Deposition and Mobilization of Microplastics in a Low-Energy Fluvial Environment from a Geomorphological Perspective

Though microplastic (MP/MiP) pollution of the environment is a popular research topic, a relatively limited number of studies are investigating its geomorphological context. However, site-specific hydrological and morphological parameters fundamentally affect the MP transport, deposition and mobilization. Therefore, we aimed to evaluate the geomorphological influencing factors on MP deposition in the fluvial sediments of the Tisza River (Central Europe). Between the two surveys (in 2019 and 2020), small flood waves rearranged the MP pollution, as in the sediments of the Tisza it decreased by 30% and in the tributaries by 48%. The previously highly polluted upstream and downstream sections became moderately polluted, but the contamination increased in the Middle Tisza, and the hot-spots were rearranged. The increasing longitudinal trend in the MP content exists if the minimum values of the hydrologically uniform sections are considered. The tributaries are important MP sources, as 80% of them had a higher (by 20%) MP content in their sediments than the Tisza had near the confluence, and they increased the MP content of the Tisza by 52% on average. The point-bars were the most polluted in-channel forms, while the side-bars and sediment sheets had less MP content, by 18 and 23%, respectively. The spatial trend of the MP content of these forms was not the same. Therefore, during the planning of sampling campaigns, it is very important to consider the geomorphological setting of a sampling site: we suggest sampling side-bars. No clear connection between the particle size of the sediments and their MP content was found

Prostorna distribucija prirodnih radionuklida merena u Srbiji upotrebom biomonitora

Активност природних радионуклида је мерена у 217 узорака маховина Hypnum cupressiforme које су сакупљене крајем лета 2015. године на комплетној територији Републике Србије са циљем да се установи просторна дистрибуција радионуклида. Мерења су вршена NaI детектором облика јаме. Посебна пажња је посвећена 7Be који се већ деценијама користи као природни обележивач у изучавању транспортних процеса у атмосфери. Добијено је да је дистрибуција атмосферске депозиције 7Be неуниформна и да се најмања и највећа измерена вредност разликују девет пута. Просторна дистрибуција 7Be не показује корелацију са рељефом терена за разлику од 137Cs кога има више у планинским и шумовитим пределима. Присутност радионуклида из урановог и торијумовог низа у доброј мери зависи од структуре и састава тла на локацијама са којих су узимани узорци.The activities of natural radionuclide were measured in 217 moss samples that were collected at the entire territory of Serbia. Measurements were taken by well-type NaI detector in order to establish the spatial distribution of radionuclides. Special attention was paid to 7Be. It is obtained that the distribution of atmospheric deposition of 7Be is non-uniform; the minimum and maximum measured value differs nine times. No coincidence of the spatial distribution of 7Be with the relief was observed. It was noticed that higher values of 137Cs were detected in mountain and wooded areas. The presence of radionuclides from the Uranium and Thorium chains in the large extent depends on the structure of the soil at the sampling site

Socioekonomske posledice suša i suvišnih unutrašnjih voda u Vojvodini/Srbiji

Nagy, Imre; Vuksanović, Gordana; Mesaroš, Minučer; Marković, Slobodan; Gavrilov, Milivoj; Pavić, Dragoslav; Basarin, Biljana; Lukić, Ti

Towards UAV Assisted Monitoring Of An Aquatic Vegetation Within The Large Rivers – The Middle Danube

UAV technologies provide a time- and cost-efficient framework for a variety of environmental monitoring domains. It also increases data resolution and provides new insights into observed objects and phenomena, especially within the difficult-to-access and complex for monitoring aquatic habitats. The objective of this study was to develop UAV-based acquisition and GIS-based image processing guidelines for aquatic macrophyte detection and monitoring in large temperate rivers. According to the European standard CEN EN -14184:2014, the assessment of aquatic macrophytes should be performed using the transect approach. Large rivers, such as the Danube, represent an exception and should be evaluated using 1km transects. Therefore, seven transects of the Middle Danube in Serbia were simultaneously surveyed using traditional field methods and novel UAV technology. UAV images were acquired using RGB and multispectral cameras carried by a fixed-wing drone. The images were processed and orthomosaics were classified using Object Based Image Analysis (OBIA), to create digital GIS maps of the river transects. During the traditional monitoring approach, the relative abundance of 22 macrophyte species was recorded along the transects. Using the UAV technology and OBIA approach eight macrophyte classes were distinguished based on dominant macrophyte taxa or plant life form traits. Aquatic macrophytes were 'almost perfectly' distinguished from the orthomosaics, achieving a high classification accuracy of 96 % / 88 % / 0.84 for RGB and 94 % / 97 % / 0.95 Producers /Users accuracy/Kappa index for the multispectral approach. Individual macrophyte classes accuracy varied between 0.5 and 1 Kappa and were generally higher for the multispectral imagery approach. Although the resolution of the taxonomic data is lower, UAV monitoring provided the necessary spatial context of macrophytes distribution and absolute area occupied by macrophytes. It also provided information on the diversity and distribution of habitats along the river. Therefore, the UAV-assisted monitoring approach described in this study can be effectively integrated into macrophyte monitoring during large river expeditions such as the JDS

