1. Land use effect on nutrient loading – nutrient models new assessment tools Inese Huttunen, Markus Huttunen and Bertel Vehviläinen Finnish Environment Institute

3. Basic structure of WSFS-Vemala  Hydrological WSFS-model: Inputs daily precipitation and temperature Simulates hydrological cycle on daily time step Covers all Finland, 6200 sub-basins, 58 000 lakes Simulated daily Data-assimilation, ensemble forecasts  Water quality simulation with Vemala Diffuse loading (agriculture and non-agriculture) Point load, settlements, atmospheric deposition Simulates transport in rivers and lakes Total phosphorus, total nitrogen, suspended solids, organic carbon (TOC)

5. Relationship between concentration and runoff / use of VIHMA annual loads Runoff r (= r1+r2+r3+r4+r5) is divided into 5 classes r x, each class has Ptot concentration c x,x which is calibrated r1: runoff in runoff class 1, 0-1 mm/day r2 runoff in runoff class 2, 1-3 mm/day r3 runoff in runoff class 3, 3-6 mm/day r4 runoff in runoff class 4, 6-10 mm/day r5 runoff (unlimited) in runoff class 5, > 10 mm/day Concentration relationship with runoff  VIHMA tool (Puustinen, SYKE) is used to simulate annual agricultural load and Vemala load is adjust  1 100 000 field plots are simulated separately by knowing slope, plant, soil type, P soil

6. Nutrient balance in lakes Inflow loading Outflowing load Sedimentation Internal load Accumulation = Loading – outflow – sedimentation + internal loading Annual Phosphorus balance for Karhijärvi Inflow loading 10.2 t Outflow load 8.9 t Sedimentation 5.9 t Internal loading 3.2 t

7. Calibration  Calibration is the process of modifying the parameters to a model until the difference between output from the model and observed data sets is minimum  Optimization criteria is:  all observation points located at the same calibration area are taken into calibration: + there is a need to use all available observations in the calibration even if the are very infrequent (few times per year), − more frequently observed points gets more weight in the calibration procedure.  appropriate weights for each type of observations are found and tested to reach the best possible calibration result  Water quality observations are not daily

8. Phosphorus concentration

9. Phosphorus load

10. Agricultural load 59% of the total loading into Archipelago Sea

11. Use of VEMALA to simulate different scenarios  Vemala can be used to simulated present situation  We can change present loadings and simulate concentrations and loadings in the river catchments in changed conditions:  Possible changes are: Crop management changes by VIHMA / ICECREAM Wetland effect Scattered settlement loading changes Point load changes Climate change scenarios Combination of above mentioned  Scenario simulations has been done in TEHO project for Aurajoki, Loimijoki and Eurajoki

12. Wetland simulation  All possible small ditch catchments with area 20 – 200 ha  Which has at least 20% of agricultural fields  Its possible to simulate the effect of all possible wetlands, we can simulate nutrient sedimentaion in wetland, plant uptake

14. Scenarios of agricultural practices in TEHO  Buffer zones  Increase of vegetation cover during the winter (30%, 50%, 70% of the total agricultural area): Equally in all catchment On the steeper sloped fields  Using of mannure decreased by 50%  Decresed using of P fertilizer Conclusions from TEHO scenarios:  There is no one single method to reduce agricultural loading, seceral reduction methods need to be combined  The best reduction can be achieved by combination of: Increased vegetation cover on fields over 3% slope Buffer zones are established Reduced P fertilizer application, that P soil < 14 mg/l Best management practices of mannure apllication

15. Summary  Agricultural load needs to be reduced to improve the state of the Baltic Sea  Mitigation measures are done on the field scale and there are needed tools to estimate what is the effect of mitigation measures on the river catchment scale  Nutrient load models (Vemala) can be used to simulate different scenarios how should the agricultural practices be changed to reduce the agricultural loading  There are no one single method to reduce agricultural loading, its a combination of methods  More detailed process description improves the models capability to simulate climate change or agricultural management scenarios

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