Century‐long records reveal slight,ecoregion‐localized changes in Athabasca River flows

Reports of abruptly declining flows of Canada's Athabasca River have prompted concern because this large, free‐flowing river could be representative for northern North America, provides water for the massive Athabasca oil‐sands projects and flows to the extensive and biodiverse Peace–Athabasca, Slave and Mackenzie River deltas. To investigate historic hydrology along the river and its major tributaries, we expanded the time series with interpolations for short data gaps; calculations of annual discharges from early, summer‐only records; and by splicing records across sequential hydrometric gauges. These produced composite, century‐long records (1913–2011) and trend detection with linear Pearson correlation provided similar outcomes to nonparametric Kendall τ‐b tests. These revealed that the mountain and foothills reaches displayed slight increases in winter discharges versus larger declines in summer discharges and consequently declining annual flows (~0.16% per year at Hinton; p < 0.01). Conversely, with contrasting boreal contributions, the Athabasca River at Athabasca displayed no overall trend in monthly or annual flows, but there was correspondence with the Pacific Decadal Oscillation that contributed to a temporary flow decline from 1970 to 2000. These findings from century‐long records contrast with interpretations from numerous shorter‐term studies and emphasize the need for sufficient time series for hydrologic trend analyses. For Northern Hemisphere rivers, the study interval should be at least 80 years to span two Pacific Decadal Oscillation cycles and dampen the influence from phase transitions. Most prior trend analyses considered only a few decades, and this weakens interpretations of the hydrologic consequences of climate change. Copyright © 2014 John Wiley & Sons, Ltd.     

River flow forecasting using wavelet and cross‐wavelet transform models

In this study, short‐term river flood forecasting models based on wavelet and cross‐wavelet constituent components were developed and evaluated for forecasting daily stream flows with lead times equal to 1, 3, and 7 days. These wavelet and cross‐wavelet models were compared with artificial neural network models and simple perseverance models. This was done using data from the Skrwa Prawa River watershed in Poland. Numerical analysis was performed on daily maximum stream flow data from the Parzen station and on meteorological data from the Plock weather station in Poland. Data from 1951 to 1979 was used to train the models while data from 1980 to 1983 was used to test the models. The study showed that forecasting models based on wavelet and cross‐wavelet constituent components can be used with great accuracy as a stand‐alone forecasting method for 1 and 3 days lead time river flood forecasting, assuming that there are no significant trends in the amplitude for the same Julian day year‐to‐year, and that there is a relatively stable phase shift between the flow and meteorological time series. It was also shown that forecasting models based on wavelet and cross‐wavelet constituent components for forecasting river floods are not accurate for longer lead time forecasting such as 7 days, with the artificial neural network models providing more accurate results. Copyright © 2008 John Wiley & Sons, Ltd.     

A hydrological record extension model for reconstructing streamflows from tree‐ring chronologies

Characterizing drought events is an important factor in designing and operating water resource projects, but instrumental hydrologic records are generally short (<100 years). Because estimates of drought statistics can improve when longer records are available, we developed a stochastic model to extend instrumental streamflows based on tree‐ring chronologies. This Record Extension plus Noise (or REXTN) model consists of an autoregressive term to account for the temporal persistence of streamflows, predictor variables with longer records, and a noise term. The noise term was included to avoid underestimating the variability of the flows and to generate multiple extensions, which offer the possibility of quantifying the uncertainty of drought statistics such as the critical drought. For cases where having multiple extensions is not desirable, a statistically based algorithm was developed to select a single extended record. Using a simulation experiment, model REXTN was found to perform better than other existing reconstruction methods. The model was then applied to extend streamflows of the Poudre River, CO, USA, based on tree ring‐chronologies back to the year 1600, and the reconstructions were used to determine drought statistics such as duration and magnitude. When results based on the classical linear regression model were compared with those calculated by model REXTN, the latter was found to better match flow and drought statistics from the instrumental records, as well as to give a broader range of drought duration and magnitude. The REXTN model provides a useful addition to the range of tools available to hydrologists for coping with the uncertainty associated with water resource management under future climate scenarios. Copyright © 2014 John Wiley & Sons, Ltd.     

