References - Modelling Uncertainty in Flood Forecasting Systems - page 152

Burian, S.J. and Durrans (2002). Evaluation of an artificial neural network rainfall disag-
gregation model. Water Science and Technology, 45 (2), pp. 99-104, IWA Publishing.
Burnash, R.J.C., Ferrel, R.L. and McGuire, R.A. (1973). A general streamflow
simulation system—conceptual modelling for digital computers. Report by the Joint
Federal State River Forecasting Centre, Sacramento, CA.
Carpenter, T.M., Georgakakos, K.P. and Sperfslagea, J.A. (2001). On the parametric and
NEXRAD-radar sensitivities of a distributed hydrologic model suitable for operational
use. Journal of Hyrdology, 253, pp. 169-193.
Carroll, D.L. (1996). Chemical laser modelling with genetic algorithms. American
Institute of Aeronautics and Astronautics (AIAA) Journal, 34 (2), pp. 338-346.
Caselton, W.F. and Luo, W. (1992). Decision Making with Imprecise Probabilities:
Dempster-Shafer Theory and Application. Water Resources Research,
28 (12), pp. 3071-3083.
Chang, C.-H., Tung, Y.-K. and Yang, J.-C. (1994). Monte Carlo Simulation for
Correlated Variables with Marginal Distributions. Journal of Hydraulic Engineering,
ASCE, 120 (3), pp. 313-331.
Chen, H.-K., Hsu, W.-K. and Chiang, W.-L. (1998). A comparison of vertex method with
JHE method. Fuzzy Sets and Systems, 95, pp. 201-214.
Chow, V.T., Maidment, D.R., and Mays, L.W. (1988). Applied Hydrology. McGraw-Hill,
New York, NY.
Cluckie, I.D. and Collier, C.G. (1991). Hydrological Applications of Weather Radar. Ellis
Horwood Ltd., England.
Collotte, P., Erlich, M. and Weets, G. (2003). OSIRIS Project Objectives and
Achievements. In Proc., OSIRIS Workshop: Flood Events: Are We Prepared, March
2003, Berlin, Germany, pp. 7-15.
Crawford, N.H., and Linsley, R.K. (1966). Digital simulation in hydrology: Standford Water-
shed Model Mark IV. Dept. of Civil Engineering, Tech. Rep. 39, Standford University,
Standford.
Cullen, A.C. and Frey, H.C. (1999). Probabilistic techniques in exposure assessment: A hand
book for dealing with variability and uncertainty in models and inputs. Plenum Press, New
York.
Cunge, J.A., Holly, F.M. and Verwey, A. (1980). Practical Aspects of Computational
River Hydraulics. Pitman Publishing Limited.
Dartmouth Flood Observatory (2003). Global Active Archive of Large Flood Events. Re-
trieved 10 October 2003 http://www.dartmouth.edu/%7Efloods/Archives /index.html.
Dawson, C.W. and Wilby, R. (1998). An artificial neural network approach to rainfall-
runoff modelling. Hydrological Sciences Journal, 43 (1), pp. 47-66.
De Finetti, B. (1974). Theory of Probability: A critical introductory treatment, Volume 1.
John Wiley & Sons.
Demspster, A.P. (1969). Upper and lower probability inferences for families of hypothe-
ses with monotone density rations. Annals of Mathematical Statistics, 40(3), pp. 953-969.