Rainfall erosivity and extreme precipitation in the Netherlands

In order to assess the rainfall erosivity of the Netherlands, several parameters which describe distribution, concentration, and variability of precipitation were used (the annual amount of precipitation, the precipitation concentration index and the modified Fournier index), as well as eleven extreme precipitation indices (maximum1-day precipitation amount, maximum 5-day precipitation amount, simple daily intensity index, number of heavy precipitation days, number of very heavy precipitation days, number of days above 25 mm, consecutive dry days, consecutive wet days, very wet days, extremely wet days, and annual total wet-day precipitation). The precipitation data for calculating the above mentioned parameters is obtained from the Royal Netherlands Meteorological Institute for the period 1957–2016. Based on statistical analysis and the calculated values, the results have been presented with the Geographic Information System (GIS) to point out the most vulnerable parts of the Netherlands with regard to pluvial erosion. This study presents the first results of combined rainfall erosivity and extreme precipitation indices for the investigated area. Trend analysis implies a shift from being largely in the low erosivity class to being completely in the moderate erosivity class in the future, thus indicating an increase in rainfall erosivity. Furthermore, the observed precipitation extremes suggest that both the amount and the intensity of precipitation are increasing. The results of this study suggest that the climate conditions in the Netherlands are changing, and that this change might have a negative influence on the rainfall erosivity of the country

Application of Angot precipitation index in the assessment of rainfall erosivity: Vojvodina Region case study (North Serbia)

The paper aims to provide an overview of the most important parameters (the occurrence, frequency and magnitude) in Vojvodina Region (North Serbia). Monthly and annual mean precipitation values in the period 1946–2014, for the 12 selected meteorological stations were used. Relevant parameters (precipitation amounts, Angot precipitation index) were used as indicators of rainfall erosivity. Rainfall erosivity index was calculated and classified throughout precipitation susceptibility classes liable of triggering soil erosion. Precipitation trends were obtained and analysed by three different statistical approaches. Results indicate that various susceptibility classes are identified within the observed period, with a higher presence of very severe rainfall erosion in June and July. This study could have implications for mitigation strategies oriented towards reduction of soil erosion by water.Prispevek podaja pregled najpomembnejših padavinskih parametrov (pojavnost, pogostost in velikost) v Vojvodini (severna Srbija). Za 12 izbranih meteoroloških postaj so bile uporabljene mesečne in letne povprečne vrednosti padavin v obdobju 1946–2014. Kot kazalnike erozivnosti padavin smo upora-bili ustrezne padavinske parametre (količina padavin, padavinski indeks Angot). Izračunali smo indeks erozivnosti padavin in ga razvrstili v razrede glede na možnost pojavljanja erozije prsti. Trende smo preučili s tremi različnimi statističnimi pristopi. V preučevanem obdobju smo prepoznali različne razrede indeksa, z zelo močno padavin erozijo junija in julija. Raziskava je dober temelj za oblikovanje strategij, usmerjenih v zmanjšanje vodne erozije prst

Uncovering the Relationship between Human Connectivity Dynamics and Land Use

CDR (Call Detail Record) data are one type of mobile phone data collected by operators each time a user initiates/receives a phone call or sends/receives an sms. CDR data are a rich geo-referenced source of user behaviour information. In this work, we perform an analysis of CDR data for the city of Milan that originate from Telecom Italia Big Data Challenge. A set of graphs is generated from aggregated CDR data, where each node represents a centroid of an RBS (Radio Base Station) polygon, and each edge represents aggregated telecom traffic between two RBSs. To explore the community structure, we apply a modularity-based algorithm. Community structure between days is highly dynamic, with variations in number, size and spatial distribution. One general rule observed is that communities formed over the urban core of the city are small in size and prone to dynamic change in spatial distribution, while communities formed in the suburban areas are larger in size and more consistent with respect to their spatial distribution. To evaluate the dynamics of change in community structure between days, we introduced different graph based and spatial community properties which contain latent footprint of human dynamics. We created land use profiles for each RBS polygon based on the Copernicus Land Monitoring Service Urban Atlas data set to quantify the correlation and predictivennes of human dynamics properties based on land use. The results reveal a strong correlation between some properties and land use which motivated us to further explore this topic. The proposed methodology has been implemented in the programming language Scala inside the Apache Spark engine to support the most computationally intensive tasks and in Python using the rich portfolio of data analytics and machine learning libraries for the less demanding tasks