Theme for 2007:
Estimating Extreme Floods in California's Central Valley
California State University, Sacramento
Special Recognition Award
The 2007 Special Recognition Award was presented to Maurice D. Roos, P.E.. See the award language, some biographical information, and the presentation on the Symposium's Maurice D. Roos award page.
A Half Century of Watching Floods
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The purpose of this talk is to present some personal observations on the big floods we have seen in northern California the past half century or so starting with 1950. There are at least three types of floods in California — winter season general floods, spring and early summer snowmelt floods, and strong thunderstorm floods. A personal look at the big floods of 1950, 1955, 1964, 1969, 1983, 1986, 1995, and 1997 and seeing the floods getting larger over the years. Flood forecasting has improved greatly over the past 30 years, largely from three factors: computer advances, data gathering, especially with the California Data Exchange Center (CDEC), and quantitative precipitation forecasts.
Extreme Flood Concepts, an Historical Perspective
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The concept of what constitutes an 'extreme flood' depends on the perspective of those developing or espousing their application. In early times, the concept was generally associated with the largest floods that had occurred locally or at least within the nearby region. Over time, great floods impacted the nation, policies for national investment in water management infrastructure evolved, and the desire to wisely manage the nation's floodplains stimulated the need for more refined and purposespecific definitions of and methods for estimating extreme floods. Players in this arena include a better informed public and stakeholders, policy makers, hydrologic scientists, engineers, statisticians, and the occasional soothsayer. This presentation will offer a working definition of 'extreme floods', highlight notable flood, legislation, and policy happenings that have resulted in major focus on particular concepts of extreme events, and conclude with some reflections on current ideas and thoughts on the way forward.
Flood Hydroclimatology: Insights into Mixed Flood Populations
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Flood hydroclimatology (Hirschboeck 1988) is the analysis of flood events within the context of their history of variation in magnitude, frequency, seasonality — over a relatively long period of time — and analyzed within the spatial framework of changing combinations of meteorological causative mechanisms. It was first proposed in the late 1980s as a conceptual framework within which to think about the underlying physical reasons for flood variations, how these might be linked to climate variability, and why the most extreme flood events and outliers in the upper tails of some flood distributions continue to confound practitioners of standard flood frequency analysis (FFA). Flood hydroclimatology challenges the underlying "iid" assumption that flood peaks are independently, identically distributed by re-examining flood time series to arrive at a mechanistic understanding of long-term flooding variability and its probabilistic representation based on hydroclimatically defined mixed populations. Strengths and weaknesses of the approach are illustrated with an example from Arizona gaging stations and the potential for use of the approach to address Central Valley FFA is addressed.
Flood hydroclimatology research to date has shown that:
- In regions where floods are produced by several types of meteorological events, different storm types may exhibit unique probability distributions.
- Unusually large floods in drainage basins of all sizes are likely to be associated with well defined circulation anomalies — hence such features are good candidates for mixed distribution categories.
- The interaction between storm properties and drainage basin properties may result in different combinations of mixed distributions.
- In the largest and most extreme floods studied, persistence was always a factor and served to bridge meteorological and climatological time scales.
Some implications of the approach are:
- The distributions of key subgroups may be better for estimating the probability and cause of extremely rare floods than the overall frequency distribution of the entire flood series.
- To preserve spatial homogeneity, basins can be grouped according to how their floods respond to different types of mechanisms and circulation patterns.
- The conceptual framework of climate-driven, time-shifting means, variances and/or mixed distributions provides a useful explanation for non-stationarity in flood times series which challenges the iid assumption.
- To address how flood frequencies might respond to a changing climate, such changes can be conceptualized as time-varying atmospheric circulation regimes that generate a mix of shifting streamflow probability distributions.
