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Journal Cover Natural Hazards
  [SJR: 0.465]   [H-I: 45]   [121 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1573-0840 - ISSN (Online) 0921-030X
   Published by Springer-Verlag Homepage  [2281 journals]
  • Vulnerability assessment for preliminary flood risk mapping and management
           in coastal areas
    • Abstract: Abstract Planning and management of coastal environment, both terrestrial and marine, is affected by several actions in environment resource conservation and improvement, paying specific attention to risk forecasting and preventing. In such context, the EU flood Directive 2007/60/EC, which requires Member States the assessment and management of flood risk, and the EU water framework Directive (2000/60/EC) are the key factors in the integrated river basin management to assure an efficient and rational use of resources. Afterwards, coastal risk assessment and mapping are a propaedeutic phase to plan and manage coastal areas. In this work, risk analysis refers to the results obtained by the combined application of coastal flooding and erosion risks in the activities carried out to prepare the Regional Coast Management Plan for the Ionian coast of Basilicata Region located in the south of Italy. In order to define the driving forces acting on the shore, high-resolution lidar data, bathymetric information and wave climate statistics referred to different acquisition times are used. The systemic vulnerability estimation is achieved by composing both hazard factors combined in the Coastal Criticality Index depending on the assessment of Coastal Flood Index and Coastal Erosion Index based on morphologic and socio-economic variables.
      PubDate: 2016-05-01
  • Contextualizing vulnerability assessment: a support to geo-risk management
           in central Africa
    • Abstract: Abstract In central Africa, a combination of several types of major geo-hazards threatens the highly populated area centred on the Lake Kivu Basin and the Virunga Volcanic Province. Contributing to Disaster Risk Reduction (DRR) policies not only go through hazards mechanisms analysis, but also through vulnerability assessment. This paper stresses the methodological choices made to target vulnerability assessment in a context of scarce and unreliable data. We discuss here the various stages we have overcome and the analyses conducted at the local scale, i.e. on targeted urban sites. The cities of Bukavu and Goma (Republic Democratic of Congo) count about 800,000 inhabitants each, and catastrophic events are frequently recorded. As a result of our analysis, grounding vulnerability assessment exclusively on a general definition seems not appropriate. Relevant peculiarities of the studied area should also be taken into account in vulnerability and risk assessment. Our research contributes to increase the relevance of DRR policies for risk-exposed populations. Following, one of our main concerns will be to challenge stakeholders who have to face numerous other issues on a daily basis, such as security, land issue or resources.
      PubDate: 2016-05-01
  • Integrated assessment of socio-economic risks of hazardous hydrological
           phenomena in Slavyansk municipal district
    • Abstract: Abstract In 2012, the damage costs of floods in Russia amounted to about €300m, and these floods have caused nearly 200 fatalities (Kotlyakov et al. in Reg Res Rus 3(1):32–39, 2013). Risk assessment is one of the most pressing scientific topics in Russia, but most of the works are devoted to natural hazards assessment. The purpose of this work is to estimate the influence of hazardous hydrological phenomena on society. The field research was conducted in the Slavyansk municipal district in the Krasnodar region (the south-western part of Russia), which is a highly populated coastal territory with a high frequency of hazardous hydrological events. Modified methods of the Ministry of the Russian Federation for Affairs for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters (EMERCOM) were used for potential economic damage calculation. The paper did not only focus on direct, tangible risks, but also included social risk (i.e. risk to life and health). Social vulnerability has been calculated directly as a percentage of vulnerable people, estimated in opinion polls, while in many recent papers the social vulnerability index was calculated as a combination of several statistical indicators. The resulting percentage of vulnerable people was converted to numbers of potential victims. Finally, the social risk was expressed by financial indicators in terms of the cost of the value of statistical life lost (Mrozek and Taylor in J Policy Anal Manag 21(2):253–270, 2002; Viscusi and Aldy in J Risk Uncertain 27(1):5–76, 2003). Social risk can be underestimated in comparison with economic risk because of a low “value of life” in Russia (no life insurance, neglecting of basic safety rules, etc.) (Guriev in Myths of economics, Alpina Business Books, Moscow, 2009).
