1. Nitrogen loading from forested catchments Marie Korppoo VEMALA catchment meeting, 25/09/2012 Marie Korppoo, Markus Huttunen 12/02/2015 Open DATA: Nutrient loading to the sea VEMALA v.3 – nutrients and elements transport and processes in rivers and lakes

2. ●Provide estimate of nutrient loading to the Baltic Sea: ○For each river in Finland ○Present loading (as daily values), short term forecast ○Scenarios: climate change, human activities Agriculture Forestry Point sources, scattered dwelling, atmospheric deposition ●Model development was needed ○Nutrient leaching, transport and retention in watersheds ○Biologically available fractions ●Provides also: ○Nutrient loading for inland lakes (58 000 lakes) ○Scenarios for nutrient loading from agriculture Field scale, different crop, farming actions, fertilization level 2 Aim of the work

3.  Water quality model developed partly under the MMEA project to model bioavailable nutrients in freshwater ecosystems.  It simulates nutrient processes, leaching and transport on land, and in rivers and lakes.  It simulates from the Finnish water basins to the Baltic Sea:  Nutrient gross loading  Retention in lakes and in the river network  Nutrient net loading  Nutrient species modelled:  Phosphorus: Total phosphorus (TP), phosphate (PO 4 3- ), organic phosphorus (Porg) and particulate phosphorus (PP)  Nitrogen: Total nitrogen (TN), nitrate (NO 3 - ), ammonium (NH 4 + ) and organic nitrogen (Norg)  Suspended solids (SS)  Total organic carbon (TOC)  Phytoplankton  Oxygen (O 2 ) 3 VEMALA v.3

4. 4 Description of the VEMALA models VersionSubstance Hydrological model Terrestrial model River modelLake model agricultural loadingnon-agricultural loading VEMALA 1.1TP, TN, SSWSFS concentration-runoff relationship nutrient transport model nutrient mass balance model VEMALA- ICECREAM TPWSFS field scale process based model concentration-runoff relationship VEMALA-NTN, NO 3 - WSFS semi-process based, 5 crop classes semi-process based, 1 forest class VEMALA v.3 TN, TP, SS, TOC, PO 4 3-, PP, Porg, NO 3 -, NH 4 +, Norg, Phytoplankton, O 2 WSFS VEMALA-ICECREAM (PP, Porg, PO 4 3-, SS), VEMALA-N (NO 3 -, NH 4 +, Norg), VEMALA 1.1 (TOC) Biogeochemical model VEMALA v.3

5.  The Water Framework Directive (WFD) requires the use of several nutrient-sensitive biological parameters (phytoplankton, phytobenthos, macro-algae, macrophytes and seagrass) to establish the good ecological status (GES).  Moreover, these biological parameters are dependent on the availability of bioavailable nutrients rather than total nutrients. These bioavailable nutrients (nitrate, ammonium and phosphate) are among the most commonly monitored parameters in Europe.  Therefore, there is a need to model bioavailable nutrients (phosphate, ammonium and nitrate) to better predict the algal biomass and the state of the environment.  Finally, by simulating better the river processes (e.g. sedimentation and denitrification) in the VEMALA model the total nutrient loads simulations to the Sea will be improved due to a better simulation of the retention in the river basin.  Moreover, future scenarios (climate, agriculture and point load changes) will be more reliable. The aim of the VEMALA v.3 development

6.  VEMALA v.3 is designed to model the bioavailable nutrients phosphate, nitrate and ammonium in rivers. Moreover, it simulates particulate phosphorus, organic phosphorus, organic nitrogen and the phytoplankton biomass.  In this new model, the nutrients are no longer modeled separately but are linked in the aquatic ecosystem to one another through phytoplankton dynamics, organic matter degradation and sedimentation.  The river and lake sub-model in VEMALA v.3 is a deterministic biogeochemical model using enzyme-catalysed reactions to simulate the interactions between nutrients and the algal biomass. It is based on the phytoplankton sub-model AQUAPHY (Lancelot et al., 1991), and the biogeochemical model RIVE (Billen et al.,1994). 6 VEMALA v.3

7.  Variables simulated in VEMALA v.3  Phosphate (PO 4 3- ), dissolved organic phosphorus (Porg) and particulate inorganic phosphorus (PP)  Nitrate (NO 3 - ), ammonium (NH 4 + ) and organic nitrogen (Norg)  Phytoplankton  Suspended solids (SS)  Total organic carbon (TOC)  Oxygen (O 2 ) 7 VEMALA v.3

