Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management

There has recently been a return in climate change risk management practice to bottom‐up, robustness‐based planning paradigms introduced 40 years ago. The World Bank's decision tree framework (DTF) for “confronting climate uncertainty” is one incarnation of those paradigms. In order to better represent the state of the art in climate change risk assessment and evaluation techniques, this paper proposes: (1) an update to the DTF, replacing its “climate change stress test” with a multidimensional stress test; and (2) the addition of a Bayesian network framework that represents joint probabilistic behavior of uncertain parameters as sensitivity factors to aid in the weighting of scenarios of concern (the combination of conditions under which a water system fails to meet its performance targets). Using the updated DTF, water system planners and project managers would be better able to understand the relative magnitudes of the varied risks they face, and target investments in adaptation measures to best reduce their vulnerabilities to change. Next steps for the DTF include enhancements in: modeling of extreme event risks; coupling of human‐hydrologic systems; integration of surface water and groundwater systems; the generation of tradeoffs between economic, social, and ecological factors; incorporation of water quality considerations; and interactive data visualization.     

Agricultural Adaptation to Drought for Different Cropping Systems in Southern China under Climate Change

This study investigates agricultural adaptation to drought for different cropping systems in southern China. The study area was divided into three regions: South China (SC), South of the Yangtze River (SYR), and Southwest China (SWC). An index of agricultural adaptation to drought (D) was established. Our findings indicated that the average total crop water demand varied greatly among the regions from 1961 to 2010 in southern China. The maximum value was found in the SC region, followed by the SYR and SWC regions. The effects of droughts on different crops were noticeable. Frequent droughts were recorded in late rice than in early rice in the SC and SYR regions. Droughts in the SWC region mainly affected winter wheat. Moreover, the effects of droughts on crops varied during different growth stages. More frequent and serious droughts occurred during the crop critical flowering stage. Particularly, the frequency of moderate and severe droughts for late rice in the SYR region was 62% during the critical flowering stage. For the SC and SYR regions, the D values of early rice (0.29 and 0.29) were lower than that of late rice (0.31 and 0.33), respectively. For the SWC region, the D values of winter wheat and rice were both low, with averages of 0.16 and 0.29, respectively. Our study provides interesting insights for improving the drought defense abilities for different cropping systems by changing crop planting proportion on a regional scale in China.     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.     

(Mal)Adaptation opportunism: when other interests take over stated or intended climate change adaptation objectives (and their unintended effects)

This paper introduces the terminology of (mal)adaptation opportunism – a situation in which projects undertaken in the name of climate change adaptation (CCA) are overrun by interests other than the stated or intended objectives of the CCA project. A goal of CCA projects is to reduce poverty and promote social justice. The case of the threat of displacement of the community of Kewunor by the Trasacco Estate Development Company (TEDC), after the construction of the Ada Sea Defense System (AdSDS) of Ghana as a CCA, is illustrative of this concept of (mal)adaptation opportunism. Through a narrative presentation of eight different accounts concerning this issue, I demonstrate how (mal)adaptation opportunism arises and is often motivated by economic interests. This case illustrates how economic interests can take over not only CCA projects but also their maladaptive effects.     

Creating Pedestrian Crash Scenarios in a Driving Simulator Environment

Objective: In 2012 in the United States, pedestrian injuries accounted for 3.3% of all traffic injuries but, disproportionately, pedestrian fatalities accounted for roughly 14% of traffic-related deaths (NHTSA 2014 NHTSA. Traffic Safety Facts 2012 Pedestrians. Washington, DC: Author; 2014. DOT HS 811 888. [Google Scholar]). In many other countries, pedestrians make up more than 50% of those injured and killed in crashes. This research project examined driver response to crash-imminent situations involving pedestrians in a high-fidelity, full-motion driving simulator. This article presents a scenario development method and discusses experimental design and control issues in conducting pedestrian crash research in a simulation environment. Driving simulators offer a safe environment in which to test driver response and offer the advantage of having virtual pedestrian models that move realistically, unlike test track studies, which by nature must use pedestrian dummies on some moving track.

Methods: An analysis of pedestrian crash trajectories, speeds, roadside features, and pedestrian behavior was used to create 18 unique crash scenarios representative of the most frequent and most costly crash types. For the study reported here, we only considered scenarios where the car is traveling straight because these represent the majority of fatalities. We manipulated driver expectation of a pedestrian both by presenting intersection and mid-block crossing as well as by using features in the scene to direct the driver's visual attention toward or away from the crossing pedestrian. Three visual environments for the scenarios were used to provide a variety of roadside environments and speed: a 20–30 mph residential area, a 55 mph rural undivided highway, and a 40 mph urban area.

Results: Many variables of crash situations were considered in selecting and developing the scenarios, including vehicle and pedestrian movements; roadway and roadside features; environmental conditions; and characteristics of the pedestrian, driver, and vehicle. The driving simulator scenarios were subjected to iterative testing to adjust time to arrival triggers for the pedestrian actions. This article discusses the rationale behind creating the simulator scenarios and some of the procedural considerations for conducting this type of research.

Conclusions: Crash analyses can be used to construct test scenarios for driver behavior evaluations using driving simulators. By considering trajectories, roadway, and environmental conditions of real-world crashes, representative virtual scenarios can serve as safe test beds for advanced driver assistance systems. The results of such research can be used to inform pedestrian crash avoidance/mitigation systems by identifying driver error, driver response time, and driver response choice (i.e., steering vs. braking).     

