twinning water quality modelling in latvia helene ejhed, 20060904 kickoff meeting twinning on...

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


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


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


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


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


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


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


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


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.


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

twinning water quality modelling in latvia helene ejhed, 20060904 kickoff meeting twinning on...

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