Delineation of homogenous regions using hydrological variables predicted by projection pursuit regression

Durocher, Martin; Chebana, Fateh; Ouarda, Taha B. M. J.

doi:10.5194/hess-20-4717-2016

Cited by 20 publications

(13 citation statements)

References 39 publications

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“…Another conclusion was that the index-flood model (Dalrymple, 1960) performed similarly to the direct estimation of the flood quantiles by regression (Thomas and Benson, 1975). Similar comparisons were repeated in a separate context with similar results (Durocher et al, 2016a;Haddad and Rahman, 2012). Overall, the decision between these two approaches appears to be mostly conceptual.…”

Section: Introductionmentioning

confidence: 88%

A nationwide regional flood frequency analysis at ungauged sites using ROI/GLS with copulas and super regions

Durocher

Burn

Zadeh

2018

Journal of Hydrology

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Region of influence is a common approach to estimate runoff information at ungauged locations. To estimate flood quantiles from annual maximum discharges, the Generalized Least Squares (GLS) framework has been recommended to account for unequal sampling variance and intersite correlation, which requires a proper evaluation of the sampling covariance structure. Since some jurisdictions do not have clear guidelines to perform this evaluation, a general procedure using copulas and a nonparametric intersite correlation model is investigated to estimate sampling covariance structure in situations where no common at-site distribution is imposed or when some paired sites do not have common periods of record.The investigated methodology is applied on 771 sites in Canada. The Normal copula is verified to be an adequate model that better fit paired observations than other types of extreme copulas. A sensitivity analysis is carried out to evaluate the impact of either ignoring, or considering a simpler form of, intersite correlation. Additionally, super regions are defined based on drainage area and mean annual precipitation to improve the calibration of pooling groups across large territories and a wide range of climate conditions. Performance criteria based on cross-validation revealed that using super regions and a combination of geographic distance and similarity between catchment descriptors improves the calibration of the pooling groups by providing more accurate estimates.

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Section: Introductionmentioning

confidence: 88%

A nationwide regional flood frequency analysis at ungauged sites using ROI/GLS with copulas and super regions

Durocher

Burn

Zadeh

2018

Journal of Hydrology

Self Cite

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“…The marginal GEV distributions were fit for each station separately using maximum likelihood estimation. A regional estimation of the shape parameter ξ would have been desirable (Evin et al, 2016). Pooling the events of different stations, however, was not sensible since even the specific discharges were dependent on the catchment area.…”

Section: Marginal Modelmentioning

confidence: 99%

“…Bárdossy and Li (2008) have introduced an interpolation method based on copulas. They have used both the Gaussian and a v-transformed normal copula, which was used by Durocher et al (2016) for predicting flood quantiles at ungauged basins based on physiographical locations. Quessy et al (2016) applied the general class of chi-square copulas in a spatial context.…”

Section: Introductionmentioning

confidence: 99%

Modeling the spatial dependence of floods using the Fisher copula

Brunner

Furrer

Favre

2019

Hydrol. Earth Syst. Sci.

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Abstract. Floods often affect not only a single location, but also a whole region. Flood frequency analysis should therefore be undertaken at a regional scale which requires the considerations of the dependence of events at different locations. This dependence is often neglected even though its consideration is essential to derive reliable flood estimates. A model used in regional multivariate frequency analysis should ideally consider the dependence of events at multiple sites which might show dependence in the lower and/or upper tail of the distribution. We here seek to propose a simple model that on the one hand considers this dependence with respect to the network structure of the region and on the other hand allows for the simulation of stochastic event sets at both gauged and ungauged locations. The new Fisher copula model is used for representing the spatial dependence of flood events in the nested Thur catchment in Switzerland. Flood event samples generated for the gauged stations using the Fisher copula are compared to samples generated by other dependence models allowing for modeling of multivariate data including elliptical copulas, R-vine copulas, and max-stable models. The comparison of the dependence structures of the generated samples shows that the Fisher copula is a suitable model for capturing the spatial dependence in the data. We therefore use the copula in a way such that it can be used in an interpolation context to simulate event sets comprising gauged and ungauged locations. The spatial event sets generated using the Fisher copula well capture the general dependence structure in the data and the upper tail dependence, which is of particular interest when looking at extreme flood events and when extrapolating to higher return periods. The Fisher copula was for a medium-sized catchment found to be a suitable model for the stochastic simulation of flood event sets at multiple gauged and ungauged locations.

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“…Annual maximum flood (AMF) and peaks over threshold (POT) are widely used in the prediction of extreme events. So many studies have been carried out to develop the regionalization approaches which were designed for the assessment of extreme events in the ungauged sites by extracting information from the similar group of gauged watersheds [13][14]. Region of influence (ROI) approach applies Euclidean distance to group the sites based on the information extracted from the gauged sites with respective to the target site considered [15].…”

Section: Introductionmentioning

confidence: 99%

Partitioning around medoids approach application for computation of regional flood and landslide quantiles

et al. 2020

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Flood and landslides causes serious damage to the functioning of the society which results in a huge loss of human life, material and other environmental impacts. In this paper, partitioning around medoids approach is executed for the assessment of flood quantiles over 145 sites using 11 basin characteristics. The study region is classified into 6 clusters as a result of the partitioning algorithm which are further proved to be homogeneous by applying the heterogeneity measure test. Results from the study provided the regional flood quantile measurements for the ungauged sites derived from L moments with good accuracy limits for the recurrence intervals 50, 100, 200 and 500 years. As a floods landslides may caused by rainfalls, especially over long time periods, which both increase the weight of slopes and can lubricate planes of weakness within rock or sediment. It is shown that landslides are also allocated in some of the clustered zones, depending of geological conditions of the clusters. Thus regional flood quintiles in conjunction with geology and topography forms landslide activity quantiles.

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Delineation of homogenous regions using hydrological variables predicted by projection pursuit regression

Cited by 20 publications

References 39 publications

A nationwide regional flood frequency analysis at ungauged sites using ROI/GLS with copulas and super regions

A nationwide regional flood frequency analysis at ungauged sites using ROI/GLS with copulas and super regions

Modeling the spatial dependence of floods using the Fisher copula

Partitioning around medoids approach application for computation of regional flood and landslide quantiles

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