Followed Journals
Journal you Follow: 0
 
Sign Up to follow journals, search in your chosen journals and, optionally, receive Email Alerts when new issues of your Followed Journals are published.
Already have an account? Sign In to see the journals you follow.
Similar Journals
Journal Cover
Natural Hazards
Journal Prestige (SJR): 0.767
Citation Impact (citeScore): 2
Number of Followers: 299  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-0840 - ISSN (Online) 0921-030X
Published by Springer-Verlag Homepage  [2625 journals]
  • Discussion of “Consequences of dike breaches and dike overflow in a
           bifurcating river system” by Anouk Bomers, Ralph M. J. Schielen and
           Suzanne J. M. H. Hulscher
    • Abstract: Abstract In this discussion, the authors will point out that even if Bomers et al. (Nat Hazards 97:309–334, 2019) tackle an important problem, ignoring the uncertainties related to the roughness coefficients, Manning coefficients, the downstream boundary and most importantly the errors of the chosen software, HEC-RAS, are serious shortcomings of their study.
      PubDate: 2020-03-29
       
  • Assessing the impact of topography and land cover data resolutions on
           two-dimensional HEC-RAS hydrodynamic model simulations for urban flood
           hazard analysis
    • Abstract: Abstract This study assesses the effects of topography and land cover data resolutions on the estimates of flood extent, inundation depths, flow velocities, and arrival times of a two-dimensional (2D) hydrodynamic HEC-RAS model under differently sized mesh structures, with the example of the urban floodplain of Kilicozu Creek (Kirsehir, Turkey). To analyse these effects under a wide range of data conditions, seven different resolution digital surface models (DSMs) (from 0.0432 to 10 m/pixel) and Manning’s roughness layers (MRLs) (from 2 to 25 m/pixel) are produced for the subject floodplain by processing the high-quality DSM and orthophoto of the Kirsehir city centre. Additionally, seven different computational point spacings (CPSs) (from 2 m × 2 m to 25 m × 25 m) are tested to evaluate changes in the model outputs depending on the dimensions of mesh grids. Simulations are carried out for 19 different DSM, MRL, and CPS configurations under the 500-year flood scenario. The simulation performed for the most detailed model configuration is utilised as the base model simulation to compare the performances of other simulations. The model simulation configurated with the 2 m cell size DSM, 10 m cell size MRL, and 10 m × 10 m CPS shows comparable performance to the base model simulation with a small loss in the accuracy of the estimates, indicating that very-fine-resolution (less than 2 m) topography and high-resolution (less than 10 m) land cover data may not be indispensable to produce reliable simulations with 2D urban flood modelling using HEC-RAS software.
      PubDate: 2020-03-28
       
  • Assessment of surface runoff conditioned by road works and urban
           settlements in large plain basins
    • Abstract: Abstract The province of Buenos Aires located in Argentina contains numerous agricultural plain basins of world importance among which the Samborombón river basin stands out, where regular floods affect agricultural activities and urban expansion. This sector has large road works with approach embankments that obstruct the natural drainage, a poorly planned urban growth, and an increase in the rainfall regime in recent decades. The aim of this work is to carry out an analysis and assessment of the surface runoff conditioned by road works and urban settlements in large plain basins, taking the Samborombón river basin as a case study. Satellite images were used to define the floodplain and identify the main road works and urban settlements that develop within it. Subsequently, hydrological simulations were carried out to assess how these anthropic structures modify the surface runoff and the flooded areas. To validate the simulation results, the flooded areas obtained were compared with a similar flood event of a Landsat image. The results show that the road works embankments and urban settlements restrict the floodplain area of the river, generating an increase in the flooded area and delaying the water runoff. This problem, together with the rainfall increase, shows the need to generate a territorial management plan and adopt mitigation measures. The use of sacrificial embankments could be an economic alternative that would prevent the obstruction of water runoff, being able to use the basin as a pilot site for this innovative idea.
      PubDate: 2020-03-26
       
