摘要：m.lti-objective optim.zation linked with an urban storm.ater m.del is used in this study to identify cost-effective low im.act developm.nt (LID) im.lem.ntation designs for sm.ll urbanizing watersheds. The epsilon-Non-Dom.nated Sorting Genetic Algorithm.II (ε-NSGAII) has been coupled with the US Environm.ntal Protection Agency’s Storm.ater m.nagem.nt m.del (SWm.) to balance the costs and the hydrologic benefits of candidate LID solutions. Our objective in this study is to identify the near-optim.l tradeoff between the total LID costs and the total watershed runoff volum. constrained by pre-developm.nt peak flow rates. This study contributes a detailed analysis of the costs and benefits associated with the use of green roofs, porous pavem.nt, and bioretention basins within a sm.ll urbanizing watershed inState College,Pennsylvania. Beyond m.lti-objective analysis, this paper also contributes im.roved SWm. representations of LID alternatives and dem.nstrates their usefulness for screening alternative site layouts for LID technologies.