Ahti Lepistö

Losses of Nitrogen and Phosphorus from Agricultural and Forest Areas in Finland during the 1980s and 1990s

The temporal changes and spatial variability of phosphorus andnitrogen losses and concentrations in Finland during the period1981–1997 were studied in 15 small agricultural and forestedcatchments. In addition, four coastal river basins with highagricultural land use located in southern Finland were includedin the study in order to assess the representativeness ofagricultural loss estimates from small agricultural catchments.The mean annual loss specific for agricultural land was estimatedto be on average 110 kg km-2 a-1 for total phosphorusand 1500 kg km-2 a-1 for total nitrogen. The resultsfrom small agricultural catchments were in agreement with thecorresponding loss estimates from rivers, with an average of137 kg km-2 a-1 for total phosphorus and 1800 kg km-2a-1 for total nitrogen. The results from the studiedagricultural catchments and rivers during the period 1981–1997suggest that weather-driven fluctuation in discharge was usuallythe main reason for changes in nutrient losses, and little or noimpact of changes in agricultural production or managementpractises can be observed. In forested areas the total phosphorusloss (average 9 kg km-2 a-1) and total nitrogen loss(average 250 kg km-2 a-1) were lower than inagricultural areas. In forested catchments the impact of forestryoperations, such as clear-cutting and fertilization, and theimpact of atmospheric nitrogen deposition can be seen in changesin nutrient losses.

Nitrogen flows from European regional watersheds to coastal marine waters

Approaches A comprehensive evaluation of net anthropogenic inputs of reactive nitrogen (NANI) through atmospheric deposition, crop N fi xation, • fertiliser use and import of food and feed has been carried out for all European watersheds. A database on N, P and Si fl uxes delivered at the basin outlets has been assembled. A number of modelling approaches based on either statistical regression analysis or mechanistic description of the processes involved • in nitrogen transfer and transformations have been developed for relating N inputs to watersheds to outputs into coastal marine ecosystems.

Modeling combined effects of forestry, agriculture and deposition on nitrogen export in a northern river basin in Finland.

Abstract The development of the spatial N export and retention model N_EXRET for large river basins is presented, utilizing remote-sensing-based land use and forest classification. Export coefficients describing the contribution from agriculture, forestry and peat harvesting were estimated based on empirical studies. Representativeness of forest treatment coefficients have been evaluated by use of data from a small, well-documented test catchment. Simulation results from the application of the model to the Oulujoki river basin (22 840 km2) are discussed. Model estimated N fluxes were compared with measured N fluxes in separate points of the river basin. Based on source apportionment, agriculture contributes 17% of the total export, varying between 8% in the uppermost subbasin and 38% in the lowermost subbasin close to the sea. Forestry contributes almost as much, 16%, with less pronounced variation (11–24%) between the different sub-basins. In the separate subbasins, 7–37% of the incoming gross N export was retained. Based on mass balances and sensitivity analyses, retention was estimated to be in the range of 5–10 kg ha−1yr−1 in lakes and 0–1 kg ha−1yr−1 in peatlands. The model results were validated by testing to data from the 3 closely situated river basins. However, further testing is needed in river basins where land use and deposition patterns differ clearly from these northern basins.

A National-Scale Nutrient Loading Model for Finnish Watersheds—VEMALA

VEMALA is an operational, national-scale nutrient loading model for Finnish watersheds. It simulates hydrology; nutrient processes; leaching; and transport on land, rivers, and lakes. The model simulates nutrient gross load, retention, and net load from Finnish watersheds to the Baltic Sea. It was developed over a period of many years and three versions are currently operational, simulating different nutrients and processes. The first version of VEMALA (vs. 1.1) is based on a regression model between nutrient concentration and runoff. Since the first version, the model has been developed towards a more process-based nutrient loading model, by developing a catchment scale, semi-process-based model of total nitrogen loading, VEMALA-N, and by incorporating and developing a field-scale process-based model, ICECREAM, for total phosphorus loading simulations (VEMALA-ICECREAM). The model performance was tested in two ways: (1) by comparison of simulated net nitrogen and phosphorus loads with loads calculated from monitoring data for all major watersheds in Finland and (2) by comparing simulated and observed daily nutrient concentrations for the river Aurajoki by both old and new, process-based model approaches. Comparison of the results shows that the model is suitable for nutrient load simulation at a watershed scale and at a national scale; the new versions of the model are also suitable for applications at a smaller scale.

