Examination of homogeneity of selected Irish pooling groups

Abstract

Abstract. Flood frequency analysis is a necessary and important part of flood risk assessment and management studies. Regional flood frequency methods, in which flood data from groups of catchments are pooled together in order to enhance the precision of flood estimates at project locations, is an accepted part of such studies. This enhancement of precision is based on the assumption that catchments so pooled together are homogeneous in their flood producing properties. If homogeneity is assured then a homogeneous pooling group of sites lead to a reduction in the error of quantile estimates, relative to estimators based on single at-site data series alone. Homogeneous pooling groups are selected by using a previously nominated rule and this paper examines how effective one such rule is in selecting homogeneous groups. In this paper a study, based on annual maximum series obtained from 85 Irish gauging stations, examines how successful a common method of identifying pooling group membership is in selecting groups that actually are homogeneous. Each station has its own unique pooling group selected by use of a Euclidean distance measure in catchment descriptor space, commonly denoted d ij and with a minimum of 500 station years of data in the pooling group. It was found that d ij could be effectively defined in terms of catchment area, mean rainfall and baseflow index. The study then investigated how effective this selected method is in selecting groups of catchments that are actually homogenous as indicated by their L-Cv values. The sampling distribution of L-CV (t 2 ) in each pooling group and the 95% confidence limits about the pooled estimate of t 2 are obtained by simulation. The t 2 values of the selected group members are compared with these confidence limits both graphically and numerically. Of the 85 stations, only 1 station's pooling group members have all their t 2 values within the confidence Correspondence to: S. Das (samirandas@gmail.com) limits, while 7, 33 and 44 of them have 1, 2 or 3 or more, t 2 values outside the confidence limits. The outcomes are also compared with the heterogeneity measures H1 and H2. The H1 values show an upward trend with the ranges of t 2 values in the pooling group whereas the H2 values do not show any such dependency. A selection of 27 pooling groups, found to be heterogeneous, were further examined with the help of box-plots of catchment descriptor values and one particular case is considered in detail. Overall the results show that even with a carefully considered selection procedure, it is not certain that perfectly homogeneous pooling groups are identified.

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

“…In the present study, the size of the neighbourhoods is the same. Hence, if a homogeneity test is performed with a given neighbourhood size, some of the neighbourhoods will be considered homogenous, while the others will be considered heterogeneous (Das and Cunnane, 2011). However, the heterogeneity measure in Eq.…”

Performance of flood frequency pooling analysis in a low CV context

“…The groups PG0 (corresponding to a perfectly homogeneous group) and PG1 (corresponding to nearly a homogeneous group) represent practically homogeneous conditions, while PG2 and PG3 represent moderately heterogeneous conditions, and PG4 and PG5 represent highly heterogeneous conditions. This range of heterogeneity arose from the ROI approach of forming groups using Irish data as described in Das and Cunnane (2011). As an example, Table 5 describes PG2 in detail.…”

“…In equation (1) log-transformed AREA and SAAR data are used to reduce the variability among those data sets and all three variables are standardized by dividing each variable by the standard deviation of that variable. The above distance measure has been found to be suitable for pooling analysis in the Irish context (Das and Cunnane 2011). The procedure of selection of pooling variables and the associated weights are described detail in Das and Cunnane (2011), where two sets of catchment descriptors were selected as potential pooling variables:…”

“…The above distance measure has been found to be suitable for pooling analysis in the Irish context (Das and Cunnane 2011). The procedure of selection of pooling variables and the associated weights are described detail in Das and Cunnane (2011), where two sets of catchment descriptors were selected as potential pooling variables:…”

“…some degree of heterogeneity exists. In fact, in only a relatively small proportion of cases is the homogeneity criterion effectively satisfied for Irish conditions (Das and Cunnane 2011). Therefore it is necessary to assess the performance of the Index Flood pooling analysis considering that heterogeneity may have to be taken into account.…”