      PubDate: 2016-05-01
  • Foreword: Vulnerability assessment in natural hazard risk—a dynamic
    • PubDate: 2016-05-01
  • Towards the understanding of the flash flood through isotope approach in
           Kedarnath valley in June 2013, Central Himalaya, India
    • Abstract: Abstract During middle June 2013, Kedarnath valley in Rudraprayag district of Uttarakhand, India, was affected by catastrophic rainfall episode that caused massive loss of human lives and damage to the properties and livestock. Isotopic signatures of rainfall, snow/ice melt water and river water of Mandakani River were measured from 25 May 2013 to 16 June 2013, and these isotopic signatures are used to estimate the contribution of rainfall-derived runoff on flooding day. The result indicates that during the course of flood in Mandakani River, isotopic signature of river water was −15.97 ‰, whereas average isotopic signature of river before the flood shows −10.39 ‰. By using the two-component mixed model, the contribution of rainfall-derived runoff is found to be 78 % and the contribution of snow/ice melt runoff is 22 % during the flash flood in Mandakani River surrounding the Shri Kedarnath Temple, Central Himalaya, India.
      PubDate: 2016-05-01
  • Scenario-based community flood risk assessment: a case study of Taining
           county town, Fujian province, China
    • Abstract: Abstract Community-based flood risk assessment has gained increasing attention as communities are the first responder to disasters and thus the key player of disaster risk reduction. In this study, using a scenario-based risk model and the combination of 1D/2D hydrodynamic model and participatory geographic information system, a methodology for flood risk assessment at the community level is put forward, including flood hazard assessment, exposure analysis, vulnerability assessment, and loss estimation and risk profiling. With this methodology, a set of potential damage/loss scenarios with various probabilities of flood occurrence can be established, and the spatial distribution of the loss in different probabilities can be mapped as well. It is proved that the proposed methodology is effective in flood risk assessment at the community level. The case study of Taining county town shows that the threats and impacts of flood disaster on the community are significant, and it is necessary to take structural and non-structural measures to reduce the flood risk.
      PubDate: 2016-05-01
  • Floods and associated socioeconomic damages in China over the last century
    • Abstract: Abstract Climate and land-use change increases the probability of heavy rains and flooding. In this study, we present a spatiotemporal evaluation of the changes in floods and associated socioeconomic damage in China over the last century. Results showed that 5–10-year flood were the main problem in flood disasters in China in recent decades. Floods were most common in the Yangtze River basin (27.2 % of all floods), followed by the Huaihe River basin (27, 12.7 %) in twentieth century. The area of agriculture covered and affected by floods exhibited a significant uptrend from 1950 to 2013, and the averages for both of covered area and affected area from 1991 to 2013 reflect a doubling over the averages from 1950 to 1970. A significant downtrend was found in death tolls with the deadliest flood in 1954 (42,447 deaths), and mountain torrents disaster was the main cause of death in recent decades because of the fluctuation of extreme precipitation events. Moreover, due to the combined effects of climate change and rapid urbanization, the risks of flooding increased, which mainly concentrated on the plains along the big rivers such as the Yangtze River, Pearl River and Yellow River, causing an uptrend in direct economic damage in recent years. Results obtained from this study reveal trends and distributions of floods and associated socioeconomic damages in China, which can help to fully understand floods variation.
