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River Discharge, Rainfall and Flood Data Challenge Model Based Projections of Increased Flood Risk

Pall, P., Aina, T., Stone, D.A., Stott, P.A., Nozawa, T., Hilberts, A.G.J., Lohmann, D. and Allen, M.R. 2011. Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000. Nature 470: 382-385.
Bouziotas et al. presented a paper at the EGU in 2011 ( which concluded: "Analysis of trends and of aggregated time series on climatic (30-year) scale does not indicate consistent trends worldwide. Despite common perception, in general, the detected trends are more negative (less intense floods in most recent years) than positive." Similarly, Svensson et al. (2005) and Di Baldassarre et al. (2010) did not find systematical change neither in flood increasing or decreasing numbers nor change in flood magnitudes in their analysis.

These findings are also largely consistent with Kundzewicz et al. (2005) who report that "out of more than a thousand long time series made available by the Global Runoff Data Centre (GRDC) in Koblenz, Germany, a worldwide data set consisting of 195 long series of daily mean flow records was selected, based on such criteria as length of series, currency, lack of gaps and missing values, adequate geographical distribution, and priority to smaller catchments. The analysis of annual maximum flows does not support the hypothesis of ubiquitous growth of high flows. Although 27 cases of strong, statistically significant increase were identified by the Mann-Kendall test, there are 31 decreases as well, and most (137) time series do not show any significant changes (at the 10% level)." Continuing, Kundzewicz et al. conclude that "destructive floods observed in the last decade all over the world have led to record high material damage. The conventional belief is that the increasing cost of floods is associated with increasing human development on flood plains (Pielke & Downton, 2000)."

This sharply contrasted with the findings in the Pall et al. paper published in Nature in 2011 based on comparing multiple model runs with CO2 at 1900 and 2000 levels. Their analysis involved running a widely-used Met Office climate model thousands of times with slightly different starting conditions, and in finer-than-normal detail, simulating both the actual weather patterns seen over 2000 and those the country would have experienced at that time if atmospheric carbon dioxide had stayed at 1900 levels. Reported Pall et al., "we can never know for sure whether climate change caused any particular weather, but these results show it substantially increased the risk that the autumn 2000 floods - which damaged almost 10,000 properties and led to insured losses worth an estimated £1.3 billion - would happen." Additionally, they state that "in nine out of ten comparisons between the real climate and the hypothetical emissions-free climate, the presence of twentieth-century greenhouse gas emissions increased the risk of floods in England and Wales by 20 per cent or more. And in two thirds of cases, the increase was 90 per cent or more."

In the virtual world of the climate models, extremes of all kinds including flooding are shown to increase in frequency and are linked to man's contribution to increasing greenhouse gases. Model based scenarios of future climate allegedly indicate a likelihood of increased intense precipitation and flood hazard. However, numerous studies based on the observation of precipitation and river flow data to date provide no conclusive support for such claims.

Additional References
Bouziotas, D., Deskos, G., Mastrantonas, N., Tsaknias, D., Vangelidis, G., Papalexiou, S.M. and Koutsoyiannis, D. 2011. Long-term properties of annual maximum daily river discharge worldwide. European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, 13, Vienna, EGU2011-1439, European Geosciences Union.

Di Baldassarre, G., Montanari, A., Lins, H.F., Koutsoyiannis, D., Brandimarte, L. and Blöschl,G. 2010. Flood fatalities in Africa: from diagnosis to mitigation. Geophysical Research Letters 37: L22402

Kundzewicz, Z.W., D. Graczyk, D., Maurer,T., Przymusi?ska, I., Radziejewski, M., Svensson, C., and Szwed, M. 2005. Trend detection in river flow time-series: 1. annual maximum flow. Hydrological Sciences Journal 50: 797-810.

Pielke, R. A. and Downton, M.W. 2000. Precipitation and Damaging Floods: Trends in the United States, 1932-1997. Journal of Climate 13: 3625-3637

Svensson, C., Kundzewicz, Z.W. and Maurer, T. 2005. Trend detection in river flow series: 2 Flood and low - flow index series. Hydrological Sciences Journal 50: 811-824.

Archived 4 May 2011