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Reconstructing tidal signals is indispensable for verifying altimetry products, forecasting water levels, and evaluating long-term trends. Uncertainties in the estimated tidal parameters must be carefully assessed to adequately select the relevant tidal constituents and evaluate the accuracy of the reconstructed water levels. Customary harmonic analysis uses ordinary least squares (OLS) regressions for their simplicity. However, the OLS may lead to incorrect estimations of the regression coefficient uncertainty due to the neglect of the residual autocorrelation. This study introduces two residual resamplings (moving-block and semiparametric bootstraps) for estimating the variability of tidal regression parameters and shows that they are powerful methods to assess the effects of regression errors with nontrivial autocorrelation structures. A Monte Carlo experiment compares their performance to four analytical procedures selected from those provided by the RT_Tide, UTide, and NS_Tide packages and the robustfit.m MATLAB function. In the Monte Carlo experiment, an iteratively reweighted least squares (IRLS) regression is used to estimate the tidal parameters for hourly simulations of one-dimensional water levels. Generally, robustfit.m and the considered RT_Tide method overestimate the tidal amplitude variability, while the selected UTide and NS_Tide approaches underestimate it. After some substantial methodological corrections the selected NS_Tide method shows adequate performance. As a result, estimating the regression variance–covariance with the considered RT_Tide, UTide, and NS_Tide methods may lead to the erroneous selection of constituents and underestimation of water level uncertainty, compromising the validity of their results in some applications. Significance Statement: At many locations, the production of reliable water level predictions for marine navigation, emergency response, and adaptation to extreme weather relies on the precise modeling of tides. However, the complicated interaction between tides, weather, and other climatological processes may generate large uncertainties in tidal predictions. In this study, we investigate how different statistical methods may lead to different quantification of tidal model uncertainty when using data with completely known properties (e.g., knowing the tidal signal, as well as the amount and structure of noise). The main finding is that most commonly used statistical methods may estimate incorrectly the uncertainty in tidal parameters and predictions. This inconsistency is due to some specific simplifying assumptions underlying the analysis and may be reduced using statistical techniques based on data resampling. [ABSTRACT FROM AUTHOR]

This is the second part of an investigation aimed at documenting the tidal hydrodynamics of the St. Lawrence fluvial estuary (SLFE). In Part I, the calibration and validation of a high-resolution, two-dimensional (2D), time-dependent hydrodynamic model of the SLFE was presented. Herein, the process-based (structural) validation procedure used to quantitatively assess the ability of the model to reproduce spatial and temporal patterns observed in the field data is presented. Tidal and flow features were found to be reproduced satisfactorily in terms of their lateral and longitudinal variability at both the intratidal and fortnightly scales. These properties can be used to describe the real system dynamics, including flooding--drying processes, tidal propagation and modulation, and transient momentum balance, providing insights into the general physical processes of the SLFE and of large tidal rivers globally. [ABSTRACT FROM AUTHOR]

In this study, a high-resolution, two-dimensional (2D), time-dependent hydrodynamic model of the St. Lawrence fluvial estuary was developed with the objective of documenting the tidal hydrodynamics of this complex yet poorly understood region. The hydrodynamic model solves the shallow-water equations over a finite-element--discretized domain, with an average spatial resolution of 50 m, and includes a drying--wetting component for the treatment of shallow intertidal areas. The numerical terrain model is composed of high-density topographic data and detailed friction fields associated with bottom substrate and macrophytes. Calibration and validation were carried out using recently acquired data for water level and velocity. Results show very good accuracy in water levels, with prediction skills higher than 0.99 at all stations (where a skill of 1 means perfect agreement between model and observations in terms of their relative average error) and root-mean-square errors (RMSEs) less than 5% of local tidal ranges downstream; at upstream stations where tidal ranges are significantly reduced, RMSEs were lower than 6 cm. Discharges were reproduced with similarly good accuracy, with errors lower than 6% of the maximum observed discharges at 11 of the 13 surveyed transects; the two remaining sections are subject to larger interpolation and bathymetric uncertainties. In this paper, critical aspects of model development are discussed, including the 2D approximation, temporal and spatial resolution, bathymetric uncertainty, error in the boundary conditions, and calibration under nonstationary conditions. This work is the first part of a two-part investigation serving as a methodological framework for model setup, calibration, and validation in large tidal rivers. [ABSTRACT FROM AUTHOR]