Analysis of Driver Evasive Maneuvering Prior to Intersection Crashes Using Event Data Recorders

Objective: Intersection crashes account for over 4,500 fatalities in the United States each year. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging vehicle-based active safety systems that have the potential to help drivers safely navigate across intersections and prevent intersection crashes and injuries. The performance of an I-ADAS is expected to be highly dependent upon driver evasive maneuvering prior to an intersection crash. Little has been published, however, on the detailed evasive kinematics followed by drivers prior to real-world intersection crashes. The objective of this study was to characterize the frequency, timing, and kinematics of driver evasive maneuvers prior to intersection crashes.

Methods: Event data recorders (EDRs) downloaded from vehicles involved in intersection crashes were investigated as part of NASS-CDS years 2001 to 2013. A total of 135 EDRs with precrash vehicle speed and braking application were downloaded to investigate evasive braking. A smaller subset of 59 EDRs that collected vehicle yaw rate was additionally analyzed to investigate evasive steering. Each vehicle was assigned to one of 3 precrash movement classifiers (traveling through the intersection, completely stopped, or rolling stop) based on the vehicle's calculated acceleration and observed velocity profile. To ensure that any significant steering input observed was an attempted evasive maneuver, the analysis excluded vehicles at intersections that were turning, driving on a curved road, or performing a lane change. Braking application at the last EDR-recorded time point was assumed to indicate evasive braking. A vehicle yaw rate greater than 4° per second was assumed to indicate an evasive steering maneuver.

Results: Drivers executed crash avoidance maneuvers in four-fifths of intersection crashes. A more detailed analysis of evasive braking frequency by precrash maneuver revealed that drivers performing complete or rolling stops (61.3%) braked less often than drivers traveling through the intersection without yielding (79.0%). After accounting for uncertainty in the timing of braking and steering data, the median evasive braking time was found to be between 0.5 to 1.5 s prior to impact, and the median initial evasive steering time was found to occur between 0.5 and 0.9 s prior to impact. The median average evasive braking deceleration for all cases was found to be 0.58 g. The median of the maximum evasive vehicle yaw rates was found to be 8.2° per second. Evasive steering direction was found to be most frequently in the direction of travel of the approaching vehicle.

Conclusions: The majority of drivers involved in intersection crashes were alert enough to perform an evasive action. Most drivers used a combination of steering and braking to avoid a crash. The average driver attempted to steer and brake at approximately the same time prior to the crash.     

工业厂房中基础方案优化选择研究

首先建立起影响软土地基中工业厂房基础方案选择的指标体系,然后应用层次分析法计算定量指标的评判变换矩阵和灰色评估计算定性指标的评判变换矩阵。最后用模糊综合评判法计算各方案的综合评价值,从而达到从多种可行的方案中找出最优方案的目的。     

Using Public Participation Geographic Information Systems to Identify Places of Watershed Service Provisioning

In this study, we used public participation geographic information systems methods to collect spatial data identifying places that stakeholders in Mobile Bay, Alabama think are important providers of watershed services. These methods allowed us to spatially analyze participatory data from general public respondents and directly compare them with other scientific data in a geographic information systems database. This study identified which places in the region participants believe are important providers of specific watershed services, including fish nurseries, storm protection, flood protection, and water quality protection, which would likely have public support for conservation. Additionally, we assessed the accuracy of participant watershed service identification using land cover data to identify inconsistencies and participant knowledge gaps. This information can be used to target outreach education efforts. We found that the accuracy with which participants correctly identified places with the necessary land cover to provide each service varied considerably. We believe this to be a useful tool for managers to elicit stakeholder input and to identify knowledge gaps regarding the provisioning of watershed services.     

Developing CO2 Emission Parameters to Measure the Environmental Impact on Cooling Applications

This study examines parametric approaches to the calculation of refrigerant-based CO₂ emissions in different cooling areas. Both the exergy analyses of refrigerants, used in domestic, commercial, transportation and industrial applications, and the environmental performances regarding exergetic irreversibility are investigated separately. Then, CO₂ emissions caused by systems are examined via two different parameters, I°) Environmental Impact Factor and ??°) Integrated Impact Factor (CIF). The study is based on a vapor compression cooling cycle model, commonly preferred by cooling applications, and the analyses have been made for 1 kW cooling capacity in relation to evaporator temperatures of the systems. In all cooling application, R134A gas stands out among the others in terms of coefficient of performance and exergy efficiency. Moreover, both emission analyses show that it has the lowest emission value. The paper concludes with an evaluation of the reasons for the refrigerant choice, the design and the selection of such a system, and why exergetic and environmental parameters should be preferred.     

Community acceptance of policy options for managing the maintenance of rainwater tanks

This research examined community acceptance of policy instruments that could be used to promote ongoing maintenance of domestic rainwater tank systems. Using an online survey of 533 tank owners in South East Queensland, Australia, the research investigated four sets of factors that influence policy acceptance: features of the policy, judgements of policy fairness and effectiveness, contextual framing, and individual attitudes and motivations towards tank maintenance. An experimental design incorporating choice modelling was employed. Results demonstrated that perceptions of policy fairness and effectiveness are important to acceptance. Policies that include enabling features associate with increased perceptions of effectiveness, and policies that use incentives are linked to increased perceptions of both fairness and effectiveness. Individual attitudes and motivations regarding tank maintenance were significant predictors of policy support. Perceptions of a person's own ability to undertake tank maintenance tasks were negative predictors of policy intervention, suggesting that people who believe they can carry out maintenance themselves may not see the need for a policy that encourages tank maintenance to exist. The findings are discussed in relation to issues of policy design.