Masterplanning at the Port of Dover: The Use of Discrete-Event Simulation in Managing Road Traffic

The Port of Dover is Europe’s busiest ferry port, handling £119 billion or 17% of the UK’s annual trade in goods. The Port is constrained geographically to a small area and faces multiple challenges, both short- and long-term, with managing the flow of five million vehicles per year to/from mainland Europe. This article describes some of the work that the Port is doing to minimize the impact of port road traffic on the local community and environment using discrete-event simulation modeling. Modeling is particularly valuable in identifying where future bottlenecks are likely to form within the Port due to projected growth in freight traffic and comparing the effectiveness of different interventions to cope with growth. One of our key findings is that space which can be used flexibly is far more valuable than dedicated space. This is supported by the much greater reduction in traffic congestion that is expected to be achieved given a 10% increase in freight traffic by reallocating space at the front of the system to temporarily hold vehicles waiting to pass through border control and check-in compared to extending the amount of space for ferry embarkation at the rear of the system. The importance of flexible space has implications for port design that can be applied more broadly. Modeling is also useful in identifying critical thresholds for vehicle processing times that would cause the system to become overwhelmed. Increasing the check-in time by just three to five minutes, for example, would completely exceed the Port’s capacity and produce indefinite queueing. This finding has important implications for Brexit planning. From a wider context, the research presented here nicely illustrates how simulation can be used to instill more evidence-based thinking into port masterplanning and support “green port” and other corporate sustainability initiatives

Optimizing hydropower dam location and removal in the São Francisco River basin, Brazil to balance hydropower and river biodiversity tradeoffs

To support eco-friendly hydropower planning in developing regions, we propose a spatial optimization model for locating dams to balance tradeoffs between hydropower generation and migratory fish species richness. Our model incorporates two special features. First, it is tailored to the dispersal of tropical migratory fishes, which require long, unimpeded river stretches to complete their life-cycle. To model fish with this type of dispersal pattern, we introduce the concept of a river pathway, which represents a novel way to describe river connectivity. Second, it combines decisions about dam placement and removal, thus facilitating opportunities for hydropower offsetting. We apply our model to the São Francisco River basin, Brazil, an area of hydropower-freshwater biodiversity conflict. We find that dams have reduced weighted migratory fish richness 51% compared to a pre-dam baseline. We also find that even limited dam removal has the potential to significantly enhance fish biodiversity. Offsetting the removal of a single dam by the optimal siting of new dams could increase fish richness by 25% above the current average. Moving forward, optimizing new dam sites to increase hydropower by 20%, rather than selecting the fewest number of dams, could reduce fish species losses by 89%. If decisions about locating new dams are combined with dam removal, then a win-win can even be achieved with 20% greater hydropower and 19% higher species richness. Regardless of hydropower targets and dam removal options, a key observation is that optimal sites for dams are mostly located in the upper reaches of the basin rather than along the main stem of the São Francisco River or its main tributaries

Over 200,000 kilometers of free-flowing river habitat in Europe is altered due to impoundments

European rivers are disconnected by more than one million man-made barriers that physically limit aquatic species migration and contribute to modification of freshwater habitats. Here, a Conceptual Habitat Alteration Model for Ponding is developed to aid in evaluating the effects of impoundments on fish habitats. Fish communities present in rivers with low human impact and their broad environmental settings enable classification of European rivers into 15 macrohabitat types. These classifications, together with the estimated fish sensitivity to alteration of their habitat are used for assessing the impacts of six main barrier types (dams, weirs, sluices, culverts, fords, and ramps). Our results indicate that over 200,000 km or 10% of previously free-flowing river habitat has been altered due to impoundments. Although they appear less frequently, dams, weirs and sluices cause much more habitat alteration than the other types. Their impact is regionally diverse, which is a function of barrier height, type and density, as well as biogeographical location. This work allows us to foresee what potential environmental gain or loss can be expected with planned barrier management actions in rivers, and to prioritize management actions

Using Google Scholar Institutional Level Data to Evaluate the Quality of University Research

In recent years, the extent of formal research evaluation, at all levels from the individual to the multiversity has increased dramatically. At the institutional level, there are world university rankings based on an ad hoc combination of different indicators. There are also national exercises, such as those in the UK and Australia that evaluate research outputs and environment through peer review panels. These are extremely costly and time consuming. This paper evaluates the possibility of using Google Scholar (GS) institutional level data to evaluate university research in a relatively automatic way. Several citation-based metrics are collected from GS for all 130 UK universities. These are used to evaluate performance and produce university rankings which are then compared with various rankings based on the 2014 UK Research Excellence Framework (REF). The rankings are shown to be credible and to avoid some of the obvious problems of the REF ranking, as well as being highly efficient and cost effective. We also investigate the possibility of normalizing the results for the university subject mix since science subjects generally produce significantly more citations than social science or humanities

Concurrent Sessions C: Prioritization - Prioritizing Fish Passage Barrier Removal in Great Lakes Tributaries

Rivers in the Great Lakes basin are highly fragmented due to the presence of thousands of in-stream barriers (dams and road-stream crossings). The removal or modification of barriers can restore migratory pathways for river-spawning fishes, but the costs (financial, species invasions) and benefits (access to breeding habitats) differ among potential mitigation projects. We are undertaking a three-phase project with the goal of providing a transparent method for comparing these costs and benefits to assess which barrier removal projects would offer the greatest return on investment. First, we collated several existing barrier databases to create a single, comprehensive database for the Great Lakes basin. Second, we used field surveys (n=1088 barriers) of two components of barrier passability (vertical drop, water velocity) to create a statistical model predicting probability of fish passage for each barrier in the basin. Third, we developed mathematical optimization models to determine the most efficient barrier repair/removal strategies to maximize the amount of available breeding habitat. Our database of the location of dams (n=7,091) and road-stream crossings (n=268,818) is the most comprehensive inventory to date for the GL basin. Barrier passability was positively related to upstream drainage area and negatively related to stream channel slope. Across the Great Lakes basin, spatial patterns in drainage area and slope drive several characteristic patterns in barrier passability. Barrier removal strategies generated by the optimization models are characterized by a nonlinear relationship between budget and return on investment (i.e. access to breeding habitats). We will discuss key factors that drive barrier prioritization, future data needs, and the strengths and limitations of an optimization-based approach to river restoration planning

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less tim