LEADER 03872nam 22005535 450 001 9910350342503321 005 20240705111254.0 010 $a981-13-3507-9 024 7 $a10.1007/978-981-13-3507-5 035 $a(PPN) 232961751 035 $a(CKB)4100000007204752 035 $a(MiAaPQ)EBC5611905 035 $a(DE-He213)978-981-13-3507-5 035 $a(EXLCZ)994100000007204752 100 $a20181206d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDecision Making with Uncertainty in Stormwater Pollutant Processes $eA Perspective on Urban Stormwater Pollution Mitigation /$fby Buddhi Wijesiri, An Liu, Prasanna Egodawatta, James McGree, Ashantha Goonetilleke 205 $a1st ed. 2019. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2019. 215 $a1 online resource (88 pages) 225 1 $aSpringerBriefs in Water Science and Technology,$x2194-7244 311 $a981-13-3506-0 327 $aUnderstanding uncertainty associated with stormwater quality modelling -- Pollutant build-up and wash-off processes variability -- Assessment of build-up and wash-off process uncertainty and its influence on stormwater quality modelling -- Case study ? uncertainty assessment of heavy metals build-up and wash-off processes -- Practical implications and recommendations for future research. 330 $aThis book presents new findings on intrinsic variability in pollutant build-up and wash-off processes by identifying the characteristics of underlying process mechanisms, based on the behaviour of various-sized particles. The correlation between build-up and wash-off processes is clearly defined using heavy metal pollutants as a case study. The outcome of this study is an approach developed to quantitatively assess process uncertainty, which makes it possible to mathematically incorporate the characteristics of variability in build-up and wash-off processes into stormwater quality models. In addition, the approach can be used to quantify process uncertainty as an integral aspect of stormwater quality predictions using common uncertainty analysis techniques. The information produced using enhanced modelling tools will promote more informed decision-making, and thereby help to improve urban stormwater quality. 410 0$aSpringerBriefs in Water Science and Technology,$x2194-7244 606 $aEnvironmental pollution 606 $aHydraulic engineering 606 $aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution$3http://scigraph.springernature.com/things/product-market-codes/U35040 606 $aWater Quality/Water Pollution$3http://scigraph.springernature.com/things/product-market-codes/212000 606 $aGeoengineering, Foundations, Hydraulics$3http://scigraph.springernature.com/things/product-market-codes/T23020 615 0$aEnvironmental pollution. 615 0$aHydraulic engineering. 615 14$aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution. 615 24$aWater Quality/Water Pollution. 615 24$aGeoengineering, Foundations, Hydraulics. 676 $a551.488 700 $aWijesiri$b Buddhi$4aut$4http://id.loc.gov/vocabulary/relators/aut$0933181 702 $aLiu$b An$c(Researcher on water pollution),$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aEgodawatta$b Prasanna$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMcGree$b James$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aGoonetilleke$b Ashantha$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910350342503321 996 $aDecision Making with Uncertainty in Stormwater Pollutant Processes$92100386 997 $aUNINA