      PubDate: 2016-05-01
  • Effectiveness of evacuation facilities in Honiara City, Solomon Islands: a
           spatial perspective
    • Abstract: Abstract Urban areas in South Pacific island countries are experiencing the effects of natural disasters related to extreme weather events, cyclones and flooding. The aim of this study was to evaluate 27 existing evacuation facilities in Honiara City and nearby areas from a spatial perspective. We use the concept of “service areas” to determine whether a given facility, or all facilities taken collectively, is accessible to the populations within its geographic proximity. To determine geographic proximity, we use the network analysis capabilities of a geographic information system (GIS) to establish service areas. Service areas are defined as the area within which people can reach a facility along a road network in a given amount of time based on the cost, or impedance, of travel along the network. Using this approach, we use the overlay capabilities of the GIS to estimate the percentage of each facility’s service area that “captures” the populations, or areas, in greatest need. With GIS census data, road network data, flood hazard data and evacuation facility data from the recent April 2014 extreme weather event, we examine the relative effectiveness of the existing facilities. We focus on disasters associated with severe weather, especially flooding and storm surge. Our analysis suggests that the 27 existing evacuation facilities in Honiara and nearby areas taken collectively provide reasonably good coverage of those populations in greatest need in a flooding or storm-surge event. However, we also find some facilities are poorly located and subsequently under used.
      PubDate: 2016-05-01
  • An efficient artificial intelligence model for prediction of tropical
           storm surge
    • Abstract: Abstract Process-based models have been widely used for storm surge predictions, but their high computational demand is a major drawback in some applications such as rapid forecasting. Few efforts have been made to employ previous databases of synthetic/real storms and provide more efficient surge predictions (e.g. using storm similarity of an individual storm to those in the database). Here, we develop an alternative efficient and robust artificial intelligent model, which predicts the peak storm surge using the tropical storm parameters: central pressure, radius to maximum winds, forward velocity, and storm track. The US Army Corp of Engineers, North Atlantic Comprehensive Coastal Study, has recently performed numerical simulations of 1050 synthetic tropical storms, which statistically represent tropical storms, using a coupled high resolution wave–surge modeling system for the east coast of the US, from Cape Hatteras to the Canadian border. This study has provided an unprecedented dataset which can be used to train artificial intelligence models for surge prediction in those areas. While numerical simulation of a storm surge at this scale and resolution (over 6 million elements scaling from 20 m to more than 100 km) is extremely expensive, the artificial intelligence takes the advantage of the previous simulations, and effectively learns the relationship between storm parameters representing storm forcing and surge. The artificial neural network method which was used for this study, was shown to outperform support vector machine for extreme storms. ANN model, which is based on a neurobiological analogy, can be conveniently developed, retrained by new data, and is nonparametric. The AI model, which was developed for Rhode Island, was validated using a set of randomly selected synthetic storms as well as real tropical storms in this region. The model performance was found satisfactory with root-mean-square error of <35 cm for observed and synthetic storms. It was also shown that it is not possible to develop a reliable artificial intelligence model for this region using a limited number of data (e.g. 200 storms), which is usually available in historical records.
      PubDate: 2016-05-01
  • Diurnal asymmetry in slant column density of NO 2 , O 3 , H 2 O and O 4
           during CAIPEEX–IGOC over Mahabubnagar, a rural site in Southern
           Peninsular India
    • Abstract: Abstract In order to study the column densities of atmospheric trace gases over a rural environment, zenith-sky scattered light observations have been carried out by employing a high-precision, portable UV-V-IR spectrometer (Ocean Optics Model HR2000) at Mahabubnagar (16°42′N, 77°58′E) during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment–Integrated Ground Observational Campaign during October 1, 2011–November 11, 2011. The observed and calculated differential optical density spectra of NO2, O3, H2O and O4 are compared in the spectral range 462–498 nm and found good agreement within a percent deviation up to 1, 1, 0.5 and 0.8 %, respectively. Differential slant column densities (SCDdiff) of NO2, O3, H2O and O4 are retrieved to present the diurnal variation at morning and evening hours between 65° and 95° solar zenith angles (SZAs). The SCDdiff at morning and evening 90° SZA are observed to be 6.4 × 1016 and 9.4 × 1016 mol cm−2 for NO2; 1.03 × 1020 and 1.38 × 1020 mol cm−2 for O3; 1.7 × 1024 and 1.8 × 1024 mol cm−2 for H2O, 1.23 × 1044 and 1.57 × 1044 mol cm−2 for O4, respectively. The diurnal variations of NO2 in twilight period are observed to vary from 36 to 75 %, O3 from 23 to 40 %, H2O from 2 to 20 % and O4 from 23 to 53 % during the study period. The SCDs of NO2, O3 and O4 are observed to be higher in the evening twilight hours compared to the morning twilight hours, which may be due to higher temperature observed at evening as compared to morning between 65° and 95° SZAs.
