Donald H. Burn

Detection of hydrologic trends and variability

This paper describes the development and application of a procedure that identifies trends in hydrologic variables. The procedure utilizes the Mann–Kendall non-parametric test to detect trends, a permutation approach to estimate the test distribution, and accounts for the correlation structure in the data in determining the significance level of the test results. The research investigates 18 hydrologic variables that reflect different parts of the hydrologic cycle. The hydrologic variables are analyzed for a network of 248 Canadian catchments that are considered to reflect natural conditions. A selection of catchments identified to have trends in hydrologic variables is studied further to investigate the presence of trends in meteorological variables and the relationship between the hydrologic and the meteorological response to climatic change. It is concluded that a greater number of trends are observed than are expected to occur by chance. There are differences in the geographic location of significant trends in the hydrologic variables investigated implying that impacts are not spatially uniform.

Hydrologic effects of climatic change in west-central Canada

Abstract The paper examines the impact of climatic change on the timing of the spring runoff event. Impact detection is accomplished using a non-parametric statistical test for trend that is applied to the assembled data sets. The application of the approach is to a set of 84 natural rivers from the west-central region of Canada. The results indicate that there are a greater number of rivers that exhibit earlier spring runoff than can be attributed to chance occurrence. The observed impacts on the timing of spring runoff are more prevalent in the recent portion of the data record, which is consistent with what one would expect if the impacts are a result of greenhouse gas induced climatic change.

Catchment similarity for regional flood frequency analysis using seasonality measures

Abstract A regionalization approach that uses information related to the timing of flood events is presented. The approach is applied within the region of influence (ROI) framework and has the advantage of reserving the use of information derived from flood magnitudes for the examination of the homogeneity of flood regions as opposed to first using this information to form regions. The regionalization technique is applied to a set of catchments from the Canadian prairies and is demonstrated to result in the identification of regions that are effective for the estimation of extreme flow quantiles.

Assessing the effectiveness of hydrological similarity measures for flood frequency analysis

This paper evaluates the relative performance of four hydrological similarity measures that are used to form homogeneous pooling groups for regional frequency analysis. One pair of similarity measures is based on seasonality indexes that reflect the timing of extreme events. A further pair of measures considers a characterisation, at the basin scale, of the frequency distribution of rainfall extremes and the extent of the impervious portion of the catchment. The measures are applied to a case study encompassing a large area in Northern-Central Italy. The similarity measures are examined in the context of a pooling scheme that is designed to identify hierarchical, focused pooling groups. The performance of the similarity measures is quantified using a Monte Carlo experiment. The results demonstrate that similarity measures based on seasonality indexes are effective for estimating extreme flow quantiles for the study area. For ungauged catchments, a similarity measure incorporating both rainfall statistics and permeability information is most effective.

Climate change effects on the hydrologic regime within the Churchill-Nelson River Basin

Abstract This paper evaluates the possible effects of climate change on four hydrologic variables pertaining to the magnitude and timing of hydrologic events within the Churchill-Nelson River Basin in west-central Canada. By using the Mann-Kendall trend test, and a regionalization procedure, the severity of climatic effects within the river basin may be quantified and used to increase awareness of future consequences for water resource systems planning and management strategies. It was found that the magnitude of hydrologic events decreased over time while snowmelt runoff events occurred earlier. The only exceptions to this behavior were the spring mean monthly streamflow values which exhibited increasing trends due to the potential for snow melting during this period. The timing of a hydrologic event was found to be influenced to the greatest extent by changes in temperature. Geographically, the decreasing trends were concentrated in the southern regions of the river basin while the increasing trends appeared primarily in the northern regions.

Hydrological trends and variability in the Liard River basin / Tendances hydrologiques et variabilité dans le basin de la rivière Liard

Abstract Abstract A study of the trends and variability of hydrological variables was conducted for natural streamflow gauging stations within the Liard River basin in northern Canada. Trends were investigated using the Mann-Kendall test, with an approach that corrects for serial correlation. The field significance of the results was evaluated using a bootstrap resampling approach. The relationships between trends in hydrological variables and both meteorological variables and a large-scale oceanic and atmospheric process were investigated using correlation analysis. The results reveal more trends in some hydrological variables than are expected to occur by chance. The observed trends are related to both trends in meteorological variables and a large-scale oceanic and atmospheric process.

Flood frequency analysis for ungauged sites using a region of influence approach

Abstract A framework is presented for regional flood frequency analysis that is applicable for estimating extreme flow quantiles at ungauged catchments. The methodology uses the Region of Influence (ROI) approach to regionalization and explicitly incorporate a homogeneity test in the process of selecting the collection of stations that comprise the ‘region’ for an ungauged site. The relative merits of the methodology are demonstrated through an application to extreme flow data for sites in Newfoundland, Canada. The new approach is compared with results obtained from regression analysis and is shown to provide improved estimates of extreme quantiles at sites which are considered to be ungauged.

An appraisal of the “region of influence” approach to flood frequency analysis

Abstract Regional flood frequency entails the pooling of data from sites within a defined region to enhance the estimation of at-site quantiles. Conventional regionalization techniques normally identify a fixed set of stations forming a contiguous region. An approach to regional flood frequency analysis that involves each site having a potentially different set of stations included for the at-site estimation of extremes was compared with a more traditional regionalization technique. The characteristics of the stations identified as being of relevance for the purposes of at-site estimation using the two approaches were contrasted and also the extreme flow values obtained were compared. The results indicated that the region of influence approach results in a group of stations with greater homogeneity than was the case for the regionalization technique and also leads to extreme flow estimates which are more accurate.

Non-stationary pooled flood frequency analysis

Abstract The presence of significant non-stationarity in a hydrologic time series cannot be ignored when estimating design values for future time horizons. This paper introduces a second-order non-stationary approach to pooled flood frequency analysis. The proposed approach separates the non-stationary pooled quantile function into a local time-dependent component, comprising the location and scale distribution parameters, and a regional component that can be regarded as time-independent under the assumption of second-order non-stationarity. A local trend analysis is used for identification, local significance assessment and estimation of the changes in the time-dependent components. A regional trend analysis based on a regional bootstrap-resampling algorithm is then applied for assessment of the changes at a regional scale. A Monte-Carlo experiment is used for evaluating the performance of the method in the estimation of trend magnitudes in the location and scale parameters of a non-stationary series. The model is then applied on a study catchment from a homogeneous region. The results show that ignoring even a weakly significant non-stationarity in the data series may seriously bias the quantile predicted for time horizons as near as 0–20 years in the future.

An entropy approach to data collection network design

Abstract A new methodology is developed for data collection network design. The approach employs a measure of the information flow between gauging stations in the network which is referred to as the directional information transfer. The information flow measure is based on the entropy of gauging stations and pairs of gauging stations. Non-parametric estimation is used to approximate the multivariate probability density functions required in the entropy calculations. The potential application of the approach is illustrated using extreme flow data from a collection of gauging stations located in southern Manitoba, Canada.