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Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Final workshop Twinning on development of modelling capacity to support water quality.

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Presentation on theme: "Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Final workshop Twinning on development of modelling capacity to support water quality."— Presentation transcript:

1 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Final workshop Twinning on development of modelling capacity to support water quality monitoring in Latvia Modelling: rationales and selection Photo Lake Övre hammardammen, Fredrik Ejhed

2 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Experience ? Model tested for similar conditions User experience User interface Data ? Requirements Availability Purpose ? Load and source apportionment Scenario of change Investigative modelling Substances Resolution ? – temporal and spatial Daily drive data but annual results Dynamic results needed in lakes and coastal processes Spatial resolution – time and cost proportional WFD demand both high spatial resolution and overview Monitoring data dependence Models ?

3 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Freeware vs commercial -aspects  Access  Support  Developments  Modules - Package  Cost

4 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Model concepts Level of complexity Model type Physical Empirical High Low Daily simulations of flow and solute concentrations Annual predictions based on export coefficients Methods differ profoundly in their complexity, level of process representation and data requirements Rewritten from EUROHARP documentation Combination of models above

5 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Model concepts Limitations and advantages Model type Physical Empirical Advantages Process descriptions Scenarios possibilities Low data requirements Simple models Limitations Expert user High data requirements Timeconsuming Few scenario possibilities Valid only for model range

6 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Calibration of models  The conceptual and processbased model is calibrated using monitoring data  Empirical models e.g. regression analysis are only valid within the data range used Fig. Total nitrogen concentration before and after calibration of soil retention, Skivarpsån Sweden, model for HELCOM PLC4 and WFD

7 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Results –weakest link rule  A good model need good driving data Ex. problems with faulty point source coordinates in an inlet watercourse to lake Vättern in Sweden, model for HELCOM PLC-4 and WFD. Total nitrogen concentrations vs. time.

8 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Purpose and resolution Latvia  WFD demands high resolution for programmes of measures as well as overview for characterisation.  Eutrophication –Load and source apportionment –Scenario of change  Priority hazardous substances –Load and chemical fate –Dispersion –Ecological status

9 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Monitoring vs. Modelling  Monitoring at strategic sites  Regionalised data – WFD typology  Modelling gives overview  Modelling gives physical processes  Models needed to plan measures  No model without monitoring data Monitoring sites in Sweden used for WFD and HELCOM PLC-4

10 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 6 Parameter regions for calibration of HBV hydrology HBV 230 stations for calibration 140 stations for validation timesplit validation also Hydrological modelling HBV

11 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Models to meet Latvian purpose and resolution – diffuse sources of eutrophication  EUROHARP models for eutrophication –EH evaluated models to harmonize reporting procedures on diffuse sources. –Only 2 out of the nine EH models evaluated very suitable for scenario calculations and hydrology, TRK and SWAT –TRK and SWAT have been applied with good results in Sweden with similar climate as in Latvia.  Alternative eutrophication model –INCA, a good alternative due to a modest need of input data, single interface and a complete catchment model.

12 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Selected models - Eutrophication  Hydrology models Because of the importance of process and models selected due to their difference in complexity: –SCS –HBV  Water quality models Because of the varying need of high resolution in hydrology environment –CE-QUAL-W2  Catchment models Because of the importance of diffuse and point sources and the models ability to perform scenario calculations –TRK –SWAT –INCA  Source apportionment and scenario tools Because of the importance of presentation and user friendly tests of scenarios of change –WATSHMAN

13 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Models comparison ModelsSCSHBVCE- QUAL- W2 TRKSWATINCAWATSHMAN Modest data requirements YYNYNYY High time resolutionNYYYYYY High spatial resolution YYYYYYY Processbased conceptual model NYYYYYN Calibration data required NYYYYYN Scenario possibilitiesNYYYYYY Complete catchment model NNNYYYY

14 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Models comparison - continue ModelsSCSHBVCE- QUAL- W2 TRKSWATINCAWATSHMAN DistributedYY (semi) Y (fully) Y (semi) N (semi) Y (semi +) Y (semi) Time consumingNYYYYYN Single interfaceNYYNYYY Exchangeable submodels NY-YN*-Y Applied for national assessments -Y-Y--N Applied in Northern Europe YYYYYYY Non-Expert userYNNNNNY FreewareYYYYYYY *some process submodels can be chosen in a scrollist and some can be exchanged - have not been verified

15 Twinning water quality modelling in Latvia Helene Ejhed, 20070626 Priority hazardous substances Models and concept  Decision support system – SOCOPSE.se Recommendation of concept:  Chemical fate modeling – fugacity approach  Screening monitoring  MFA (Material Flow analysis) and LCA (Life Cycle Analysis)  QSAR modeling – for chronic toxicity and physical data for new substances  OMEGA for ecological status  Fully distributed hydrological model for dispersion in water environment


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