Temporal Gravity Variations near Shrinking Vatnajökull Ice Cap, Iceland

Repeated gravity measurements were carried out from 1991 until 1999 at sites SE of Vatnajökull, Iceland, to estimate the mass flow and deformation accompanying the shrinking of the ice cap. Published GPS data show an uplift of about 13 ± 5 mm/a near the ice margin. A gravity decrease of –2 ± 1 μGal/a relative to the Höfn base station, was observed for the same sites. Control measurements at the Höfn station showed a gravity decrease of –2 ± 0.5 µGal/a relative to the station RVIK 5473 at Reykjavík (about 250 km from Höfn). This is compatible, as a Bouguer effect, with a 10 ± 3 mm/a uplift rate of the IGS point at Höfn and an uplift rate of ~20 mm/a near the ice margin. Although the derived gravity change rates at individual sites have large uncertainties, the ensemble of the rates varies systematically and significantly with distance from the ice. The relationship between gravity and elevation changes and the shrinking ice mass is modelled as response to the loading history. The GPS data can be explained by 1-D modelling (i.e., an earth model with a 15-km thick elastic lithosphere and a 7·10¹⁷ Pa·s asthenosphere viscosity), but not the gravity data. Based on 2-D modelling, the gravity data favour a low-viscosity plume in the form of a cylinder of 80 km radius and 10¹⁷ to 10¹⁸ Pa·s viscosity below a 6 km-thick elastic lid, embedded in a layered PREM-type earth, although the elevation data are less well explained by this model. Strain-porosity-hydrology effects are likely to enhance the magnitude of the gravity changes, but need verification by drilling. More accurate data may resolve the discrepancies or suggest improved models.     

Characteristic scales, temporal variability modes and simulation of monthly Elbe River flow time series at ungauged locations

Spatial and temporal patterns of the long-range extreme monthly Elbe River flows across Germany are investigated, using various statistical methods, among others, principal component and wavelet analysis. Characteristic time scales are derived for various time series statistics. The wavelet analysis of the raw river discharge data as well as of the major principal component reveal the main oscillatory components and their temporal behavior, namely low frequency oscillations at interannual (6.9 yr) and interdecadal (13.9 yr) scales. The EOFs at ungauged stations are estimated from the principal components of the observed time series sampled over a limited time span whose length equals the major temporal variability scale (≈7 yr). The EOFs (empirical orthogonal functions) obtained in this way are subsequently used to simulate long-range flows at these locations. A comparison of this method with linear interpolation and ordinary kriging of the EOF shows the superiority of the former in representing the distributional properties of the observed time series. The simulated time series preserve also short and long-memory.     

Reconstruction of multi‐decadal groundwater level time‐series using a lumped conceptual model

Multi‐decadal groundwater level records, which provide information about long‐term variability and trends, are relatively rare. Whilst a number of studies have sought to reconstruct river flow records, there have been few attempts to reconstruct groundwater level time‐series over a number of decades. Using long rainfall and temperature records, we developed and applied a methodology to do this using a lumped conceptual model. We applied the model to six sites in the UK, in four different aquifers: Chalk, limestone, sandstone and Greensand. Acceptable models of observed monthly groundwater levels were generated at four of the sites, with maximum Nash–Sutcliffe Efficiency scores of between 0.84 and 0.93 over the calibration and evaluation periods, respectively. These four models were then used to reconstruct the monthly groundwater level time‐series over approximately 60 years back to 1910. Uncertainty in the simulated levels associated with model parameters was assessed using the Generalized Likelihood Uncertainty Estimation method. Known historical droughts and wet period in the UK are clearly identifiable in the reconstructed levels, which were compared using the Standardized Groundwater Level Index. Such reconstructed records provide additional information with which to improve estimates of the frequency, severity and duration of groundwater level extremes and their spatial coherence, which for example is important for the assessment of the yield of boreholes during drought periods. Copyright © 2016 British Geological Survey. Hydrological Processes © 2016 John Wiley & Sons Ltd     

