Reference Hydrometric Basin Network Research Articles

Regional disparities in water availability and low flow conditions in rivers across Canada

Water resources play an important role in many aspects of our daily lives, e.g. industrial food processing, irrigation, and hydropower generation, etc. The natural flow regime and water availability were studied across Canada using 167 catchments from the Water Survey of Canada dataset (Reference Hydrometric Basin Network - RHBN). We established a systematic analysis of water availability (annual and monthly runoff) to determine both the quantity and distribution of water within the year. In each province, we investigated the severity of low flow conditions namely the magnitude, seasonality, and duration of extreme low flows. There are prominent disparities in water availability at the annual and monthly time scales across Canada. The annual runoff characteristics showed a relatively abundant quantities of water on the east and west coasts (800-2300 mm/year). Annual runoff is critically low (<150 mm/year) in the prairies and northern territories. Monthly analyses revealed eminent differences in the timing and magnitude of high and low flows. The spring snowmelt is the main trigger of high flows in most provinces. However, the quantities of water during freshet period varied dramatically across provinces. British Columbia showed among the highest hydrological variability where some catchments showed relatively high flows year around. In Canada, a second high flow period was observed in some provinces (e.g., Quebec, Ontario, and the Maritimes). The underpinning hydrological processes and the precipitation regime are discussed to explain the regional hydrologic disparities. The monthly flow of the 80th percentile (Q80; monthly flow duration curve) was used as the cutoff to describe low flows both in terms of magnitude and duration. The Q80 variability across Canadian rivers was significantly large (0.3-100 mm/month). Many regions have one period of extreme low flows except in Newfoundland, New Brunswick, British Columbia, Ontario, Quebec and Saskatchewan where 2 seasons of low flows can be observed. In Newfoundland and New Brunswick the low flow period was the shortest (2.6 months). In contrast, in the prairies and north territories, the low flow period extended between 3.4 and 4 months. We further explained the disparities in water availability and low flows from analysis of the daily flow duration curve (FDC). We quantified the differences in the flow response from flow indices calculated from FDC (baseflow index, low flow index, and slope of the FDC). The results of water availability and low flows have important socio-economic impacts on water supply, reservoir operations, and far-reaching implications on the health of aquatic habitats.

Detection of trends in flood magnitude and frequency in Canada

Changes in flood regimes in Canada were examined using a large-scale dataset of hydrometric stations from across the country. Significant trends were analysed in time series of both Annual Maximum (AMAX) and Peaks-Over-Threshold (POT) series of streamflow data. POT series were extracted from daily flows for each watershed using a semi-automated threshold selection method. Since flood regimes are complex by nature, a multi-temporal and multifaceted approach was employed to identify and properly characterize the types of changes. Common time periods of the recent 30-, 40-, 50-, and 60-years were studied. Trends were investigated both in terms of flood magnitude and frequency of these time series. Changes were examined using different groupings of sites based on dominant hydro-climatic regions, drainage area size, and land-use changes based on hydrometric reference stations. Trends were examined both at local and field scale. Notably significant trends were identified in the Atlantic, Central, Prairie, and Northern regions. Additionally, Reference Hydrometric Basin Network (RHBN) watersheds were found to have more statistically significant trends than the non-RHBN sites.New Hydrological InsightsAn increased number of threshold exceeding events was observed from this analysis. Flow magnitudes series showed more increasing trends in the most recent time windows while there are more decreasing trends in longer time periods. Different types of changes were observed for different hydro-climatic regions.

A comparison of conventional and wavelet transform based methods for streamflow record extension

