Climate change and growing urbanization are making stormwater management a priority, but to do so, it helps to understand the effects of gray-green stormwater control measures on the overall stormwater system. Grayer SCMs such as cisterns or underground detention structures are designed to remove, temporarily store, then release water. Greener SCMs are designed to promote infiltration, thus reducing runoff and pollution loads; reducing the stormwater burden for centralized sewer systems.

A new paper in the Journal of Sustainable Water in the Built Environment, “Life-Cycle Costing for Distributed Stormwater Control Measures on the Gray-Green Continuum: A Planning-Level Tool” by Jennifer Krieger and Emily Grubert, Ph.D, A.M.ASCE, presents a module that advances understanding of stormwater cost profiles using a process-based tool.

Abstract

Managing stormwater is an important element of sustainable water management. Access to multiple types of stormwater control measures (SCMs) along the gray-green continuum presents decision makers with flexibility in managing stormwater. Greener SCMs offer potential benefits like longer-term water retention, runoff reductions, and pollution reduction. Lack of access to context-specific life-cycle costs, however, particularly for less conventional SCMs, poses challenges for planners. To address this challenge, this paper presents a new Excel-based life-cycle cost tool that enables planners to evaluate internally consistent U.S. cost profiles for suites of SCMs using process-based quantity estimation covering materials, labor, equipment, energy, and environmental costs. The module includes 16 classes of distributed SCMs on the gray-green continuum, which can be assessed individually or in groups. The tool is preloaded with dynamic defaults but is designed to be highly customizable and includes built-in scenario analyses. Integration with the overall Integrated Decision Support Tool (i-DST) enables performance-based analysis. This paper describes the tool and presents example analyses.

Read the full paper in the ASCE Library: https://doi.org/10.1061/JSWBAY.0000933