Abstract

Erosive rainfall varies pronouncedly in time and space. Severe events are often restricted to a few square kilometers. Radar rain data with high spatiotemporal resolution enable this pattern of erosivity to be portrayed with high detail. We used radar data with a spatial resolution of 1 km"span class="inline-formula"""sup"2"/sup""/span" over 452 503 km"span class="inline-formula"""sup"2"/sup""/span" to derive a new erosivity map for Germany and to analyze the seasonal distribution of erosivity. The expected long-term regional pattern was extracted from the scattered pattern of events by several steps of smoothing. This included averaging erosivity from 2001 to 2017 and smoothing in time and space. The pattern of the resulting map was predominantly shaped by orography. It generally agrees well with the erosivity map currently used in Germany (Sauerborn map), which is based on regressions using rain gauge data (mainly from the 1960s to 1980s). In some regions the patterns of both maps deviate because the regressions of the Sauerborn map were weak. Most importantly, the new map shows that erosivity is about 66 % larger than in the Sauerborn map. This increase in erosivity was confirmed by long-term data from rain gauge stations that were used for the Sauerborn map and which are still in operation. The change was thus not caused by using a different methodology but by climate change since the 1970s. Furthermore, the seasonal distribution of erosivity shows a slight shift towards the winter period when soil cover by plants is usually poor. This shift in addition to the increase in erosivity may have caused an increase in erosion for many crops. For example, predicted soil erosion for winter wheat is now about 4 times larger than in the 1970s. These highly resolved topical erosivity data will thus have definite consequences for agricultural advisory services, landscape planning and even political decisions. Document type: Article

Abstract

Public transport transforms urban communities and the lives of citizens living in them by stimulating economic growth, promoting sustainable lifestyles and providing a greater quality of life. Globally, the healthiest cities have one thing in common, a public and active transport network that does not depend on each person owning a personal motorised vehicle. Growing dependence on the automobile has created a multitude of problems, some of which public transport can help solve. Adverse social, environmental and health effects related to automobile emissions and car-dependency suggest that using public transport will result in a decrease in an individual&rsquo s carbon footprint, will lessen overall CO2 emissions, and will help to ease urban traffic congestion as well as encourage more effective and efficient land use. With many urban areas experiencing ongoing traffic problems, it is acknowledged that any sustainable long-term solution must entail a significant public transport element. The aim of this research study, conducted in November and December 2017, was to obtain essential baseline information on service user satisfaction levels with the existing public bus services in Galway City, Ireland. By measuring levels of satisfaction, it is possible to build our overall knowledge of the public transport network and thus identify improvements in the service that would lead to an increase in bus passenger numbers and result in reductions in the amount of cars on the roads. Results suggest deficiencies in public transport infrastructure, such as Dedicated Bus Lanes, and the lack of attention to customer services are hindering improvements in the public bus service. Document type: Article

Abstract

The use of Poisson cluster processes to model rainfall time series at a range of scales now has a history of more than 30 years. Among them, the randomised (also called modified) Bartlett–Lewis model (RBL1) is particularly popular, while a refinement of this model was proposed recently "span class="cit" id="xref_paren.1""(RBL2; "a href="#bib1.bibx10""Kaczmarska et al."/a", "a href="#bib1.bibx10""2014"/a")"/span". Fitting such models essentially relies upon minimising the difference between theoretical statistics of the rainfall signal and their observed estimates. The first statistics are obtained using closed form analytical expressions for statistics of the orders 1 to 3 of the rainfall depths, as well as useful approximations of the wet–dry structure properties. The second are standard estimates of these statistics for each month of the data. This paper discusses two issues that are important for the optimal model fitting of RBL1 and RBL2. The first issue is that, when revisiting the derivation of the analytical expressions for the rainfall depth moments, it appears that the space of possible parameters is wider than has been assumed in past papers. The second issue is that care must be exerted in the way monthly statistics are estimated from the data. The impact of these two issues upon both models, in particular upon the estimation of extreme rainfall depths at hourly and sub-hourly timescales, is examined using 69 years of 5 min and 105 years of 10 min rainfall data from Bochum (Germany) and Uccle (Belgium), respectively. Document type: Article

Abstract

The emergence of fully Automated Vehicles (AVs) is expected to occur in the next 10 to 30 years. The uncertainties related to AVs pose a series of questions about what the societal consequences of such technology are. Mainly, what are the consequences of AVs regarding accessibility? This paper uses Geurs and Van Wee’s definition of accessibility to give an exploratory answer to this question. Using a scenario-based approach which allows identifying critical decisions that will emerge shortly (or are already emerging) concerning automated travelling, this paper proposes that AVs have great potential to both seriously aggravate and considerably alleviate accessibility problems. A great deal will depend on how these critical decisions will be approached and the choices that will be made. This debate is most needed because existing research on AVs tends to focus on how to make them a commercially viable and safe technological enterprise, and on what their benefits and drawbacks are regarding variables such as carbon emissions, energy consumption, and total miles travelled. Narratives of this nature can be problematic, as they are unlikely to promote sufficient awareness about the real disruptive potential of AVs. It is crucial that stakeholders realise the extent to which—if the governance of AVs implementation processes is not taken very seriously, and the identified critical decisions are not carefully approached—these machines can materialise a dystopian mobility future. Document type: Article

