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Journal Cover Natural Hazards
  [SJR: 0.851]   [H-I: 60]   [248 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  [2351 journals]
  • The impact of environmental regulation on the coordinated development of
           environment and economy in China
    • Authors: Huaming Zhang; Zhishuang Zhu; Yingjun Fan
      Pages: 473 - 489
      Abstract: The contradiction between environmental protection and economic development has become an important issue in China. Environmental regulation, as a vital content of public regulation, is an effective approach to rectify market failure. Thus, studying the impact of environmental regulation on the coordinated development between environment and economy is beneficial to design the most suitable environmental management system for Chinese government. Based on the theory of regulation economics and industrial organization, this paper incorporates environmental regulation policy in the traditional SCP paradigm and analyzes the conduction mechanism of market structure and market behaviors on the coordinated development between environment and economy. With the empirical analysis, we find the existence of an EKC curve, which means that tightening the environmental regulation is an effective means of guaranteeing economic growth and optimizing environmental quality. Eventually, we point out the problems existing in China’s current environmental regulation system and design a new one which is more suitable for the current economic development stage of China.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3137-3
      Issue No: Vol. 91, No. 2 (2018)
  • Hydrodynamic modeling of flash flood in mountain watersheds based on
           high-performance GPU computing
    • Authors: Xiaozhang Hu; Lixiang Song
      Pages: 567 - 586
      Abstract: Numerical accuracy and computational efficiency are the two key factors for flash flood simulation. In this paper, a two-dimensional fully hydrodynamic model is presented for the simulation of flash floods in mountain watersheds. A robust finite volume scheme is adopted to accurately simulate the overland flow with wet/dry fronts on highly irregular topography. A graphics processing unit-based parallel method using OpenACC is adopted to realize high-performance computing and then improve the computational efficiency. Since the finite volume scheme is explicit which involves many computationally intensive loop structures without data dependence, the parallel flash flood model can be easily realized by using OpenACC directives in an incremental developing way based on the serial model codes, except that data structure and transportation should be optimized for parallel algorithm. Model accuracy is validated by benchmark cases with exact solutions and experimental data. To further analyze the performance of the model, we considered a real flash flooding-prone area in China using a NVIDIA Tesla K20c card and three grid division schemes with different resolution. Results show that the proposed model can fast simulate the rainfall−runoff process related to the rapid mountain watersheds response, and a higher speedup ratio can be achieved for finer grids resolution. The proposed model can be used for real-time prediction of large-scale flash flood on high-resolution grids and thus has bright application prospects.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3141-7
      Issue No: Vol. 91, No. 2 (2018)
  • Has foreign direct investment increased air pollution in China' A
           hierarchical linear model approach
    • Authors: Xiang Cao; Ping Wang; Bangzhu Zhu
      Pages: 659 - 669
      Abstract: Focusing on the mechanism of foreign direct investment on environment, we attempt to build a series of hierarchical linear models to explore the impact of foreign direct investment on China’s sulfur dioxide (SO2) emissions by using the panel data of industrial sector in Chinese provinces from 2002 to 2013. The findings show that: Firstly, the industrial SO2 emission shows a slow downward trend. Secondly, 27.96% of the variations of SO2 emission intensity come from the differences between the provinces. Thirdly, foreign direct investment can explain 50.50% of the different changes in provincial SO2 emission intensity due to economic scale effect, structural effect, technological effect, and environmental regulation effect. Among them, the scale effect and technical effect are negatively correlated with SO2 emissions intensity, while structural and environmental regulation effects positively. Moreover, foreign direct investment can significantly inhibit the positive correlation of structural effect and weaken the negative correlation of technology effect on SO2 emission intensity, but do not have a significant impact on SO2 emission intensity by economic scale effect and environmental regulation effect.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3148-0
      Issue No: Vol. 91, No. 2 (2018)
  • Investigation of inducements and defenses of flash floods and urban