Sufficient hydrological data, such as streamflow, are important to represent the long-term characteristics of a watershed in order to support decision-making, policy and management. Lack of data remains one of the main challenges of hydrological analyses. Therefore, the main goal of this study is to extend streamflow records using a proposed approach where the wavelet transform (WT) is incorporated as a pre-processing method into eight existing record extension techniques, namely the ordinary least-square regression (OLS), maintenance of variance (MOVE) types 1–4, Kendall-Theil robust line (KTRL), KTRL2 and robust line of organic correlation (RLOC). The performance of the WT-based methods in estimating individual data values, means and standard deviations of the extended records, and a series of percentiles of the extended records was then compared with that of the respective conventional methods (i.e., without the WT). The data used in the analysis consisted of 67 pairs of target-index stations that were obtained from Canada’s Reference Hydrometric Basin Network database, all of which contain outliers. As such, the results and discussions obtained are applicable for cases where the data contain outliers. The WT-based methods (particularly the KTRL-WT, KTRL2-WT and RLOC-WT) demonstrated consistent improvements in precision and accuracy compared with their conventional counterparts, especially in estimating the means and standard deviations of the extended records. In estimating individual data values, the WT-based methods showed inconsistent improvements. Finally, in terms of percentiles, greater improvements were seen in the estimation of higher percentiles, more specifically for the MOVE1-WT, MOVE2-WT, KTRL2-WT and RLOC-WT compared with their conventional counterparts.

Identification of changes in floods and flood regimes in Canada using a peaks over threshold approach

AbstractRecent flood events in Canada have led to speculation that changes in flood behaviour are occurring; these changes have often been attributed to climate change. This paper examines flood data for a collection of 132 gauging stations in Canada. All of these watersheds are part of the Canadian Reference Hydrometric Basin Network (RHBN), a group of gauging stations specifically assembled to assist in the identification of the impacts of climate change. The RHBN stations are considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Daily flow data for each watershed are used to derive a peaks over threshold (POT) dataset. Several measures of flood behaviour are examined based on the POT data, which afford a more in‐depth analysis of flood behaviour than can be obtained using annual maxima data. Analysis is conducted for four time periods ranging from 50 to 80 years in duration; the latter period results in a much smaller number of watersheds that have data for the period. The changes in flood responses of the watersheds are summarized by grouping the watersheds by size (small, medium, and large) and also by hydrologic regime (nival, mixed, and pluvial). The results provide important insights into the nature of the changes that are occurring in flood regimes of Canadian rivers, which include more flood exceedances, reduced maximum flood exceedance magnitudes for snowmelt events, and earlier flood events. Copyright © 2016 John Wiley &amp; Sons, Ltd.

A spatiotemporal analysis of hydrological trends and variability in the Athabasca River region, Canada

Summary Trends and variability in the hydrologic regime of the Athabasca River region were analyzed. Twenty hydrologic variables were selected for flow analysis within both the Athabasca River Basin (ARB) and, for comparison, surrounding watersheds. Intra- and inter-basin scale analyses were performed, including a comparison of changes in streamflow at stations forming part of the Reference Hydrometric Basin Network (RHBN) and non-designated gauges. Streamflow trends were also compared with trends in air temperature and precipitation over the entire Athabasca and surroundings study region. Noteworthy results include strong decreasing trends in annual, warm season (March to October) and summer month flows over the majority of the study region, in addition to a greater number of decreasing trends in Athabasca watershed flows compared to the surrounding basins. The timing of the spring freshet was found to have not shifted toward an earlier onset, contrary to results from previous studies. Lastly, trends in streamflow were similar to those for precipitation over the ARB and surrounding region, but did not relate strongly to trends in air temperature. The results of this study should be of assistance to water- resources managers and policy makers in making decisions about water use in this rapidly changing watershed.

Effect of Short and Long Term Memory on Trend Significancy of Mean Annual Flow by Mann-Kendall Test

