Multiple Regression Analysis as a Comprehensive Tool to Model Flood Hazard in Sewersheds

Daniel Jato-Espino, Nora Sillanpää, Ignacio Andrés-Doménech, Jorge Rodriguez-Hernandez

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

Abstrakti

Flood modelling in urban areas is usually undertaken using stormwater tools, which are complex and time-consuming in terms of parametrization. To replace them, this research developed a methodology for predicting flooding probability in urban watersheds (sewersheds) through the modelling of peak flow rates from a set of watershed and sewer network-related factors relevant for the occurrence of floods. This was addressed through the stepped integration of Multiple Linear Regression (MLR), Multiple Nonlinear Regression (MNR) and Multiple Binary Logistic Regression (MBLR). A case study of a sewershed in Espoo (Finland) was used to validate the proposed approach and test it for future estimates, enabling the prediction of flooding probabilities under different Climate Change scenarios.
AlkuperäiskieliEnglanti
OtsikkoNew Trends in Urban Drainage Modelling
AlaotsikkoUDM 2018
ToimittajatGiorgio Mannina
KustantajaSpringer
Sivut571-575
ISBN (elektroninen)978-3-319-99867-1
ISBN (painettu)978-3-319-99866-4
DOI - pysyväislinkit
TilaJulkaistu - 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Urban Drainage Modelling - Palermo, Italia
Kesto: 23 syysk. 201826 syysk. 2018
Konferenssinumero: 11

Julkaisusarja

NimiGreen Energy and Technology
KustantajaSpringer International Publishing
ISSN (painettu)1865-3529
ISSN (elektroninen)1865-3537

Conference

ConferenceInternational Conference on Urban Drainage Modelling
LyhennettäUDM
Maa/AlueItalia
KaupunkiPalermo
Ajanjakso23/09/201826/09/2018

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