      PubDate: 2016-05-01
  • Monitoring reclaimed lands subsidence in Hong Kong with InSAR technique by
           persistent and distributed scatterers
    • Abstract: Abstract This paper introduced an advanced SBAS algorithm to investigate the subsidence time-series of reclaimed lands. A new method for fusing persistent and distributed scatterers in time-series images was presented in this algorithm. Moreover, nonlocal filter based on DS was employed for the interferometric phase which improved results quality with high spatial resolution. The reclaimed lands near Hong Kong Science Park and Hong Kong Disneyland (HKD) were selected for the investigation by high-resolution TerraSAR-X images. The reclaimed lands area was classified into three types labeled as undeveloped area, developing area and developed area. The results showed that: Undeveloped area had significant subsidence due to soft soil consolidation, especially in HKD’s reclaimed lands with deformation rate up to −459 mm/year; developing and developed area also had subsidence phenomenon due to building pressure caused by mass constructions of infrastructure. In particular, in the preliminary stage after construction, there was a dramatic subsidence trend, which easily threatened the security and stability of infrastructure facilities such as underground pipes and drainage system.
      PubDate: 2016-05-01
  • The danger of mapping risk from multiple natural hazards
    • Abstract: Abstract In recent decades, society has been greatly affected by natural disasters (e.g. floods, droughts, earthquakes), and losses and effects caused by these disasters have been increasing. Conventionally, risk assessment focuses on individual hazards, but the importance of addressing multiple hazards is now recognised. Two approaches exist to assess risk from multiple hazards: the risk index (addressing hazards, and the exposure and vulnerability of people or property at risk) and the mathematical statistics method (which integrates observations of past losses attributed to each hazard type). These approaches have not previously been compared. Our application of both to China clearly illustrates their inconsistency. For example, from 31 Chinese provinces assessed for multi-hazard risk, Gansu and Sichuan provinces are at low risk of life loss with the risk index approach, but high risk using the mathematical statistics approach. Similarly, Tibet is identified as being at almost the highest risk of economic loss using the risk index, but lowest risk under the mathematical statistics approach. Such inconsistency should be recognised if risk is to be managed effectively, whilst the practice of multi-hazard risk assessment needs to incorporate the relative advantages of both approaches.
      PubDate: 2016-05-01
  • Recognising na-tech events in Brazil: moving forward
    • Abstract: Abstract Loss of containment of industrial facilities and equipment triggered by natural hazards (called na-tech events) has been widely discussed in both the technical and scientific literature at least since the 1980s. Floods and landslides are amongst the most important immediate causes of na-tech events and may increase the risk to people and environment that is posed by facilities that handle hazardous materials. A na-tech event that occurred along the coastline of São Paulo state, Brazil, in February 2013, due to a precipitation event with a 1.5-h maximum rainfall of 209 mm, was the impetus for this study. We have investigated the availability of good data in some Brazilian accident databases aiming to support discussion about the increasing frequency and extent of na-tech events and the significance of the risk posed to humans by hazardous industrial facilities located in areas prone to occurrence of these events. The study has demonstrated that Brazil needs information sufficiently organised and accessible to enable evaluations of this risk, especially in coastal regions where there are predisposing factors for the occurrence of na-tech events. We propose both to include these events in the existing Brazilian accident databases and to optimise the databases by unifying or partially sharing the data. The ongoing initiative of the Brazilian National Civil Defence to improve its database can be expanded by recording na-tech events. Complementary research to identify potential sources of quality information on occurrences of na-tech events in the country is proposed in order to strengthen this initiative. Consequently, frequency analysis could be developed based on past incident data and the additional risk posed to humans by na-tech scenarios estimated and incorporated in a traditional quantitative risk assessment. Risk management in areas prone to na-tech events is expected to be improved.