  • Optimized multi-output machine learning system for engineering informatics
           in assessing natural hazards
    • Abstract: Abstract This work develops a novel metaheuristic optimization-based least squares support vector regression (LSSVR) model with a multi-output (MO) algorithm for assessing natural hazards. The MO algorithm is more efficient than the single-output algorithm because the relations among outputs can be estimated simultaneously by the proposed prediction model. Furthermore, the hyperparameters in MOLSSVR are optimized using an accelerated particle swarm optimization (APSO) algorithm combined with a self-tuning method to generate the best predictions and the fastest convergence. The APSO algorithm is validated by solving benchmark functions with unimodal and multimodal characteristics. The performance of APSO-MOLSSVR is compared with those of hybrid and single models yielded from standard multi-input single-output algorithms. A graphical user interface was designed as a stand-alone application to provide a user-friendly system for executing advanced data mining techniques. In real-world engineering cases, APSO-MOLSSVR achieved an error rate that was up to 63.55% better than those achieved using prediction models that are proposed in the single-output scheme. The system much more quickly and efficiently identified the optimal parameters and effectively solved multiple-output problems.
      PubDate: 2020-03-21
       
  • Pan-European hydrodynamic models and their ability to identify compound
           floods
    • Abstract: Abstract The interaction between storm surges and inland run-off has been gaining increasing attention recently, as they have the potential to result in compound floods. In Europe, several flood events of this type have been recorded in the past century in Belgium, France, Ireland, Italy and UK. First projections of compound flood hazard under climate change have been made, but no study has so far analysed whether existing, independent climate and hydrodynamic models are able to reproduce the co-occurrence of storm surges, precipitation, river discharges or waves. Here, we investigate the dependence between the different drivers in different observational and modelled data set, utilizing gauge records and high-resolution outputs of climate reanalyses and hindcasts, hydrodynamic models of European coasts and rivers. The results show considerable regional differences in strength of the dependence in surge–precipitation and surge–discharge pairs. The models reproduce those dependencies, and the time lags between the flood drivers, rather well in north-western Europe, but less successfully in the southern part. Further, we identified several compound flood events in the reanalysis data. We were able to link most of those modelled events with historical reports of flood or storm losses. However, false positives and false negatives were also present in the reanalysis and several large compound floods were missed by the reanalysis. All in all, the study still shows that accurate representation of compound floods by independent models of each driver is possible, even if not yet achievable at every location.
      PubDate: 2020-03-21
       
  • Evaluating landscape-scale wildfire exposure in northwestern Iran
    • Abstract: Abstract We implemented a fine-scale fire modeling approach to assess wildfire exposure in the highly valued resources and assets (HVRAs) of Ardabil Province (18,000 km2), northwestern Iran. For this purpose, we used the minimum travel time algorithm and simulated 60,000 wildfires under wildfire season most frequent weather scenarios. Wildfire exposure was analyzed on different vegetation types and municipalities using burn probability (BP), conditional flame length (CFL), and fire size (FS) modeling outputs. Also, we obtained the fire potential index (FPI) and source–sink ratio metrics to assess wildfire transmission across the study area. The BP ranged from 0.0003 to 0.013 (mean = 0.0008) and varied substantially among and within the HVRAs of the study area. While the lowest BP values located in broadleaf forests, the highest BP values concentrated on flashy fuel areas, including cereal crops, mountain meadows, and grazed pastures. The average CFL was 0.3 m, with the highest values peaking in cereal crops and wooded pastures located on slopes. FS ranged from about 1–1700 ha, with an average value of 225 ha. Fires ignited in the northern part of the study area resulted in the most significant FS values, due to the large contiguous patches of high fuel loads. High FPI values were associated with large fire ignition areas and anthropic fire occurrence hotspots in the northern and southern parts of the study area. Cereal crops and grazed pastures behaved as relevant wildfire sources of fires exposing rural communities. The results of this study may help support the development of an improved wildfire risk management policy in the study area. The methods from this study could be replicated in neighboring areas and other cultural landscapes of the Middle East, where wildfires pose a threat to human assets and natural values.
      PubDate: 2020-03-20
       
