Optimizing Green Infrastructure Implementation with a Land Parcel-Based Credit Trading Approach on Different Spatial Scales

Implementing green infrastructure (GI) to reach certain stormwater reduction goal may be a challenging task for some land parcels (LP) in urban areas due to their unfavorable landuse conditions. In this paper, we proposed a capacity/credit trading (CT) method that allows city LPs with favorable landuse conditions to build more GIs than required and trade their extra capacity as monetary credit to LPs with building difficulties; this will allow the whole city area to achieve general stormwater mitigation goal in a more cost effective way. We investigated the effects of CT on cost reduction and (re)distribution of GIs among LPs over different trading scales, and an optimization model was constructed on the basis of different zoning of CT. The model was applied to determine GI distributions among individual LPs in order to minimize the overall cost. With a case study, we demonstrated that, without CT, requiring individual LPs to meet the mitigation goal on their own can be costly, and the cost grows with implementation pressure from storm runoff reduction; engaging CT for GI implementation reduced the cost significantly even at a small trading scale. Our analysis showed that, cost increment for GI implementation can be cut in half by performing CT at a spatial scale of 500–600 m that includes 5–6 LPs; when the CT trading zone is expanded to 1200 m that include 17 LPs, the cost increment can be cut by 3/4. The benefit of CT is obtained by re-distributing GIs among different LPs; but the spatial scale of CT needs to be limited to preserve the virtue of onsite treatment of stormwater with GIs. The proposed approach can be used to take advantage of the city landuse diversities to lower the overall cost of GI implementation for stormwater management.