Now showing 1 - 3 of 3
  • Publication
    Bankfull discharge and recurrence intervals in Irish rivers
    Different definitions of the bankfull condition in rivers are based on morphological characteristics, boundary conditions and geometrical properties. Consequently, the magnitude and associated return period of the bankfull discharge can be ambiguous. Knowledge of this discharge is important in index flood estimation and subsequent regional flood frequency analysis. This study investigates bankfull discharges and recurrence intervals at 88 locations in the Irish river network using a combination of surveyed bankfull levels, rating curves and equations and photographic records at the sites in question. Catchments ranged in area from approximately 23 km2 to 2778 km2. Recurrence intervals were determined by fitting generalised extreme value (GEV) distributions to the annual maximum flow series at the sites investigated. These intervals were found to be less than 2 years (the median annual flood) at 42 stations (48%) and less than 2·33 years (the mean annual flood assuming a GEV type 1 distribution) at 47 stations (53%). Higher return periods of between 2·33 and 10 years and 10 and 25 years were observed at a further 20% and 6% of locations respectively. Using multivariate regression analysis, the computed bankfull discharges are correlated with catchment descriptors and three expressions are presented for estimating bankfull flows.
      573Scopus© Citations 10
  • Publication
    Influences on flood frequency distributions in Irish river catchments
    (Copernicus Publications on behalf of the European Geosciences Union, 2012) ; ;
    This study explores influences on flood frequency distributions in Irish rivers. Generalised Extreme Value (GEV) type I distributions are recommended in Ireland for estimating flood quantiles. This paper presents the findings of an investigation that identified the GEV statistical distributions that best fit the annual maximum (AM) data series extracted from 172 gauging stations of 126 rivers in Ireland. Analysis of these data was undertaken to explore hydraulic and hydro-geological factors that influence flood frequency distributions. A hierarchical approach of increasing statistical power that used probability plots, moment and L-moment diagrams, the Hosking goodness of fit algorithm and a modified Anderson-Darling (A-D) statistical test was followed to determine whether a type I, type II or type III distribution was valid. Results of the Hosking et al. method indicated that of the 143 stations with flow records exceeding 25 years, data for 95 (67%) was best represented by GEV type I distributions and a further 9 (6%) and 39 (27%) stations followed type II and type III distributions respectively. Type I, type II and type III distributions were determined for 83 (58%), 16 (11%) and 34 (24%) stations respectively using the modified A-D method (data from 10 stations was not represented by GEV family distributions). The influence of karst terrain on these flood frequency distributions was assessed by incorporating results on an Arc-GIS platform showing karst features and using Monte Carlo simulations to assess the significance of the number and clustering of the observed distributions. Floodplain effects were identified by using two-sample t-tests to identify statistical correlations between the distributions and catchment properties that are indicative of strong floodplain activity. The data reveals that type I distributions are spatially well represented throughout the country. While also well represented throughout the country, the majority of type III distributions appear in areas where attenuation influences from floodplains are likely. The majority of type II distributions appear in a single cluster in a region in the west of the country that is underlain by karst but importantly, is characterised by shallow of glacial drift with frequent exposures of rock outcrops. The presence of karst in river catchments would be expected to provide additional subsurface storage and in this regard, type III distributions might be expected. The prevalence of type II distributions in this area reflects the finite nature of this storage. For prolonged periods of rainfall, rising groundwater levels will fill karst voids, remove subsurface storage and contribute to recharge related sinkhole flooding. Situations where rainfall intensities exceed karst percolation rates also produce high levels of surface runoff (discharge related flooding) that can promote type II distributions in nearby river catchments. Results therefore indicate that in some instances, assuming type I distributions is incorrect and may result in erroneous estimates of flood quantiles at these locations. Where actual data follows a type II distribution, flood quantiles may be underestimated by in excess of 35% and for type III distributions, overestimates by over 25% can occur.
      3070Scopus© Citations 26
  • Publication
    A modified Muskingum routing approach for floodplain flows: theory and practice
    Hydrological or hydraulic flood routing methods can be used to predict the floodplain influences on a flood wave as it passes along a river reach. While hydraulic routing uses both the equation of continuity and the equation of momentum to describe the dynamics of river flows, the simpler data requirements of hydrological routing makes it useful for preliminary estimates of the time and shape of a flood wave at successive points along a river. This paper presents a modified linear Muskingum hydrological routing method where the floodplain effects on flood peak attenuation and flood wave travel time are included in routing parameters. Developing the routing parameters initially involved routing hydrographs of different flood peak and duration through a 1-dimensional model of a generalised river reach in which a range of geometrical and resistance properties were varied. Comparison of upstream and simulated downstream hydrographs for each condition investigated, allowed the attenuation and travel time (storage constant, K, in standard Muskingum routing) of the flood wave to be estimated. Standard Muskingum 1 routing was then used to develop downstream hydrographs for each K value together with assumed storage weighting factors (x) ranging from 0 to 0.5. Flood peak attenuations were again determined through comparison of the upstream and routed downstream hydrographs and with these, linear relationships between x and these attenuations were developed. Actual weighting factors, corresponding to storage constants, were subsequently determined using these relationships for all attenuations determined from the 1-dimensional model simulations. Using multi-variate regression analysis, the computed values of K and x were correlated to catchment and hydrograph properties and expressions for determining both K and x in terms of these properties were developed. The modified Muskingum routing method based on these regressed expressions for K and x was applied to a case study of the River Suir in Ireland where good agreement between measured and routed hydrographs was observed.
      1269Scopus© Citations 27