           waterlogging in Fuzhou, China, from 1950 to 2010
    • Authors: Meihong Ma; Huixiao Wang; Pengfei Jia; Ronghua Liu; Zhen Hong; Laura Gabrielle Labriola; Yang Hong; Lijuan Miao
      Pages: 803 - 818
      Abstract: In recent years, flash floods and urban waterlogging have become a widespread phenomenon in Fuzhou, which pose a serious threat to people’s lives and property. The primary disaster-causing factors include the intensity and duration of rainfall. Therefore, this article analyzes the characteristics, causes of rainfall, and the existing problems of the two disasters in Fuzhou. The main conclusions are as follows: (1) The rainfall in Fuzhou is concentrated in March to September, with high rainfall intensity and rainfall amounts, and frequent extreme rainfall events combined with high rainfall intensity in flash flood-prone areas are higher than that in the plains area. (2) Precipitation, geographical conditions, and urban construction mainly caused the two major disasters and are weak in technology and management. Therefore, it is necessary to adhere to both the structural measures and non-structural measures to coordinate the relationship between people and floods, to strengthen the research on the mechanisms of precipitation, and to forecast and provide early warning of flash floods and urban waterlogging, all of which can provide reference for the defensive disasters in mountainous coastal cities.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3156-0
      Issue No: Vol. 91, No. 2 (2018)
  • Air quality index assessment prelude to mitigate environmental hazards
    • Authors: Sutapa Chaudhuri; Arumita Roy Chowdhury
      Pages: 1 - 17
      Abstract: Air pollution has been a major transboundary problem and a matter of global concern for decades. Climate change and air pollution are closely coupled. Just as air pollution can have adverse effects on human health and ecosystems, it can also impact the earth’s climate. As we enter an era of rapid climate change, the implications for air quality need to be better understood, both for the purpose of air quality management and as one of the societal consequences of climate change. In this study, an attempt has been made to estimate the current air quality to forecast the air quality index of an urban station Kolkata (22.65°N, 88.45°E), India for the next 5 years with neural network models. The annual and seasonal variability in the air quality indicates that the winter season is mostly affected by the pollutants. Air quality index (AQI) is estimated as a geometric mean of the pollutants considered. Different neural network models are attempted to select the best model to forecast the AQI of Kolkata. The meteorological parameters and AQI of the previous day are utilized to train the models to forecast the AQI of the next day during the period from 2003 to 2012. The selection of the best model is made after validation with observation from 2013 to 2015. The radial basis functional (RBF) model is found to be the best network model for the purpose. The RBF model with various architectures is tried to obtain precise forecast with minimum error. RBF of 5:5-91-1:1 structure is found to be the best fit for forecasting the AQI of Kolkata.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3080-3
      Issue No: Vol. 91, No. 1 (2018)
  • Spatiotemporal variation of hydrological drought based on the Optimal
           Standardized Streamflow Index in Luanhe River basin, China
    • Authors: Xu Chen; Fa-wen Li; Ping Feng
      Pages: 155 - 178
      Abstract: To establish the drought index objectively and reasonably and evaluate the hydrological drought accurately, firstly, the optimal distribution was selected from nine distributions (normal, lognormal, exponential, gamma, general extreme value, inverse Gaussian, logistic, log-logistic and Weibull), then the Optimal Standardized Streamflow Index (OSSI) was calculated based on the optimal distribution, and last, the spatiotemporal evolution of hydrological drought based on the OSSI series was investigated through the monthly streamflow data of seven hydrological stations during the period 1961–2011 in Luanhe River basin, China. Results suggest: (1) the general extreme value and log-logistic distributions performed prominently in fitting the monthly streamflow of Luanhe River basin. (2) The main periods of hydrological drought in Luanhe River basin were 148–169, 75–80, 42–45, 14–19 and 8–9 months. (3) The hydrological drought had an aggravating trend over the past 51 year and with the increase in timescale, the aggravating trend was more serious. (4) The lower the drought grade was, the broader the coverage area. As for the Luanhe River basin, the whole basin suffered the mild and more serious drought, while the severe and more serious drought only cover some areas. (5) With the increase in time step, the frequency distribution of mild droughts across the basin tended to be concentrated, the frequency of extreme droughts in middle and upper reaches tended to increase and the frequency in downstream tends to decrease. This research can provide powerful references for water resources planning and management and drought mitigation.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3118-6
