A runoff trading system to meet watershed-level stormwater reduction goals with parcel-level green infrastructure installation.
Ontology highlight
ABSTRACT: Green infrastructure (GI) has been recommended widely to reduce runoff from the built environment. However, reliance on public land for GI implementation could cause a heavy financial burden on local governments. Although economic incentives and market-based mechanisms may encourage public participation in managing stormwater by installing GI on private parcels, a runoff trading market has not been fully developed in practice. To establish a market, in part, requires a watershed-based planning framework and fully informed parcel owners in regard to tradable credits, costs, and benefits. We propose a scenario-based Stormwater Management Planning Support System for Trading Runoff Abatement Credits (SMPSS-TRAC) to facilitate the calculation and allocation of stormwater runoff abatement credits in order to assist the decision-making of GI investment. We apply SMPSS-TRAC to a watershed located in Hamilton County, Ohio, USA and develop five scenarios representing increasing use of GI. We test the scenarios under a 5-year rainfall intensity and set a cap of runoff for each scenario at a level that is equal to the runoff from an undeveloped status (1.03-inch runoff depth for the watershed). With the proposed SMPSS-TRAC, the watershed authority could encourage all parcel owners to install suitable GI or purchase credits from the market. When detention basins are needed to meet a stated goal, the watershed authority would build them on vacant lots and share costs with all parcels within the same sub-catchment. The last scenario with four types of GI installed, shows that the watershed reaches market equilibrium and generates 15,358?m3 credit surplus. SMPSS-TRAC has the potential for including multiple stakeholders' preferences and concerns in searching for preferable scenarios.
SUBMITTER: Fu X
PROVIDER: S-EPMC6719726 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
ACCESS DATA