Daily Updating of Operational Statistical Seasonal Water Supply Forecasts for the western U.S.1

Abstract: Official seasonal water supply outlooks for the western United States are typically produced once per month from January through June. The Natural Resources Conservation Service has developed a new outlook product that allows the automated production and delivery of this type of forecast year‐round and with a daily update frequency. Daily snow water equivalent and water year‐to‐date precipitation data from multiple SNOTEL stations are combined using a statistical forecasting technique (“Z‐Score Regression”) to predict seasonal streamflow volume. The skill of these forecasts vs. lead‐time is comparable to the official published outlooks. The new product matches the intra‐monthly trends in the official forecasts until the target period is partly in the past, when the official forecasts begin to use information about observed streamflows to date. Geographically, the patterns of skill also match the official outlooks, with highest skill in Idaho and southern Colorado and lowest skill in the Colorado Front Range, eastern New Mexico, and eastern Montana. The direct and frequent delivery of objective guidance to users is a significant new development in the operational hydrologic seasonal forecasting community.     

Assessment of the functionality of a pilot-scale reactor and its potential for electrochemical degradation of calmagite, a sulfonated azo-dye

Electrochemical degradation (ECD) is a promising technology for in situ remediation of diversely contaminated environmental matrices by application of a low level electric potential gradient. This investigation, prompted by successful bench-scale ECD of trichloroethylene, involved development, parametric characterization and evaluation of a pilot-scale electrochemical reactor for degradation of calmagite, a sulfonated azo-dye used as a model contaminant. The reactor has two chambers filled with granulated graphite for electrodes. The system has electrical potential, current, conductivity, pH, temperature, water-level and flow sensors for automated monitoring. The reactor supports outdoor and fail-safe venting, argon purging, temperature regulation and auto-shutdown for safety. Treatment involves recirculating the contaminated solution through the electrode beds at small flow velocities mimicking low fluid-flux in groundwater and submarine sediments. The first phase of the investigation involved testing of the reactor components, its parametric probes and the automated data acquisition system for performance as designed. The results showed hydraulic stability, consistent pH behavior, marginal temperature rise (<5 degrees C) and overall safe and predictable performance under diverse conditions. Near complete removal of calmagite was seen at 3-10V of applied voltage in 8-10h. The effects of voltage and strength of electrolyte on degradation kinetics have been presented. Further, it was observed from the absorption spectra that as calmagite degrades over time, new peaks appear. These peaks were associated with degradation products identified using electrospray ionization mass spectrometry. A reaction mechanism for ECD of calmagite has also been proposed.     

Comparison of fine-scale acoustic monitoring systems using home range size of a demersal fish

We compared the results from fixed acoustic transmitters and transmitters implanted in lingcod Ophiodon elongatus provided by two fine-scale passive acoustic monitoring systems: the older Vemco^? Radio Acoustic Positioning (VRAP) system and the newer VR2W Positioning System (VPS) with either three or four receivers. The four-receiver VPS method calculated five times more positions of lingcod than VRAP and more than twice as many as the three-receiver VPS. Calculated positions of fixed transmitters were less precise with VRAP than either VPS approach. Measurements of home range for lingcod were similar between the four-receiver VPS and VRAP, which were both greater than the three-receiver VPS. Comparisons varied when lingcod were in/near complex habitats. As new technology develops, it is important to understand how new methods compare to previous methods. This may be important when describing patterns of movement or habitat use in the context of changes in habitat or management efforts.     

Measuring the environmental performance of IPPC industry: I. Devising a quantitative science-based and policy-weighted Environmental Emissions Index

This paper describes the derivation of an Environmental Emissions Index (EEI) intended to quantify the environmental performance of Integrated Pollution Prevention and Control (IPPC) installations and sectors. Characterisation and normalisation methods used in lifecycle analyses were applied to 20 routinely reported emissions parameters, pertaining to six environmental impact categories. Distance to policy targets for relevant emissions were used to weight impact categories, and link the EEI to policy priorities. Ireland and the EU15 were considered as scales of context. The European Pollutant Emission Register was a convenient source of normalisation data, but restricted the context of the EEI to industrial emissions, and distorted outputs. Using national and EU15 total loading estimates for normalisation resulted in an EEI that better reflected the relative contribution of reported emissions towards overall environmental pressures. Using Ireland's pharmaceutical sector as a case study indicated that weighting factors, and the toxicity range of NMVOC emissions, were the largest sources of EEI uncertainty. Through the integration of inventory data, scientific characterisation, and policy targets, the EEI translates reported emissions data from IPPC installations and sectors into a benchmark of environmental performance. It may be regarded as an evolving tool of potential utility to regulators and policy makers.     