  • Trends in cooling and heating degree-days overtimes in Bangladesh' An
           investigation of the possible causes of changes
    • Abstract: Abstract An understanding of the trend in cooling and heating degree-days acts as a driving force for building energy demand under climate change conditions. However, little is known about the spatiotemporal trend patterns in cooling and heating degree-days in recent times and their possible causes in Bangladesh. Therefore, we explored the trend and variability of cooling degree-days (CDD) and heating degree-days (HDD) and their possible reasons for variation for the study period 1980–2017 based on daily temperatures datasets from 27 sites in Bangladesh. The results show that the highest annual mean CDD and HDD were identified in the southwestern and central climatic regions of Bangladesh. The CDD trend has significantly increased in Bangladesh, and the HDD trend has increased but non-significance. The outcomes of detrended fluctuation analysis (DFA) and R/S analysis exhibit that CDD and HDD will continue their contemporary trend direction in the future. Land–Ocean Temperature Index (LOTI) had a significant positive influence on CDD; however, there was no significant correlation between HDD and atmospheric circulation indices. The importance analysis from the random forest (RF) model showed that the LOTI is the highest contributing variable for CDD and East Asian Summer Monsoon Index (EASMI) is the largest influential variable for HDD affecting climate variability in Bangladesh. ECMWF ERA5 reanalysis datasets depict that higher summer geopotential height, an anticyclonic center, enhanced relative humidity, declined total and high cloud covers, decreasing surface solar radiation, and high skin temperature fluxes might have influenced on CDD and HDD variations in Bangladesh.
      PubDate: 2020-03-18
       
  • The influence of DEM spatial resolution on landslide susceptibility
           mapping in the Baxie River basin, NW China
    • Abstract: Abstract The selection of an appropriate map resolution is highly important for landslide susceptibility assessment. No consistent objective criteria, however, are currently applied to the choice of map resolution. This research, in conjunction with slope units, explores the effect of digital elevation model (DEM) resolution on susceptibility modelling using three statistical models (frequency ratio, index of entropy, and weight of evidence). Seven different spatial resolutions (30, 40, 50, 60, 70, 80, and 90 m) and three statistical models are investigated. For each resolution, we compare the performance of the three models using area under curve (AUC) analysis. The results show that, independent of the statistical models, the best performances are produced at 70 m DEM resolution. This highlights that finer resolutions do not necessarily lead to higher predictive accuracy in landslide susceptibility mapping. Rather, the frequency ratio model seems to be optimal for the coarser resolutions (i.e. 70, 80, and 90 m).
      PubDate: 2020-03-18
       
  • History of floods in Greece: causes and measures for protection
    • Abstract: Abstract Floods as diachronic and international phenomena affect numerous people, buildings and infrastructure. Throughout human history, floods are the most lethal and have caused more economic losses than other natural disasters. In this review, the history of floods is considered focusing in ancient Greece since the early Bronze Age. Ancient Greeks avoided living near lakes and rivers probably for hygiene reasons and protection from floods. Representative impressive hydraulic anti-flooding works including dams, walls, channels from different cities and other settlements in the Minoan era, and the Archaic, Classical, Hellenistic and Roman period are presented. It is concluded that the risk with respect to flood events is more severe today than in ancient times. The ongoing urbanization and deforestation through the centuries have led to an increasing and unmanageable flood risk. For this reason, a set of special measures should be applied in vulnerable areas aiming to mitigate severe damages that floods might cause, including anti-flooding dams, water flow diverting technologies, rainwater harvesting and rain gardens for stormwater retention, reforestation and other smart environmental strategies. The examples of anti-flood hydro-technologies described in this paper may have some relevance for water engineering even in modern times.
      PubDate: 2020-03-16
       
  • Low-cost UAV surveys of hurricane damage in Dominica: automated processing
           with co-registration of pre-hurricane imagery for change analysis
    • Abstract: Abstract In 2017, hurricane Maria caused unprecedented damage and fatalities on the Caribbean island of Dominica. In order to ‘build back better’ and to learn from the processes causing the damage, it is important to quickly document, evaluate and map changes, both in Dominica and in other high-risk countries. This paper presents an innovative and relatively low-cost and rapid workflow for accurately quantifying geomorphological changes in the aftermath of a natural disaster. We used unmanned aerial vehicle (UAV) surveys to collect aerial imagery from 44 hurricane-affected key sites on Dominica. We processed the imagery using structure from motion (SfM) as well as a purpose-built Python script for automated processing, enabling rapid data turnaround. We also compared the data to an earlier UAV survey undertaken shortly before hurricane Maria and established ways to co-register the imagery, in order to provide accurate change detection data sets. Consequently, our approach has had to differ considerably from the previous studies that have assessed the accuracy of UAV-derived data in relatively undisturbed settings. This study therefore provides an original contribution to UAV-based research, outlining a robust aerial methodology that is potentially of great value to post-disaster damage surveys and geomorphological change analysis. Our findings can be used (1) to utilise UAV in post-disaster change assessments; (2) to establish ground control points that enable before-and-after change analysis; and (3) to provide baseline data reference points in areas that might undergo future change. We recommend that countries which are at high risk from natural disasters develop capacity for low-cost UAV surveys, building teams that can create pre-disaster baseline surveys, respond within a few hours of a local disaster event and provide aerial photography of use for the damage assessments carried out by local and incoming disaster response teams.
      PubDate: 2020-03-12
       