Climate variability and change is threatening water resources around the world. One hundred and fourtheen (114) stations from Reference Hydrometric Basin Network (RHBN) around Canada with at least 30 years continuous data (up to 2011) were selected to study the trend in mean annual runoff for different periods of 30 to 100 years in step 10 years by non-parametric Mann-Kendall test. Effect of short term persistant (STP) and long term persistant (LTP) on this test were made through lag 1 serial correlation (r1) and Hurst exponent (H), respectively. r1 for about one third of the total cases considered were negative. H, based on “equivalent Normal deviate” (eNv), was slightly right-skewed with minimum and maximum values of 0.20 and 0.87, respectively. About half of the data sets were anti-persistant (H0.1). The number of positive and negative trends, were nearly the same, though fluctuating for different time spans. p-value after pre-whitening was highly correlated with those of before pre-whitening, for both negatve and positive trends. There were about 16% of cases that pre-whitening decreased the p-values of the Mann-Kendall trend test, where nearly all of them were negatively trended. The effect of LTP on Mann-Kendall trend test was minor, due to inconsistancy of originally significant trend case and significant H of greater than 0.5. For recent 30 years length of record (1982-2011), British Columbia is experiencing positive trends in the west and negative trend in the east. Most parts of the New Brunswick is experincing the positive trend, while negative trend is due to Southeast of Ontario. For the more logest duration of 40 years, trend statistics and geographical pattern were changed. While the significant trends are decreased, more significant negative trends are governed over New Brunswick. There is no positive trend in British Colimbia in the past 50 years (1962-2011) while there are both negative and positive trends in New Brunswick and negative trends are switched to positive trends in south east of Ontario. For long duration of > 70 years, there are only positive trends in Southeast of Canada (South New Brunswick and South East of Ontario) while centeral and East of Canada have experinced a negative trend.

Analyzing the combined influence of solar activity and El Niño on streamflow across southern Canada

It is well known that the spatial and temporal patterns in streamflow can be correlated with many teleconnections, e.g., solar activity and climatic phenomena such as El Niño. However, fewer studies have attempted to analyze both the influence of solar activity and large scale climatic phenomena on natural processes, particularly hydrological processes. In this study we examine long term records of solar activity and El Niño for their combined influence on streamflow across southern Canada. Data used in the analysis include sunspot number, sea surface temperature anomaly in Niño region 3.4, and annual mean streamflow from 50 Canadian Reference Hydrometric Basin Network (RHBN) stations with record lengths ≥50 years (14 of them ≥90 years). Analysis is performed using Fourier spectrum analysis (FSA), continuous wavelet transform (CWT), and cross wavelet transform coherence analysis (WTC). Results of FSA show that for almost all the 14 RHBN stations with record lengths of ≥90 years, streamflow exhibits periodicities of approximately 11 and 22 years (which is in accordance with solar activity), as well as shorter term periodicities consistent with El Niño (2–7 years). WTC analysis confirms the correlation between these periodicities (2–7 years, 11 years, 22 years) in streamflow with solar activity and El Niño records. Both solar activity and El Niño's influences on annual mean streamflow in 18–32 year bands are common, while the influence of El Nino is more extensive in the 2–7 and ∼11 year bands. Through examination of correlations between solar activity and streamflow, El Niño and streamflow, and finally El Niño and solar activity, WTC analysis has identified that solar activity affects El Niño first, and this influence is then transferred by El Niño to streamflow. This study expands on earlier efforts examining linkages between El Niño and streamflow across southern Canada to an examination of linkages between solar activity, El Niño, and streamflow.

Frequency Analysis Incorporating a Decision Support System for Hydroclimatic Variables

Statistical criteria used to evaluate the best distribution fit give large weights to the center of distributions. This is, however, not consistent with the objective of frequency analysis which is to estimate the quantiles with large return periods. In this study, the usefulness of a recently proposed decision support system (DSS), which defines the class of distributions prior to a model selection practice with respect to tail behavior of sample data, was investigated using three large hydroclimatic databases [Reference Hydrometric Basin Network (RHBN), precipitation, and UNESCO]. According to the DSS, although a considerable majority of RHBN flood sample data belonged to Class C (regularly varying distributions), a slight and great majority of UNESCO discharge as well as annual precipitation sample data, respectively, belonged to Class D (subexponential distributions). This difference in classification is attributed to the nature of studied variables: RHBN sample data represent extreme events with heavy tails (Class C), whereas UNESCO and especially precipitation sample data come from relatively lighter tailed processes and therefore belong mostly to Class D distributions. The impact of classification on model selection was the largest for the RHBN and the smallest for precipitation sample data. This confirms that discriminating between classes of competing models prior to model selection is critical when the sample data come from extreme events. Observed inconsistency in model selection for the RHBN database resulted in an underestimation of quantiles in more than 2/3 of the cases regardless of class of distributions. For the UNESCO and precipitation data, however, inappropriate model selection resulted equally in over- and under-estimation in Class C, whereas it resulted in underestimation of quantiles in Class D in the majority of observed inconsistencies. It can be concluded that an inappropriate model selection due to choosing a wrong class of distributions leads, in the majority of cases, to an underestimation of the quantity of the variable under study which is associated with a higher socioeconomy risk compared to that corresponding to an overestimation of a specific quantile. It was also observed that model selection using Bayesian Information Criterion (compared to Akaike Information Criterion) is more consistent with tail behavior of the natural processes.