Environmental emergency decision support system based on Artificial Neural Network

We present a general methodology for developing environmental emergency decision support systems (EEDSS) based on an Artificial Neural Network (ANN). We highlight the method for developing the system using an illustrative example of an unexpected atmospheric accident with an ANN prototype system for a district in Shanghai. The network architecture of the ANN is introduced. Then the development process and key technologies are addressed. The procedures for matching the environmental emergency decision support characteristics are as follows: (1) digitization (coding) of case information and emergency measures, in which the information of cases are divided into the input attributes and decision-making information, and standardized and digitized through the Feature Evaluation (FE) method and the Intensity Hierarchical (IH) method, respectively; (2) construction of environmental emergency ANN, in which Gradient Descent with Momentum and Adaptive Learning Rate (GDMALR) method (traingdx function), a modified back-propagation algorithm, is employed to do training; and (3) translation (decoding) of decision-making information, in which output data of ANN is interpreted into practical contingency measures with Translation Based on Conventional Import Ratios (TBCIR) method. The training features, time, errors, accuracy, and input attribute weights of the prototype system are analyzed. The usage of the prototype system is demonstrated through a hypothetical case. This article encounters the challenge of ANN’s own lack of training samples. We discuss to the concept of integrating Case-Based Reasoning (CBR), Genetic Algorithm (GA), and ANN to overcome this difficulty and form a technology system for generating useful decision support information for environmental emergency response.     

Leader self‐awareness: An examination and implications of women's under‐prediction

Self‐awareness represents an important aspect of leadership. However, past research on leader self‐awareness has focused on one component of self‐awareness, self versus others' ratings, leaving the second component, the ability to anticipate the views of others, largely neglected. We examined this second component of self‐awareness by focusing on women leaders who have been found to under‐predict how others rate them. In two studies, we measured how women leaders anticipate the views of their bosses in regard to their leadership. In Study 1, 194 leaders rated their leadership, were rated by their bosses, and then predicted how their bosses rated their leadership. While we found that women under‐predict their boss ratings compared with men, we did not find that boss gender or feedback played a role in this under‐prediction. In Study 2, 76 female leaders identified (via open‐ended questions) possible reasons and consequences of under‐prediction for women in organizations. Results from Study 2 reveal the following: (1) the reasons for women's under‐prediction include a lack of self‐confidence, differences in feedback needs, learned gender roles, and self‐sexism; and (2) the perceived consequences of under‐prediction are negative for both women and the organization. Copyright © 2013 John Wiley & Sons, Ltd.     

Microbial responses to combined oxidation and catalysis treatment of 1,4-dioxane and co-contaminants in groundwater and soil

Post-treatment impacts of a novel combined hydrogen peroxide (H₂O₂) oxidation and WO_x/ZrO₂ catalysis used for the removal of 1,4-dioxane and chlorinated volatile organic compound (CVOC) contaminants were investigated in soil and groundwater microbial community. This treatment train removed ~90% 1,4-dioxane regardless of initial concentrations of 1,4-dioxane and CVOCs. The Illumina Miseq platform and bioinformatics were used to study the changes to microbial community structure. This approach determined that dynamic shifts of microbiomes were associated with conditions specific to treatments as well as 1,4-dioxane and CVOCs mixtures. The biodiversity was observed to decrease only after oxidation under conditions that included high levels of 1,4-dioxane and CVOCs, but increased when 1,4-dioxane was present without CVOCs. WO_x/ZrO₂ catalysis reduced biodiversity across all conditions. Taxonomic classification demonstrated oxidative tolerance for members of the genera Massilia and Rhodococcus, while catalyst tolerance was observed for members of the genera Sphingomonas and Devosia. Linear discriminant analysis effect size was a useful statistical tool to highlight representative microbes, while the multidimensional analysis elucidated the separation of microbiomes under the low 1,4-dioxane-only condition from all other conditions containing CVOCs, as well as the differences of microbial population among original, post-oxidation, and post-catalysis states. The results of this study enhance our understanding of microbial community responses to a promising chemical treatment train, and the metagenomic analysis will help practitioners predict the microbial community status during the post-treatment period, which may have consequences for long-term management strategies that include additional biodegradation treatment or natural attenuation.

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Impact of time since collection on avian eggshell color: a comparison of museum and fresh egg specimens

Studies of avian eggshell coloration have been a long-standing research focus in behavioral evolutionary ecology. Museum collections have provided a widely used resource because they allow efficient sampling across broad temporal, geographical, and taxonomic ranges, even for species that are rare and for which sampling in the wild is ethically or practically unwarranted. We used reflectance spectrophotometry across the avian visual spectrum to compare eggshell color of specimens of the song thrush (Turdus philomelos) in two museums (Natural History Museum, UK and Auckland Museum, New Zealand) with each other and with eggshells collected fresh in New Zealand. These data enabled us to test the effects of source and storage in different museums, as well as time since collection, across four metrics of eggshell coloration: blue-green and ultraviolet chroma, overall brightness, and the spectral coefficient of variation. Variation within an egg, within a clutch, and among clutches, was similar between the two museum datasets but different from those of fresh eggs. We found significant differences in all four metrics between the collections, and that fresh eggshells reflected stronger in the blue-green wavelength than in museum eggs. This difference is most likely due to different preservation techniques and storage histories. Furthermore, an effect of time since collection was only apparent in the blue-green chroma and was higher in more recent museum eggshell samples. Our results support the use of historic museum samples in intraspecific studies of shell coloration providing that efforts are made to compare specimens, which were collected during similar periods.