      Issue No: Vol. 91, No. 1 (2018)
  • Hydrological modeling of storm runoff and snowmelt in Taunton River Basin
           by applications of HEC-HMS and PRMS models
    • Authors: Fei Teng; Wenrui Huang; Isaac Ginis
      Pages: 179 - 199
      Abstract: Reliable predictions of storm runoff from rainfall and snowmelt are important for flood hazard mitigation and resilience. In this study, the HEC-HMS and PRMS hydrological models have been applied to simulate storm runoff in Taunton River Basin for the storm event in 2010 when maximum rainfall intensity reached approximate 5 in/day in March, and the snowfall reached about 11 inches in December. Model parameters were calibrated, and model performance was evaluated by comparing model-simulated daily stream flow with observations. For the rainstorm period during March–April, results indicate that both HEC-HMS and PRMS provide very good predictions of rainfall runoff with the correlation values above 0.95, and PRMS produces lower root-mean-square errors than those from HEC-HMS. Over the 12-month period including the snowfall in December, the time series of flow by PRMS match better with observations than those from the HEC-HMS. The 12-month overall correlation values for HEC-HMS and PRMS are 0.91 and 0.97 at Bridgewater Station, and 0.89 and 0.97 at Threemile Station, respectively. For an extreme storm scenario of the maximum historical 36.7-inch snowfall in early February in combination with the rainstorm in March–April of 2010, model simulations indicate that the flow would substantially increase by about 50% or more. Comparisons between HEC-HMS and RPMS models have been analyzed to provide references for storm runoff modeling.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3121-y
      Issue No: Vol. 91, No. 1 (2018)
  • Forest fire spread simulation algorithm based on cellular automata
    • Authors: Xiaoping Rui; Shan Hui; Xuetao Yu; Guangyuan Zhang; Bin Wu
      Pages: 309 - 319
      Abstract: Traditional models result in low efficiency and poor accuracy when simulating the spread of large-scale forest fires. We constructed an improved model that couples cellular automata with an existing forest fire model to ensure better time accuracy of forest fire spread. Our model considers the impact of time steps on simulation accuracy to provide an optimal time step value. The model was tested using a case study of forest fire spread at Daxing’an Mountain in May 2006. The results show that the optimal time step for the forest fire spread geographic cellular automata simulation algorithm is 1/8 of the time taken for cellular material to be completely combusted. When compared with real fire data from Landsat Thematic Mapper (TM) images, our model was found to have high temporal and spatial consistency, with a mean Kappa coefficient of 0.6352 and mean accuracy of 87.89%. This algorithm can be used to simulate and predict forest fire spread and is also reversible (i.e., it can identify fire source points).
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3127-5
      Issue No: Vol. 91, No. 1 (2018)
  • Carbon dioxide emission reduction quota allocation study on Chinese
           provinces based on two-stage Shapley information entropy model
    • Authors: Kejia Yang; Yalin Lei; Weiming Chen; Lingna Liu
      Pages: 321 - 335
      Abstract: Chinese central government made a commitment to achieve a 40–45% reduction in carbon dioxide (CO2) per unit of GDP by 2020 compared with 2005. This targeted reduction was allocated averagely among all the provinces rather than individually according to different situations of each province. Though some research has been done regarding this rough allocation, two shortcomings in previous studies exist: Firstly, CO2 marginal abatement cost (MAC) has been ignored as one of the CO2 emission reduction allocation indexes. Secondly, either subjective or objective method has been used rather than comprehensively of both subjective and objective method to calculate the weight of each index in the previous studies. In order to fill the gaps, this paper builds a two-stage Shapley information entropy model to allocate CO2 emission reduction quota among the Chinese provinces based on the equity and efficiency principles. Afterward, three CO2 emission reduction quota allocation scenarios have been proposed. The results show that the CO2 MAC is an indispensable index in CO2 emission reduction quota allocation, because its value of CO2 Shapley information entropy is the highest among five indexes. CO2 emission reduction quota of lower-MAC provinces should be allocated larger, while the quota of higher-MAC provinces should be allocated smaller. Therefore, two suggested policies have been proposed: First, differential CO2 emission reduction quota allocation should be proposed. Second, synergetic development should be promoted.
