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The national-level nutrient loading estimation tool for Finland: Watershed Simulation and Forecasting System WSFS-Vemala Markus Huttunen, Finnish Environment Institute SYKE, HELCOM workshop on transboundary inputs and retention, 19.5.2015

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The national-level nutrient loading estimation tool for Finland: Watershed Simulation and Forecasting System WSFS-Vemala

Markus Huttunen, Finnish Environment Institute SYKE, HELCOM workshop on transboundary inputs and retention, 19.5.2015

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Basic structure of the WSFS-Vemala

Hydrological SYKE-WSFS model:

○ Simulation of the hydrological cycle ○ Snow, soil moisture, ground water, runoff ○ Water transport in rivers and lakes ○ 1 day time step, semi distributed (6000 sub-basins) ○ Covers all Finland

Nutrient loading model VEMALA:

○ Diffuse loading to rivers and lakes (agriculture, forest) ○ Point sources, scattered dwelling, atmospheric deposition ○ Nutrient transport and retention in rivers and lakes ○ Total phosphorus and nitrogen, suspended solids, TOC

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Purpose of the WSFS-VEMALA

Real time information of nutrient loading

○ Nutrient concentrations in rivers and lakes ○ Riverine loading to the Baltic Sea ○ Short term forecasts

Scenarios

○ Climate change ○ Land use and farming practices ○ Changes in point sources, etc. ○ Co-effect of climate change and different actions:

In single lake
In river basin
In loading from Finland to the Baltic Sea

○ Support implementation of WFD and MSFD

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1 day timestep. History since 1960. Scenarios until 2100.
Covers all Finland + transboundary basins:

○ Tornio ○ Parts of Neva catchment flowing to Finland

Field scale simulation of agriculture:

○ About 1 000 000 field parcels. 2 300 000 hectars.

Simulation of 1 ha and larger lakes:

○ About 58 000 lakes in Finland ○ Relevant for retention simulation

Spatial & temporal resolution of WSFS-Vemala

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Hydrological expertise in Finland Hydrological Modeling and Forecasting System (1/2)

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National level nutrien load modeling (2/4) Hydrological expertise in Finland

Structure of WSFS-Vemala water quality model

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VEMALA V2-ICECREAM field scale simulation Tattari et.al., 2001

19.5.2015

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Catchment scale VEMALA-N processes

19.5.2015

Fertilizer Plant uptake Organic matter pool Leaching Nitrate Ammoni um

5 Land use/crop lasses: spring cereals, winter cereals, root crops, grasslands, forest Miner Nitr Immobilization Denitrification

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Variables simulated in VEMALA v.3
Phosphate (PO4

3-), dissolved organic phosphorus (Porg) and

particulate inorganic phosphorus (PP)

Nitrate (NO3
), ammonium (NH4

+) and organic nitrogen (Norg)

Phytoplankton, Suspended solids (SS), Total organic carbon (TOC)
Oxygen (O2)
Effect of actions on bioavailable fractions of nutrients

VEMALA v.3 river and lake transport

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National level nutrien load modeling (1/4) Hydrological expertise in Finland

Annual phosphorus load from Finland to Baltic sea

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Annual riverine phosphorus load from Finland

Point sources directly to the Baltic Sea are not included
Unmonitored catchments are not in the comparison (right graph)
Mean monthly method calculations provided by A. Räike, SYKE

Comparison of annual riverine phosphorus loads from Finland

1000 2000 3000 4000 5000 6000 1991 1993 1995 1997 1999 2001 2003 2005 2007 Phosphorus load, t/year 1000 2000 3000 4000 5000 6000 Annual discharge, m3/s Model Mean monthly method Mean discharge

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Retention simulation

Percentage of nitrogen (left) and phosphorus (right) loading antering the sea

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Both in nitrogen (left) and phosphorus (right) the main potential for load reduction is near South-West Coast

Nutrient loading to the Sea from human sources

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Field data:

○ P-content of soil, soil type, fertilization, cultivation ○ Data mostly exists, but not available for modelling

Forestry actions (clear cut, ditch maintanance, fertilization)
Scattered dwelling: implementation of sewage systems
Point sources: quite good information in Finland
More accurate information of human sources improve

accuracy of estimates: ○ Propotion of natural background loading ○ Retention estimates ○ Potential for actions to reduce loading

Transboundary river basins:

○ Comparable information needed for the whole basin

Sources of uncertainty

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In (already in near) future climate and agriculture will cange:

○ Climate change will effect on background leaching and loading from agriculture ○ Changes in growing season, precipitation, food & fertilizer prices will effect production in agriculture

Scenarios for nutrient loading

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By modelling we can estimate the areal limits for nutrient loading from

human sources: ○ Environmental limits which support reaching good ecological state in waters ○ Retention in major role in areal limits

We should provide scenarios: By which land allocation and farming

and nutrient mitigation actions can certain amount of food be produced in the future climate within the nutrient loading limits of good ecological state: ○ Nutrient saving and recycling enable higher production in agriculture within the environmental limits of loading ○ Nutrient prices are also expected to increase ○ How to support nutrient saving actions to be cost-effective

Realistic scenarios support decision makers and actors especially in