      PubDate: 2016-05-01
  • Hyper-resolution mapping of regional storm surge and tide flooding:
           comparison of static and dynamic models
    • Abstract: Abstract Storm tide (combination of storm surge and the astronomical tide) flooding is a natural hazard with significant global social and economic consequences. For this reason, government agencies and stakeholders need storm tide flood maps to determine population and infrastructure at risk to present and future levels of inundation. Computer models of varying complexity are able to produce regional-scale storm tide flood maps and current model types are either static or dynamic in their implementation. Static models of storm tide utilize storm tide heights to inundate locations hydrologically connected to the coast, whilst dynamic models simulate physical processes that cause flooding. Static models have been used in regional-scale storm tide flood impact assessments, but model limitations and coarse spatial resolutions contribute to uncertain impact estimates. Dynamic models are better at estimating flooding and impact but are computationally expensive. In this study we have developed a dynamic reduced-complexity model of storm tide flooding that is computationally efficient and is applied at hyper-resolutions (<100 m cell size) over regional scales. We test the performance of this dynamic reduced-complexity model and a separate static model at three test sites where storm tide observational data are available. Additionally, we perform a flood impact assessment at each site using the dynamic reduced-complexity and static model outputs. Our results show that static models can overestimate observed flood areas up to 204 % and estimate more than twice the number of people, infrastructure, and agricultural land affected by flooding. Overall we find that that a reduced-complexity dynamic model of storm tide provides more conservative estimates of coastal flooding and impact.
      PubDate: 2016-05-01
  • Assessing agricultural drought vulnerability in the Sanjiang Plain based
           on an improved projection pursuit model
    • Abstract: Abstract Drought is one of the main natural disasters affecting regional agriculture, and regional agricultural drought vulnerability assessment is necessary to establish regional drought forecast, monitoring, and early warning mechanisms. The results can provide a theoretical basis for the identification of drought hazard and disaster prevention. In this study, the concept of the overall dispersion and local aggregation of projection points was proposed by Friedman and Tukey (IEEE Trans Comput 23:881–890, 1974), and improvements to the projection pursuit model are proposed here by measuring discrete projection points according to the information entropy. This improved model was applied to assess the agricultural drought vulnerability of 18 counties located in the Sanjiang Plain for 4 years (2004, 2007, 2010, and 2013). Information entropy was shown to provide improved measurements in the data discreteness relative to standard deviations, and the cutoff radius was defined between 0 and ln 2, thus allowing the use of the exhaustion method to determine the cutoff radius. The overall agricultural drought vulnerability in the Sanjiang Plain area shows a downward trend over time. The main reason for this result is the reduced regional sensitivity and the increased drought resistance ability each year. Economic development speeds up the urbanization process, decreasing the proportion of agricultural population and the proportion of agricultural GDP each year and increasing the irrigation index, per capita GDP, rural per capita net income and other indicators each year. These developments decrease the sensitivity of the agricultural system, improve the adaptive capacity, and reduce the vulnerability. Spatially, the vulnerability of various regions shows some differences. The vulnerabilities of Hulin, Luobei, Youyi, and Fuyuan are the lowest and showed a downward trend over time. The sensitivities of these regions were also low; the population density, the proportion of agricultural population and other sensitive indicators were significantly smaller than those for other regions. Furthermore, the drought threat is small, the region has many state-owned farms, the economic situation is good, and the drought resistance ability is strong. The vulnerabilities of Baoqing, Muling, Raohe, and Tongjiang are moderate, with high sensitivities but strong adaptive capacity. The vulnerabilities of Yilan, Jidong, Mishan, Fujin, and Boli have changed greatly, mainly due to the rapid economic development in recent years, increasing the agricultural drought resistance. The vulnerabilities of Tangyuan, Suibin, Jixian, Huachuan, and Huanan are the highest, and with little change, these regions are highly sensitive and prone to drought. In addition, the regional economic development level is relatively low, and the agricultural drought resistance is not high.