Extrapolating Frequency Curves, or Not
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[Abstract not available]
Pitfalls of Risk Analysis In Designing Flood Control Projects
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[Abstract not available]
Improved Tools for Estimating Extreme Floods
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Extreme precipitation information is of interest for a variety of purposes, including public safety, water supply, dam design and operation, and transportation planning. Two common parameters calculated for extreme precipitation purposes are probable maximum precipitation (PMP) and intensity-durationfrequency (IDF). The definition of PMP is "theoretically, the greatest depth of precipitation for a given duration that is physically possible over a given area at a particular geographical location at a certain time of the year." PMP estimates are used to calculate the probable maximum flood (PMF), which in turn is used to evaluate the adequacy of hydraulic structures. IDF calculations are used in a variety of precipitation-related tasks, including PMP.
Recent advances in geographical information systems (GIS) technology have enabled development new opportunities for mapping extreme precipitation. Another important development has been PRISM (Parameter-elevation Regressions on Independent Slopes Model), an expert system that uses point data and a digital elevation model (DEM) to generate gridded estimates of climate parameters. PRISM is wellsuited to mountainous regions, because the effects of terrain on climate play a central role in the model's conceptual framework. It also works quite well in data-sparse regions.
In addition to improved mapping and geographical analysis techniques, improvements have been made in statistical approaches. One exciting development has been "regional frequency analysis" (RFA), a set of statistical techniques based on work by Hoskins and Wallace. RFA works especially well in data sparse regions by "trading space for time": data from several sites are used in estimating event frequencies at any one site using a method called "L-moments." L-moments form the basis of an elegant mathematical theory in their own right, and can be used to facilitate the estimation process in regional frequency analysis. L-moment methods are demonstrably superior to those that have been used previously, and are now being adopted by major organizations worldwide.
Comparing Statistical Approaches to EstimatingFloods
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Results from computing the flood frequency on the American River using 3-day discharge data using different methods is shown. The analyses were made only to provide comparisons between the various methods and not make any recommendations as to the most appropriate flood flow frequency method to use. Extrapolations are made for the 100-year, 200-year, and 500-year floods.
Some Ideas on Estimating the Reasonably Foreseeable Flood
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We have heard a lot about statistical processes and risk. I think we need a simpler method to explain to folks what we are trying to accomplish in flood protection and then in measuring how well our designed systems are working. I would propose that we go back to an earlier concept, the standard project flood (SPF), which is modeled after recent events, which have been measured in the region. I am not sure we should call it that, because the Corps' definition of the SPF is too close to that of the probably maximum flood (PMF). So maybe we call it the Maximum Regional Storm, MRS, or simply the Reasonably Foreseeable Flood, RFS. How would we estimate such a flood? For major rivers it would be transposing the largest measured event in the region.
Looking Toward an Urban Flood Standard
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The California legislature and the Congress are considering the adoption of new approaches to size floodwater management projects and thresholds for floodplain management regulations. Current "level of protection" assessment techniques conflate a series of facts and assessments into one number, obscuring the important individual aspects of system performance or floodplain characteristics — or methodological uncertainties. Potential flood magnitudes faced by communities may be better addressed by methodologies designed to provide realistic estimates of potential worst-case floods rather than flood magnitude "prediction" based on flood-magnitude probability distributions that rely on extrapolating existing stream-gage data. Uncertainties in either system performance, hydraulics, hydrology, topography, or channel stability also need to be addressed by extending floodplainmanagement regulations to areas behind levees or that could be flooded by reasonably foreseeable floods. Scientific and governmental attention to refining both the "level of protection" and "worst-case" flood methodologies is long overdue.
How Do We Estimate the Size of the "Reasonably Foreseeable Flood" From Which Urban Areas Should Be Protected?
- American River Watershed Institute
- California State University, Sacramento — College of Natural Sciences and Mathematics
- EDAW, Inc.
- El Dorado Irrigation District
- Jones and Stokes
- Local Government Commission
- MBK Engineers
- Placer County Water Agency
- Regional Water Authority/Sacramento Groundwater Authority
- Sacramento Region Water Forum
- Sierra College Natural History Museum
- U.S. Bureau of Reclamation