Mean residence time of lagoons in shallow vegetated floodplains

Lagoons interspersed within wetlands are expected to increase the residence time of the flow in the system which, in turn, will lead to enhanced pollutant removal thus ensuring a good ecological status of the ecosystem. In this study, lagoons interspersed in vegetated wetlands have been mimicked in the laboratory to develop a theoretical model to establish the impact three major driving parameters (the vegetation density surrounding a lagoon, the depth aspect ratio [length vs. depth] of the lagoon and the circulating flow – through the Reynolds number) have on determining the residence time of the flow in the lagoon. The results indicate that, according to the maximum free available area of the flow, the presence of vegetation (Juncus maritimus) decreases the residence time. In addition, an increase in the Reynolds number of the circulating flow in the wetlands also resulted in a decrease in the lagoon residence time. Nevertheless, lagoon residence times were found to depend on the depth of the lagoon, with deeper lagoons having higher residence times. The length of the lagoon, however, was found not to affect the residence time. High lagoon residence times in either natural or constructed wetlands are desirable because they enhance pollutant removal from the water. Although, if the residence times are too long, this may lead to anoxic water conditions that could in fact threaten the wetland's ecosystem.     

Development of large shallow Lake Peipsi (North-Eastern Europe) over the Holocene based on the stratigraphy of phosphorus fractions

We studied high-resolution stratigraphy of phosphorus (P) forms in the Holocene sediments of large shallow Lake Peipsi (Estonia/Russia) in order to evaluate the lake ecosystem response to environmental changes and track the lake’s eutrophication history. We distinguished four main periods in the history of Lake Peipsi, each having likely different factors responsible for the distribution pattern of P fractions in the sediment record. We suggest that in the oldest period, from ca. 10.4 up to 7.3 cal ka BP, the sediment composition was mainly determined by rising water level, the second period dated 7.3–2.3 cal ka BP was governed mainly by stable hydrology and P loading, while the third period between 2.3 and 0 cal ka BP was primarily influenced by emerging anthropogenic impact. The sediments from the last period since 1950 are subject of ongoing diagenetic processes but still reflect rapid eutrophication of the lake. Comparison of the results with periods derived from other sediment proxies proved the usability of P fractions stratigraphy in reconstruction of the development of lakes.     

Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression (SVR) with GWO,BAT and COA algorithms

In this study, we developed multiple hybrid machine-learning models to address parameter optimization limitations and enhance the spatial prediction of landslide susceptibility models. We created a geographic information system database, and our analysis results were used to prepare a landslide inventory map containing 359 landslide events identified from Google Earth, aerial photographs, and other validated sources. A support vector regression (SVR) machine-learning model was used to divide the landslide inventory into training (70%) and testing (30%) datasets. The landslide susceptibility map was produced using 14 causative factors. We applied the established gray wolf optimization (GWO) algorithm, bat algorithm (BA), and cuckoo optimization algorithm (COA) to fine-tune the parameters of the SVR model to improve its predictive accuracy. The resultant hybrid models, SVR-GWO, SVR-BA, and SVR-COA, were validated in terms of the area under curve (AUC) and root mean square error (RMSE). The AUC values for the SVR-GWO (0.733), SVR-BA (0.724), and SVR-COA (0.738) models indicate their good prediction rates for landslide susceptibility modeling. SVR-COA had the greatest accuracy, with an RMSE of 0.21687, and SVR-BA had the least accuracy, with an RMSE of 0.23046. The three optimized hybrid models outperformed the SVR model (AUC = 0.704, RMSE = 0.26689), confirming the ability of metaheuristic algorithms to improve model performance.     

Characterization of stabilized waste: Evaluation of pollution risk

This study relates to the characterization of stabilized waste. Various parameters such as granulometric distribution, percentage of mineral and organic matter were estimated to appreciate environmental hazard potential and possibility of metal leaching of the samples of waste from Grange site in France. From the results, it was shown that the granulometric distribution was variable. Therefore, a strong proportion of fines (44.6 %) and medium (45.9 %) was observed due to the age of waste that supports the degradation of a great quantity of organic matter. That was confirmed by the strong mineral matter rate (63.8 %) obtained to determine the organic percentage of matter (36.2 %). The amount of heavy metals such as iron, nickel, copper, zinc, cadmium and lead was also studied. The results obtained were in a good agreement with the ones of the literature. Indeed, it appeared that iron, lead, copper, nickel and zinc are in relative strong proportion while cadmium was not very present. Iron represents 78 % of the metals. From the leaching tests, it was shown that the heavy metals concentration were very weak. Moreover, the deposit of studied waste could be a potential source of organic pollution (COD = 150 Mg C/L on average) in the case of precipitation and flood.     

Impact of rainfall on the hygienic quality of blue mussels and water in urban areas in the Inner Oslofjord,Norway

The effects of precipitation on the hygienic quality of water and blue mussels collected from five different localities in the urban areas in the Inner Oslofjord were investigated, with samples analysed for Escherichia coli, Salmonella spp., pathogenic Vibrio spp., Norovirus, Sapovirus, Cryptosporidium spp. and Giardia duodenalis. The sampling sites were located at varying distances from the outlet of combined sewer overflows (CSO)-impacted rivers/streams. In general, 1–3 log₁₀ increases in fecal indicator bacteria and human pathogens were observed after heavy rainfalls. Blue mussels appeared to be a useful indicator of the impact of sewage at these sites, and generally a good correlation was identified between concentrations of E. coli and other human pathogens in the mussels. Provision of general advice to the public of avoiding areas near the outlets of CSO-impacted rivers after heavy rainfall may reduce the risk of gastroenteritis by bathers and others that may swallow water during recreational activities.     

The Influence of Hydromorphological Stressors on Estuarine Vegetation Indicators

Estuaries are one of the most threatened ecosystems, with a great number of stressors related to pollution, hydromorphological changes, and invasive species. However, the response of the biological indicators proposed for their ecological status assessment is not always well established. When using estuarine vegetation (saltmarshes and seagrasses) as an indicator, there are several theoretical concepts regarding the relationships between the variations of this indicator and hydromorphological stressors. It is precisely these relationships which are presented in this work. To carry out this objective, based on the first intercalibration process, a set of metrics for saltmarsh and seagrass taxonomic compositions (e.g., loss of number of taxa and richness) and abundance (e.g., relative coverage and relative extent) have been selected and applied to different estuaries located in Northern Spain. Additionally, a methodology for the hydromorphological status assessment, based on the analysis of the anthropogenic changes in the hydrodynamic and morphological estuarine characteristics (e.g., the extension of land claim areas or changes in the estuarine perimeter), has been developed and applied to these transitional water bodies in order to find a gradient of pressured sites in which we seek correlations between the vegetation metrics and hydromorphological stressors. As a result, the response of the different vegetation indicators is variable. In some cases, a negative correlation of the indicator with the pressure degree exists, whereas in other cases, the relationship is not as clear. Nonetheless, according to the results, it can be suggested that the placing of anthropogenic structures diminishes the quality of the estuarine vegetation. Therefore, to maintain a suitable environment for the estuarine vegetation seems necessary in order to reduce the number of the hydrodynamic structures which are no longer in use.