A Two‐Decade Watershed Approach to Stream Restoration Log Jam Design and Stream Recovery Monitoring: Finney Creek,Washington

A federal, state, and private partnership leveraged resources and employed a long‐term, systematic approach to improve aquatic habitat degraded by decades of intensive forest management in Finney Creek, a tributary to the Skagit River of Northwest Washington State. After more than a decade of work to reduce sediment sources and the risk of landslides within the watershed, log jam installation commenced in 1999 and progressed downstream through 2010. Log jam design was adapted as experience was gained. A total of 181 log jams, including 60 floating log ballasted jams, were constructed along 12 km of channel. The goal was to alter hydraulic processes that affect aquatic habitat formation along 39 km of stream with emphasis on 18.5 km of lower Finney Creek. Aquatic habitat surveys over a five‐year period show an increase in the area of large pools and an accompanying increase in residual and maximum pool depth in the lower river reach. Channel cross sections show a generally deeper channel at the log jams, better channel definition in the gravel deposits at the head of the log jams, and improved riffle and thalweg development below the log jams. Stream temperature in the upper river decreased by 1.0°F in the first three years, and 1.1°F in the lowest treated reach over nine years. There is a trend of less stream heating over the restoration time period. Photo points show that riparian vegetation is recolonizing gravel bars.     

Chronic institutional failure and enhanced vulnerability to flash‐floods in the Cuenca Altadel Río Lerma,Mexico

The dominant paradigm in disaster risk reduction (DRR) policies has been seriously contested because of its reliance on interventions based on technocratic expertise. In the Mexican context, the influence of informal practices such as clientelism and cartelisation of the political system produces environmental degradation and vulnerability to disasters within the communities in the study site. This paper contributes to understanding of failed institutional processes and parallel practices that intensify vulnerability to disasters by contrasting the discourses of agents within a peri‐urban community in central Mexico. Employing the Situational Analysis Approach as a methodological framework, the study identifies divergent views and practices within the community, leading to different responses to disasters and to different perceptions regarding institutional performance. In addition, it finds that institutional decision‐making, based only on scientific and technical expertise, has resulted in unintended consequences that influence ongoing vulnerability to floods in the site under review.     

Judgement days: moral attitudes in the wake of local disasters

The deaths and destruction stemming from a disaster are traumatic enough to implicate victims' beliefs not only about disasters themselves but also about other social and political concerns. In particular, disasters are associated with the scapegoating of out‐groups, suggesting that even deep‐rooted moral concerns may shift, at least temporarily, after disasters. This study uses exposure to local natural disaster fatalities to examine moral judgements regarding gays¹ in United States surveys from 1984–98. Survey respondents whose county has suffered a disaster feel appreciably more negatively towards gays, even though most of the disasters in this data set are relatively small and local. The increased antipathy towards gays dissipates within months, and is most marked among those who had, before the disaster, considered themselves more religious. These results raise the possibility that some groups, especially those already marginalised by society, may suffer in a backlash in the wake of a natural disaster.     

Towards a natural disaster intervention and recovery framework

Contemporary responses to facilitate long‐term recovery from large‐scale natural disasters juxtapose between those of humanitarian agencies and governments and those of the affected community. The extent to which these mechanisms articulate is crucial to the recovery propensity of the affected communities. This research examines such action by exploring the relationship between the scale of post‐disaster response interventions, the extent of community participation in them, and their impact on community recovery, using a community wealth capital framework. The investigation was applied to a study of the longer‐term community recovery of the island of Vilufushi, Republic of Maldives, which was almost completely destroyed by the Indian Ocean tsunami of 26 December 2004. Data were analysed through the employment of a pattern match technique and a holistic recovery network analysis. The research framework, informed by the case‐study results, other long‐term recovery evaluations, and existing resilience theory, is reconfigured as a testable roadmap for future post‐disaster interventions.     

The nuclear disaster management system in Taiwan: a case study of the third (Maanshan) nuclear power plant

This paper explores the effectiveness of the nuclear disaster management system in Taiwan via a review of the third (Maanshan) nuclear power plant. In doing so, the Fukushima Daiichi nuclear disaster in Japan on 11 March 2011 is reviewed and compared with the situation in Taiwan. The latter's nuclear disaster management system is examined with respect to three key variables: information; mobilisation; and inter‐organisational cooperation. In‐depth interviews with 10 policy stakeholders with different backgrounds serve as the research method. The results point up the need for improvement in all dimensions. In addition, they highlight three principal problems with the nuclear disaster management system: (i) it might not be possible to provide first‐hand nuclear disaster information immediately to the communities surrounding the Maanshan facility in Pingtung County, southern Taiwan; (ii) the availability of medical resources for treating radiation in Hengchun Township is limited; and (iii) the inter‐organisational relationships for addressing nuclear disasters need to be strengthened. Hence, cooperation among related organisations is necessary.     