      PubDate: 2016-05-01
  • Reliability analysis with an icing model for estimating extreme events
    • Abstract: Abstract The objective of the work presented here is to improve estimates of atmospheric icing hazards, specifically for equivalent radial ice accumulation (Req) on electrical transmission lines, by solving CRREL empirical icing model as a function of random variables using reliability methods. The propagation of uncertainty in the model is preformed using first-order reliability methods (FORM) and Monte Carlo simulations. This methodology is used on clustered freezing rainstorms that form the basis of a de-aggregate hazard analysis. In this paper, freezing rain storms were clustered based on anomaly maps constructed using NCEP reanalysis data of 1000–500 hPa geopotential heights or SLP. The procedure is demonstrated with data from Montreal. The physical meanings of the different clusters were also presented in terms of wind speed, total precipitation, air mass positions, and compare with Rauber’s archetypical patterns. For single population results, the design point identified by FORM analysis for high values of Req corresponds to high total precipitation, high freezing ratios, but only slightly higher than average wind speed. For the de-aggregated analysis, different design points are associated with each clusters. These results correspond to the measured physical characteristics of extreme storms associated with the clusters. In particular, the design point associated with the cluster containing the 1961 ice storm has relatively higher equivalent wind speeds then the other clusters. The performance function being nonlinear, the results from FORM are approximate making Monte Carlo simulations more appropriate for calculating return periods. The hazard function for Req derived from reliability methods for Montreal produces results similar to those of Jones and White in The estimation and application of extremes, electrical. Transmission in a New Age, ASCE, pp 32–47, (2002) using a superstation and extreme value analysis. For the 50-year return period, de-aggregate and single population reliability analysis gives similar results. The analysis indicates Req of approximately 35, 45 and 55 mm for return periods of 50, 100 and 200 years, respectively.
      PubDate: 2016-05-01
  • School disaster resilience assessment in the affected areas of 2011 East
           Japan earthquake and tsunami
    • Abstract: Abstract A school is considered to be the core of the community in many countries, and school plays a vital role in disaster issues, both in terms of preparedness and post-disaster recovery. An integrated resilience assessment called school disaster resilience assessment (SDRA) was applied in the post-disaster recovery context in the city of Kesennuma, in Tohoku region of Japan. The city was impacted heavily by the East Japan Earthquake and Tsunami, and several schools were affected in the city. SDRA, which is an integrated tool to understand the overall disaster resilience of the school system, consists of five dimensions: physical conditions, human resources, institutional issues, external relationships, and natural conditions. Each dimension has three parameters, and each parameter has five variables. The data are collected for 75 variables. Application of SDRA in 31 schools of the city points out the importance of strengthening the relationship between school and community, and enhancing the involvement of various stakeholders in the planning process. This is significant in the recovery process due to the dynamic nature of the community, and the school–community relationship needs to evolve accordingly with the dynamism of city’s recovery. Experiences from the other city of similar size, which was affected by disasters 11 years back, and has carried out innovative disaster education program, suggest that in order to enhance school’s resilience, not only schools but also local government needs to make efforts for school disaster management and community-based disaster management. Periodic assessment in disaster recovery process is required so that appropriate activities and policies can be adopted, and the results can be visible on the ground.
