Improving confidence in estuary modelling

Transcription

1 Improving confidence in estuary modelling Richard Whitehouse HR Wallingford Draws on R&D funded by: Estuaries Session Shelf Seas Workshop 23 March 2010

2 Estuary Management flooding risk and water quality recreation and navigation coastal defence and conservation

3 Industry needs..to be asking the questions We all need to be facilitating knowledge transfer: a major technical challenge is in the identification, capture and retention of knowledge distillation of scientific results translating results of sediment process research into models and communication

4 Needs of evidence based decision making define the right questions appropriate quality (and quantity) of data a robust conceptual model credible analysis & modelling results informed basis for making a decision

5 Plans and activities: Typical questions what will be the impact of sea level rise and climate change on the habitat resource of an estuary? will construction of a new bridge affect adjacent flood defences? will deepening of a riverside berth affect the adjacent inter-tidal mudflats? will increased freshwater abstraction lead to enhanced siltation in the upper estuary?

6 EIAS* (EMPHASYS, 2000) *Estuary Impact Assessment System what questions can be answered now what information is required to answer these questions what tools and techniques are available and what are their limitations how can the results be interpreted first published 2000 and 2002 version web based guide 2004, 2007

7 Resources on coastal and estuary processes and morphology Not limited to:

8 Conclusions ERP (FD2107) estuaries do not all respond in the same manner similar types of estuary behave in a similar manner differences at the detailed level are important Historical Trend Analysis guide expectations of future change if there are precedents use validated models with historic data (hindcasting) lack of data either: ensemble predictions with one model or: inter-compare model results

9 Predictive methods data analysis of processes and morphology projections based on analysis EGA and hypothesis based (i.e. testable) conceptual model Top Down semi-empirical/analysis based morphological model Bottom Up both: process based computational model and: morphological model Hybrid Semi-empirical/computational model

10 Time (yrs) and space (km) scales Approximate timescale prediction horizons for morphology based on hindcasting Space and timescale graph Top Down Hybrid Bottom Up Time (years) and space (km) scales

11 Model validation a) validity of concepts b) reliability of equations c) numerical scheme d) test predictions against observations e) adequacy of documentation f) functional validation - the testing of predictions made by the model against measured values, including question of accuracy of the measurements - use of Brier Skill Score Sutherland, Haigh, FD2107 g) best practice hindcasting - does hindcasting guarantee future prediction?

12 Model validation 14 days (Sutherland et al, 2004) Quantified model performance using Brier Skill Score: Quantified outcome maps onto qualitative assessment of poor reasonable/fair. Can be improved with better model. Measured changed Change in bathymetry between survey 2 and survey 4 Modelled change Teignmouth Change in bed level (m) Deposition Erosion

13 ERP - FD example ASMITA estuary represented as a series of boxes filling/emptying under tidal action flow, equilibrium channel profile, equilibrium sediment concentration single element/multi element along estuary channel or components represent SLR and nodal tide

14 Used by Townend et al, 2006 Humber Geological setting (LOIS)

15 Volume (m^3) Tidal range (m) ASMITA 2-element model (Humber) Channel fixed s urface volu me Townend et al, 2006 Year X Predictions Data

16 What are the coastal links? Appendix F of SMP2 guidance on inclusion of estuaries in SMPs Photo: Waveney DC

17 Coastal system mapping A B 2009, French & Burningham as part of EA R&D SC060074

18 System modelling Using SCAPE (benefit from Tyndall centre work) and ASMITA models Walkden and Rossington, 2009, proof of concept modelling, EA R&D SC Cliff erosion, beach transport Sediment flux to estuary Estuary response More work needed on fines

19 Contrasting sediment environments at regional scale Apparently muddy environment Visibly sandy environment

20 Estuary sediment subenvironments Sandy margin of estuary Low water clay exposure How to deal with transport of sediment mixtures, segregation and patterns of dominance?

21 What controls fine sediment boundaries? Saltmarsh cliff, Laugharne, S Wales Sand/mud boundary, Eden Estuary Blackwater

22 Ways forward need to understand behaviour of real multimodal sediments: behaviour and transfers in shelf, coastal and estuarine environments geotechnical and sedimentological descriptions of mixtures of clays, silts, sands and gravels hydraulics, geotechnics, loose boundary hydraulics establish the process characterisations that allow realistic estimates of sediment transport to be made including suspended concentrations per grain size

23 Ways forward predicting the direction of net sediment transport is as much of a challenge as its magnitude laboratory measurements needed for process evaluation field measurements and monitoring to retain sight of the real world scales and behaviour parameterisation of processes and production of algorithms benefit in system scale reduced complexity modelling and need the detail too on processes, parameters controlling boundaries

24 Results from equilbrium estuary form model (Townend, Whitehouse and Manning, 2009 FCERM conference) Simple models for estuary form including tide and wave capture gross properties Based on comparison with existing data Further advances constrained by lack of data Bathymetry needed Ways forward River flows spate versus mean, annual quantities Sediment properties grain size and bed density are minimum properties needed, need erosion properties too Collate existing data and collect new data for 30 (statistical validity?) contrasting estuaries

25 Data needs bathymetry datasets to capture shape long term monitoring for baseline conditions hydraulic, sedimentological, biological, chemical parameters erosion rate database (sands/silts/clays) sediment SPM & morphology change temporal and spatial range and variability rapid response and regional characterisation build on existing framework of coastal observatories framework for data management in place Role of Coastal Forums, Estuary Partnerships, thematic university and Research Council centres

26 Enhanced datasets and methods through CESTORM Coastal and Estuarine Sediment Transport for Regional Management