Trends in timing of low stream flows in Canada: impact of autocorrelation and long‐term persistence

AbstractThe annual timing of river flows might indicate changes that are climate related. In this study, trends in timing of low flows for the Reference Hydrometric Basin Network were investigated under three different hypotheses namely: independence, short‐term persistence (STP) and long‐term persistence (LTP). Both summer and winter time series were characterized with scaling behaviour providing strong evidence of LTP. The Mann–Kendall trend test was modified to account for STP and LTP, and used to detect trends in timing of low flows. It was found that considering STP and LTP resulted in a significant decrease in the number of detected trends. Numerical analysis showed that the timing of summer 7‐day low flows exhibited significant trends in 16, 9 and 7% of stations under independence, STP and LTP assumptions, respectively. Timing of summer low flow shifted toward later dates in western Canada, whereas the majority of stations in the east half of the country (except Atlantic Provinces) experienced a shift toward earlier dates. Timing of winter low flow experienced significant trends in 20, 12, and 6% of stations under independence, STP and LTP assumptions, respectively. Shift in timing of winter low flow toward earlier dates was dominant all over the country where it shifted toward earlier dates in up to 3/4 of time series with significant trends. There are local patterns of upward significant/insignificant trends in southeast, southwest and northern Canada. This study shows that timing of low flows in Canada is time dependent; however, addressing the full complexity of memory properties (i.e. short term vs long term) of a natural process is beyond the scope of this study. Copyright © 2009 John Wiley &amp; Sons, Ltd.

Development of a new method of wavelet aided trend detection and estimation

AbstractThe detection and estimation of trends in the presence of noise, periodicities, or discontinuous patterns is important in hydrology and climate research studies. The basic idea of currently available trend estimation techniques (tests) is that the trends should be smooth and monotonic; however, hydro‐climatologic variables contain multiple signals, and have segments of increasing and decreasing trends. As a result, estimating trends in time series is an essential but arcane art and it is therefore important to continue developing the theory and practice of trend analysis.In this paper, a new technique is proposed based on the continuous wavelet transform (CWT). CWT permits the transformation of observed time series into wavelet coefficients according to time and scale simultaneously. These coefficients can be used to detect and estimate trends or to reconstruct signals that are of interest. The proposed CWT method was first tested on computer‐generated data exhibiting both periodic and noise components. It was then applied to observed monthly minimum streamflow observations extracted from the Reference Hydrometric Basin Network (RHBN) for five different eco‐zones in Canada.It was concluded that the proposed wavelet transform (WT) based method provides a very flexible and accurate tool for detecting and estimating complicated signals. The results from monthly minimum observations indicate that short period fluctuations are decreasing, while multi‐annual variability is increasing in Canada. And finally, a persistent ∼55‐year signal is well correlated with the Pacific Decadal Oscillation in all records, which indicates that trends are not controlled by a single factor. Copyright © 2009 John Wiley &amp; Sons, Ltd.

Identification of hydrological trends in the presence of serial and cross correlations: A review of selected methods and their application to annual flow regimes of Canadian rivers

Identification of temporal changes in hydrological regimes of river basins is an important topic in contemporary hydrology because of the potential impacts of climate change on river flow regimes. For this purpose, generally parametric and nonparametric techniques have been employed; the latter have been widely used mainly because of a fewer number of assumptions involved in their implementation. The results of these techniques when applied at local/point scales are affected by the presence of serial correlation in time series of hydrological variables and interpretation of the collective results is sensitive to cross correlation present in a hydrological network. Though challenging, often these issues have received little attention in a majority of studies on trends. This study reviews the usefulness of some selected methods for the identification of hydrological trends in the presence/absence of short-term serial and cross correlations. To facilitate easy comprehension and clear demonstration of the ability of various reviewed methods for detecting trends in time series of hydrological variables and interpreting their collective results, a complete case study of annual mean daily flows of Canadian river basins, included in the reference hydrometric basin network, is presented and discussed. Such a comparative evaluation of various methods has never been attempted earlier. Both the reviewed literature and detailed results of the case study demonstrate that failure to incorporate the effects of serial and cross correlations in the trend investigation study could result in erroneous conclusions. Hence, the old practice of identifying hydrological trends without the consideration of serial and cross correlations should be avoided and these characteristics should be given adequate attention in all studies on temporal trends.