      PubDate: 2018-03-01
      DOI: 10.1007/s11069-017-3129-3
      Issue No: Vol. 91, No. 1 (2018)
  • Assessment of the hurricane-induced power outages from a demographic,
           socioeconomic, and transportation perspective
    • Authors: Mehmet Baran Ulak; Ayberk Kocatepe; Lalitha Madhavi Konila Sriram; Eren Erman Ozguven; Reza Arghandeh
      Abstract: Natural disasters have devastating effects on the infrastructure and disrupt every aspect of daily life in the regions they hit. To alleviate problems caused by these disasters, first an impact assessment is needed. As such, this paper focuses on a two-step methodology to identify the impact of Hurricane Hermine on the City of Tallahassee, the capital of Florida. The regional and socioeconomic variations in the Hermine’s impact were studied via spatially and statistically analyzing power outages. First step includes a spatial analysis to illustrate the magnitude of customers affected by power outages together with a clustering analysis. This step aims to determine whether the customers affected from outages are clustered or not. Second step involves a Bayesian spatial autoregressive model in order to identify the effects of several demographic-, socioeconomic-, and transportation-related variables on the magnitude of customers affected by power outages. Results showed that customers affected by outages are spatially clustered at particular regions rather than being dispersed. This indicates the need to pinpoint such vulnerable locations and develop strategies to reduce hurricane-induced disruptions. Furthermore, the increase in the magnitude of affected customers was found to be associated with several variables such as the power network and total generated trips as well as the demographic factors. The information gained from the findings of this study can assist emergency officials in identifying critical and/or less resilient regions, and determining those demographic and socioeconomic groups which were relatively more affected by the consequences of hurricanes than others.
      PubDate: 2018-03-10
      DOI: 10.1007/s11069-018-3260-9
  • Micro-level perception to climate change and adaptation issues: A prelude
    • Authors: Naveen P. Singh; Bhawna Anand; Mohd Arshad Khan
      Abstract: Climate change adds another dimension of challenges to the growth and sustainability of Indian agriculture. The growing exposure to livelihood shocks from climate variability/change and limited resource base of the rural community to adapt has reinforced the need to mainstream climate adaptation planning into developmental landscape. However, a better understanding of micro-level perceptions is imperative for effective and informed planning at the macro-level. In this paper, the grass-root level perspectives on climate change impacts and adaptation decisions were elicited at farm level in the Moga district of Punjab and Mahbubnagar district of Telangana, India. The farmers opined that the climatic variability impacts more than the long-term climate change. They observed change in the quantum, onset and distribution of rainfall, rise in minimum as well as maximum temperature levels, decline in crop yield and ground water depletion. The key socio-economic effects of climate change included decline in farm income, farm unemployment, rural migration and increased indebtedness among farmers. In order to cope with climate variability and change thereon, farmers resorted to adaptation strategies such as use of crop varieties of suitable duration, water conservation techniques, crop insurance and participation in non-farm activities and employment guarantee schemes. Farmers’ adaptation to changing climate was constrained by several technological, socio-economic and institutional barriers. These include limited knowledge on the costs–benefits of adaptation, lack of access to and knowledge of adaptation technologies, lack of financial resources and limited information on weather. Besides, lack of access to input markets, inadequate farm labour and smaller farm size were the other constraints. Further, on the basis of the grass-root elicitation a ‘Need-Based Adaptation’ planning incorporating farmers’ perceptions on climate change impacts, constraints in the adoption of adaptation strategies and plausible adaptation options were linked with the most suitable ongoing programmatic interventions of the Government of India. The study concluded that micro-level needs and constraints for various adaptation strategies and interventions should be an integral part of the programme development, implementation and evaluation in the entire developmental paradigm.
