Galen Newman, Youjung Kim, Karishma Joshi, Jiali Liu
{"title":"Integrating Prediction and Performance Models into Scenario-based Resilient Community Design.","authors":"Galen Newman, Youjung Kim, Karishma Joshi, Jiali Liu","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Urban expansion can worsen climate change conditions and enlarge hazard zones. Sea level rise due to climate change makes coastal populations more susceptible to flood risks. The use of land change prediction modelling to inform scenario-based planning has been shown to help increase capabilities when dealing with uncertainties in urbanization such as urban growth and flood risk, when compared to singular comprehensive plans. This research uses the Land Transformation model to predict three different urban growth scenarios for Tampa, FL to determine how effective the current comprehensive plan is in adapting urban growth to decreasing flood risk and pollutant load. To achieve this, the research develops master plans according to each scenario then assesses their probable impact using the Long-Term Hydrologic Impact Analysis Low Impact Development Spreadsheet as a performance model. Findings show that the current future land use plan for Tampa, while it appears to be better than current patterns of development, has higher flood exposure, stormwater runoff, and pollutant discharge that current conditions but more than a purely resilient approach to future growth.</p>","PeriodicalId":93116,"journal":{"name":"Journal of digital landscape architecture : JoDLA","volume":"5 ","pages":"510-520"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7448720/pdf/nihms-1617538.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of digital landscape architecture : JoDLA","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Urban expansion can worsen climate change conditions and enlarge hazard zones. Sea level rise due to climate change makes coastal populations more susceptible to flood risks. The use of land change prediction modelling to inform scenario-based planning has been shown to help increase capabilities when dealing with uncertainties in urbanization such as urban growth and flood risk, when compared to singular comprehensive plans. This research uses the Land Transformation model to predict three different urban growth scenarios for Tampa, FL to determine how effective the current comprehensive plan is in adapting urban growth to decreasing flood risk and pollutant load. To achieve this, the research develops master plans according to each scenario then assesses their probable impact using the Long-Term Hydrologic Impact Analysis Low Impact Development Spreadsheet as a performance model. Findings show that the current future land use plan for Tampa, while it appears to be better than current patterns of development, has higher flood exposure, stormwater runoff, and pollutant discharge that current conditions but more than a purely resilient approach to future growth.