Time filter

Source Type

Pyhäjärvi, Finland

Lepisto A.,Finnish Environment Institute | Huttula T.,Finnish Environment Institute | Koponen S.,Aalto University | Kallio K.,Finnish Environment Institute | And 3 more authors.
Aquatic Ecosystem Health and Management | Year: 2010

New tools, such as intensive measurements, together with advanced mathematical models, are increasingly needed in water management and environmental research. The new approaches are being developed at Pyhajarvi, a large (155 km 2) lake in southwest Finland. Pyhajarvi is highly valuable in terms of water supply, fisheries and recreational use. The ecological state of Pyhajarvi has been closely monitored for decades, particularly since eutrophication became a major concern in the late 1980s. Two relatively new research methods were used to assess the spatial water quality of Pyhajarvi: (i) transect measurements from a moving boat; and (ii) remote sensing data based estimates. First, a flow-through method from a moving boat was successfully used to collect high resolution transect water quality data from the lake over six field campaigns. The method is relatively accurate but costly, and its use is mostly limited to special campaigns and intensive research, but not for long-term monitoring. Second, remote sensing methods were used to retrieve water quality information which was found consistent with the surface measurements from the boat. The estimation of parameters such as turbidity and humic substance concentration is possible with simple algorithms when using remote sensing (MERIS) data. The quantitative estimation of water quality by the methods used here requires concurrent in situ measurements for algorithm training. These methods will be further developed utilizing frequent on-line water quality and weather data from a recently installed lake float. © 2010 AEHMS. Source

Koskiaho J.,Finnish Environment Institute | Lepisto A.,Finnish Environment Institute | Tattari S.,Finnish Environment Institute | Kirkkala T.,Pyhajarvi Institute
Water Science and Technology | Year: 2010

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. © IWA Publishing 2010. Source

Patynen A.,Finnish Environment Institute | Patynen A.,University of Jyvaskyla | Elliott J.A.,UK Center for Ecology and Hydrology | Kiuru P.,Finnish Environment Institute | And 3 more authors.
Boreal Environment Research | Year: 2014

We linked the models PROTECH and MyLake to test potential impacts of climate-change-induced warming on the phytoplankton community of Pyhäjärvi, a lake in southwest Finland. First, we calibrated the models for the present conditions, which revealed an apparent high significance of internal nutrient loading for Pyhäjärvi. We then estimated the effect of two climate change scenarios on lake water temperatures and ice cover duration with MyLake. Finally, we used those outputs to drive PROTECH to predict the resultant phy-toplankton community. It was evident that cyanobacteria will grow significantly better in warmer water, especially in the summer. Even if phosphorus and nitrogen loads to the lake remain the same and there is little change in the total chlorophyll a concentrations, a higher proportion of the phytoplankton community could be dominated by cyanobacteria. The model outputs provided no clear evidence that earlier ice break would advance the timing of the diatom spring bloom. © 2014. Source

Grigorievskiy A.,Aalto University | Miche Y.,Aalto University | Ventela A.-M.,Pyhajarvi Institute | Severin E.,Lille University of Science and Technology | And 3 more authors.
Neural Networks | Year: 2014

In this paper, an Optimally Pruned Extreme Learning Machine (OP-ELM) is applied to the problem of long-term time series prediction. Three known strategies for the long-term time series prediction i.e. Recursive, Direct and DirRec are considered in combination with OP-ELM and compared with a baseline linear least squares model and Least-Squares Support Vector Machines (LS-SVM). Among these three strategies DirRec is the most time consuming and its usage with nonlinear models like LS-SVM, where several hyperparameters need to be adjusted, leads to relatively heavy computations. It is shown that OP-ELM, being also a nonlinear model, allows reasonable computational time for the DirRec strategy. In all our experiments, except one, OP-ELM with DirRec strategy outperforms the linear model with any strategy. In contrast to the proposed algorithm, LS-SVM behaves unstably without variable selection. It is also shown that there is no superior strategy for OP-ELM: any of three can be the best. In addition, the prediction accuracy of an ensemble of OP-ELM is studied and it is shown that averaging predictions of the ensemble can improve the accuracy (Mean Square Error) dramatically. © 2013 Elsevier Ltd. Source

Verta M.,Finnish Environment Institute | Salo S.,Finnish Environment Institute | Korhonen M.,Finnish Environment Institute | Porvari P.,Finnish Environment Institute | And 2 more authors.
Science of the Total Environment | Year: 2010

We conducted a whole-lake experiment by manipulating the stratification pattern (thermocline depth) of a small polyhumic, boreal lake (Halsjärvi) in southern Finland and studying the impacts on lake mercury chemistry. The experimental lake was compared to a nearby reference site (Valkea-Kotinen Lake). During the first phase of the experiment the thermocline of Halsjärvi was lowered in order to simulate the estimated increase in wind speed and in total lake heat content (high-change climate scenario). The rate of methyl mercury (MeHg) production during summer stagnation (May-August) was calculated from water profiles before the treatment (2004), during treatment (2005, 2006) and after treatment (2007). We also calculated fluxes of MeHg from the epilimnion and from the hypolimnion to the sediments using sediment traps. Experimental mixing with a submerged propeller caused a 1.5-2. m deepening of the thermocline and oxycline. Methyl mercury production occurred mostly in the oxygen free layers in both lakes. In the experimental lake there was no net increase in MeHg during the experiment and following year; whereas the reference lake showed net production for all years. We conclude that the new exposed epilimnetic sediments caused by a lowering of the thermocline were a major sink for MeHg in the epilimnion. The results demonstrate that in-lake MeHg production can be manipulated in small lakes with anoxic hypolimnia during summer. The climate change induced changes in small boreal lakes most probably affect methyl mercury production and depend on the lake characteristics and stratification pattern. The results support the hypothesis that possible oxygen related changes caused by climate change are more important than possible temperature changes in small polyhumic lakes with regularly occurring oxygen deficiency in the hypolimnion. © 2010 Elsevier B.V. Source

Discover hidden collaborations