Changing coastlines: data assimilation for morphodynamic prediction and predictability
Lead Research Organisation:
University of Reading
Department Name: Mathematics and Statistics
Abstract
In 2005, severe flooding in the aftermath of Hurricane Katrina focussed the world's attention on the importance of accurate knowledge of the topography of the coastal zone in natural disaster management and prediction. The topography of the sea floor, generally known as the bathymetry, evolves over time as sediment is eroded, transported and deposited by water action. The change in bathymetry itself changes the motion of the water, which is also influenced by tides and weather patterns, such as storm surges. An accurate, up-to-date knowledge of coastal bathymetry would allow improved flood forecasting. Improved prediction of future bathymetry, and knowledge of the uncertainty in that prediction, would allow construction of better sea defences, better management of coastal habitats, and better understanding of the effects of changes in land use near the coast. It may also provide better understanding of the effects of climate change (e.g. sea level rise, and increased numbers of extreme storm events) on the longer-term evolution of an estuary. Coastal sediment transport models are becoming increasingly sophisticated. However, observed bathymetric samples typically only provide partial coverage of the domain of such a model. Hence, initialisation of such models using only a set of recent observations is not feasible. The effective and efficient use of limited data, such as these, requires state-of-the-art mathematical, statistical and computational methods, known as data assimilation techniques. Data assimilation combines empirical observations with model predictions to give more accurate and well-calibrated forecasts and enables the uncertainties in the forecasts to be calculated. Whilst data assimilation has been in use in the context of atmospheric and oceanic prediction for some years, its use in the context of coastal sediment modelling is novel. This project will use data assimilation techniques with a coastal sediment transport model to maintain up-to-date near-shore bathymetry, predict future bathymetry, answer statistical questions regarding uncertainty and predictability, gain insight into physical processes taking place during intense storm events and to design an optimal observation strategy for coastal monitoring. Three coastal sites have been identified for numerical experiments. Methodologies will be developed and tested using data from the first site and validated using independent data from the other sites, demonstrating the wider applicability of ideas. The novel use of data assimilation will allow improved estimates of the current bathymetry, and improved predictions of future bathymetry via better initialisation, error estimates for the improved bathymetry, and a means to estimate model parameters from indirect observations. The direct involvement of the Environment Agency in the project will ensure that the resulting benefits are transferred into operational practice.
Publications
Bannister R
(2007)
Modelling of forecast errors in geophysical fluid flows
in International Journal for Numerical Methods in Fluids
Dance S
(2008)
Unbiased ensemble square root filters
in PAMM
García-Pintado J
(2013)
Scheduling satellite-based SAR acquisition for sequential assimilation of water level observations into flood modelling
in Journal of Hydrology
Gratton S
(2007)
Approximate Gauss-Newton Methods for Nonlinear Least Squares Problems
in SIAM Journal on Optimization
Hunter N
(2008)
Benchmarking 2D hydraulic models for urban flooding
in Proceedings of the Institution of Civil Engineers - Water Management
Lawless A
(2007)
Approximate Gauss-Newton methods for optimal state estimation using reduced-order models
in International Journal for Numerical Methods in Fluids
Livings D
(2008)
Unbiased ensemble square root filters
in Physica D: Nonlinear Phenomena
Mason D
(2009)
Calibration of uncertain flood inundation models using remotely sensed water levels
in Journal of Hydrology
Mason D
(2007)
Improving River Flood Extent Delineation From Synthetic Aperture Radar Using Airborne Laser Altimetry
in IEEE Transactions on Geoscience and Remote Sensing
Mason D
(2007)
Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling
in Hydrological Processes
Mason D
(2010)
Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007
in Estuarine, Coastal and Shelf Science
Morrell J
(2007)
A cell by cell anisotropic adaptive mesh ALE scheme for the numerical solution of the Euler equations
in Journal of Computational Physics
Nichols N
(2008)
Using Model Reduction Methods within Incremental Four-Dimensional Variational Data Assimilation
in Monthly Weather Review
Petrie R
(2010)
Ensemble-based data assimilation and the localisation problem
in Weather
Scott T
(2007)
Data assimilation for a coastal area morphodynamic model: Morecambe Bay
in Coastal Engineering
Scott, T. R.
(2009)
DATA ASSIMILATION FOR MORPHODYNAMIC PREDICTION AND PREDICTABILITY
in Coastal Engineering 2008, Vols 1-5
Smith P
(2012)
Data assimilation for state and parameter estimation: application to morphodynamic modelling
in Quarterly Journal of the Royal Meteorological Society
Smith P
(2009)
Variational data assimilation for parameter estimation: application to a simple morphodynamic model
in Ocean Dynamics
Smith P
(2011)
A hybrid data assimilation scheme for model parameter estimation: Application to morphodynamic modelling
in Computers & Fluids
Stewart L
(2007)
Correlated observation errors in data assimilation
in International Journal for Numerical Methods in Fluids
Thornhill G
(2012)
Integration of a 3D variational data assimilation scheme with a coastal area morphodynamic model of Morecambe Bay
in Coastal Engineering
Watkinson L
(2007)
Weak constraints in four-dimensional variational data assimilation Weak constraints in four-dimensional variational data assimilation
in Meteorologische Zeitschrift
Wright N
(2008)
Case Study of the Use of Remotely Sensed Data for Modeling Flood Inundation on the River Severn, U.K.
