Review of recent advances in index flood estimation

Bocchiola, Daniele; Michele, Carlo De; Rosso, Renzo

doi:10.5194/hess-7-283-2003

Cited by 71 publications

(65 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Other conceptual approaches have been also proposed, based on an analytical derivation of the probability distribution of floods (e.g. Becciu et al, 1993;Brath et al, 2001;Bocchiola et al, 2003). The index flood estimation method based on the rational formula implicitly assumes that the average value of the annual maximum peak discharges is related to the average value of the annual maximum rainfall depth within a critical time interval, which is assumed equal to a characteristic time scale of the catchment response.…”

Section: F Preti Et Al: Forest Cover Influence On Regional Flood Frmentioning

confidence: 99%

Forest cover influence on regional flood frequency assessment in Mediterranean catchments

Preti

Forzieri

Chirico

2011

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The paper aims at evaluating to what extent the forest cover can explain the component of runoff coefficient as defined in a regional flood frequency analysis based on the application of the rational formula coupled with a regional model of the annual maximum rainfall depths. The analysis is addressed to evaluate the component of the runoff coefficient which cannot be captured by the catchment lithology alone. Data mining is performed on 75 catchments distributed from South to Central Italy. Cluster and correlation structure analyses are conducted for distinguishing forest cover effects within catchments characterized by hydromorphological similarities. We propose to improve the prediction of the runoff coefficient by a linear regression model, exploiting the ratio of the forest cover to the catchment critical rainfall depth as dependent variable. The proposed regression enables a significant bias correction of the runoff coefficient, particularly for those small mountainous catchments, characterised by larger forest cover fraction and lower critical rainfall depth.

show abstract

Section: F Preti Et Al: Forest Cover Influence On Regional Flood Frmentioning

confidence: 99%

Forest cover influence on regional flood frequency assessment in Mediterranean catchments

Preti

Forzieri

Chirico

2011

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…divided by an index value (e.g. Bocchiola et al, 2003), have identical frequency distributions across all sites within a given homogenous area, or region (Hosking and Wallis, 1993;. The regional distribution is usually named growth curve and is more accurate as compared to single site analysis (e.g.…”

Section: T Imentioning

confidence: 99%

“…The index value can be calculated by the single site sample average (e.g. Bocchiola et al, 2003), or by the median (middle ranking value of the single site observed series, e.g. Robson and Reed, 1999) or by a site to site location parameter (e.g.…”

Section: Index Value Approachmentioning

confidence: 99%

See 1 more Smart Citation

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

Bocchiola

Janetti

Gorni

et al. 2008

Nat. Hazards Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…As CASC2D is an event model, initial conditions are also included in the criteria. The proposed procedure that will be used is a hydrologic simulation using monte -carlo (MC) methods (e.g., Bocchiola et al, 2003) coupled wi th the stochastic storm transposition (SST) technique (Foufoula -Georgiou, 1989) to estimate extreme rainfall probabilities. The procedure is based on the stochastic storm transposition and runoff approach used by Franchini et al (1996) with some modifications.…”

Section: Distributions For Process Parameters and Inputsmentioning

confidence: 99%

Distributed Modeling of Extreme Floods on Large Watersheds

England

Juliën

Velleux

et al. 2005

Impacts of Global Climate Change

View full text Add to dashboard Cite

Estimates of extreme floods and probabilities are needed for hydrologic engineering and dam safety risk analysis. Physically-based, distributed watershed models are used as an avenue to estimate extreme floods, and as a basis to extrapolate frequency curves. The main elements of this research include improving and using a two -dimensional, physically-based rainfall-runoff model (CASC2D) to estimate extreme floods and probabilities for dam safety on a large (12,000 km 2 ) watershed, the Arkansas River above Pueblo, Colorado. New tools have been developed so the model can be applied at this scale. CASC2D can be successfully used to model extreme floods based on observations of extreme rainfall (from both rain gage networks and weather radar) for large watersheds. Future research will focus on the storm transposition concept and linkages with radar.

show abstract

Review of recent advances in index flood estimation

Cited by 71 publications

References 22 publications

Forest cover influence on regional flood frequency assessment in Mediterranean catchments

Forest cover influence on regional flood frequency assessment in Mediterranean catchments

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

Distributed Modeling of Extreme Floods on Large Watersheds

Contact Info

Product

Resources

About