8.  The variables included in the new VEMALA v.3 model are:  Total organic carbon (TOC)  Suspended sediments (SS)  Phosphorus (particulate inorganic phosphorus (PP), phosphate (PO 4 3- ) and dissolved organic phosphorus (Porg))  Nitrogen (organic nitrogen (Norg), nitrate (NO 3 - ) and ammonium (NH 4 + ))  Phytoplankton (2 different species)  Oxygen (O 2 ) 8

9.  Phosphorus cycling in the river sub-model:  Variables represented: particulate inorganic phosphorus (PP), phosphate (PO 4 3- ), dissolved organic phosphorus (Porg) and phytoplankton phosphorus (Phyto_P).  Total phosphorus= PP+PO 4 3- +Porg+Phyto_P  Phosphate is produced by the mineralisation of the organic matter and consumed by the phytoplankton growth.  Organic phosphorus does not sediment but is mineralised or produced by phytoplankton lysis or grazing.  Particulate inorganic phosphorus is a function of suspended sediments (SS) and PO 4 3- concentrations in the water to simulate adsorption/desorption processes. PP is also affected by sedimentation/resuspension following the suspended sediments dynamics.

10.  Nitrogen cycling in the river sub-model:  Variables represented: Nitrate (NO 3 - ), ammonium (NH 4 + ), organic nitrogen (Norg) and phytoplankton nitrogen (Phyto_N)  Total nitrogen=NO 3 - + NH 4 + +Norg+Phyto_N  Ammonium is produced by mineralisation (organic matter degradation) and consumed by phytoplankton growth  Nitrate is consumed by phytoplankton growth and denitrification  Organic nitrogen does not sediment but is mineralised or produced by phytoplankton lysis or grazing  Sedimentation of nitrogen is only taken into account through phytoplankton sedimentation

11.  The modelling of bioavailable nutrients with the VEMALA v.3 model will allow the definition of:  The phytoplankton growth in Finnish water bodies  The proportion of biologically available fractions in the run off to the Sea  The contribution of the different loading sources to the biologically available nutrients  The impact of the different farming actions and loading reduction actions on the biologically available nutrient loads  The effect of climate change on the biologically available nutrient fractions 11

12.  It can simulate the water quality in rivers and lakes larger than 1ha in Finland :  As daily, monthly or annual loads -> e.g. Aurajoki 12 Where can it be used?

13. 13  As daily concentrations -> e.g. Aurajoki Phytoplankton (µgChla L -1 ) Nitrate (mg L -1 ) Total nitrogen (mg L -1 ) Ammonium (mgN L -1 )

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15.  It can simulate:  The retention in lakes and the river network. -> Sed/denit…  The phytoplankton growth in Finnish water bodies -> Phytoplankton growth in Aurajoki 15

16.  It can simulate:  The contribution of the different loading sources to the total or biologically available nutrients: Source apportionment  The proportion of biologically available fractions in the run off to the sea 16

17.  It can also simulate scenarios:  The impact of the different farming actions and loading reduction actions on the total or biologically available nutrient loads  The effect of climate change on the total or biologically available nutrient loads  VEMALA can help in the WFD implementation, to test various management scenarios on the reduction of bioavailable loads and phytoplankton growth.  It can also simulate the transport of inert components in rivers downstream of an industrial leak for determining toxicity risks. 17

18.  Finally, VEMALA v.3 can also simulate the transport of inert components in rivers downstream of an industrial leak for determining toxicity risks (MINEVIEW project): Simulation of a hypothetical 1 tonne of Nickel discharged on the 09/11/2014 into the freshwater ecosystem from talvivaara 18

19. ●Available now: ○Nutrient loading (N,P) of rivers to the Baltic Sea as total nutrients ●In the model also: ○Loading scenarios for fields ○Loading scenarios for lakes ○Division of loading by source 19 Data for MMEA

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22. 22 Basic information about loading available for each lake (58 000 lakes)

23. 23 Basic loading scenarios for each lake

26. ●River loading to the Baltic Sea: ○Real time data and forecast for explaning the state of the sea, however river loading explains only partly ○As input for all kind of sea models ○Scenarios show possible future pathways and variation for loading to the sea: Climate change, human activities, nutrient load reduction actions ●Nutrient loading data for lakes: ○Basic information for local people and water protection assosities: where is the loading coming from ○Scenarios: possible future pathways, limits for the effect of nutrient loading actions ●Nutrient loading data for fields: ○Limits for possibilities to effect on nutrient loading by farming actions ○Background data for planning farming actions: If farmer has possibility to select, he has infromation which actions are favorable for erosion and nutrient leaching: benefit for farmer and waters 26 Examples how the data can be used

27. 27 Article under preparation

28. Nitrogen loading from forested catchments Marie Korppoo VEMALA catchment meeting, 25/09/2012 marie.korppoo@ymparisto.fi Thank you for your attention