in Journal of Hydraulic Engineering
Description | In 2005, severe flooding in the aftermath of Hurricane Katrina focussed the world's attention on the importance of accurate knowledge of the topography of the coastal zone in natural disaster management and prediction. The topography of the sea floor, generally known as the bathymetry, evolves over time as sediment is eroded, transported and deposited by water action. The change in bathymetry itself changes the motion of the water, which is also influenced by tides and weather patterns, such as storm surges. Coastal sediment transport models are becoming increasingly sophisticated. However, observed bathymetric samples typically only provide partial coverage of the domain of such a model. Hence, initialisation of such models using only a set of recent observations is not feasible. The effective and efficient use of limited data, such as these, requires state-of-the-art mathematical, statistical and computational methods, known as data assimilation techniques; the application of these techniques to coastal morphodynamic modelling is novel and presents an exciting opportunity for improvements. In this project we combined a simple decoupled hydrodynamic and sediment transport model with a data assimilation scheme to investigate the ability of such methods to improve the accuracy of the predicted bathymetry for a case study of Morecambe Bay. UK. The observation data used for assimilation purposes comprised waterlines derived from satellite Synthetic Aperture Radar (SAR) imagery and swath bathymetry data collected by a ship-borne survey. A LiDAR survey of the entire bay was used for validation purposes. The comparison of the predictive ability of the model alone with the model-forecast-assimilation system demonstrated that using data assimilation significantly improves the forecast skill. An investigation of the assimilation of the swath bathymetry as well as the waterlines demonstrated that the overall improvement is initially large, but decreases over time as the bathymetry evolves away from that observed by the survey. The result of combining the calibration runs into a pseudo-ensemble provided a higher skill score than for a single optimized model run. In these experiments the model parameters were set by manual calibration; this is laborious and is found to produce different parameter values depending on the type and coverage of the validation dataset. The second part of the project considered the problem of model parameter estimation in more detail. By employing the technique of state augmentation, it was possible to use data assimilation to estimate uncertain model parameters concurrently with the model state. This approach removes inefficiencies associated with manual calibration and enables more effective use of observational data. We developed a novel hybrid sequential 3D-Var data assimilation algorithm for joint state-parameter estimation and demonstrated its efficacy using idealized models The results of this study are extremely positive and suggest that there is great potential for the use of data assimilation-based state-parameter estimation in coastal morphodynamic modelling. |
Exploitation Route | Since the end of the project, the application of data assimilation to coastal morphodynamic modelling has already been taken up by researchers at the engineering consultancy/research institute Deltares. Our new technique for concurrent state and parameter estimation has so far only been investigated in idealized systems and requires further development and testing in more realistic systems. This work is beginning in the new application area of river flood modelling. |
Sectors | Aerospace Defence and Marine Environment Leisure Activities including Sports Recreation and Tourism Government Democracy and Justice |
Description | Since the end of the project, the application of data assimilation to coastal morphodynamic modelling has already been taken up by researchers at the engineering consultancy/research institute Deltares, with the development of their OpenDA package. Our new technique for concurrent state and parameter estimation has so far only been investigated in idealized systems and requires further development and testing in more realistic systems. This work is beginning in the new application area of river flood modelling. |
First Year Of Impact | 2011 |
Sector | Aerospace, Defence and Marine,Environment |
Description | EPSRC Senior Fellowship in Digital Technology for Living with Environmental Change |
Amount | £1,706,722 (GBP) |
Funding ID | EP/P002331/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2016 |
End | 08/2021 |
Description | Satellite Applications Catapult (CORSAIR) |
Organisation | Satellite Applications Catapult |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | We have been carrying out research on automatic flood delineation using synthetic aperture radar data provided by the Satellite Applications Catapult. Report to the catapult (March 2018) |
Collaborator Contribution | Synthetic Aperture Radar (SAR) images were provided under the CORSAIR programme. |
Impact | Mason, D. C., Dance, S. L., Vetra-Carvalho, S. and Cloke, H. L. (2018) Robust algorithm for detecting floodwater in urban areas using Synthetic Aperture Radar images. Journal of Applied Remote Sensing. doi: 10.1117/1.JRS.12.045011 |
Start Year | 2016 |
Description | Ongoing "Magnificent Maths" Days |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | Yes |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Building on the event funded by this grant, the University of Reading continues to hold an annual "Magnificent Maths" day or 2-day summer school for Year 12 school students, featuring workshops, talks and career panels. Teachers comment that a Maths related school trip is a rare opportunity. Many of the same schools bring their students year after year, showing the value that they place on this activity for enthusing their students about choosing to continue Maths to A-level as well as further on at University. |
Year(s) Of Engagement Activity | 2010,2011,2012,2013,2014,2015 |
URL | http://www.prospectus.rdg.ac.uk/archive/teachersandadvisors/advisors/taSTEMEvents.aspx |