Improved Recharge Estimation from Portable,Low‐Cost Weather Stations

Groundwater recharge estimation is a critical quantity for sustainable groundwater management. The feasibility and robustness of recharge estimation was evaluated using physical‐based modeling procedures, and data from a low‐cost weather station with remote sensor techniques in Southern Abbotsford, British Columbia, Canada. Recharge was determined using the Richards‐based vadose zone hydrological model, HYDRUS‐1D. The required meteorological data were recorded with a HOBO^TM weather station for a short observation period (about 1 year) and an existing weather station (Abbotsford A) for long‐term study purpose (27 years). Undisturbed soil cores were taken at two locations in the vicinity of the HOBO^TM weather station. The derived soil hydraulic parameters were used to characterize the soil in the numerical model. Model performance was evaluated using observed soil moisture and soil temperature data obtained from subsurface remote sensors. A rigorous sensitivity analysis was used to test the robustness of the model. Recharge during the short observation period was estimated at 863 and 816 mm. The mean annual recharge was estimated at 848 and 859 mm/year based on a time series of 27 years. The relative ratio of annual recharge‐precipitation varied from 43% to 69%. From a monthly recharge perspective, the majority (80%) of recharge due to precipitation occurred during the hydrologic winter period. The comparison of the recharge estimates with other studies indicates a good agreement. Furthermore, this method is able to predict transient recharge estimates, and can provide a reasonable tool for estimates on nutrient leaching that is often controlled by strong precipitation events and rapid infiltration of water and nitrate into the soil.     

Hydrological trend analysis with innovative and over-whitening procedures

Different statistical methodologies can be employed to identify possible trend components in any hydro-meteorological time series. A pre-whitening (P-W) procedure has been suggested to reduce the serial correlation effect on Mann-Kendall (M-K) trend analysis. In this paper, instead of P-W, an over-whitening (O-W) procedure is suggested, which generates serially independent series with the same trend slope value. Analytically necessary formulations for O-W are presented with a non-parametric but simple innovative trend assessment procedure, which are supported by extensive simulation studies. The applications of the methodology are presented for eight factual time series records from tropical, temperate and arid regions including temperature, rainfall, streamflow, relative humidity and CO₂ concentrations for different short and long durations. Relative humidity and CO₂ records are monthly time series and, hence, there are trend and periodicity components. It is noticed in all cases that the natural trends remain as they were after the O-W procedure, thus providing an opportunity to determine reliably the trends embedded even in the serially dependent series. The O-W procedure is applicable even in the cases of periodicity in the original records.     

Performance of an artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a tropical site

Performance of a feed‐forward back‐propagation artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a single meteorological station is presented. Both short‐term and long‐term forecasting was attempted, with ground level data collected by the meteorological station in Colombo, Sri Lanka (79° 52′E, 6° 54′N) during two time periods, 1994–2003 and 1869–2003. Two neural network models were developed; a one‐day‐ahead model for predicting the rainfall occurrence of the next day, which was able to make predictions with a 74·3% accuracy, and one‐year‐ahead model for yearly rainfall depth predictions with an 80·0% accuracy within a ± 5% error bound. Each of these models was extended to make predictions several time steps into the future, where accuracies were found to decrease rapidly with the number of time steps. The success rates and rainfall variability within the north‐east and south‐west monsoon seasons are also discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

Improving at-site flood frequency analysis with additional spatial information: a probabilistic regional envelope curve approach

Extreme flood events have detrimental effects on society, the economy and the environment. Widespread flooding across South East Queensland in 2011 and 2013 resulted in the loss of lives and significant cost to the economy. In this region, flood risk planning and the use of traditional flood frequency analysis (FFA) to estimate both the magnitude and frequency of the 1-in-100 year flood is severely limited by short gauging station records. On average, these records are 42 years in Eastern Australia and many have a poor representation of extreme flood events. The major aim of this study is to test the application of an alternative method to estimate flood frequency in the form of the Probabilistic Regional Envelope Curve (PREC) approach which integrates additional spatial information of extreme flood events. In order to better define and constrain a working definition of an extreme flood, an Australian Envelope Curve is also produced from available gauging station data. Results indicate that the PREC method shows significant changes to the larger recurrence intervals (≥100 years) in gauges with either too few, or too many, extreme flood events. A decision making process is provided to ascertain when this method is preferable for FFA.     