      PubDate: 2016-05-01
  • Drought prediction in Apalachicola–Chattahoochee–Flint River
           Basin using a semi-Markov model
    • Abstract: Abstract The Markov models widely used in hydrology are not adequate for drought analysis because they are independent of previous processes in dealing with associated significant autocorrelations of hydrological events. Therefore, use of semi-Markov model becomes more realistic for studying droughts processes due to dynamics of the system. An embedded Markov-based model was developed to assess chances of occurrence of hydrological droughts in which waiting times of the series were defined explicitly. This presents a more global parametric method to define drought duration compared to those frequently used. This model was applied to monthly streamflow series of Apalachicola River, Chattahoochee River and Flint River in Apalachicola–Chattahoochee–Flint (ACF) River Basin, located in southeastern USA. The streamflow conditions below the mean resulting to Near Drought and Critical Drought conditions were considered crucial. Drought occurrence probabilities and corresponding flows indicate a 42 % chance of Near Drought condition and 18 % chance of Critical Drought condition, with transition time of about 1.8 months. The model results were validated using last ten-year data series. Correlation coefficient (r) and root-mean-square error statistics demonstrate that the model can predict Near Drought and Critical Drought conditions with high accuracy, resulting in errors less than 5 % statistical significance. The method is capable of preserving longer memory persistence of historic flow trends in the ACF River Basin, and gives an effective recursive equation of defining occurrence of droughts. The semi-Markov model developed in this work will provide valuable lead in estimating similar drought indices in other related river systems.
      PubDate: 2016-05-01
  • A wind tunnel study of sand-cemented bodies on wind erosion intensity and
           sand transport
    • Abstract: Abstract Wind tunnel experiments were used to test the capacity of sand-cemented bodies (SCB) on mulch beds. The total sand transport rate decreased as the level of SCB coverage increased. At higher SCB coverage (more than 40 %), the sand transport was basically unaffected by further increases in SCB coverage. While at low SCB coverage (less than 10 %), wind velocity played an important role in sand transport. Under the same SCB coverage, the sand transport depends on the increasing SCB size, due to the decrease in SCB density. The wind erosion intensity exponentially decreased with increasing SCB coverage (less than 40 %). The vertical profiles of horizontal mass flux from the SCB mulch–sand surface were also described by an exponential relationship. The vertical sand movement of particles was more sensitive to changes in SCB coverage at 20–40 %, compared with at less than 10 %. When the SCB coverage was more than 40 %, the decay rate of sand transport with height was nearly invariable. In summary, increases in SCB coverage had anti-erosion benefits for the underlying sand surface and could be considered for the development of a new type of sand fixation technology.
      PubDate: 2016-05-01
  • Spatio-temporal distribution of flood disasters and analysis of
           influencing factors in Africa
    • Abstract: Abstract To analyse inner- and inter-annual changes, disaster events of 55 countries in Africa from 1990 to 2014 recorded in the International Disaster Database (EM-DAT) were recounted by year and month and were reorganised in five different regions. Thematic maps of flood disasters in Africa between 1990 and 2014 were drawn using ArcGIS 9.3 to research the spatial distribution patterns of average annual flood frequency, total deaths, total affected, and damage. There were eight natural and socio-economic indicators chosen to explore the main factors influencing the spatio-temporal distribution of flood disasters in Africa, including precipitation, ENSO, runoff, forest coverage rate, reservoir capacity, per capita GDP, population, and urbanisation rate. Studies show that seasonal changes of flood disasters in various regions of Africa, except North Africa, are closely related to precipitation. Annual flood frequencies, from 1990 to 2014, showed a fluctuating upward trend and were in good agreement with ENSO years. In terms of spatial distributions, Ethiopia, Kenya, Somalia, Tanzania in eastern Africa, Nigeria in western Africa, and Libya, and Sudan in northern Arica are flood-prone countries, and main factors influencing spatial disparities include runoff, per capita GDP, population, and urbanisation rate.
      PubDate: 2016-05-01
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