  • Proudman resonance with tides, bathymetry and variable atmospheric
           forcings
    • Abstract: Abstract Proudman resonance is a primary amplification mechanism for meteotsunamis, which are shallow-water waves generated by atmospheric forcings. The effect of tides, sloping bathymetry and the speed, amplitude and aspect ratio of the atmospheric forcing on Proudman resonant wave growth are investigated using analytical approximations and numerical models. With tides included, maximum wave growth through Proudman resonance occurred when the atmospheric-forcing speed matched the tidal-wave speed. Growth greater than Proudman resonance occurred with a positive tidal elevation together with a tidal current in the opposite direction to wave propagation, due to linear growth combined with further amplification from wave-flux conservation. Near-Proudman resonant growth occurred when the forced-wave speed or free-wave speed varied by either a small amount, or varied rapidly, around a speed appropriate for Proudman resonance. For a forcing moving at Proudman resonant speed, resultant wave growth was proportional to the total, time-integrated forcing amplitude. Finally, Proudman resonant wave growth was lower for forcings with lower aspect ratios (AP), partly because forced-wave heights are proportional to 1 + AP2, but also because free waves could spread in two dimensions. Whilst the assumptions of strict Proudman resonance are never met, near-Proudman resonant growth may occur over hundreds of kilometres if the effective Froude number is near 1 and the resultant wave propagates predominantly in one dimension.
      PubDate: 2020-03-12
       
  • Characteristics of a new regional seismic-intensity prediction equation
           for Spain
    • Abstract: Abstract An updated compilation of intensity files was performed based mainly on the most recent studies of earthquake intensity distribution in Spain [above all, the revision by Martínez Solares and Mezcua (Catálogo Sísmico de la Península Ibérica (800 a.C.-1900). Monografía No. 18, Instituto Geográfico Nacional, 2002)] and an intensity dataset generated by the Instituto Geográfico Nacional in 2008 using the Did you feel it Internet-based program. The large amount of data (more than 37,000 intensity data points) enabled us to calculate an intensity prediction equation for the whole of the Spanish mainland, as well as regional equations corresponding to three Spanish seismotectonic zones. The intensity prediction equations for the three different seismotectonic regions in the Iberian Peninsula (Betic, Stable Continental Region—SCR and Pyrenees) reflect their differences. The Pyrenees zone provides the highest maxima intensities for magnitudes M 5 and 6 in the 20–100 km range of hypocentral distance, but for that distance interval, the intensities for magnitude M = 4 shown by the SCR region is higher. Finally, when comparing the theoretical intensity values obtained using the average intensity prediction equation for the Spanish mainland with the values in the dataset, anomalous behaviour occurs in the 60–120 km range, which can be explained by the Moho bounce of the energy that increases the corresponding intensity values in this distance range. This effect is suggested also by studying the PGV amplitude decay with distance using a set of 11 shallow events in the 4.5–5.1 moment magnitude interval.
      PubDate: 2020-03-11
       
  • Correction to: Coastal food: a composite method for past events
           characterisation providing insights in past, present and future
           hazards—joining historical, statistical and modelling approaches
    • Abstract: The original article was published with erroneous placement of its figures. Following reports by the author group concerning the errors, the article was granted an update + correction to show the desired rendering of the work. This correction stands to support the update, and the original article has been corrected.
      PubDate: 2020-03-09
       
