Population index flood method for regional frequency analysis

Sveinsson, Óli G. B.; Boes, Duane C.; Salas, José D.

doi:10.1029/2001wr000321

Cited by 55 publications

(63 citation statements)

References 7 publications

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“…Various limitations of regional analysis have been raised right from the start of its use [26], including the distortion that arises from dividing the peak flows by their sample mean instead of the unknown population mean [90,91], spatial heterogeneity of regions (i.e., the distribution of scaled flows not being identical across sites [61]), and spatial dependence of high flows [41,90]. Nevertheless, it is rare that regional analysis has been expressed in terms of a formal statistical model (e.g., including explicit assumptions about how the parameters of the GEV distribution vary within the region).…”

Section: Regional Analysismentioning

confidence: 99%

Statistics of extremes in hydrology

Katz¹,

Parlange²,

Naveau³

2002

Advances in Water Resources

1,402

1,108

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The statistics of extremes have played an important role in engineering practice for water resources design and management. How recent developments in the statistical theory of extreme values can be applied to improve the rigor of hydrologic applications and to make such analyses more physically meaningful is the central theme of this paper. Such methodological developments primarily relate to maximum likelihood estimation in the presence of covariates, in combination with either the block maxima or peaks over threshold approaches. Topics that are treated include trends in hydrologic extremes, with the anticipated intensification of the hydrologic cycle as part of global climate change. In an attempt to link downscaling (i.e., relating large-scale atmosphereocean circulation to smaller-scale hydrologic variables) with the statistics of extremes, statistical downscaling of hydrologic extremes is considered. Future challenges are reviewed, such as the development of more rigorous statistical methodology for regional analysis of extremes, as well as the extension of Bayesian methods to more fully quantify uncertainty in extremal estimation. Examples include precipitation and streamflow extremes, as well as economic damage associated with such extreme events, with consideration of trends and dependence on patterns in atmosphere-ocean circulation (e.g., El Niñ no phenomenon).

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Section: Regional Analysismentioning

confidence: 99%

Statistics of extremes in hydrology

Katz¹,

Parlange²,

Naveau³

2002

Advances in Water Resources

1,402

1,108

View full text Add to dashboard Cite

show abstract

“…The lack of observed data for distribution fitting of extreme values in hydrological sciences can be overcome by using regional approaches, including index value approach (Darlymple, 1960;Sveinsson et al, 2001). This implies that values of a hydrological variable that are scaled, i.e.…”

Section: T Imentioning

confidence: 99%

“…Robson and Reed, 1999) or by a site to site location parameter (e.g. Sveinsson et al, 2001). Here, the mean of the single site distribution is used, estimated by the sample average of the observed values at the specific site i, defined as…”

Section: Index Value Approachmentioning

confidence: 99%

Regional evaluation of three day snow depth for avalanche hazard mapping in Switzerland

Bocchiola

Janetti

Gorni

et al. 2008

Nat. Hazards Earth Syst. Sci.

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Abstract. The distribution of the maximum annual three day snow fall depth H 72 , used for avalanche hazard mapping according to the Swiss procedure (Sp), is investigated for a network of 124 stations in the Alpine part of Switzerland, using a data set dating back to 1931. Stationarity in time is investigated, showing in practice no significant trend for the considered period. Building on previous studies about climatology of Switzerland and using an iterative approach based on statistical tests for regional homogeneity and scaling of H 72 with altitude, seven homogenous regions are identified. A regional approach based on the index value is then developed to estimate the T -years return period quantiles of H 72 at each single site i, H 72i (T ). The index value is the single site sample average µ H 72i . The dimensionless values of H * 72i =H 72i /µ H 72i are grouped in one sample for each region and their frequency of occurrence is accommodated by a General Extreme Value, GEV, probability distribution, including Gumbel. The proposed distributions, valid in each site of the homogeneous regions, can be used to assess the T -years return period quantiles of H * 72i . It is shown that the value of H 72i (T ) estimated with the regional approach is more accurate than that calculated by single site distribution fitting, particularly for high return periods. A sampling strategy based on accuracy is also suggested to estimate the single site index value, i.e. the sample average µ H 72i , critical for the evaluation of the distribution of H 72i . The proposed regional approach is valuable because it gives more accurate snow depth input to dynamics models than the present procedure based on single site analysis, so decreasing uncertainty in hazard mapping procedure.

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“…As an example, Darlymple (1960) and Hosking and Wallis (1993) used the observed sample mean as estimator of the index flood, Robson and Reed (1999) suggested the observed median (middle ranking value in the series of annual maximum flood), while Sveinsson et al (2001) propose, as index flood, the location parameter determined on a site to site basis. In the framework of the Flood Evaluation (VAPI) project, carried out by the National Group for Prevention from Hydrological Disasters (GNDCI) supported by the National Research Council (CNR) of Italy, flood peak estimation guidelines were provided for the whole of Italy and the index flood is represented by the expected value of the maximum annual flood peak (De Michele and Rosso, 2001) [ ]…”

Section: General Remarks On Index Flood Estimationmentioning

confidence: 99%

Review of recent advances in index flood estimation

Bocchiola

Michele

Rosso

2003

Hydrol. Earth Syst. Sci.

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Index flood estimation for regional flood frequency analysis needs to be based on the information available. The most appropriate method depends on the specific application and its choice requires a problem-oriented analysis. This paper presents a simple theoretical framework to deal with index flood estimation for a specific river site. The methodological approaches available for the purpose are reviewed. For each, the information required is specified and the reliability of the estimate, particularly desirable in risk analysis and management, is discussed. Where flood observations are lacking, indirect estimation must be undertaken using scenarios including those commonly met in hydrological practice; generally, these depend on the amount and type of information available. For each scenario, the methodologies are outlined, in order of the expected degree of complexity. After a guided analysis, an investigator can adopt the method providing the best tradeoff between effort in collecting and handling data and the resultant reliability which can be expected.

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Population index flood method for regional frequency analysis

Cited by 55 publications

References 7 publications

Statistics of extremes in hydrology

Statistics of extremes in hydrology

Regional evaluation of three day snow depth for avalanche hazard mapping in Switzerland

Review of recent advances in index flood estimation

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