scholarly journals Sedimentological data-driven bottom friction parameter estimation in modelling Bristol Channel tidal dynamics

2021 ◽  
Author(s):  
Simon Warder ◽  
Athanasios Angeloudis ◽  
Matthew Piggott
Keyword(s):  
Parameter Estimation ◽  
Model Performance ◽  
Resource Assessment ◽  
Tidal Currents ◽  
Bottom Friction ◽  
Tidal Range ◽  
Piecewise Constant ◽  
Sea Bed ◽  
Tidal Stream

Accurately representing the bottom friction effect is a significant challenge in numerical tidal models. Bottom friction effects are commonly defined via parameter estimation techniques. However, the bottom friction coefficient (BFC) can be related to the roughness of the sea bed. Therefore, sedimentological data can be beneficial in estimating BFCs. Taking the Bristol Channel and Severn Estuary as a case study, we perform a number of BFC parameter estimation experiments, utilising sedimentological data in a variety of ways. Model performance is explored through the results of each parameter estimation experiment, including applications to tidal range and tidal stream resource assessment. We find that theoretically derived sediment-based BFCs are in most cases detrimental to model performance. However, good performance is obtained by retaining the spatial information provided by the sedimentological data in the formulation of the parameter estimation experiment; the spatially varying BFC can be represented as a piecewise-constant field following the spatial distribution of the observed sediment types. By solving the resulting low-dimensional parameter estimation problem, we obtain good model performance as measured against tide gauge data. This approach appears well suited to modelling tidal range energy resource, which is of particular interest in the case study region. However, the applicability of this approach for tidal stream resource assessment is limited, since modelled tidal currents exhibit a strong localised response to the BFC; the use of piecewise-constant (and therefore discontinuous) BFCs is found to be detrimental to model performance for tidal currents.

scholarly journals Investigation of the Modulation of the Tidal Stream Resource by Ocean Currents through a Complex Tidal Channel

2019 ◽  
Vol 7 (10) ◽  
pp. 341 ◽  
Author(s):  
Alice J. Goward Brown ◽  
Matt Lewis ◽  
Benjamin I. Barton ◽  
Gus Jeans ◽  
Steven A. Spall
Keyword(s):  
Tidal Energy ◽  
Resource Assessment ◽  
Tidal Currents ◽  
The West ◽  
Ocean Modelling ◽  
Through Flow ◽  
The World ◽  
Tidal Stream ◽  
Flow Through ◽  
Resource Uncertainty

Tidal energy has the opportunity to bring reliable electricity to remote regions in the world. A resource assessment, including the response of the tidal stream resource to fluctuations in the Indonesian Through Flow (ITF) is performed using the Regional Ocean Modelling System (ROMS) to simulate four different scenarios for flow through the Lombok Strait in Indonesia. Tidal currents simulated with a variable ITF are compared against a tide-only (TO) simulation to identify how the ITF spatially changes the resource across the Lombok Strait. We find that the uncertainty in the tidal currents from the TO simulation is 50% greater than the variable ITF simulation. To identify change to resource, surface velocities from Strong ITF and Weak ITF scenarios are considered. As a result of the fluctuations in the ITF, certain characteristics, such as the asymmetry and magnitude, of the tidal current vary greatly. However, the magnitude of change is variable, with regions to the west of the strait experiencing greater modulation than in the east, suggesting that resource uncertainty can be minimised with selective site positioning.

scholarly journals Hydrological model performance and parameter estimation in the wavelet-domain

2009 ◽  
Vol 6 (2) ◽  
pp. 2451-2498 ◽  
Author(s):  
B. Schaefli ◽  
E. Zehe
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Time Domain ◽  
Model Performance ◽  
Time Varying ◽  
Wavelet Domain ◽  
Frequency Content ◽  
Time Varying Frequency ◽  
The Time Domain

Abstract. This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights which frequencies are not well reproduced by the model, which gives specific indications about how to improve the model structure.

Tides of the Ross Sea and Ross Ice Shelf cavity

2003 ◽  
Vol 15 (1) ◽  
pp. 31-40 ◽  
Author(s):  
LAURENCE PADMAN ◽  
SVETLANA EROFEEVA ◽  
IAN JOUGHIN
Keyword(s):  
Ross Sea ◽  
Spring Tide ◽  
Model Performance ◽  
Tidal Currents ◽  
Tidal Range ◽  
Ocean Tide ◽  
Shelf Area ◽  
Ice Shelf ◽  
Ross Ice Shelf ◽  
Ocean Tide Models

