Practical Applications of Bed Scour Calculations: Two Case Studies

Author(s):  
Leif M. Burge ◽  
Laurence Chaput-Desrochers ◽  
Richard Guthrie

Pipelines can be exposed at water crossings where rivers lower the channel bed. Channel bed scour may cause damage to linear infrastructure such as pipelines by exposing the pipe to the flow of water and sediment. Accurate estimation of depth of scour is therefore critical in limiting damage to infrastructure. Channel bed scour has three main components: (1) general scour, (2) bed degradation, and (3) pool depth. General scour is the temporary lowering of the channel bed during a flood event. Channel bed degradation is the systematic lowering of a channel bed over time. Pool depth is depth of pools below the general bed elevation and includes the relocation of pools that result from river dynamics. Channel degradation is assessed in the field using indicators of channel incision such as channel bed armoring and bank characteristics, through the analysis of long profiles and sediment transport modelling. Pool depth is assessed using long profiles and channel movement over time. The catastrophic nature of bed lowering due to general scour requires a different assessment. A design depth of cover is based on analysis of depth of scour for a given return period (eg. 100-years). There are three main steps to predict general scour: (1) regional flood frequency analysis, (2) estimation of hydraulic variables, and (3) scour depth modelling. Typically, four scour models are employed: Lacey (1930), Blench (1969), Neill (1973), and Zeller (1981), with the average or maximum value used for design depth. We provide herein case studies for potential scour for pipeline water crossings at the Little Smoky River and Joachim Creek, AB. Using the four models above, and an analysis of channel degradation and pool depth, the recommended minimum depth of cover of 0.75 m and 0.142 m, respectively, were prescribed. Variability between scour models is large. The general scour model results varied from 0.45 m and 0.75 m for the Little Smoky River and 0.16 m to 0.51 m for Joachim Creek. While these models are more than 30 years old and do not adequately account for factors such as sediment mobility, they nevertheless do provide usable answers and should form part of the usual toolbox in water crossing scour calculations.

2020 ◽  
Vol 6 (12) ◽  
pp. 2425-2436
Author(s):  
Andy Obinna Ibeje ◽  
Ben N. Ekwueme

Hydrologic designs require accurate estimation of quartiles of extreme floods. But in many developing regions, records of flood data are seldom available. A model framework using the dimensionless index flood for the transfer of Flood Frequency Curve (FFC) among stream gauging sites in a hydrologically homogeneous region is proposed.  Key elements of the model framework include: (1) confirmation of the homogeneity of the region; (2) estimation of index flood-basin area relation; (3) derivation of the regional flood frequency curve (RFFC) and deduction of FFC of an ungauged catchment as a product of index flood and dimensionless RFFC. As an application, 1983 to 2004 annual extreme flood from six selected gauging sites located in Anambra-Imo River basin of southeast Nigeria, were used to demonstrate that the developed index flood model: , overestimated flood quartiles in an ungauged site of the basin.  It is recommended that, for wider application, the model results can be improved by the availability and use of over 100 years length of flood data spatially distributed at critical locations of the watershed. Doi: 10.28991/cej-2020-03091627 Full Text: PDF


2016 ◽  
Vol 20 (12) ◽  
pp. 4717-4729 ◽  
Author(s):  
Martin Durocher ◽  
Fateh Chebana ◽  
Taha B. M. J. Ouarda

Abstract. This study investigates the utilization of hydrological information in regional flood frequency analysis (RFFA) to enforce desired properties for a group of gauged stations. Neighbourhoods are particular types of regions that are centred on target locations. A challenge for using neighbourhoods in RFFA is that hydrological information is not available at target locations and cannot be completely replaced by the available physiographical information. Instead of using the available physiographic characteristics to define the centre of a target location, this study proposes to introduce estimates of reference hydrological variables to ensure a better homogeneity. These reference variables represent nonlinear relations with the site characteristics obtained by projection pursuit regression, a nonparametric regression method. The resulting neighbourhoods are investigated in combination with commonly used regional models: the index-flood model and regression-based models. The complete approach is illustrated in a real-world case study with gauged sites from the southern part of the province of Québec, Canada, and is compared with the traditional approaches such as region of influence and canonical correlation analysis. The evaluation focuses on the neighbourhood properties as well as prediction performances, with special attention devoted to problematic stations. Results show clear improvements in neighbourhood definitions and quantile estimates.


2012 ◽  
Vol 4 (1) ◽  
pp. 36-41 ◽  
Author(s):  
Abhijit Bhuyan ◽  
Munindra Borah

The annual maximum discharge data of six gauging sites have been considered for L-moment based regional flood frequency analysis of Tripura, India. Homogeneity of the region has been tested based on heterogeneity measure (H) using method of L-moment. Based on heterogeneity measure it has been observed that the region consist of six gauging sites is homogeneous. Different probability distributions viz. Generalized extreme value (GEV), Generalized Logistic (GLO), Generalized Pareto (GPA), Generalized Normal (GNO), Pearson Type III (PE3) and Wakebay (WAK) have been considered for this investigation. PE3, GNO and GEV have been identified as the candidate distributions based on the L-moment ratio diagram and ZDIST -statistics criteria. Regional growth curves for three candidate distributions have been developed for gauged and ungauged catchments. Monte Carlo simulations technique has also been used to estimate accuracy of the estimated regional growth curves and quantiles. From simulation study it has been observed that PE3 distribution is the robust one.


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