Pollution history and recovery of a boreal lake exposed to a heavy bleached pulping effluent load

We examined the effects of heavy pulp mill discharges on the Lake Lievestuoreenjärvi ecosystem and the later recovery of diatom and chironomid communities from age-dated short core samples. Beginning in 1927 the lake received a heavy effluent load from a sulphite pulp mill. Except for the recession during the Second World War and the temporary closure of the mill from 1967 to 1971, the industrial load, containing large quantities of nutrients, organic matter and toxic compounds, increased continuously. In the early 1980s, laboratory documents were falsified by the directors of the mill and the systematic illegal effluent overload led to a collapse of the whole lake ecosystem. In 1985, the outdated plant was finally closed down. Based on the assessment of chemical properties and biological remains of the sediment, we distinguished five developmental phases in the ecological state of the lake. In the pre-industrial phase, the pelagic and profundal benthic communities were dominated by species preferring ultraoligotrophic or oligotrophic lakes. Concomitant with the increasing discharge and deposition of chlorine compounds, resin acids, and mercury, as well as strong acidity and hypolimnetic and epilimnetic anoxia, the ecological status changed in a short period from excellent to bad. Finally, in the early 1960s, the majority of the lake was virtually dead and the aquatic life survived only in the uppermost littoral zone. Since 1985, a fast recovery in the water quality has led to a strong, but temporary eutrophy in pelagic communities. The main peak of eutrophication was caused by the invasion of a species new to the lake,Aulacoseira granulata var.angustissima. Later, the pelagic communities shifted towards oligotrophy, but the original, pre-industrial status has not been re-established. The profundal benthic communities have not achieved the pre-industrial structure, but at present indicate mesotrophy.     

Groundwater vulnerability mapping: A GIS and fuzzy rule based integrated tool

Contamination of groundwater has become a major concern in recent years. Since testing of water quality of all domestic and irrigation wells within large watersheds is not economically feasible, one frequently used monitoring strategy is to develop contamination potential maps of groundwater, and then prioritize those wells located in the potentially highly contaminated areas for testing of contaminants. However, generation of contamination potential maps based on groundwater sensitivity and vulnerability is not an easy task due inherent uncertainty. Therefore, the overall goal of this research is to improve the methodology for the generation of contamination potential maps by using detailed landuse/pesticide and soil structure information in conjunction with selected parameters from the DRASTIC model. The specific objectives of this study are (i) to incorporate GIS, GPS, remote sensing and the fuzzy rule-based model to generate groundwater sensitivity maps, and (ii) compare the results of our new methodologies with the modified DRASTIC Index (DI) and field water quality data. In this study, three different models were developed (viz. DI_fuzz, VI_fuzz and VI_{fuzz_ped}) and were compared to the DI. Once the preliminary fuzzy logic-based (DI_fuzz) was generated using selected parameters from DI, the methodology was further refined through VI_fuzz and VI_{fuzz_ped} models that incorporated landuse/pesticide application and soil structure information, respectively. This study was conducted in Woodruff County of the Mississippi Delta region of Arkansas. Water quality data for 55 wells were used to evaluate the contamination potential maps. The sensitivity map generated by VI_{fuzz_ped} with soil structure showed significantly better coincidence results when compared with the field data.     

Light outburst of a compact galaxy

In a field near M3 photographed in U,B,V from 1963 to 1969 one of 750 compact galaxies shows a brightening of 1 mag in B during 1966/67.     

Risk Assessment and Disaster Management for Natural and Anthropogenically Induced Geologic Hazards: Application to the Preolkhon Region,Western Lake Baikal,Siberia, Russia

In the Western Lake Baikal, recent Baikal Rift's tectonics control the topography, seismicity, climate, geomorphology, and economy. Scarps, facets, structural terraces, horsts and grabens, and trapezoid valleys can be clearly observed. They have been generated by the recent tectonic movements along the faults and represent a serious geologic hazard. The specific geological conditions predetermine a unique variety of landscapes. Thus, the main type of the economy is tourism. However, unorganized tourism leads to the degradation of the unique landscapes. It increases risk and requires disaster management. Three criteria has been used for risk assessment: (1) degree of geologic hazard; (2) degree of landscape degradation; and (3) degree of the economy's vitality. The high ecological significance and low stability to antropogeneous pressure are typical for landscapes of the Western Lake Baikal. Thus, some special activities of disaster management should be implemented based on our investigation.     

Enhancement of the method of summer precipitation forecasting

The physical-synoptic principles of the automated method of summer precipitation forecasting introduced into operational prognostic practice in 2006 by the decree of the Central Methodical Commission of the Federal Service for Hydrometeorology and Environmental Monitoring (Roshydromet) are presented. Beside that, improved modifications of this method, which are automatically updated, are shown. Validation of those updates based on observational data collected in 2004 has shown improvement of all major criteria of forecasts efficiency. The performed improvement is based on the more detailed quantitative realization of mechanism of various showers formation (including heavy rainfalls).     

Authigenic iron and titanium oxides in triassic red beds: (St. Bees Sandstone), Cumbria,Northern England

Authigenic iron and titanium oxides occur in three main textural varieties in the St. Bees Sandstone, a Triassic red bed succession in Cumbria. These are: (a) overgrowths of haematite, titaniferous haematite, anatase, and rutile which generally occur on detrital host grains of similar compositions. The overgrowths may occur as syntaxial rim cements or rhombohedral and prismatic projections and are always in optical continuity, (b) discrete crystals of anatase (including octahedrite) and haematite 10-40 μm in size occur in pore spaces, and (c) fine grained ( < 1 μm) pigmentary haematite occurs as grain coatings around detrital grains and in the interstitial matrix. The euhedral nature and pore-filling habit clearly indicate the authigenic origin of these iron- and titanium oxides. All three textural varieties are believed to have been precipitated from ground waters containing dissolved ferrous and titanium ions. These ions were derived from the intrastratal solution of detrital iron and titanium bearing grains including ferromagnesian silicates and iron-titanium oxides. The precipitation of iron oxides from migrating ground waters in the manner described here goes some way to explaining how thick, uniformly red successions can be formed.     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.