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 Using satellite altimetry and tide gauges for storm surge warning

2015 ◽  
Vol 365 ◽  
pp. 28-34
Author(s):  
O. B. Andersen ◽  
Y. Cheng ◽  
X. Deng ◽  
M. Steward ◽  
Z. Gharineiat
Keyword(s):  
Storm Surge ◽  
North Sea ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Deep Ocean ◽  
High Water ◽  
Tide Gauges ◽  
Temporal Sampling ◽  
The North ◽  
The North Sea

Abstract. The combination of the coarse temporal sampling by satellite altimeters in the deep ocean with the high temporal sampling at sparsely located tide gauges along the coast has been used to improve the forecast of high water for the North Sea along the Danish Coast and for the northeast coast of Australia. For both locations we have tried to investigate the possibilities and limitations of the use of satellite altimetry to capture high frequency signals (surges) using data from the past 20 years. The two regions are chosen to represent extra-tropical and tropical storm surge conditions. We have selected several representative high water events on the two continents based on tide gauge recordings and investigated the capability of satellite altimetry to capture these events in the sea surface height data. Due to the lack of recent surges in the North Sea we focused on general high water level and found that in the presence of two or more satellites we could capture more than 90% of the high water sea level events. In the Great Barrier Reef section of the northeast Australian coast, we have investigated several large tropical cyclones; one of these being Cyclone Larry, which hit the Queensland coast in March 2006 and caused both loss of lives as well as huge devastation. Here we demonstrate the importance of integrating tide gauges with satellite altimetry for forecasting high water at the city of Townsville in northeast Australia.

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.

Analysis and prediction of storm water levels in Delaware inland bays

Shore & Beach ◽  
2019 ◽  
pp. 29-35
Author(s):  
Michele Strazzella ◽  
Nobuhisa Kobayashu ◽  
Tingting Zhu
Keyword(s):  
Analytical Model ◽  
Tide Gauge ◽  
Hurricane Sandy ◽  
Water Levels ◽  
Tide Gauges ◽  
Storm Tide ◽  
Barrier Beach ◽  
Wave Overtopping ◽  
Inland Bays ◽  
Damping Parameter

A simple approach based on an analytical model and available tide gauge data is proposed for the analysis of storm tide damping inside inland bays with complex bathymetry and for the prediction of peak water levels at gauge locations during storms. The approach was applied to eight tide gauges in the vicinity of inland bays in Delaware. Peak water levels at the gauge locations were analyzed for 34 storms during 2005-2017. A damping parameter in the analytical model was calibrated for each bay gauge. The calibrated model predicted the peak water levels within errors of about 0.2 m except for Hurricane Sandy in 2012. The analytical model including wave overtopping was used to estimate the peak wave overtopping rate over the barrier beach from the measured peak water level in the adjacent bay.

scholarly journals Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 387
Author(s):  
Yiting Liang ◽  
Yuanhua Zhang ◽  
Yonggang Li
Keyword(s):  
Parameter Estimation ◽  
Kinetic Model ◽  
Model Parameters ◽  
Hydrogen Ions ◽  
Removal Process ◽  
Cobalt Removal ◽  
Estimation Scheme ◽  
Zinc Hydrometallurgy ◽  
The Impact ◽  
Parameter Estimation Scheme

A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.

A Robust Method for Parameter Estimation from Catch and Effort Data

1989 ◽  
Vol 46 (1) ◽  
pp. 137-144 ◽  
Author(s):  
D. Ludwig ◽  
C. J. Walters
Keyword(s):  
Parameter Estimation ◽  
Robust Estimation ◽  
Robust Method ◽  
Amount Of Information ◽  
Surplus Production ◽  
Production Models ◽  
Composite Estimation ◽  
Estimation Scheme