Regionalization approaches for the periodic parameters of monthly flows: a case study of Ceyhan and Seyhan River basins

Five alternative regionalization approaches in two broad categories, named function‐free and functional approaches, have been proposed to predict periodic behaviours in the basic parameters of monthly stream flows throughout homogeneous regions defined. Function‐free and functional approaches rely on the standardized (or normalized) forms of raw and fitted values of the monthly periodic parameters considered. Homogeneous regions are identified based on these standardized/normalized parameters by means of the hierarchical clustering analysis. The proposed models are tested for two major river basins in south Turkey. It is concluded that the proposed regional models are very effective to estimate periodic behaviour of monthly flows. The functional approaches are quite plausible, and the function‐free approach needs much more parameters. Both types of regionalization approaches can be reliably used to get regional monthly flow estimates for the flow sections where monthly records are not available or too short. Copyright © 2010 John Wiley & Sons, Ltd.     

HYDRODYNAMIC AND EXPERIMENTAL STUDY OF UNCONFINED GROUND WATER BALANCE ELEMENTS IN REPRESENTATIVE AND EXPERIMENTAL BASINS

Abstract

A mathematical model is built for monthly river flows of the Orinoco river. The model consists of a cyclic part which explains up to 93% of the total variance of the series of monthly water levels, and a stochastic part which is shown to follow a 1st order autoregressive scheme with a primary variable or random component that behaves as “white noise” and appears to have near 60% chance of coming from a normal population. A time series of flow anomalies is obtained from long term monthly means. Statistical techniques are applied to the series of flow anomalies in order to obtain the mean number of crossings at an arbitrary level during an arbitrary time. There are also studied the mean length of an upward excursion over an arbitrary level and the mean time between successive upcrossings. The actual results for the Orinoco river are in good agreement with the statistical theory showing that this kind of analysis can be extremely useful in the design and planning of reservoir operations. (Key words: hydrology, runoff, statistical analysis.)     

Effects of the Three Gorges Reservoir on the hydrological droughts at the downstream Yichang station during 2003–2011

Since the Three Gorges Reservoir (TGR) was put into operation in June 2003, the effects of the TGR on downstream hydrology and water resources have become the focus of public attention. This article examines the effects of the TGR on the hydrological droughts at the downstream Yichang hydrological station during 2003–2011. The two‐parameter monthly water balance model was used to generate the monthly discharges at the Yichang station for the period of 2003–2011 to represent the unregulated flow regime and thus to provide a comparison benchmark for the observed flow series at the Yichang station after the operation of the TGR. To provide a reference series for the observed monthly discharge series of the entire study period of 1951–2011, we constructed the naturalized monthly discharge series at the Yichang station by joining the observed monthly discharge at the Yichang station for the period of 1951–2002 and the two‐parameter monthly water balance simulated monthly runoff at the Yichang station for the period of 2003–2011. For both the observed and naturalized monthly discharge series of 1951–2011, the hydrological drought index series were calculated using the standardized streamflow index method. By comparing the drought indices of these two monthly discharge series, we investigated the effects of the TGR on the hydrological droughts at the downstream Yichang station during 2003–2011. The results show that the hydrological droughts at the downstream Yichang station are slightly aggravated by the TGR's initial operation from 2003 to 2011. The river flow reduction at the Yichang station after impoundment of the TGR might account for the downstream drought aggravation. Copyright © 2012 John Wiley & Sons, Ltd.     

Trends and multi‐annual variability of water temperatures in the river Danube,Serbia

