Twinning water quality modelling in Latvia Helene Ejhed, 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 Latvia Helene 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

Twinning water quality modelling in Latvia Helene Ejhed, 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 Latvia Helene Ejhed, 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 Latvia Helene Ejhed, 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

Twinning water quality modelling in Latvia Helene Ejhed, 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 Latvia Helene Ejhed, 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 Latvia Helene Ejhed, 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 Latvia Helene Ejhed, 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 Latvia Helene Ejhed, 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