Temporal evolution of low‐flow regimes in Canadian rivers

This study investigates temporal evolution of 1‐, 7‐, 15‐, and 30‐day annual and seasonal low‐flow regimes of pristine river basins, included in the Canadian reference hydrometric basin network (RHBN), for three time frames: 1974–2003, 1964–2003, and 1954–2003. For the analysis, the RHBN stations are classified into three categories, which correspond to stations where annual low flows occur in winter only, summer only, and both summer and winter seasons, respectively. Unlike in previous studies for the RHBN, such classification is essential to better understand and interpret the identified trends in low‐flow regimes in the RHBN. Nonparametric trend detection and bootstrap resampling approaches are used for the assessment of at‐site temporal trends under the assumption of no persistence or short‐term persistence (STP). The results of the study demonstrate that previously suggested prewhitening and trend‐free prewhitening approaches, for incorporating the effect of STP on trend significance, are not adequate for reliably identifying trends in low‐flow regimes compared to a simple bootstrap‐based approach. The analyses of 10 relatively longer records reveal that trends in low‐flow regimes exhibit fluctuating behavior, and hence, their temporal and spatial interpretations appear to be sensitive to the time frame chosen for the analysis. Furthermore, under the assumption of long‐term persistence (LTP), which is a possible explanation for the fluctuating behavior of trends, many of the significant trends in low‐flow regimes, noted under the assumption of STP, become nonsignificant and their field significance also disappears. Therefore correct identification of STP or LTP in time series of low‐flow regimes is very important as it has serious implications for the detection and interpretation of trends.

Detection of Trends in Low Flows across Canada

A study of trends and variability of low flow characteristics was conducted for the Reference Hydrometric Basin Network (RHBN). A seven-day low-flow index from 57 hydrometric stations was extracted and examined to detect trends and changes in the timing of summer and winter seven-day low-flows. A modified Mann-Kendall (MK) nonparametric trend test was applied to the time series at a 0.05 significance level. The variance of the S statistic was modified if the absolute value of serial correlation was significant at a 0.1 significance level. Numerical analysis indicated that northern Canada (stations located above latitude 60oN) experienced an increasing significant trend in seven-day low-flows. A significant downward trend dominated the Atlantic Provinces and southern British Columbia. No evidence of significant trends in the Prairies and eastern Ontario was found. Summer seven-day low-flow shifted to arrive earlier in the year in the Atlantic Provinces and southern Ontario; however, it arrived later in the year in western and northwestern Canada. In 88% of significant trends, winter seven-day low-flow shifted to arrive earlier. Although both winter and summer low flows experienced a shift towards earlier dates in the eastern part of the country, they were in opposite direction in western Canada where winter seven-day low-flows were arriving earlier whereas summer seven-day low-flows were arriving later in the year.