The problem of robust estimation of optimal effort levels from surplus production models is considered. A variety of models are used to generate data, for the purpose of testing estimation schemes. The result of an estimation is an estimate of the optimal effort. These efforts are compared using the expected discounted value of a deterministic stock, which corresponds to the model used to generate the data. Such a criterion takes into account not only the loss due to bias in the estimated optimal effort, but also the loss due to the variance of the estimator. Estimation is difficult if there is a lack of informative variation in effort levels or stock sizes. In such cases, the estimation scheme which maximizes the criterion described above sacrifices realism in the representation of the stock-production relationship in order to reduce the variance of the estimate of optimal effort. We present a composite estimation scheme which performs acceptably in all the cases we have examined, and whose performance degrades slowly as the amount of information in the data decreases.

scholarly journals Testing an “IoT” Tide Gauge Network for Coastal Monitoring

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 17-32
Author(s):  
Philip Knight ◽  
Cai Bird ◽  
Alex Sinclair ◽  
Jonathan Higham ◽  
Andy Plater
Keyword(s):  
Sea Level ◽  
Morphological Changes ◽  
Tide Gauge ◽  
Low Cost ◽  
Pressure Sensors ◽  
Wave Activity ◽  
Tide Gauges ◽  
Coastal Monitoring ◽  
Level Data ◽  
Operational Constraints

A low-cost “Internet of Things” (IoT) tide gauge network was developed to provide real-time and “delayed mode” sea-level data to support monitoring of spatial and temporal coastal morphological changes. It is based on the Arduino Sigfox MKR 1200 micro-controller platform with a Measurement Specialties pressure sensor (MS5837). Experiments at two sites colocated with established tide gauges show that these inexpensive pressure sensors can make accurate sea-level measurements. While these pressure sensors are capable of ~1 cm accuracy, as with other comparable gauges, the effect of significant wave activity can distort the overall sea-level measurements. Various off-the-shelf hardware and software configurations were tested to provide complementary data as part of a localized network and to overcome operational constraints, such as lack of suitable infrastructure for mounting the tide gauges and for exposed beach locations.

scholarly journals Inverse distributed hydrological modelling of Alpine catchments

2006 ◽  
Vol 10 (3) ◽  
pp. 395-412 ◽  
Author(s):  
H. Kunstmann ◽  
J. Krause ◽  
S. Mayr
Keyword(s):  
Parameter Estimation ◽  
Hydrological Model ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Nonlinear Parameter ◽  
Model Complexity ◽  
Distributed Hydrological Model ◽  
Nonlinear Parameter Estimation ◽  
Estimated Parameters ◽  
Physically Based

Abstract. Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical groundwater model partly yielded a slight decrease of overall model performance when compared to a simple conceptual groundwater approach. Increased model complexity therefore did not yield in general increased model performance. A detailed covariance analysis was performed allowing to derive confidence bounds for all estimated parameters. The correlation between the estimated parameters was in most cases negligible, showing that parameters were estimated independently from each other.

scholarly journals Recent sea level rise on Ireland's east coast based on multiple tide gauge analysis

2020 ◽  
Author(s):  
Amin Shoari Nejad ◽  
Andrew C. Parnell ◽  
Alice Greene ◽  
Brian P. Kelleher ◽  
Gerard McCarthy
Keyword(s):  
Time Series ◽  
Sea Level Rise ◽  
Sea Level ◽  
Continuous Time ◽  
East Coast ◽  
Tide Gauge ◽  
Tide Gauges ◽  
Missing Value ◽  
Global Average ◽  
Good Agreement

Abstract. We analysed multiple tide gauges from the east coast of Ireland over the period 1938–2018. We validated the different time series against each other and performed a missing value imputation exercise, which enabled us to produce a homogenised record. The recordings of all tide gauges were found to be in good agreement between 2003–2015, though this was markedly less so from 2016 to the present. We estimate the sea level rise in Dublin port for this period at 10 mm yr−1. The rate over the longer period of 1938–2015 was 1.67 mm yr−1 which is in good agreement with the global average. We found that the rate of sea level rise in the longer term record is cyclic with some extreme upward and downward trends. However, starting around 1980, Dublin has seen significantly higher rates that have been always positive since 1996, and this is mirrored in the surrounding gauges. Furthermore, our analysis indicates an increase in sea level variability since 1980. Both decadal rates and continuous time rates are calculated and provided with uncertainties in this paper.

Sign in / Sign up

Export Citation Format

Share Document