In situ chemical oxidation: Lessons learned at multiple sites

This paper compiles a detailed set of in situ chemical oxidation (ISCO) lessons learned pertaining to design, execution, and safety based on global experiences over the last 20 years. While the benefits of a “correct” application are known (e.g., cost effectiveness, speed, permanence of treatment), history also provides examples of a variety of “incorrect” applications. These provide an opportunity to highlight recurring themes that resulted in failures. ISCO is, and will continue to provide, an important remedial tool for site remediation, particularly as a component of a multifaceted approach for addressing large and complex sites. Future success, however, requires an objective understanding of both the benefits and the limitations of the technology. The ability to learn from the mistakes of the past provides an opportunity to eliminate, or at least minimize, them in the future. Over the last 25 years of ISCO application, process understanding and knowledge have improved and evolved. This paper combines a thorough discussion of lessons learned through decades of ISCO implementation throughout all aspects of ISCO projects with an analysis of changes to the ISCO remediation market. By discussing the interplay of these two themes and providing recommendations from collective lessons learned, we hope to improve the future of safe, cost‐effective, and successful applications of ISCO.     

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.     

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.     

Estimating Floodwater Depths from Flood Inundation Maps and Topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS‐based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large‐scale event for which we use medium resolution input layer (10 m) and a small‐scale event for which we use a high‐resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.     

The vulnerability of Australian rural communities to climate variability and change: Part I—Conceptualising and measuring vulnerability

Vulnerability is a term frequently used to describe the potential threat to rural communities posed by climate variability and change. Despite growing use of the term, analytical measures of vulnerability that are useful for prioritising and evaluating policy responses are yet to evolve. Demand for research capable of prioritising adaptation responses has evolved rapidly with an increasing awareness of climate change and its potential impacts on rural communities. Research into the climate-related vulnerability of Australian rural communities is only just beginning to emerge. Current research is dominated by hazard/impact modelling, drawing on a heritage of managing the risks posed by seasonal climate variability. There is a natural tendency to use the same risk management approach to understand the emergent nature of vulnerability. In this paper, we explore the consequences for policy advice of imperfectly examining vulnerability through the lens of an impact/hazard modelling approach to risk management. In a second paper in this series, we show how hazard/impact modelling can be complemented with more holistic measures of adaptive capacity to provide quantitative insights into the vulnerability of Australian rural communities to climate variability and change.     

Social learning in a policy-mandated collaboration: community wildfire protection planning in the eastern United States

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and transformative learning in three case studies of Community Wildfire Protection Planning (CWPP), a policy-mandated collaboration under HFRA. Not all CWPP groups engaged in social learning. Those that did learned most about organisational priorities and values through communicative learning. Few participants gained new skills or knowledge through instrumental learning. CWPP groups had to commit to learning, but the design of the collaborative-mandate influenced the type of learning that was most likely to occur. This research suggests a potential role for top-down policy in setting the structural context for learning at the local level, but also confirms the importance of collaborative context and process in fostering social learning.     

The prebiotic synthesis of pyrimidines in frozen solution

Most prebiotic syntheses depend on the reaction of concentrated precursor compounds to produce bio-organic molecules. It is now believed that the early Earth’s atmosphere was not reducing enough to have permitted copious synthesis of precursor molecules. Freezing allows reaction to occur even from dilute solution. This reaction has been demonstrated for the purines but not for the pyrimidines. It is shown here that dilute solutions of simple prebiotic molecules produce the biological pyrimidines cytosine and uracil upon freezing. Cold environments may have allowed synthesis of all of the RNA bases even from low organic yielding atmospheres, such as those of the early Earth, Mars, Titan and Europa.     

Are vocal signals used to recognize individuals during male–male competition in greater prairie-chickens (Tympanuchus cupido)?

Vocal signaling can be an important component of vertebrate communication during social interactions. If vocalizations vary among individuals but are consistent within a given individual, they may be used to discriminate among individuals. In many species, territorial males use vocalizations to discriminate between neighbors and strangers and either respond more aggressively toward strangers relative to neighbors (“dear enemy” effect) or they respond more aggressively toward neighbors relative to strangers (“nasty neighbor” effect). In the greater prairie-chicken (Tympanuchus cupido), male vocalizations are an integral part of the display males produce on leks. We investigated whether male greater prairie-chickens discriminate among familiar individuals on their own territory, familiar individuals outside their normal territory and strangers from a nearby lek. Vocal characteristics varied among males, suggesting that vocalizations may potentially be used by prairie-chickens to identify individuals. Males responded to playback of prairie-chicken calls by vocalizing at a faster rate and approaching the playback speaker, but did not vary in their response to the vocalizations based on the identity of the caller. Our results suggest that variation is present among the vocalizations of individual male greater prairie-chickens, but males do not appear to discriminate among familiar individuals and strangers based solely on their “boom” vocalizations. Greater prairie-chicken vocalization likely functions as a way of announcing that a territory is occupied and defended, but it may also serve as a way of advertising to conspecifics or as a signal that is secondary to other forms of communication.     

Prospects for Development of an Index of Biotic Integrity for Evaluating Habitat Degradation in Coastal Systems

A multivariate index for assessment of habitat quality and its degradation, the Index of Biotic Integrity (IBI), has been developed for stream fish communities. the extension of the IBI concept to coastal waters is proposed by the development of an estuarine IBI based on macrobenthos and submerged aquatic vegetation. Eleven variables are proposed for inclusion in this index, although further consideration of the appropriateness of several variables is required. It is concluded that development of an IBI for coastal systems is feasible.     

Effects of gas flow rate, inlet concentration and temperature on the biofiltration of toluene vapors

In this work the variation in the elimination capacity of a biofilter as a function of the gas flow and toluene concentration was studied. A bioreactor 0.75 m high x 14.5 cm diameter was used, divided into three equal stages, using compost to support the microorganisms, and sea shells to control the pH. The biofiltration of toluene was evaluated for flows between 0.12 and 0.73 m(3)h(-1) in a concentration range of 1-3.2 gm(-3). It was observed that on increasing the toluene inlet load by 90% (from 37 to 70 gm(3)h(-1)), the conversion by the biofilter varied by only 5% (from 98% to 93%). The biofiltration system used achieved elimination capacities of up to 82 gm(-3)h(-1) for a toluene load of 100 gm(-3)h(-1).