  • A comparative study of the wind characteristics of three typhoons based on
           stationary and nonstationary models
    • Abstract: Abstract This study presents the results of a comparative study of the wind characteristics of three typhoons presenting similar characteristics, based on stationary and nonstationary models. The original data were collected at four different heights along the seaside of the Fujian Province (China), where the typhoons passed through. First, the run-test method and discrete wavelet transform were employed to evaluate the stationarity and extract the time-varying mean wind speed after data filtering. Then, the gust factor, turbulence intensity and turbulence integral scale were compared. The results demonstrated that the wind characteristics described by the nonstationary model were more centralized and stable than those obtained by the stationary model. Lastly, the power spectral density and evolutionary power spectral density (EPSD) were compared, revealing that the von Karman spectra fitted well the measured spectra. In addition, two methods for the analysis of nonstationary wind spectra were compared. The direct extension from stationary model to nonstationary model was found not to be reasonable from the results of this comparison. Considering the instantaneous energy concentration shown in the EPSD, a nonstationary approach is recommended when analyzing near surface typhoon wind data.
      PubDate: 2020-03-09
       
  • Social vulnerability in a high-risk flood-affected rural region of NSW,
           Australia
    • Abstract: Abstract We describe factors related to the social vulnerability of populations that experienced major river flooding in northern New South Wales (NSW), Australia. Using geographical information system methods, maps of 2017 flood-affected areas in the Lismore and Murwillumbah regions were combined with 2016 National census data to compare aspects of social vulnerability with the wider region and the region with Sydney. We also used individual-level data from the NSW 45 and Up Study to compare lifestyle, behavioural and health characteristics of residents of these flood-affected areas with the broader region (n = 13,561). Populations living in the Lismore Town Centre flood footprint exhibited significantly higher levels of social vulnerability over a range of factors; in particular, almost 82% resided in the most disadvantaged socio-economic quintile neighbourhoods. The flood-affected areas of Murwillumbah and Lismore regions included 47% and 60% of residents in the most disadvantaged quintile neighbourhoods compared to 27% for whole region and 16% for Sydney. This pattern of increased vulnerability was also apparent from the 45 and Up study; participants residing in the Lismore Town Centre flood footprint had significantly higher rates of riskier lifestyle-related behaviours (smoking, alcohol consumption), pre-existing mental health conditions (depression and anxiety) and poorer health. This detailed case study demonstrates extreme local vulnerability of flood-exposed populations, over and above the already highly vulnerable regional rural populations. This information is important to inform disaster planning and response and also reinforces the importance of having a detailed understanding of affected populations.
      PubDate: 2020-03-05
       
  • Reconstruction of a flash flood event using a 2D hydrodynamic model under
           spatial and temporal variability of storm
    • Abstract: Abstract In this paper, the catastrophic flash flood event which occurred in the western part of Attica (Greece) in November 2017 is reconstructed. The flood event hit the town of Mandra, causing 24 fatalities and huge damages in the properties and the infrastructure. The flood hydrograph was derived using the two-dimensional hydrodynamic model FLOW-R2D. Attention was drawn on the uncertainties of the model output due to the uncertainty of the estimated parameters such as infiltration, friction and the uncertainty of input data. Due to the computational burden related to the model, a global sensitivity analysis based on Morris method was performed. Then, a Monte Carlo-based uncertainty analysis was performed on the two most influential factors. It was concluded that even the results of the physically based hydrodynamic models are characterised by uncertainties. However, the capability of the hydrodynamic models to describe in detail the dynamics of the overland flow is the main advantage of these models against the conventional hydrological models. It is concluded that the rational use of physically based models for analysing complex storm phenomena with high variable spatial and temporal distribution can lead to a more accurate range of magnitudes of flood peak.
      PubDate: 2020-03-05
       
  • Anomaly-based synoptic analysis on the Heavy Rain Event of July 2018 in
           Japan
    • Abstract: Abstract The Heavy Rain Event of July 2018 caused huge social impact and economic losses in Japan. In this study, the anomaly-based synoptic analysis is applied to identify the features and structures of the anomalous synoptic systems during the event period. Results show that the heavy rainfall occurred along the trough of anomalous geopotential height (GPH) and the shear line of anomalous winds at the low troposphere. The anomalous synoptic analysis, by removing the temporal climatology from the total variables, can directly reflect the large-scale features of the event, which includes the actual position of the Baiu front, the pathway of anomalous moist air masses associated with anomalous synoptic systems such as the anomalies of Okhotsk cold high and the Northwest Pacific subtropical high. Meanwhile, the opposite signs between 200 and 850 hPa GPH anomalies, which matches observed rainfall records well, could be a good indicator of the potential heavy rain period. The product of the ensemble prediction systems from the European Centre for Medium-Range Weather Forecasts is able to predict such potential anomalous signals of the Heavy Rain Event for 4–5 days in advance.
      PubDate: 2020-03-02
       