A framework to minimise total energy consumption and total tardiness on a single machine

A great amount of energy is wasted in industry by machines that remain idle due to underutilisation. A way to avoid wasting energy and thus reducing the carbon print of an industrial plant is to consider minimisation of energy consumption objective while making scheduling decisions. To minimise energy consumption, the decision maker has to decide the timing and length of turn off/turn on operation (a setup) and also provide a sequence of jobs that minimises the scheduling objective, assuming that all jobs are not available at the same time. In this paper, a framework to solve a multiobjective optimisation problem that minimises total energy consumption and total tardiness is proposed. Since total tardiness problem with release dates is an NP‐hard problem, a new greedy randomised multiobjective adaptive search metaheuristic is utilised to obtain an approximate pareto front (i.e. an approximate set of non‐dominated solutions). Analytical Hierarchy Process is utilised to determine the ‘best’ alternative among the solutions on the pareto front. The proposed framework is illustrated in a case study. It is shown that a wide variety of dispersed solutions can be obtained via the proposed framework, and as total tardiness decreases, total energy consumption increases.     

The study of production and inventory policy of manufacturing/remanufacturing environment in a closed-loop supply chain

The life cycle of electronic and electrical equipment has been ruthlessly shortened due to the rapid promotion of new products. Such a phenomenon has thereby resulted in serious environmental pollution and damages to the natural ecology. In order to reduce electronic wastes and increase recycling products, a manufacturing/remanufacturing simulation model was constructed through a series of inventory management policies. The model included the use of the traditional supply chain structures for the forward movement of goods to consumers, as well as a number of specialised operations required to perform reverse supply chain activities. Such a model took into account all the supply chain members such as the suppliers, manufacturers, logistics centres and customers at the same time. Finally, a case study on the application of the model was conducted.     

Climate change and adoption of sustainable land management practices in the Niger basin of Benin

Due to the important role that the agricultural sector plays in sustaining growth and reducing poverty in developing countries, the adoption of practices that have the potential to simultaneously improve agricultural productivity while minimizing environmental impacts is essential. This paper examines the determinants of farmers’ perceptions of climate change and subsequent adoption of sustainable land management practices in the Niger basin of Benin. Binary and multivariate probit models are applied in a two‐stage regression procedure to cross‐sectional data collected through a survey of 545 randomly selected farm households in 28 villages. The findings indicate that there are substitutabilities among three pairs of sustainable land management practices being used by the farmers. Climate change perception is positively related to land tenure, experience in farming, number of relatives, tractor use, and membership in farmers’ organizations, and negatively related to household size, remoteness, and plough use. Moreover, the findings reveal that the uptake of land management practices is related to assets, land tenure, education level of the household head, remoteness, social network, non‐irrigated land size, having a farm located near a river/lake/stream, tractor and plough use, being a subsistence farmer or not, and memberships in farmers’ organizations. The adoption of sustainable land management practices could be encouraged through improving access to markets, adequate roads, and technologies, as well as by promoting membership in farmers’ organizations.     

Factors affecting the adoption of multiple climate‐smart agricultural practices in the Indo‐Gangetic Plains of India

Climate change poses a major threat to agricultural production and food security in India, and climate‐smart agriculture (CSA) is crucial in addressing the potential impacts. Using survey data from 1,267 farm households in 25 villages from Bihar and Haryana in the Indo‐Gangetic Plains, this study analyzes the factors that determine the probability and level of adoption of multiple CSA practices, including seeds of stress‐tolerant varieties, minimum tillage, laser land leveling, site‐specific nutrient management and crop diversification. We applied a multivariate probit model for the simultaneous multiple adoption decisions, and ordered probit models for assessing the factors affecting the level of adoption. The adoption of the various CSA practices is interrelated, whereas several factors, including household characteristics, plot characteristics, market access and major climate risks are found to affect the probability and level of CSA adoption. Climate‐smart agriculture (CSA) adoption and its intensity also vary significantly between eastern Bihar, which is relatively poor and densely populated, and north‐western Haryana. Engaging multiple stakeholders such as farmers, agricultural institutions, agricultural service providers and concerned government departments at the local level is crucial for the large‐scale uptake of CSA. The study, therefore, calls for agricultural policy reforms so that most of the issues related to the uptake of CSA can be adequately addressed.     

Statistical and Hybrid Methods Implemented in a Web Application for Predicting Reservoir Inflows during Flood Events

Reservoir management is a critical component of flood management, and information on reservoir inflows is particularly essential for reservoir managers to make real‐time decisions given that flood conditions change rapidly. This study's objective is to build real‐time data‐driven services that enable managers to rapidly estimate reservoir inflows from available data and models. We have tested the services using a case study of the Texas flooding events in the Lower Colorado River Basin in November 2014 and May 2015, which involved a sudden switch from drought to flooding. We have constructed two prediction models: a statistical model for flow prediction and a hybrid statistical and physics‐based model that estimates errors in the flow predictions from a physics‐based model. The study demonstrates that the statistical flow prediction model can be automated and provides acceptably accurate short‐term forecasts. However, for longer term prediction (2 h or more), the hybrid model fits the observations more closely than the purely statistical or physics‐based prediction models alone. Both the flow and hybrid prediction models have been published as Web services through Microsoft's Azure Machine Learning (AzureML) service and are accessible through a browser‐based Web application, enabling ease of use by both technical and nontechnical personnel.