Spatial and Temporal Variability of Canadian Seasonal Streamflows

Abstract Wavelet and cross-wavelet analysis are used to identify and describe spatial and temporal variability in Canadian seasonal streamflows, and to gain insights into the dynamical relationship between the seasonal streamflows and the dominant modes of climate variability in the Northern Hemisphere. Results from applying continuous wavelet transform to mean seasonal streamflows from 79 rivers selected from the Canadian Reference Hydrometric Basin Network (RHBN) reveal striking climate-related features before and after the 1950s. The span of available observations, 1911–99, allows for depicting variance and covariance for periods up to 12 yr. Scale-averaged wavelet power spectra are used to simultaneously assess the temporal and spatial variability in each set of 79 seasonal streamflow time series. The most striking feature, in the 2–3-yr period and in the 3–6-yr period—the 6–12-yr period is dominated by white noise and is not considered further—is a net distinction between the timing and intensity of the temporal variability in autumn, winter, and spring–summer streamflows. It is found that the autumn season exhibits the most intense activity (or variance) in both the 2–3- and the 3–6-yr periods. The spring–summer season corresponds to the least intense activity for the 2–3-yr period, but it exhibits more activity than winter for the 3–6-yr period. Cross-wavelet analysis is provided between the seasonal streamflows and three selected climatic indices: the Pacific–North America (PNA), the North Atlantic Oscillation (NAO), and the sea surface temperature series over the Niño-3 region (ENSO3). The wavelet cross-spectra reveal strong climate–streamflow activity (or covariance) in the 2–6-yr period starting after 1950 whatever the climatic index and the season. Prior to 1950, local and weaker 2–6-yr activity is revealed in central and western Canada essentially in winter and autumn, but overall a non-significant streamflow–climate relationship is observed prior to 1950. Correlation analysis in the 2–6-yr band between the seasonal streamflow and the selected climatic indices revealed strong positive correlations with the ENSO in the spring–summer and winter seasons for the post-1950 period for both eastern and western Canada. A similar correlation pattern is revealed in the west with the NAO, while in the east moderate negative NAO correlations are observed only in the autumn season prior to 1950. After 1950 strong NAO correlations emerge for all the seasons. The cross-wavelet spectra and the correlation analysis in the 2–6-yr band suggest the presence of a change point around 1950 in the east and west seasonal streamflows.

Wavelet analysis of variability in annual Canadian streamflows

Wavelet analysis is used to identify and describe variability in annual Canadian streamflows and to gain insights into the dynamical link between the streamflows and the dominant modes of climate variability in the Northern Hemisphere. Results from applying continuous wavelet transform to mean annual streamflows from 79 rivers selected from the Canadian Reference Hydrometric Basin Network (RHBN) reveal striking climate‐related features before the 1950s and after the 1970s. The span of available observations, 1911–1999, allows for depicting variance for periods up to 12 years. Scale‐averaged wavelet power spectra are used to simultaneously assess the interannual and spatial variability in 79 annual streamflow time series. The most striking feature, in the 2–3 year band and in the 3–6 year band (the 6–12 year band is dominated by white noise (since 1950) and is not considered further) is a net distinction between the timing and intensity of the interannual variability in western, central, and eastern streamflows, which is shown to be linked to the regional climatology. It is found that for the 2–3 year band, the Canadian streamflows are depicted mainly by the Pacific North America (PNA) during 1950–1999, and the Northern Hemisphere Annular Mode (NAM) only prior to 1950, and the North Atlantic Oscillation (NAO) after 1970. Similarly, in the 3–6 year band, the streamflows are depicted mostly by the NAO, the sea surface temperature anomalies over the Niño‐3 region (ENSO3) and the PNA during the period 1950–1999, and the NAM prior to 1950. Furthermore, strong local correlations between teleconnection patterns and western, central, and eastern streamflows are also revealed in both the 2–3 and 3–6 year bands with striking changes around 1950 and 1970. The correlation analysis in the 2–3 year and 3–6 year bands revealed the presence of two change points in the west and east streamflows occurring around 1950 and 1970.

Geostatistical regional trend detection in river flow data

AbstractMany studies have identified global warming and climate change as some of the biggest challenges facing Canada. In this paper, the regional temporal trend in river flows is investigated using a space–time model. Though the primary focus is the time component, the spatial relationship among monitoring stations in a region is used to develop a space–time model that is composed of a random time trend as a function of space, and a random error term as a function of both time and space. The estimate of regional time trend is a linear combination of the differenced observations that minimizes the variance of estimated errors.Data from 248 river stations in the Reference Hydrometric Basin Network (RHBN) established by Environment Canada is analysed. These hydrological monitoring stations are grouped into ten non‐overlapping homogeneous regions covering all of Canada. An estimate of trend, along with its variance, is calculated for each region. Some significant trends are found for the annual mean, maximum and minimum flows, as well as for the mean monthly flows for July and December, and are consistent with those detected in other Canadian studies. Copyright © 2001 John Wiley &amp; Sons, Ltd.