Cross-sectional gradients in water levels and velocities play a determining role in the circulation dynamics of tidal rivers and estuaries. Documenting and analyzing their variability throughout a tidal cycle require observations with high spatial and temporal resolution. A survey strategy and a data analysis procedure have been designed to obtain continuous and synoptic water level and velocity fields over a tidal cycle, along 13 cross-sections of the St. Lawrence fluvial estuary dominated by large tidal ranges. The method combines both RTK GPS and ADCP technologies for the simultaneous measurement of water levels and velocities along repeated boat transects, allowing fast data acquisition over wide river sections and under rapidly changing conditions. The reconstruction of continuous and synoptic fields is made by interpolation. Simplifying assumptions about data stationarity and/or homogeneity are avoided by adapting the interpolation procedures to the shape and distribution of the underlying data in a space-time reference frame, thus minimizing distortion in the reconstructed quantities. The capabilities and limitations of the method are assessed through error computations and comparisons with alternate data analysis methods and complementary data sets from tide gauges. With these latest observations, new insights into the tidal hydrodynamics of the St. Lawrence fluvial estuary are gained in regions of contrasting tidal and fluvial properties, specifically related to the effects of channel curvature and bathymetry on tidal propagation and cross-channel flow properties at the intratidal scale. [ABSTRACT FROM AUTHOR]

One of the most challenging areas in tidal analysis is the study of nonstationary signals with a tidal component, as they confront both current analysis methods and dynamical understanding. A new analysis tool has been developed, NS_TIDE, adapted to the study of nonstationary signals, in this case, river tides. It builds the nonstationary forcing directly into the tidal basis functions. It is implemented by modification of T_TIDE; however, certain concepts, particularly the meaning of a constituent and the Rayleigh criterion, are redefined to account for the smearing effects on the tidal spectral lines by nontidal energy. An error estimation procedure is included that constructs a covariance matrix of the regression coefficients, based on either an uncorrelated or a correlated noise model. The output of NS_TIDE consists of time series of subtidal water levels [mean water level (MWL)] and tidal properties (amplitudes and phases), expressed in terms of external forcing functions. The method was tested using records from a station on the Columbia River, 172 km from the ocean entrance, where the tides are strongly altered by river flow. NS_TIDE hindcast explains 96.4% of the signal variance with a root-mean-square error of 0.165 m obtained from 288 parameters, far better than traditional harmonic analysis (38.5%, 0.604 m, and 127 parameters). While keeping the benefits of harmonic analysis, its advantages compared to existing tidal analysis methods include its capacity to distinguish frequencies within tidal bands without losing resolution in the time domain or data at the endpoints of the time series. [ABSTRACT FROM AUTHOR]

Estuarine salt marshes globally face numerous threats, not least of which include changing hydrological conditions from human alteration and climate change impact to river flows, sea levels and coastal processes. While changing inundation is evident in many systems, often, the detail of which estuarine processes are changing and to what extent they contribute to flooding and habitat distribution remains unknown. Water levels in the microtidal Swan River Estuary (Derbarl Yerrigan), Western Australia, which has experienced significant climate drying since the 1970's, were disaggregated to assess contributions from tides, mean sea level, barometric effects, river flows and river-tide interactions. These contributions were mapped to the habitat of a salt marsh community. The effect of declining river flows on tides were further assessed by wavelet and harmonic analyses. We found that tides and barometric effects presently dominate flooding events of relevance to the salt marsh community. Declining winter runoff resulted in an increase in the tidal amplitude in the upper estuary. There was also a positive winter mean sea level pressure trend, associated with the winter rainfall decline. Altogether, there was zero net change to flooding of a salt marsh in the estuary from these processes. Therefore, steady sea level rise masked changes in the relative contribution of flooding mechanisms in the estuary which have implications for the stability of the marsh ecosystem. Disaggregating process contributions to salt marsh water levels offers a means to better assess the hydrodynamic processes presently sustaining salt marsh communities and to inform how they might change in the future. These results show that numerous hydrological processes can interact to mask non-stationary changes to estuarine hydrology supporting salt marsh habitat. • Processes flooding a salt marsh in a micro-tidal estuary disaggregated. • Drying climate and sea-level rise impact estuary hydrodynamics. • Declining river runoff and rising air pressure decrease flooding pressure. • Tidal amplification and rising sea-level increased flooding pressure. • Stationary flooding masks non-stationary estuarine hydrodynamics. [ABSTRACT FROM AUTHOR]