Spatial and temporal variability of organic C and N concentrations and export from 30 boreal rivers induced by land use and climate

Climate change scenarios for northern boreal regions indicate that there will be increasing temperature and precipitation, and the changes are expected to be larger in winter than in summer. These precipitation and discharge patterns, coupled with shorter ice cover/soil frost periods in the future would be expected to contribute significantly to changing flow paths of organic matter over a range of land use patterns. In order to study the impact of climate change on the seasonality of organic matter export we compared total organic carbon (TOC) and total organic nitrogen (TON) concentrations and export, during different seasons and climatically different years, over 12 years for 30 Finnish rivers separated into forest, agriculture and peat dominated catchments. The mean monthly TOC concentrations were highest during autumn and there was also a peak in May during the highest flow period. The mean monthly concentrations of TON were lowest during winter, increased in spring and remaining high throughout summer and autumn. The TOC/TON ratios were lowest during summer and highest during winter, and in all seasons the ratios were lowest in catchments with a high proportion of agricultural land and highest in peat-dominated catchments. The seasonality of TOC and TON exports reflected geographical location, hydrology and land use patterns. Most of the TOC and TON were transported during the high flow following the spring snowmelt and during rainfall in autumn. In all catchments the relative importance of the spring snowmelt decreased in wet and warm years. However, in peat-dominated catchments the proportion of spring period was over 30% of the annual export even in these wet and warm years, while in other catchments the proportion was about 20%. This might be linked to the northern location of the peat-dominated catchments and the permanent snow cover and spring snowmelt, even in warm years.

Links Between Runoff Generation, Climate and Nitrate-N Leaching from Forested Catchments

To assess links between hydroclimatological factors and NO 3 − -N concentrations in streamflow from boreal forests with shallow soils, data from two catchments were analyzed. TOPMODEL was used to calculate the surface runoff fraction, daily dynamics of soil moisture, groundwater levels, and extensions of saturated areas. The stable isotope 18O was used for isotopic hydrograph separation (IHS) during one snowmelt season. Air-temperature and flow increase were the dominating factors explaining annual NO 3 − -N dynamics. Correlation also was found between NO 3 − -N concentrations and the surface runoff fraction. Increased concentrations during times of shallow groundwater were found both during cold and warm periods in one catchment. In the other, shallow groundwater was correlated to decreasing concentrations during cold periods, and increasing concentrations during warm periods. A two component model of event and pre-event water fractions and corresponding NO 3 − -N concentrations was set up for the snowmelt season. Model predictions mirrored NO 3 − -N concentration s during the first five days of the snowmelt. After that, the model overestimated NO 3 − -N concentrations, which indicates retention of NO 3 − -N in the event water fraction, originating from the snowmelt. The highest concentrations occurred during the initiations of flow increase, which indicates flushing of surficial NO 3 − -N

On-line measurements provide more accurate estimates of nutrient loading: a case of the Yläneenjoki river basin, southwest Finland

Automatic on-line measurement stations for water quality components and water level were equipped with dataloggers and GSM transmitters; the stations were installed at two sites in the Yläneenjoki river basin, SW Finland. Measurements during five seasons in 2006-2007 were conducted to find out whether the produced data would provide more accurate estimates of material and nutrient transport than traditional water sampling. Sensor-based monitoring estimates for transport of total suspended solids (TSS) were clearly higher (difference -6-61%), total phosphorus also higher, and that of nitrate (NO(3)-N) somewhat lower (difference (-51%-4%), as compared with manual sampling based estimates. The winter season studied here was mild i.e. winter-type which is becoming more common in Finland with the changing climate. Sensor-based monitoring proved its benefits particularly in such conditions.

