| Literature DB >> 31466155 |
Xin Fu1, Matthew E Hopton2, Xinhao Wang3, Haynes Goddard1, Haiqing Liu3.
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. Published by Elsevier B.V.Entities:
Keywords: Green infrastructure; Planning support system; Scenario planning; Stormwater management; Stormwater trading
Year: 2019 PMID: 31466155 PMCID: PMC6719726 DOI: 10.1016/j.scitotenv.2019.06.439
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963