Abstract

Earthquake loss estimation systems in the US, for example HAZUS (Hazard in US), have been established based on sufficient damage records for the purpose of prevention and efficient response to earthquake hazards; however, in Korea, insufficient data sets of earthquakes and damage records are currently available. In this study, the earthquake damages to pipelines in Korea using the pipeline repair rate (RR) recommended in HAZUS was reevaluated with the degree of confidence when RR is used without modification for the damage estimation of pipelines in Korea. The numerical analyses using a commercial finite element model, ABAQUS, were carried out to compare stresses and strains mobilized in both brittle and ductile pipelines constructed by the design criteria and construction specifications of both Korea and the US. These pipelines were embedded in dense sand overlying three different in situ soils (clay, sand, and gravel) subjected to earthquake excitations with peak ground accelerations (PGAs) of 0.2 to 1.2 g and 1994 Northridge and 1999 Chi-Chi earthquake loadings. The numerical results show that differences in the stress and strain rates are less than 10%. This implies that RR in HAZUS can be used for earthquake damage estimation of pipelines with a 90% confidence level in Korea. Document type: Article

Abstract

OpenStreetMap provides a valuable crowd-sourced database of raw geospatial data for constructing models of urban street networks for scientific analysis. This paper reports results from a research project that collected raw street network data from OpenStreetMap using the Python-based OSMnx software for every U.S. city and town, county, urbanized area, census tract, and Zillow-defined neighborhood. It constructed nonplanar directed multigraphs for each and analyzed their structural and morphological characteristics. The resulting data repository contains over 110,000 processed, cleaned street network graphs (which in turn comprise over 55 million nodes and over 137 million edges) at various scales—comprehensively covering the entire U.S.—archived as reusable open-source GraphML files, node/edge lists, and GIS shapefiles that can be immediately loaded and analyzed in standard tools such as ArcGIS, QGIS, NetworkX, graph-tool, igraph, or Gephi. The repository also contains measures of each network’s metric and topological characteristics common in urban design, transportation planning, civil engineering, and network science. No other such dataset exists. These data offer researchers and practitioners a new ability to quickly and easily conduct graph-theoretic circulation network analysis anywhere in the U.S. using standard, free, open-source tools. Document type: Article

Abstract

Traffic congestion is one of the most vexing city problems and involves numerous factors which cannot be addressed without a holistic approach. Congestion cannot be narrowly tackled at the cost of a city&rsquo s quality of life. Focusing on transport and land use planning, this paper examines transport policies and practices on both the supply and demand sides and finds that indirect travel demand management might be the most desirable solution to this chronic traffic ailment. The concept of absorption of traffic demand through the renaissance of streets as a way for traffic relief is introduced from two perspectives, with some examples from dense Asian urban contexts to demonstrate this. Firstly, jobs&ndash housing balance suggests the return of production activities to residential areas and sufficient provision of diverse space/housing options to deal with work-related traffic. The second approach is to promote the street as a multi-activity destination rather than a thoroughfare to access dispersed daily needs, and to advocate more street life to diminish non-commuting traffic. Based on this, suggestions for better transport planning policies are put forward. Document type: Article

Abstract

Abstract. Due to their widespread and continuous expansion, transportation networks are considerably exposed to natural hazards such as earthquakes, floods, landslides or hurricanes. The vulnerability of specific segments and structures among bridges, tunnels, pumps or storage tanks can translate not only into direct losses but also into significant indirect losses at the systemic level. Cascading effects such as post-event traffic congestion, building debris or tsunamis can contribute to an even greater level of risk. To support the effort of modeling the natural hazards' implications at the full transportation network scale, we developed a new applicable framework, relying on (i) GIS to define, analyze and represent transportation networks; (ii) methods for determining the probability of network segments to fail due to natural-hazard effects; (iii) Monte Carlo simulation for multiple scenario generation; (iv) methods to analyze the implications of connectivity loss on emergency intervention times and transit disruption; and (v) correlations with other vulnerability and risk indicators. Currently, the framework is integrated into ArcGIS Desktop as a toolbox entitled “Network-risk”, which makes use of the ModelBuilder functions and is free to download and modify. Network-risk is an attempt to bring together interdisciplinary research with the goal of creating an automated solution to deliver insights on how a transportation network can be affected by natural hazards, directly and indirectly, assisting in risk evaluation and mitigation planning. In this article we present and test Network-risk at the full urban scale for the road network of Bucharest. This city is one of Europe's most exposed capitals to earthquakes, with high seismic-hazard values and a vulnerable building stock but also significant traffic congestion problems not yet accounted for in risk analyses and risk reduction strategies. Document type: Article