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Twinning water quality modelling in LatviaHelene Ejhed, 20060904
Kickoff meeting
Twinning on development of modelling capacity to support
water quality monitoring in Latvia
Modelling: rationales and approaches
Photo Lake Övre hammardammen, Fredrik Ejhed
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
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
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
Modelling - for what purpose ?
The purpose needs to be defined before application
Source apportionment
Programmes of measures
Modelling investigation of failure to meet good quality
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
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
Solution – provide overview model results and high resolution model results for sensitive water bodies
Monitoring data dependence
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
Model concepts
Level of complexityModel 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
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
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
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
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
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
Validation and assessment analysis
Validation of model in time split or spatial split of data
Validation of target expectations
Validation of e.g. flow, concentration, load
Using simple statistical tools
In EUROHARP annual timestep results validated using mean deviation, mean absolute deviation and standard deviation
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
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.
Twinning water quality modelling in LatviaHelene Ejhed, 20060904
Model choice
Well tested models for the region
Experience of the models
Keep an open flexible structure in model systems– developments in model system may be hindered by a
single choice of model.– continuous developments necessary– recalculations of old results for assessment of
developments towards the environmental targets