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.     

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.     

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.     

Preparation and Fundamental Characterization of Cellulose Nanocrystal from Oil Palm Fronds Biomass

The objective of this work was to isolate cellulose nanocrystal (CNC) from oil palm fronds (Elaeis guineensis) and its subsequent characterization. Isolation involves sodium hydroxide/anthraquinone pulping with mechanical refining followed by total chlorine free bleaching (includes oxygen delignification, hydrogen peroxide oxidation and peracetic acid treatment) before acid hydrolysis. Bleaching significantly decreased kappa number and increased α-cellulose percentage of fibers as confirmed by Technical Association of the Pulp and Paper Industry standards. Transmission electron microscopy (TEM), X-ray diffraction, Fourier transform infrared spectroscopy and thermogravimetric analysis revealed that acid hydrolysis along with bleaching improved crystallinity index and thermal stability of the extracted nanocrystals. It was observed that CNC maintained its cellulose 1 polymorph despite hydrolysis treatment. Mean diameter as observed by TEM and average fiber aspect ratio of obtained CNC was 7.44 ± 0.17 nm and 16.53 ± 3.52, respectively making it suitable as a reinforcing material for nanocomposite.     

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.     

Hormesis and plant biology

A database has been developed that demonstrates experimental evidence of hormesis. It includes information from a broad range of biological models, including plants, and information on study design, dose-response features, and physical/chemical properties of the agents. An assessment of plant hormetic dose responses is presented based on greater than 3000 plant endpoints. Plant hormetic dose responses were observed for numerous endpoints including disease incidence, reproductive indices, mutagenic endpoints, various metabolic parameters, developmental processes, and a range of growth indicators. Quantitative features of these dose responses typically display a maximum stimulatory response less than two-fold greater than controls and a width of the stimulatory response usually less than 10-fold in dose range. The database establishes that hormetic dose responses commonly occur in plants, are broadly generalizable, and have quantitative features similar to hormetic dose responses found for animals.     

Vorwort

Ohne Zusammenfassung Verantwortliche Herausgeber: Jan Schwarzbauer · Peter Heininger · Evelyn Claus     

The development of effects-based air quality management regimes

This paper considers the evolution of attempts to control and manage air pollution, principally but not exclusively focussing upon the challenge of managing air pollution in urban environments. The development and implementation of a range of air pollution control measures are considered. Initially the measures implemented primarily addressed point sources, a small number of fuel types and a limited number of pollutants. The adequacy of such a source-control approach is assessed within the context of a changing and challenging air pollution climate. An assessment of air quality management in the United Kingdom over a 50-year timeframe exemplifies the range of issues and challenges in contemporary air quality management. The need for new approaches is explored and the development and implementation of an effects-based, risk management system for air quality regulation is evaluated.     

Particle size distribution of airborne Aspergillus fumigatus spores emitted from compost using membrane filtration

Information on the particle size distribution of bioaerosols emitted from open air composting operations is valuable in evaluating potential health impacts and is a requirement for improved dispersion simulation modelling. The membrane filter method was used to study the particle size distribution of Aspergillus fumigatus spores in air 50 m downwind of a green waste compost screening operation at a commercial facility. The highest concentrations (approximately 8 × 10⁴ CFU m⁻³) of culturable spores were found on filters with pore diameters in the range 1–2 μm which suggests that the majority of spores are emitted as single cells. The findings were compared to published data collected using an Andersen sampler. Results were significantly correlated (p < 0.01) indicating that the two methods are directly comparable across all particles sizes for Aspergillus spores.     

Biomass consumption and CO2, CO and main hydrocarbon gas emissions in an Amazonian forest clearing fire

Biomass consumption and CO₂, CO and hydrocarbon gas emissions in an Amazonian forest clearing fire are presented and discussed. The experiment was conducted in the arc of deforestation, near the city of Alta Floresta, state of Mato Grosso, Brazil. The average carbon content of dry biomass was 48% and the estimated average moisture content of fresh biomass was 42% on wet weight basis. The fresh biomass and the amount of carbon on the ground before burning were estimated as 528 t ha^?1 and 147 t ha^?1, respectively. The overall biomass consumption for the experiment was estimated as 23.9%. A series of experiment in the same region resulted in average efficiency of 40% for areas of same size and 50% for larger areas. The lower efficiency obtained in the burn reported here occurred possibly due to rain before the experiment. Excess mixing ratios were measured for CO₂, CO, CH₄, C₂–C₃ aliphatic hydrocarbons, and PM_2.5. Excess mixing ratios of CH₄ and C₂–C₃ hydrocarbons were linearly correlated with those of CO. The average emission factors of CO₂, CO, CH₄, NMHC, and PM_2.5 were 1,599, 111.3, 9.2, 5.6, and 4.8 g kg^?1 of burned dry biomass, respectively. One hectare of burned forest released about 117,000 kg of CO₂, 8100 kg of CO, 675 kg of CH₄, 407 kg of NMHC and 354 kg of PM_2.5.