@article { ISI:000327432500062,
	title = {A Bayesian extreme value analysis of debris flows},
	journal = {WATER RESOURCES RESEARCH},
	volume = {49},
	number = {10},
	year = {2013},
	month = {OCT},
	pages = {7009-7022},
	publisher = {AMER GEOPHYSICAL UNION},
	type = {Article},
	address = {2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA},
	abstract = {Debris flows carry a tremendous potential for physical destruction as well as a threat to human lives. Quantitative analysis of their frequency and magnitude relation is key to the development of mitigation measures to reduce hazard and risk. Yet, the data available for such analysis are typically very sparse, leading to point estimates for return levels that are too imprecise to be of practical value. The aim of the paper is to demonstrate how additional sources of information, in particular, expert judgment which uses physical causes and the size of the active area producing loose sediments, can be incorporated to produce more precise estimates with a smaller upper endpoint of interval estimates of extreme return levels. A Bayesian framework for extreme value analysis is used. We provide a rationale for the prior choice and discuss how its parameters can be elicited from the expert{\textquoteright}s knowledge. A case study of debris flows at Capricorn Creek in Western Canada is used to illustrate our methodology.},
	keywords = {Bayesian statistics, debris flows, expert judgment, extreme value analysis, frequency-magnitude relation, informative prior},
	issn = {0043-1397},
	doi = {10.1002/wrcr.20494},
	author = {Nolde, Natalia and Joe, Harry}
}
@article { ISI:000327432500062,
	title = {A Bayesian extreme value analysis of debris flows},
	journal = {Water Resources Research},
	volume = {49},
	number = {10},
	year = {2013},
	month = {OCT},
	pages = {7009-7022},
	publisher = {Amer Geophysical Union},
	type = {Article},
	abstract = {Debris flows carry a tremendous potential for physical destruction as well as a threat to human lives. Quantitative analysis of their frequency and magnitude relation is key to the development of mitigation measures to reduce hazard and risk. Yet, the data available for such analysis are typically very sparse, leading to point estimates for return levels that are too imprecise to be of practical value. The aim of the paper is to demonstrate how additional sources of information, in particular, expert judgment which uses physical causes and the size of the active area producing loose sediments, can be incorporated to produce more precise estimates with a smaller upper endpoint of interval estimates of extreme return levels. A Bayesian framework for extreme value analysis is used. We provide a rationale for the prior choice and discuss how its parameters can be elicited from the expert{\textquoteright}s knowledge. A case study of debris flows at Capricorn Creek in Western Canada is used to illustrate our methodology.},
	keywords = {Bayesian statistics, debris flows, expert judgment, extreme value analysis, frequency-magnitude relation, informative prior},
	issn = {0043-1397},
	doi = {10.1002/wrcr.20494},
	author = {Nolde, Natalia and Joe, Harry}
}