  • Simple rainfall indices for forecasting hazardous events of hydrologic and
           geologic nature
    • Abstract: Abstract Heavy rains are the main natural trigger agent of floods and slope movements responsible for significant economic and social losses in many regions of the Brazilian territory. The affected municipalities are generally scarce in technical and economic resources to invest in mitigation actions. This work aimed to define readily available rainfall indices to predict the occurrence of these dangerous events. The main pluviometric parameters used were the daily rainfall and the mobile cycle coefficient (MCC). MCC is defined as the ratio between the total amount of rainfall accumulated over a certain period and the accumulated rainfall considered normal for this period. The analyses were based on a spatial database containing daily rainfall, flood and landslides events that occurred from 1965 to 2016 in the São Carlos municipality (São Paulo, Brazil). The structuring of this database and the subsequent spatial analyses were performed using a geographic information system software. The results indicated good potential for the combined use of MCC and daily rainfall indices to predict floods in the study area. The correlations with landslides presented some incongruities that can be mainly explained by not considering the accumulated rainfall before the triggering of landslides and the small number of events available. The simplicity and easy access to these rainfall indices favor their use to subsidize Civil Defense preventive measures, while more detailed studies are not available.
      PubDate: 2020-03-02
       
  • Coastal community resilience frameworks for disaster risk management
    • Abstract: Abstract Extreme weather events due to climate change and growing economic and development activities along coastlines have resulted in increased risks from natural and human-induced disasters—affecting the safety and livelihoods of coastal communities. Assessing community resilience to disasters is, therefore, an essential step toward mitigating their current and future risks. This study provides a systematic review of coastal community resilience frameworks for disaster risk management, covering their content, structure, and assessment. Sixty-four critical resilience criteria under four dimensions are identified by analyzing the convergence and divergence of the consideration of assessment indicators in the reviewed frameworks. Existing frameworks focus mostly on ‘governance and institutions,’ ‘infrastructure,’ and ‘society and the economy.’ Despite significant risks, the impacts on the environment and potential risks of climate change are not prioritized. Only 22% of the frameworks consider future risks, rendering the remainder inadequate for assessing projected risks from climate change. None of the frameworks consulted the full spectrum of stakeholders (public, government, and experts) during the development process, which compromised their applicability, acceptability, and effectiveness. 56% of the frameworks considered a single hazard type. Community resilience is inherently multi-dimensional. Therefore, the interrelationships between multiple hazards should be adequately addressed in future frameworks.
      PubDate: 2020-03-01
       
  • Stochastic assessment of slope failure run-out triggered by earthquake
           ground motion
    • Abstract: Abstract Analysis of the run-out of landslides is essential and vital for disaster mitigation. However, accurate run-out analysis is difficult because of the uncertainty of earthquake ground motion and variability of soil properties. To solve this problem, a new run-out assessment framework that combines the methods of probability density evolution and smoothed particle hydrodynamics is proposed. This novel framework can consider multiple stochastic factors and different slope failure models of changing sliding surfaces. We used a homogeneous 2D slope as an example and generated stochastic seismic loading samples with an intensity-frequency non-stationary ground motion model. Soil property parameters (cohesion and internal friction angle) were assumed to obey logarithmic normal distribution, and run-out parameters were evolved. Moreover, based on an equivalent extreme event, the distributions of final run-out parameters were obtained. In an example with slope height of 100 m and angle of 45°, the probability that the run-out distance is < 150 m is 90%. The probability of flow depth more than 24.5 m was about 50%. The new framework has the potential to provide references for coordinating relief efforts after landslides by predicting the extent and scope of the earthquake-induced hazard; thereby minimizing casualties and property losses caused by geological disasters triggered by earthquakes.
      PubDate: 2020-02-08
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 3.235.74.184
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-