The relationship between air (Ta) and water temperature (Tw) is very important because it shows how the temperature of a water body might respond to future changes in surface Ta. Mean monthly Tw records of three gauging stations (Bezdan, Bogojevo i Veliko Gradi?te) were analysed alongside mean monthly discharge (Q) for the same stations. Additionally, Ta series from two meteorological stations (Sombor and Veliko Gradi?te) were correlated with Tw variations over the period 1950–2012. Locally weighted scatter point smoothing (LOWESS) was used to investigate long‐term trends in the raw data, alongside the Mann–Kendall (MK) trend test. Trend significance was established using Yue–Pilon's pre‐whitening approaches to determine trends in climate data. Also, the rescaled adjusted partial sums (RAPS) method was used to detect dates of possible changes in the time series. Statistically significant warming trends were observed for annual and seasonal minimum and maximum Tw at all investigated sites. The strongest warming was observed at Bogojevo gauging station for seasonal maximum Tw, with +0.05 °C per year on average. RAPS established that the trend began in the 1980s. This behaviour is linked to climate patterns in the North and East Atlantic which determine the amount of heat advected onto mainland Europe. Statistically significant correlations were found for all Tw on an annual basis. Overall, the strongest correlations (p < 0.01) between Tw residuals and the North Atlantic Oscillation (NAO) were recorded for the winter period. These findings suggest possible predictability of Tw over seasonal time‐scales. Copyright © 2016 John Wiley & Sons, Ltd.     

A model for daily flows of intermittent streams

A stochastic model for synthetic data generation is not available in the literature for daily flows of intermittent streams. Such a model is required in the planning and operation of structures on an intermittent stream for purposes where short time flow fluctuations are important. In this study a model is developed for such a case. The model consists of four steps: determination of the days on which flow occurs, determination of the days on which a flow increment occurs, determination of the magnitude of the flow increment, and calculation of the flow decrement on days when the flow is reduced. The first two steps are modelled by a three‐state Markov chain. In the third step, flow increments on the rising limb of the hydrograph are assumed to be gamma distributed. In the last step an exponential recession is used with two different coefficients. Parameters of the model are estimated from the observed daily stream flow data for each month of the year. The model is applied to a daily flow series of 35 years' length. It is seen that the model can preserve the short‐term characteristics (the ascension and recession curves and peaks) of the hydrograph in addition to the long‐term characteristics (mean, variance, skewness, lag‐one and higher lag autocorrelation coefficients, and zero flow percentage). The number of parameters of the model can be decreased by fitting Fourier series to their annual variation. Copyright © 2000 John Wiley & Sons, Ltd.     

Long‐term variations and temporal scaling of hydroclimatic time series with focus on the German part of the Elbe River Basin

Long‐term variations and temporal scaling of mean monthly time series of river flow, precipitation, temperature, relative humidity, air pressure, duration of bright sunshine, degree of cloud cover, short wave radiation, wind speed and potential evaporation within or in vicinity of the German part of the Elbe River Basin are analyzed. Statistically significant correlations between the 2–15 year scale‐averaged wavelet spectra of the hydroclimatic variables and the North Atlantic Oscillation‐ and Arctic Oscillation index are found which suggests that such long‐term patterns in hydroclimatic time series are externally forced. The Hurst parameter estimates (H) based on the Detrended Fluctuation Analysis (DFA) indicate persistence for discharge, precipitation, wind speed, air pressure and the degree of cloud cover, all having an annual cycle and a broad low‐frequency distribution. Also, DFA H parameter estimates are higher for discharge than for precipitation. The major long‐term quasi‐periodic variability modes of precipitation detected using Singular Spectrum Analysis coincide with those detected in the discharge time series. Upon subtraction of these low‐frequency quasi‐periodic modes, the DFA H parameter estimates suggest absence of the persistence for both precipitation and discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

Changes and variation in the discharge regime of the Upper Suriname River Basin and its relationship with the tropical Pacific and Atlantic SST anomalies

Long‐term changes and variability in river flows in the tropical Upper Suriname River Basin in Suriname (2–6°N, 54–58°W) are analysed, including the relation to sea surface temperatures (SSTs) in the tropical Atlantic and Pacific Ocean. To analyse variability, lag correlation and statistical properties of the data series are used. Long‐term changes are analysed using parametric and non‐parametric statistical techniques. The analyses are performed for the period 1952–1985. The results show that both river discharge series at Semoisie and Pokigron are non‐stationary and have a negative trend. The negative rainfall trend in the centre of Suriname may be responsible for the negative trend in the annual river discharges in the basin. The highest correlation (Pearson's coefficient c) is obtained when the Tropical North Atlantic (TNA) SSTs lags the monthly discharges at Pokigron by 3–4 months (c = 0·7) and when the Tropical South Atlantic (TSA) SSTs lags the discharges by 4 months (c = ? 0·7). It also follows that the high (low) monthly flows, from April–August (September–March) are associated with increasing (decreasing) SSTs in the TNA and with decreasing (increasing) SSTs in the TSA. The results also reveal that years with low (high) discharges are more related to warmer (colder) SSTs during the year in the TNA region and a southward displacement of the Inter‐Tropical Convergence Zone (ITCZ). However, the Pacific El Niño (La Niña) events may also be responsible for low (high) flow years in this basin. Copyright © 2007 John Wiley & Sons, Ltd.     

