Uncertainty, ambiguity and adaptive flood forecasting

Policy and Society

Volumn 35, Issue 2, 2016, Pages 125-136

  Wasson, R J ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Ambiguity; Flood forecasting; Organizational repsonses; Scenarios; Uncertainty

Indexed keywords

EID: 84992038048     PISSN: 14494035     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.polsoc.2016.06.002     Document Type: Article

References (58)

1. Anderson, T.L., Design of critical facilities without time-specific predictions. Sarawitz, D., Pielke, R.A. Jr., Byerly, R., (eds.) Prediction: Science, decision making, and the future of nature, 2000, Island Press, Washington, DC, 364–365.
2. Benfield, Aon., Pear-shaped phenomena: Low probability, high consequence events. 2013.
3. Baker, V.R., Paleoflood hydrology: Origin, progress, prospects. Geomorphology 101 (2008), 1–13.
4. 2 using a large ensemble of GCM simulations. Climate Dynamics 26 (2006), 489–511.
5. Benson, M.A., Thoughts on the design of design floods, in floods and droughts. Proceedings of the 2nd International Symposium in Hydrology, 1973, Water Resources Publication, Fort Collins, Colorado, 27–33.
6. Bewsher, D., Maddocks, J., Do we need to consider floods rarer than 1% AEP?. Horsham 2003 – HEALTHY Floodplains WEALTHY Future, 2003 6 pp. ( http://www.bewsher.com.au/pdf/CNF40P_1.pdf).
7. Buchanan, M., Ubiquity: The science of history or why the world is simpler than we think. 2000, Weidenfeld and Nicholson, London 230 pp.
8. Calder, I.R., The blue revolution: Land use and integrated water resources management. 1999, Earthscan, London 192 pp.
9. CapotondI, A., Guilyardi, E., Kirtman, B., Challenges in understanding and modeling ENSO. PAGES Newsletter 2013:2 (2013), 58–59 ( http://www.pages-igbp.org/download/docs/newsletter/2013-2/Full_references.pdf).
10. Clarke, L., Thinking about worst-case thinking. Sociological Inquiry 78 (2008), 154–161.
11. Clegg, B., Dice World: Science and life in a random universe. 2013, Icon, London 274 pp.
12. Collins, M., An, S.-I., Cai, W., Ganachaud, A., Guilyardi, E., Jin, F.-F., Markus Jochum, M., Lengaigne, M., Power, S., Timmermann, A., Vecchi, G., Wittenberg, A., The impact of global warming on the tropical Pacific Ocean and El Niño. Nature Geoscience 3 (2010), 391–397.
13. Dawdy, Prediction versus understanding (The Ven Te Chow Lecture). Journal of Hydrologic Engineering, 2007, January/February, 1–3.
14. Desa, M.N., Rakhecha, P.R., Probable maximum precipitation for 24-h duration over an equatorial region: Part 2-Johor, Malaysia. Atmospheric Research 84 (2007), 84–90.
15. Dooge, J.C.I., Looking for hydrologic laws. Water Resources Research 22:9 (1986), 46S–58S.
16. Douglas, E.M., Barros, A.P., Probable maximum precipitation using multifractals: Application in the Eastern United States. Journal of Hydrometeorology 4 (2003), 1012–1024.
17. Eash, D.A., Barnes, K.K., Veilleux, A.G., Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data though Water Year 2010. USGS Scientific Investigations Report 2013-5086., 2013.
18. Firestein, S., Ignorance: How it drives science. 2012, Oxford University Press 195 pp.
19. Francés, F., Botero, B.A., Probable maximum flood estimation using systematic and non-systematic information. Thorndycraft, V.R., Benito, G., Barriendos, M., Llasat, M.C., (eds.) Palaeofloods, historical floods and climatic variability: Applications in flood risk assessment (Proceedings of the PHEFRA Workshop, Barcelona, 16, 2002), 2003.
20. Francés, F., Salas, J.D., Boes, D.C., Flood frequency analysis with systematic and historical or palaeoflood data based on the two-parameter general extreme value models. Water Resources Research 30:6 (1994), 1653–1664.
21. Fuller, W.E., Flood flows. Transactions of the American Society of Civil Engineers 68 (1914), 564–618.
22. Graham, W.J., Should dams be modified for the probable maximum flood?. Journal of the American Water Resources Association 36:5 (2000), 953–963.
23. Gupta, V.K., Troutman, B.M., Dawdy, D.R., Towards a nonlinear geophysical theory of floods in river networks: An overview of 20 years of progress. Tsonis, A.A., Elsner, J.B., (eds.) Nonlinear dynamics in geosciences, 2007, Springer, 121-151.
24. Hood, C., Rothstein, H., Baldwin, R., The Government of risk-understanding risk regulation regimes. 2004, Oxford University Press, Oxford 232 pp.
25. Jakob, D., Smalley, R., Meighen, J., Xuereb, K., Taylor, B., Climate change and probable maximum precipitation. 2009, Bureau of Meteorology, Australian Government, Hydrometeorological Advisory Service, Water Division, Melbourne ( www.bom.gov.au/hydro/has/).
26. Kale, V., Baker, V., An extraordinary period of low-magnitude floods coinciding with the Little Ice Age: Palaeoflood evidence from Central and Western India. Journal of the Geological Society of India 68 (2006), 477–483.
27. Kiem, A.S., Franks, S.W., Kuczera, G., Multi-decadal variability of flood risk. Geophysical Research Letters, 30(2), 2003, 1035, 10.1029/2002GL015992 7 pp.
