Probabilistic green infrastructure cost calculations using a phased life cycle algorithm integrated with uncertainties

Abstract

Abstract Green infrastructure (GI) is often considered a cost-effective approach to urban stormwater management. Though various models have been created to simulate the life cycle cost (LCC) and present value (PV) of GI investments, decision-support tools are still few. This paper introduces a probabilistic GI cost estimation algorithm built into the Low Impact Development Rapid Assessment (LIDRA) model. This algorithm tracks annual and cumulative costs associated with the construction, operation and maintenance (O&M), and ultimate replacement of GI systems. In addition, the algorithm accounts for uncertainties in cost drivers, such as a GI's useful life (until replacement), capital and annual O&M costs, inflation, and interest rates. Net present value (NPV) is used to normalize future money flows and cumulative costs of different GI investment scenarios into a comparable current year cost equivalent. Demonstrated at the block scale, the results of the LIDRA algorithm are compared to an MS Excel-based computation of average costs. Variations of uncertainties are then integrated and further explored using an alternative implementation rate. This algorithm is a way to evaluate GI costs considering physical, socioeconomic and life cycle dimensions.