Search Results (3)

The creation of digital bathymetric models (DBM) of lakes allows not only for storage of the data on depths and shorelines in a standard format, but also for the estimation of the major morphometric characteristics of the reservoirs. To calculate the water, thermal, and chemical budgets of large lakes, it is important to know their hypsometry. We developed a new digital model of Lake Ladoga, the largest European lake, which was done to identify and correct topographic data errors, as well as to identify more depth points. The produced bathymetric model of the lake allowed for the updating of morphometric characteristics. The lake-bottom grid of 0.5 × 0.5 km with 70,190 depth points of interest was produced using the kriging procedure with the mean error ME = 0.05 m and root mean square error RMSE = 5.6 m. The statistical characteristics of the lake depth and slope are determined on the basis of the advanced digital model of the lakebed relief. The form of the lake depression corresponds to the convex type (microtype) and bears some similarity to lakes Erie, Huron, Vanern, and Malaren. We describe how the bathymetric model has been developed and the morphometric characteristics of the lake have been corrected. We also discuss the results of its application in limnological investigations. A relationship has been established between surface water temperature, transparency and the bottom depths for the various seasons of Lake Ladoga. Full article

Developing a general, predictive understanding of ecological systems requires knowing how much structural and functional relationships can cross scales and contexts. Here, we introduce the CROSSLINK project that investigates the role of forested riparian buffers in modified European landscapes by measuring a wide range of ecosystem attributes in stream-riparian networks. CROSSLINK involves replicated field measurements in four case-study basins with varying levels of human development: Norway (Oslo Fjord), Sweden (Lake Mälaren), Belgium (Zwalm River), and Romania (Argeş River). Nested within these case-study basins include multiple, independent stream-site pairs with a forested riparian buffer and unbuffered section located upstream, as well as headwater and downstream sites to show cumulative land-use impacts. CROSSLINK applies existing and bespoke methods to describe habitat conditions, biodiversity, and ecosystem functioning in aquatic and terrestrial habitats. Here, we summarize the approaches used, detail protocols in supplementary materials, and explain how data is applied in an optimization framework to better manage tradeoffs in multifunctional landscapes. We then present results demonstrating the range of riparian conditions present in our case-study basins and how these environmental states influence stream ecological integrity with the commonly used macroinvertebrate Average Score Per Taxon (ASPT) index. We demonstrate that a qualitative index of riparian integrity can be positively associated with stream ecological status. This introduction to the CROSSLINK project shows the potential for our replicated study with its panoply of ecosystem attributes to help guide management decisions regarding the use of forested riparian buffers in human-impacted landscapes. This knowledge is highly relevant in a time of rapid environmental change where freshwater biodiversity is increasingly under pressure from a range of human impacts that include habitat loss, pollution, and climate change. Full article

Water is a fundamental resource and, as such, the object of multiple environmental policies requiring systematic monitoring of its quality as a main management component. Automatic sensors, allowing for continuous monitoring of various water quality variables at high temporal resolution, offer new opportunities for enhancement of essential water quality data. This study investigates the potential of sensor-measured data to improve understanding and management of water quality at watershed level. Self-organizing data maps, non-linear canonical correlation analysis, and linear regressions are used to assess the relationships between multiple water quality and hydroclimatic variables for the case study of Lake Mälaren in Sweden, and its total catchment and various watersheds. The results indicate water discharge from dominant watersheds into a lake, and lake water temperature as possible proxies for some key water quality variables in the lake, such as blue-green algae; the latter is, in turn, identified as a potential good proxy for lake concentration of total nitrogen. The relationships between water discharges into the lake and lake water quality dynamics identify the dominant contributing watersheds for different water quality variables. Seasonality also plays an important role in determining some possible proxy relationships and their usefulness for different parts of the year. Full article