Quantity and biochemical composition of sedimentary organic matter around offshore gas extraction platforms of the Adriatic Sea

Gas platforms can exert relevant effects on various ecosystem properties of the hosting area, modifying patterns of productivity and particle sedimentation. We hypothesised that the presence of gas platforms is associated with higher organic matter (OM) contents and we tested the null hypothesis by which benthic trophic conditions do not vary significantly among gas structures with different architectural characteristics. To test these hypotheses, we investigated sedimentary OM contents and biochemical composition at increasing distance from two distinct structures: one subsea well-site and one four-leg platform (FLP). We found that sediments surrounding the structures were characterised by similar OM contents, but different biochemical compositions, and that sedimentary OM compositional change with increasing distance from the structure is confirmed only at the FLP. These results suggest that: (i) benthic eutrophication is not consistent among different structures; (ii) OM biochemical composition changes are more evident than those in OM quantity; and (iii) the effect, wherever present, disappears at a very narrow distance from the platform. As biochemical composition of OM reflects food availability for benthic organisms, our results suggest that the enrichment of macrozoobenthic communities around these structures could be the consequence of increased nutritional quality of resources.     

Geochemical disturbance of soil cover in the nonferrous mining centers of the Selenga River basin

The anthropogenic geochemical transformation of soil cover in large nonferrous mining centers of the Selenga River basin was assessed. The results of the geochemical survey of 2010–2012 revealed the spatial distribution patterns and abundances of 18 hazardous heavy metals and metalloids in the soils of Erdenet (Mongolia) and Zakamensk (Buryat republic, Russian Federation). In both cities, mining activities disturbed soil cover which accumulates Mo, Cu, As, Sb, W in Erdenet and Bi, W, Cd, Be, Pb, Mo, Sb in Zakamensk. Maximum accumulation of elements in Erdenet is restricted to the industrial zone. In Zakamensk, it has spread on ½ of the territory with the degree of multielemental pollution exceeding the extremely dangerous level by 16 times. The effect of mining centers on the state of the river system is local and does not spread to the Selenga River. Downstream from Erdenet, an artificial pool intercepts heavy metal and metalloid flows of the Erdenetii-Gol River. By contrast, downstream from the tailing dumps of the Dzhida tungsten–molybdenum plant the concentrations of ore elements W and Mo and their accessories Bi and Cd in the Modonkul River exceed background values by 146, 20, 57, and 21 times, respectively, decreasing by an order of magnitude 30 km downstream.     

Assessment of the ecological risk of technogenic soil pollution on the basis of the statistical distribution of the occurrence of micromycete species

A methodology of substantiating the ecological risk of technogenic soil pollution has been described according to the results of bioindication using microfungal communities. At the first state, the values of the factors under which the frequency of each species is maximal were estimated using ordination methods. The statistical distribution of the species sensitivity was simulated according to these data. The methodology was illustrated using the results of analysis of the toxicity of soil samples from uranium mine dumps (the village of Kadzhi-Sai, Kyrgyzstan). The preliminary estimates of the critical values of six soil pollution indices that provide the defined allowable probability of the ecological risk have been given.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Constraining SWAT Calibration with Remotely Sensed Evapotranspiration Data

Historically, many watershed studies have been based on using the streamflow flux, typically from a single gauge at the basin's outlet, to support calibration. In this setting, there is great potential for equifinality of parameters during the optimization process, especially for parameters that are not directly related to streamflow. Therefore, some of the optimal parameter values achieved during the autocalibration process may be physically unrealistic. In recent decades a vast array of data from land surface models and remote sensing platforms can help to constrain hydrologic fluxes such as evapotranspiration (ET). While the spatial resolution of these ancillary datasets varies, the continuous spatial coverage of these gridded datasets provides flux measurements across the entire basin, in stark contrast to point‐based streamflow data. This study uses Global Land Evaporation: the Amsterdam Model data to constrain Soil and Water Assessment Tool parameter values associated with ET to a more physically realistic range. The study area is the Little Washita River Experimental Watershed, in southern Oklahoma. Traditional objective metrics such as the Nash‐Sutcliffe coefficients record no performance improvement after application of this method. However, there is a dramatic increase in the number of days with receding flow where simulations match observed streamflow.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Recovering Food Commons in Post Industrial Europe: Cooperation Networks in Organic Food Provisioning in Catalonia and Norway

This paper explores food commoning through an ethnographic case study in Catalonia as our primary site while the Norwegian case is juxtaposed as a comparison, two agriculturally and economically different European countries. The ethnography analyses cooperation networks between organic food producers’ and consumers’ involving different nodes of community gardening initiatives, self-employed growers, local farmers and all of them under a unique cooperative integrating a community economy. The result it is a myriad of exchange practices ranging from reciprocity and barter to market exchange without intermediaries through on-line platforms. Along these exchanges different options of currency intervene giving rise to novel social and cooperative relations. Similar initiatives in Norway show less variation and are less experimental regarding forms of payment but share similarities in relation to material articulations, concerns and forms of alternative practice. Although these novel forms do not represent a complete break from the more standardized supply chains, and hence from the oppositions/contradictions of production and consumption, the participants see themselves as contributing to a more general process of de-commodification of food. We explore the extent to which the meaning and moral values are mutually constituted in relation to socioeconomic exchanges and environmental caring that each person experiences based on different forms of cooperation and reciprocity. Food, we suggest, is more than a commodity on the market that we may influence through our role as consumers. It is a significant focal point connecting our lives to those of others that articulates one’s relations to society in a political manner.     

Changes in Streambed Composition in Salmonid Spawning Habitat of the Elwha River during Dam Removal

One uncertainty associated with large dam removal is the level of downstream sediment deposition and associated short‐term biological effects, particularly on salmonid spawning habitat. Recent studies report downstream sediment deposition following dam removal is influenced by proximity to the source and river transport capacity. The impacts of dam removal sediment releases are difficult to generalize due to the relatively small number of dam removals completed, the variation in release strategies, and the physical nature of systems. Changes to sediment deposition and associated streambed composition in the Elwha River, Washington State, were monitored prior to (2010‐2011) and during (2012‐2014) the simultaneous removal of two large dams (32 and 64 m). Changes in the surface layer substrate composition during dam removal varied by year and channel type. Riffles in floodplain channels downstream of the dams fined and remained sand dominated throughout the study period, and exceeded levels known to be detrimental to incubating salmonids. Mainstem riffles tended to fine to gravel, but appear to be trending toward cobble after the majority of the sediment was released and transported through system. Thus, salmonid spawning habitats in the mainstem appear to have been minimally impacted while those in floodplain channels appear to have been severely impacted during dam removal.