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Pargas, Finland

Ekholm P.,Finnish Environment Institute | Valkama P.,The Water Protection Association of the River Vantaa and Helsinki Region | Jaakkola E.,Finnish Environment Institute | Kiirikki M.,Luode Consulting Oy | And 2 more authors.
Agricultural and Food Science | Year: 2012

We estimated the changes in the losses of particulate and dissolved phosphorus (P) after treating 93 ha of agricultural fields with gypsum (4 t ha-1) in a 245 ha catchment in southern Finland. Runoff was monitored using online sensors and manual sampling during one high-flow period before and six periods after the gypsum amendment. Turbidity recorded by the sensors correlated with particulate P analysed in the laboratory, which enabled the evaluation of changes in particulate P from the online data. Using a covariance model, gypsum amendment was estimated to have reduced the loss of particulate P by 64%. The loss of dissolved reactive P appeared to decrease by one third, but was estimated with less precision. No such changes were found during the same period in a nearby 'reference' catchment, where gypsum was not used. Gypsum did not affect soil test values for P, K, Mg or Ca, but it did increase the ionic strength and soil test SO4. In clayey catchments discharging into the sea, gypsum may provide an efficient means to reduce P losses from field cultivation. The duration of the gypsum effect and impact of SO4 associated with gypsum amendment on the ecology of rivers and lakes has yet to be determined. Source

Voutilainen A.,University of Eastern Finland | Huttula T.,Finnish Environment Institute | Juntunen J.,Finnish Environment Institute | Rahkola-Sorsa M.,University of Eastern Finland | And 2 more authors.
Boreal Environment Research | Year: 2014

We present diverging long-term trends in the water temperature of a large boreal lake, Lake Pyhäselkä (263 km2), located in eastern Finland. The dataset was constructed from a half century of monitoring (1962-2010). The direction of the temperature trend depended on the water layer and the season, in that the yearly average temperature in the top layer (1-10 m) as recorded in summer (June-August) increased by 2.5 °C over the monitoring period, whereas that recorded when the lake was covered by ice (January-April) decreased from 0.6 to 0.2 °C. The water temperature in the bottommost layers showed no trends. We suggest that the water temperature under the ice is decreasing in this case as a consequence of mixed effects of lake-specific physical features and climate change, which cause variations in the heat content of the inflowing water of the Pielisjoki. The epilimnetic water temperature in summer appeared in turn to follow general trends in air temperatures. Our results stress the need for taking local and site-specific phenomena into account when drawing conclusions about the effects of climate change on lakes. Source

Kohout T.,University of Helsinki | Kohout T.,Academy of Sciences of the Czech Republic | Bucko M.S.,University of Helsinki | Bucko M.S.,Geological Survey of Finland | And 5 more authors.
Permafrost and Periglacial Processes | Year: 2014

Non-invasive geophysical prospecting and a thermodynamic model were used to examine the structure, depth and lateral extent of the frozen core of a palsa near Lake Peerajärvi in northwest Finland. A simple thermodynamic model verified that the current climatic conditions in the study area allow sustainable palsa development. A ground penetrating radar (GPR) survey of the palsa under both winter and summer conditions revealed its internal structure and the size of its frozen core. GPR imaging in summer detected the upper peat/core boundary, and imaging in winter detected a deep reflector that probably represents the lower core boundary. This indicates that only a combined summer and winter GPR survey completely reveals the lateral and vertical extent of the frozen core of the palsa. The core underlies the active layer at a depth of~0.6m and extends to about 4m depth. Its lateral extent is~15m x~30m. The presence of the frozen core could also be traced as minima in surface temperature and ground conductivity measurements. These field methods and thermodynamic models can be utilised in studies of climate impact on Arctic wetlands. © 2014 John Wiley & Sons, Ltd. Source

Honkavaara E.,Finnish Geodetic Institute | Hakala T.,Finnish Geodetic Institute | Kirjasniemi J.,Lentokuva Vallas Oy | Lindfors A.,Luode Consulting Oy | And 5 more authors.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2013

A new Fabry-Perot interferometer (FPI) based light-weight spectrometric camera provides new possibilities for environmental remote sensing applications. The sensor collects spectral data cubes with adjustable spectral properties in a rectangular image format, and so stereoscopic data can be obtained by gathering images in block structures with overlapping images. The FPI camera thus enables stereoscopic, spectrometric remote sensing applications with light-weight, low-cost airborne imaging systems. Our objective is to investigate the processing and use of this new imaging technology in a water quality mapping. We carried out imaging campaigns over a small lake in summer and autumn 2012 using a light-weight unmanned airborne vehicle (UAV) and a small manned airborne vehicle (MAV). We present the preliminary results of these campaigns. Source

Attila J.,Finnish Environment Institute | Koponen S.,Finnish Environment Institute | Kallio K.,Finnish Environment Institute | Lindfors A.,Luode Consulting Oy | And 2 more authors.
Remote Sensing of Environment | Year: 2013

Three MERIS Case II water processors included in the BEAM software package were studied for estimating the water quality in the coastal waters of the northern Baltic Sea. The processors, named Case II Regional (C2R), boreal (BOR), and eutrophic (EUT), for the associated lake types, have been developed for different types of coastal or inland (Case II) waters. Chlorophyll-a (chl-a), total suspended matter (TSM), absorption of colored dissolved organic matter (aCDOM(443)), and signal depth (Z90) products of the BEAM processors were compared with in situ data. In addition, total absorption (aTOT) and scattering of TSM (bTSM) from different BEAM processors were compared against the results of coastal field campaign measurements. The in situ water quality data consisted of monitoring station data gathered by the Finnish environmental administration during 2006-2009 and data from coastal field campaigns with a flow-through system. AERONET-OC (SeaPRISM) data from the Helsinki Lighthouse station were used to validate the BEAM reflectance products. The comparison with the BEAM processor results and in situ data showed that the bias of the original BEAM algorithms can be decreased through adjustment of the coefficients that relate IOPs such as the absorption of pigments and the scattering of TSM to water quality constituents such as chl-a and turbidity. The TSM products of the BEAM processors can be used to estimate the turbidity measured at monitoring stations with an r2 of 0.76-0.84 and an RMSE of 0.7-0.85 FNUs (Formazin Nephelometric Units) on the coast of Finland. The best functionality for turbidity estimation was observed with the EUT processor, but the C2R processor also gave a sound performance. The BOR and C2R processors proved to be the best for deriving chl-a concentration. However, the accuracy of chl-a estimations was low with both processors (r2 ranged from 0.45 to 0.47 and RMSE was between 44 and 45%). Chl-a products, particularly during the phytoplankton bloom seasons of spring and summer, require further development. The Z90 product from the BOR processor was used to derive an algorithm for Secchi disk depth estimation with r2 0.48 and RMSE 0.97m. The BOR processor was the most successful at CDOM estimation (r2 0.6 and RMSE 0.49 1/m), but a simple reflectance ratio was actually able to perform better (r2 0.75 and RMSE 0.39 1/m). In many cases, the differences between the outcomes of processors were small and related only to a part of the in situ dataset. © 2012 Elsevier Inc. Source

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