harvesting Systems

Adequately sizing rainwater harvesting systems (RWH) is critical to optimizing their operation because undersizing results in systems that are unable to provide a sufficient, reliable source of water, while oversizing increases the capital costs incurred with limited marginal benefits and poses water quality risks.

Quantum Computers are promising tools for solving optimisation problems, specifically e.g. multi-objective optimization models that require finding the Pareto front. Depending on the formulation of the RWH problem, various quantum computing techniques could be used.

Rainwater harvesting (RWH) is a potential and sustainable alternative water source to solve water shortage problems, in particular, in developing countries. Rainwater harvesting systems (RWHS) can alleviate water pressure on centralized systems, minimize or delay rainfall runoff, fit relatively easily in both the centralized/decentralized infrastructure organization, and ensure uninterrupted, high-quality, water supply.