Loveridge, Melanie, Rahman, Ataur (2014) Quantifying uncertainty in rainfall–runoff models due to design losses using Monte Carlo simulation: a case study in New South Wales, Australia. Stochastic Environmental Research and Risk Assessment, 28 (8). 2149-2159 doi:10.1007/s00477-014-0862-y

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Reference Type	Journal (article/letter/editorial)
Title	Quantifying uncertainty in rainfall–runoff models due to design losses using Monte Carlo simulation: a case study in New South Wales, Australia
Journal	Stochastic Environmental Research and Risk Assessment
Authors	Loveridge, Melanie		Author
Authors	Rahman, Ataur		Author
Year	2014 (December)	Volume	28
Issue	8
Publisher	Springer Science and Business Media LLC
DOI	doi:10.1007/s00477-014-0862-ySearch in ResearchGate
	Generate Citation Formats
Mindat Ref. ID	9339924	Long-form Identifier	mindat:1:5:9339924:7
GUID	0
Full Reference	Loveridge, Melanie, Rahman, Ataur (2014) Quantifying uncertainty in rainfall–runoff models due to design losses using Monte Carlo simulation: a case study in New South Wales, Australia. Stochastic Environmental Research and Risk Assessment, 28 (8). 2149-2159 doi:10.1007/s00477-014-0862-y
Plain Text	Loveridge, Melanie, Rahman, Ataur (2014) Quantifying uncertainty in rainfall–runoff models due to design losses using Monte Carlo simulation: a case study in New South Wales, Australia. Stochastic Environmental Research and Risk Assessment, 28 (8). 2149-2159 doi:10.1007/s00477-014-0862-y
In	(2014, December) Stochastic Environmental Research and Risk Assessment Vol. 28 (8) Springer Science and Business Media LLC

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	Caballero, Wilfredo Llacer, Rahman, Ataur (2014) Application of Monte Carlo simulation technique for flood estimation for two catchments in New South Wales, Australia. Natural Hazards, 74. 1475-1488 doi:10.1007/s11069-014-1251-z
	Haddad, K., Rahman, A., Green, J. (2011) Design rainfall estimation in Australia: a case study using L moments and Generalized Least Squares Regression. Stochastic Environmental Research and Risk Assessment, 25 (6). 815-825 doi:10.1007/s00477-010-0443-7
	Haddad, Khaled, Rahman, Ataur (2011) Selection of the best fit flood frequency distribution and parameter estimation procedure: a case study for Tasmania in Australia. Stochastic Environmental Research and Risk Assessment, 25 (3). 415-428 doi:10.1007/s00477-010-0412-1
	Hamidi, Ali, Farnham, David J., Khanbilvardi, Reza (2018) Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study. Stochastic Environmental Research and Risk Assessment, 32 (8). 2293-2308 doi:10.1007/s00477-018-1563-8
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	Chou, Chien-Ming (2014) Complexity analysis of rainfall and runoff time series based on sample entropy in different temporal scales. Stochastic Environmental Research and Risk Assessment, 28 (6). 1401-1408 doi:10.1007/s00477-014-0859-6
	Aziz, K., Rahman, A., Fang, G., Shrestha, S. (2014) Application of artificial neural networks in regional flood frequency analysis: a case study for Australia. Stochastic Environmental Research and Risk Assessment, 28 (3). 541-554 doi:10.1007/s00477-013-0771-5
	Sivakumar, Bellie, Woldemeskel, Fitsum M., Puente, Carlos E. (2014) Nonlinear analysis of rainfall variability in Australia. Stochastic Environmental Research and Risk Assessment, 28 (1). 17-27 doi:10.1007/s00477-013-0689-y
	van Delft, G., El Serafy, G. Y., Heemink, A. W. (2009) The ensemble particle filter (EnPF) in rainfall-runoff models. Stochastic Environmental Research and Risk Assessment, 23 (8). 1203-1211 doi:10.1007/s00477-008-0301-z
	Niu, Jun, Sivakumar, Bellie (2014) Study of runoff response to land use change in the East River basin in South China. Stochastic Environmental Research and Risk Assessment, 28 (4). 857-865 doi:10.1007/s00477-013-0690-5

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Loveridge, Melanie, Rahman, Ataur (2014) Quantifying uncertainty in rainfall–runoff models due to design losses using Monte Carlo simulation: a case study in New South Wales, Australia. Stochastic Environmental Research and Risk Assessment, 28 (8). 2149-2159 doi:10.1007/s00477-014-0862-y

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