Two new ocean tide models for the Ross Sea including the ocean cavity under the Ross Ice Shelf, are described. The optimum model for predicting ice shelf surface height variability is based on assimilation of gravimetry-derived tidal constituents from the Ross Ice Shelf. Synthetic aperture radar interferograms provide an independent test of model performance. The standard deviation of tide height variability is largest under the eastern ice shelf along the Shirase and Siple Coasts, where it can exceed 0.8 m. The maximum peak-to-peak tidal range in this region is ∼3 m. The best predictor for ocean tidal currents north of the ice front is a dynamics-based model that solves the depth-integrated shallow water equations with a linear representation of benthic friction rather than the more usual quadratic form. Tidal currents over the open Ross Sea are dominated by diurnal, topographically trapped vorticity waves. The strongest modelled currents exceed 1 m s−1 at spring tide in a narrow band along the upper continental slope in the north-western Ross Sea. Typical tidal currents in the central continental shelf area of the Ross Sea are 10–20 cm s−1. Under the ice shelf the typical currents are ∼5 cm s−1.

scholarly journals Parameter Estimation to Improve Coastal Accuracy in a Global Tide Model

2021 ◽  
Author(s):  
Xiaohui Wang ◽  
Martin Verlaan ◽  
Jelmer Veenstra ◽  
Hai Xiang Lin
Keyword(s):  
Parameter Estimation ◽  
Tide Gauge ◽  
Model Performance ◽  
Deep Ocean ◽  
Bottom Friction ◽  
Shallow Waters ◽  
Hudson Bay ◽  
Tide Gauges ◽  
Estimation Scheme ◽  
Memory Efficient

Abstract. Global tide and surge models play a major role in forecasting coastal flooding due to extreme events or climate change. The model performance is strongly affected by parameters such as bathymetry and bottom friction. In this study, we propose a method that estimates bathymetry globally and the bottom friction coefficient in the shallow waters for a Global Tide and Surge Model (GTSMv4.1). However, the estimation effect is limited by the scarcity of available tide gauges. We propose to complement sparse tide gauges with tide time-series generated using FES2014. The FES2014 dataset outperforms GTSM in most areas and is used as observations for the deep ocean and some coastal areas, such as Hudson Bay/Labrador, where tide gauges are scarce but energy dissipation is large. The experiment is performed with a computation and memory efficient iterative parameter estimation scheme applied to Global Tide and Surge Model (GTSMv4.1). Estimation results show that model performance is significantly improved for deep ocean and shallow waters, especially in the European Shelf directly using the CMEMS tide gauge data in the estimation. GTSM is also validated by comparing to tide gauges from UHSLC, CMEMS, and some Arctic stations in the year 2014.

scholarly journals Hydrological model performance and parameter estimation in the wavelet-domain

2009 ◽  
Vol 13 (10) ◽  
pp. 1921-1936 ◽  
Author(s):  
B. Schaefli ◽  
E. Zehe
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Time Domain ◽  
Model Performance ◽  
Time Varying ◽  
Wavelet Domain ◽  
Frequency Content ◽  
Time Varying Frequency ◽  
The Time Domain

Abstract. This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights the frequencies that are not well reproduced by the model, which gives specific indications about how to improve the model structure.

scholarly journals Optimizing the Environmental and Economic Sustainability of Remote Community Infrastructure

2020 ◽  
Vol 12 (6) ◽  
pp. 2208 ◽  
Author(s):  
Jamie E. Filer ◽  
Justin D. Delorit ◽  
Andrew J. Hoisington ◽  
Steven J. Schuldt
Keyword(s):  
Environmental Impacts ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Assessment Model ◽  
Remote Communities ◽  
Remote Community ◽  
Rural Villages ◽  
Sustainable Technologies ◽  
Study Results

Remote communities such as rural villages, post-disaster housing camps, and military forward operating bases are often located in remote and hostile areas with limited or no access to established infrastructure grids. Operating these communities with conventional assets requires constant resupply, which yields a significant logistical burden, creates negative environmental impacts, and increases costs. For example, a 2000-member isolated village in northern Canada relying on diesel generators required 8.6 million USD of fuel per year and emitted 8500 tons of carbon dioxide. Remote community planners can mitigate these negative impacts by selecting sustainable technologies that minimize resource consumption and emissions. However, the alternatives often come at a higher procurement cost and mobilization requirement. To assist planners with this challenging task, this paper presents the development of a novel infrastructure sustainability assessment model capable of generating optimal tradeoffs between minimizing environmental impacts and minimizing life-cycle costs over the community’s anticipated lifespan. Model performance was evaluated using a case study of a hypothetical 500-person remote military base with 864 feasible infrastructure portfolios and 48 procedural portfolios. The case study results demonstrated the model’s novel capability to assist planners in identifying optimal combinations of infrastructure alternatives that minimize negative sustainability impacts, leading to remote communities that are more self-sufficient with reduced emissions and costs.

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