Evaluation of evolutionary algorithms for the optimization of storm water drainage network for an urbanized area

Kumar, Satish; Kaushal, D. R.; Gosain, A. K.

doi:10.1007/s11600-018-00240-8

Artykuł - szczegóły

Tytuł artykułu

Evaluation of evolutionary algorithms for the optimization of storm water drainage network for an urbanized area

Autorzy

Kumar Satish , Kaushal D. R. , Gosain A. K.

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-018-00240-8

Warianty tytułu

Języki publikacji

Abstrakty

The studies pertaining to urban storm water drainage system have picked up importance lately in light of pluvial flooding. The flooding is mostly due to urban expansion, reduction in infiltration rate and environmental change. In order to minimize flooding, hydrologists are using conceptual rainfall–runoff models as a tool for predicting surface runoff and flood forecasting. Manual calibration is often a tedious process because of the involved subjectivity, which makes the automatic approach more preferable. In this study, three evolutionary algorithms (EAs), namely SFLA, GA and PSO, were used to calibrate SWMM parameters for the two study areas of the highly urbanized catchments of Delhi, India. The work incorporates auto-tuning of a widely used SWMM, via internal coupling of SWMM with all three EAs in MATLAB environment separately. Results were tested using statistical parameters, i.e., Nash–Sutcliffe efficiency (NSE), Percent Bias (PBIAS) and root-mean-square error–observations standard deviation ratio (RSR). GA results were in good agreement with the observed data in both the study area with NSE and PBIAS values lying between 0.60 and 0.91, and 1.29 and 7.41%, respectively. Also, RSR value was near zero, indicating reasonably good model performance. Subsequently, the model reasonably predicted the flooding hotspots that should be controlled to prevent any possible inundation of the surrounding areas. SFLA results were also promising, but better than PSO. Thus, the approach has demonstrated the potential use and combination of single-objective optimization algorithms and hydrodynamic models for assessing the risk in urban storm water drainage systems, providing valuable information for decision-makers.

Słowa kluczowe

storm water drainage flooding urbanization evolutionary algorithm optimization sensitivity analysis

kanalizacja deszczowa powódź urbanizacja algorytm ewolucyjny optymalizacja analiza wrażliwości

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2019

Tom

Vol. 67, no. 1

Strony

149--165

Opis fizyczny

Bibliogr. 90 poz.

Twórcy

autor

Kumar Satish

satish.kumar140@gmail.com

Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

autor

Kaushal D. R.

kaushal@civil.iitd.ac.in

Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

autor

Gosain A. K.

gosain@civil.iitd.ac.in

Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-841fd8d7-2a88-49bd-bb12-fd2c7a0cb6ed