The INtegrated CAtchment model of phosphorus dynamics (INCA-P)

INCA-P is a dynamic, catchment-scale phosphorus model which has been widely applied during the last decade. Since its original release in 2002, the model structure and equations have been significantly altered during several development phases. Here, we provide the first full model description since 2002 and then test the latest version of the model (v1.4.4) in a small rural catchment in northeast Scotland. The particulate phosphorus simulation was much improved compared to previous model versions, whilst the latest sorption equations allowed us to explore the potential time lags between reductions in terrestrial inputs and improvements in surface water quality, an issue of key policy relevance. The model is particularly suitable for use as a research tool, but should only be used to inform policy and land management in data-rich areas, where parameters and processes can be well-constrained. More long-term data is needed to parameterise dynamic models and test their predictions. We describe the latest version of INCA-P, a dynamic catchment phosphorus model.This is the first full description of the model structure and equations since 2002.A test application demonstrates improved model performance.New sorption equations allow the impacts of legacy soil P to be simulated over time.Model applicability and limitations are discussed.

Integrated Nitrogen Modeling in a Boreal Forestry Dominated River Basin: N Fluxes and Retention in Lakes and Peatlands

Two models, N_EXRET and INCA, were applied to the Simojoki river basin (3160 km2) in northern Finland in order to assess nitrogen retention in wetlands and lakes. N_EXRET is a spatial, export coefficient-based N export and retention model developed for large river basins. It utilizes remote sensing-based land use and forest classification, evaluated export coefficients, and data on areal N deposition and point sources of N. A new version (v1.7) of the Integrated Nitrogen in CAtchments model (INCA) is a semi-distributed, dynamic nitrogen process model, which simulates and predicts nitrogen transport and processes within catchments. Average retention of the gross total N load of 700 t a-1 to the river system was estimated using N_EXRET model as 17 t N a-1 to the wetlands and 77 t N a-1 to the lakes. A good fit was found between modeled and measured values along the river. Inorganic N fluxes simulated by the INCA model were compared with measured fluxes along the river Simojoki, with a good fit between modeled and measured NH4+-N fluxes, and an adequate fit for NO3--N fluxes. Both fluxes were overestimated at the first reach, below Lake Simojärvi. High percentage of peatlands led to high NH4+-N/NO3--N ratios derived from data, indicating negligible nitrification in large river subbasins and particularly in small research catchments.

A Regional GIS-Based Model to Predict Long-Term Responses of Soil and Soil Water Chemistry to Atmospheric Deposition: Initial Results

The aim of this study was to develop GISSMART, a GIS-based model, for estimating relative regional changes in soil andsoil water chemistry for given atmospheric deposition and nutrient uptake scenarios. The regional application was performed by dividing the study area into grid cells, the size and the form of the pixels being determined on the basisof the available GIS data bases of Finnish soil and vegetationtypes. GISSMART is the biogeochemical model SMART, extended forhandling GIS data in space and time. The Kangasvaara catchment(56 ha) in eastern Finland was used as the first test site. Data from four other nearby catchments were also used, togetherwith Multisource National Forest Inventory data (25 × 25 m2) from an area of 10 × 40 km2 for estimating soil chemistry. Multisource forest inventory datafrom the Finnish Forest Research Institute, including tree species, age and growth by tree species was based on LandsatTM-images and field measurements. The same satellite based estimation method was applied to obtain regional soil chemistry input data for GISSMART. Base saturation was the key state variable and nutrient uptake the key driving variablein this application of GISSMART. The results of the model testruns were reasonable. A slight decrease in base saturation waspredicted for the assumed deposition and nutrient uptake scenarios. In future work, the aim is to improve the description of hydrological processes and land use management in the model. This would also enable assessment of the effectsof climate change and land use management scenarios.