28. Knight, F.H., Risk, uncertainty, and profit. 1921, Hart, Schaffner & Marx; Houghton Mifflin Company, Boston, MA.
29. Koutsoyiannis, D., A probabilistic view of Hershfield's method for estimating probable maximum precipitation. Water Resources Research 35:4 (1999), 1313–1322.
30. Lasswell, H.D., The emerging conception of the policy sciences. Policy Sciences 1 (1970), 3–14.
31. Malamud, B., Petley, D., Lost in translation. Science and Technology 02 (2009), 164–167 ( http://www.kcl.ac.uk/sspp/departments/geography/people/academic/malamud/lostintranslation.pdf).
32. Malamud, B.D., Turcotte, D.L., The applicability of power-law frequency statistics to floods. Journal of Hydrology 322 (2006), 168–180.
33. Mauch, C., Pfister, C., (eds.) Natural disasters, cultural responses, 2009, Lexington Books, Plymouth 382 pp.
34. Millington, N., Das, S., Simonovic, S.P., The comparison of GEV, Log Pearson Type 3 and Gumbel distributions in the upper Thames River Watershed under global climate models. 2011, Department of Civil and Environmental Engineering, The University of Western Ontario, London, Ontario, Canada.
35. Milly, P.C.D., Betancourt, J., Falkenmark, M., Hirsch, R.M., Kundzewicz, Z.W., Lettenmaier, D.P., Stouffer, R.J., Stationarity is dead: Whither water management?. Science 319 (2008), 573–574.
36. Nanson, G.C., Croke, J.C., A genetic classification of floodplains. Geomorphology 4 (1992), 459–486.
37. Nobert, S., Krieger, K., Pappenberger, F., understanding the roles of modernity, science, and risk in shaping flood management. Natural Hazards and Earth System Science 14 (2015), 1921–1942.
38. Phillips, B.D., Fordham, M., Introduction. Phillips, B.D., Thomas, D.S.K., Fothergiill, A., Blinn-Pike, L., (eds.) Social vulnerability to disasters, 2010, CRC Press, Boca Raton 392 pp.
39. Phillips, B.D., Thomas, D.S.K., Fothergiill, A., Blinn-Pike, L., (eds.) Social vulnerability to disasters, 2010, CRC Press, Boca Raton 392 pp.
40. Pielke, R. Jr., Collateral damage from the death of stationarity. GEWEX, WRCP, 2009, 5–7 ( http://sciencepolicy.colorado.edu/admin/publication_files/resource-2725-2009.11.pdf).
41. Pilkey, O.H., Pilkey-Jarvis, L., Useless arithmetic: Why environmental scientists can't predict the future. 2007, Columbia University Press, New York 230 pp.
42. Plate, Flood risk and flood management. Journal of Hydrology 267 (2002), 2–11.
43. Sarewitz, D., Pielke, R.A. Jr., Prediction in science and policy. Sarawitz, D., Pielke, R.A. Jr., Byerly, R., (eds.) Prediction: Science, decision making, and the future of nature, 2000, Island Press, Washington, DC, 11–22.
44. Sayers, P., Li, Y., Galloway, G., Penning-Rowsell, E., Fuxin, S., Kang, W., Yiwei, C., Quesne, T.L.E., Flood risk management: A strategic approach. 2013, Asia Development Bank 202 pp.
45. Scheidegger, A.E., Physical aspects of natural catastrophes. 1975, Elsevier, Amsterdam 289 pp.
46. Schrader, S., Riggs, W.M., Robert, P., Smith, R.P., Choice over uncertainty and ambiguity in technical problem solving. Journal of Engineering and Technology Management 10 (1993), 73–99.
47. Silver, N., The signal and the noise: The art and science of prediction. 2012, Penguin, London 534 pp.
48. Sornette, D., Critical phenomena in natural sciences. 2001, Springer, New York.
49. Swanson, D., Barg, S., Tyler, S., Venema, H., Sanjay Tomar, S., Bhadwal, S., Nair, S., Roy, D., Drexhage, J., Seven tools for creating adaptive policies. Technological Forecasting & Social Change 77 (2010), 924–939.
50. Taleb, N.N., Antifragile: Things that gain from disorder. 2013, Penguin 519 pp.
51. USGS (United States Geological Survey), 100-year flood-it's all about chance. Haven't we already had one this century?. General Information Product, 2010, 106.
52. Verdon, D.C., Franks, S.W., Long-term behaviour of ENSO: Interactions with the PDO over the past 400 years inferred from paleoclimate records. Geophysical Research Letters, 33, 2006, L06712, 10.1029/2005GL025052 5 pp.
53. Vogel, R.M., Matalas, N.C., England, J.F. Jr., Castellarin, A., An assessment of exceedance probabilities of envelope curve. Water Resources Research, 43, 2007, W07403, 10.1029/2006WR005586.
54. Walker, W.E., Haasnoot, M., Kwakkel, J.H., Adapt or perish: A review of planning approaches for adaptation under deep uncertainty. Sustainability 5 (2013), 955–979.
55. Wasson, R.J., Sundriyal, Y.P., Chaudhary, S., Jaiswal, M.K., Morthekai, P., Sati, S.P., Juyal, N., A 1000-year history of large floods in the Upper Ganga catchment, central Himalaya, India. Quaternary Science Reviews 77 (2013), 156–166.
56. Wisner, B., Blaikie, P., Cannon, T., Davis, I., At risk: Natural hazards, people's vulnerability and disasters. 2004, Routledge, London 471 pp.
57. WMO (World Meteorological Organisation), Manual of extreme probable maximum precipitation. WMO-No. 1045. 1986 257 pp.
58. Woo, G., Calculating catastrophe. 2011, Imperial College Press, London 355 pp.