Linear and non‐linear scaling of the Yangtze River flow

Power law correlation properties of sign and magnitude series have been studied based on the series of observation records of flow of the River Yangtze. The results obtained give improved insight into and understanding of the linear and non‐linear processes of the water cycle. With the newly developed Delayed Vector Variance method and the surrogate test, the documented linkage between the sign series and the linear process, and that between the magnitude series and non‐linear process can be verified. The spectra estimated by detrended fluctuation analysis method show different properties of intra‐annual and inter‐annual correlations in both sign and magnitude series. The linear process behaves as an 1/f noise at a time scale less than about 60 days, but shows features of anti‐persistence in terms of long‐term fluctuation. The magnitudes are clustered in three ways mainly caused by non‐linear processes, i.e. periodic clustering, strong short‐term clustering of 1/f noise at time scales less than 20 days, and long‐term clustering with weak persistence. Copyright © 2007 John Wiley & Sons, Ltd.     

Long‐term trend analysis for precipitation in Asian Pacific FRIEND river basins

In order to analyse the long‐term trend of precipitation in the Asian Pacific FRIEND region, records from 30 river basins to represent the large range of climatic and hydrological characteristics in the study area are selected. The long‐term trend in precipitation time series and its association with the southern oscillation index (SOI) series are investigated. Application of the nonparametric Mann–Kendall test for 30 precipitation time series has shown that only four of these 30 time series have a long‐term trend at the 5% level of significance. Nevertheless, most of the records tend to decrease over the last several decades. The dataset is further divided geographically into northern, middle, and southern zones, with 20°N and 20°S latitude as the dividing lines. The middle zone has the greatest variation and the southern zone the least variation over the past century. Also, the southern zone has greater variation during the past 30 years. The association between precipitation and SOI is investigated by dividing the precipitation records of each station into El Niño, La Niña, and neutral periods. The Wilcoxon rank‐sum test showed that differences in precipitation for the three classes were most marked in the southern zone of the study area. The frequencies of below‐ and above‐average precipitation for El Niño, La Niña, and neutral periods are estimated for the 30 precipitation time series as well. The results show that the frequencies of precipitation under each set of conditions, with lower precipitation generally associated with El Niño periods in the southern zone. Copyright © 2005 John Wiley & Sons, Ltd.     

Estimation of effect of unequal secular variation on geomagnetic data reduction

The geomagnetic field components are periodically measured at repeat stations. The main objective of the repeat stations is to provide data for tracing the secular variation of the geomagnetic field components. Secular variation at the repeat station is generally different from that at geomagnetic observatory used in the data reduction. The effect of the secular variation differences on geomagnetic data reduction was estimated for the regions of Europe, North America (below 60°N) and Australia, respectively, during the period of 2000-2010. These estimations were obtained by using the monthly mean values of north, east and vertical components of geomagnetic field, recorded at geomagnetic observatories. The effects were calculated by using observatories pairs, with distances from 350 km (in Europe) to 3100 km (in North America and Australia). The maximal effects were found to be the smallest in east component in Europe and North America, and vertical component in Australia; the effects increase with time from a central reduction epoch and they are not constant during mentioned eleven years; they were less than 1 nT only in Europe, for distances between the observatories up to 1000 km in all three components and for periods spanning ±1 month from a central epoch. It was found that their year to year variability is mostly due to the non-eliminated external field residuals in the observatories monthly means; their effect is up to 3 nT for ±3 months from a central epoch. Further, the real effects were compared to those modeled by IGRF-12 model. The maximal differences between the real and the modeled values are below 4.5 nT in all three components, for ±3 months from a central epoch.