A real-time water quality model of the Tagus estuary

Transcription

1 A real-time water quality model of the Tagus estuary Marta Rodrigues *, Anabela Oliveira, André B. Fortunato, Joana Costa, João Rogeiro, Ricardo Costa, Luís M. David, João L. Gomes and Gonçalo Jesus

2 Outline Motivation and Background Integrated Modeling Approach Tagus Estuary: Model Setup and Data Comparison Tagus Estuary: Operational Model WIFF Interface Final Remarks Future Work LNEC 2

3 Pressures and Threats Management Frameworks Real-time Monitoring and Prediction LNEC 3

4 Coastal Margin Observatories Anticipate events of pollution and support the emergency response Support daily and long-term management actions to minimize the risks for public and ecosystems health Support common activities in the water bodies (management and leisure) LNEC 4

5 Recent and Ongoing Projects PREPARED (7FP), SI-GeA (QREN) and RealQual (FLAD) projects Decision support and early-warning system for water quality in receiving waters 3D Forecast of Hydrodynamics and Water Quality Real-time Monitoring Interface Improvements LNEC 5

6 Pilot Study Alcântara Catchment (6200 ha) Tagus estuary: 320 km 2 LNEC 6

7 Conceptual Approach Early warning of pollution events in recreational waters Soft coupling of urban drainage and baroclinic estuarine model Real-time monitoring network LNEC 7

8 Integrated Modeling Approach Terreiro do Paço Alcântara Algés Atmospheric Forecast 1 Atmospheric Forecast 2 Atmospheric Forecast n Forecast: estuarine water level Multiple model Ensemble SWMM Rainfall Forecast Alcântara outfall Caneiro de Alcântara Forecast: oceanic circulation, river flows, atmospheric Decay Transport Hydrodynamics 4Sdrainage Earlywarning Tagus estuary

9 Numerical Model LNEC 9 SELFE (Zhang and Baptista, 2008): Computes free-surface elevation and 3D velocity, salinity and temperature Unstructured grids (horizontal) Hybrid S-Z coordinates (vertical) User-defined transport module couple of biogeochemical and fecal contamination models C F z C κ z z C w y C v x C u t C c Λ + + = Sources and sinks term

10 Sources and Sinks of the Biogeochemical Model ATMOSPHERE WATER COLUMN Growth/Lysis/Respiration Dissolved Inorganic Carbon DIC Respiration/ Grazing/Nitrification Inorganic Nutrient Uptake r/ Phytoplankton PC i PN i PP i PSi i PFe i P i Pg j Mortality Photolysis Colored Dissolved Organic Carbon Uptake NO 3 NH 4 DIP DISi DIFe Mortality Uptake/ Nitrification Mortality Regeneration Bacterioplankton BC BN BP BFe CDOC 1 CDOC 2 Dissolved Organic Matter Fecal Organic Matter m Photolysis 22 DOC 1 DOC 2 22 DON 1 DON 2 DOP 1 FC k FN k FP k FSi k FFe k Sinking SEDIMENTS State variables t/ i Phytoplankton groups j Individual pigment type k Class of fecal material

11 3D Hydrodynamics and Fecal Contamination Model Hydrodynamics SELFE Velocity Temperature Salinity Transport Near Field Model or Concentration, Flow Concentration, Flow, Discharge ECO-SELFE Fecal Contamination Model Fecal Tracers Fecal Coliforms Escherichia coli ΛC = k d C f ν s s C z Mortality Sedimentation LNEC 11

12 Tagus Estuary: Model Setup Caneiro de Alcântara Tagus river Vertical grid: 20 levels (S-Z) Horizontal grid: nodes dt = 30 s Atlantic ocean 3 open boundaries: Tagus river Caneiro de Alcântara Atlantic Ocean Atmospheric forcing LNEC 12

13 Field Surveys 5 surveys 7 stations Cover entire tide cycle (13-hour duration) Synoptic measurement by probes and samples Physic-chemical and microbiological parameters LNEC 13

14 Online Monitoring Network Equipment installed in the estuary Several types of probes : UV-Vis spectrophotometer, conductivity, temperature, dissolved oxygen, ph, ammonium, nitrates, water levels Online data transmission LNEC 14

15 Model-Data Comparison: Historical Data Water Levels Salinity Profile Depth (m) Salinity Downstream Upstream Depth (m) Salinity LNEC 15

16 Model-Data Comparison: Salinity and Temperature St1 St1 St3a St7a St3b Salinity Temperature (ºC) Tempo (days, since 01/07/2011 ) LNEC 16

17 Fecal Contamination Model Parametrization LNEC 17

18 Model-Data Comparison Tidal Cycle: Fecal Coliforms St1 St3a St7a Fecal Coliforms (MNP/100 ml) Time (days, since 01/07/2011 ) LNEC 18

19 Model-Data Comparison July and September 2011: E. coli July 2011 September 2011 Escherichia coli (MNP/100 ml) St1 St3a St7a St1 St3b St7b LNEC 19

20 Tagus Estuary: Operational Model Atmospheric Forcing Wind Air Temperature Pressure Specific Humidity WRF 9 Km ( Tagus River Flow: SNIRH Almourol station Temperature: Climatology - SNIRH Salinity: 0 [FC]=[E.coli]: Climatology - SNIRH Shortwave Radiation Longwave Radiation GFS 50 km ( Oceanic Boundary Water Levels Temperature Salinity MyOcean ( myocean.eu) [FC] = [E.coli] 0 MNP/100 ml Caneiro de Alcântara Flow Temperature Salinity [FC] [E.coli] Sewer Model LNEC 20

21 Tagus Estuary: Salinity forecast Forecasts Runs daily Forecast time range: 48 hours Forecast products: Water levels and velocities Salinity Water temperature Fecal coliforms and E. coli Fecal coliforms forecast: discharge from the caneiro de Alcântara LNEC 21

22 WIFF: User Interface LNEC 22

23 LNEC 23

24 LNEC 24

25 Final Remarks Recent advances of WIFF - towards a nowcast-forecast information system of the Tagus estuary Advances included: Baroclinic circulation and water quality (fecal contamination) of the Tagus estuary (focused on the caneiro de Alcântara discharge) Operational model good preliminary results were achieved and further validation will be performed LNEC 25

26 Future Work Improvement of the understanding of the processes (sediments water column) Implementation of the biogeochemical model in the Tagus estuary Uncertainty in predictions LNEC 26

27 Acknowledgments Funding: Project PREPARED Project SI-GeA Project SPRES Projects G-Cast, MADyCOS, LTER-RAVE Projects BGEM and RealQual Grant SFRH/BPD/87512/2012 Grant SFRH/BD/82489/2011 Grant SFRH/BSAB/1308/2012 Support: Participants in the field campaings from LNEC, IST, SIMTEJO, Univ. de Coimbra, Univ. de Aveiro António M. Baptista (CMOP), Paul Turner (CMOP), Joseph Zhang (VIMS) APL, IGP, APA Thank you for your attention! LNEC 27