      PubDate: 2018-03-09
      DOI: 10.1007/s11069-018-3250-y
  • Relationship of drought frequency and severity with range of annual
           temperature variation
    • Authors: Kumar Amrit; Rajendra P. Pandey; Surendra K. Mishra; Mihail Daradur
      Abstract: The frequency and severity of occurrence of meteorological droughts in different climatic regions depend on regional climatic factors. This study has made an effort to explore the relationship of range of annual temperature variation at a given place with the frequency of occurrence of drought and the maximum magnitude of seasonal rainfall deficit (i.e., severity). The seasonal rainfall refers to sum of monsoon season (rainy season) rainfall in India. The monthly precipitation data of 113 years (1901–2013) for 256 stations in different parts of India have been used to estimate the return period of meteorological drought at different stations. The daily normal values of observed maximum and minimum temperatures from 40 years of records have been utilized to estimate range of temperature variation (θR) during the year at each stations. In various parts of India, the θR ranges from 10 °C in humid regions to 40 °C in arid regions. The various climatic regions have been experiencing maximum deficiency of annual rainfall ranging from 30% (humid) to 90% (arid). The results reveal that places exhibiting θR values between 40 to 30 °C face more frequent droughts with average frequency of once in 3 to once in 6 years. The occurrence of extreme and severe drought events is more frequent in the regions with higher values of θR compare to that in lesser values of θR. The regions with θR values between 30 to 25 °C mostly face severe and moderate events having the average drought return period of 6–9 years, and the occurrence of extreme droughts in these regions is rare. Furthermore, regions with θR < 20 °C face moderate droughts only with an average return period of 14 years. This study divulges that the average return period and magnitude of deficiency of drought events have notable relationship with the range of temperature variation during the year at a given place.
      PubDate: 2018-03-07
      DOI: 10.1007/s11069-018-3247-6
  • ShakeMap-based prediction of earthquake-induced mass movements in
           Switzerland calibrated on historical observations
    • Authors: Carlo Cauzzi; Donat Fäh; David J. Wald; John Clinton; Stéphane Losey; Stefan Wiemer
      Abstract: In Switzerland, nearly all historical Mw ~ 6 earthquakes have induced damaging landslides, rockslides and snow avalanches that, in some cases, also resulted in damage to infrastructure and loss of lives. We describe the customisation to Swiss conditions of a globally calibrated statistical approach originally developed to rapidly assess earthquake-induced landslide likelihoods worldwide. The probability of occurrence of such earthquake-induced effects is modelled through a set of geospatial susceptibility proxies and peak ground acceleration. The predictive model is tuned to capture the observations from past events and optimised for near-real-time estimates based on USGS-style ShakeMaps routinely produced by the Swiss Seismological Service. Our emphasis is on the use of high-resolution geospatial datasets along with additional local information on ground failure susceptibility. Even if calibrated on historic events with moderate magnitudes, the methodology presented in this paper yields sensible results also for low-magnitude recent events. The model is integrated in the Swiss ShakeMap framework. This study has a high practical relevance to many Swiss ShakeMap stakeholders, especially those managing lifeline systems, and to other global users interested in conducting a similar customisation for their region of interest.
      PubDate: 2018-03-07
      DOI: 10.1007/s11069-018-3248-5
  • Early warning system for detection of urban pluvial flooding hazard levels
           in an ungauged basin
    • Authors: Melisa Acosta-Coll; Francisco Ballester-Merelo; Marcos Martínez-Peiró
      Abstract: Prolonged and high intensity rainfall often saturates urban drainage systems and generates urban pluvial flooding, resulting in hazardous flash floods. The city most affected by urban flooding in Colombia (South America) is Barranquilla since lacks a proper storm water drainage system. Heavy rainfall produces flash floods to quickly become torrential streams that flow down the streets endangering pedestrians. This research describes a low-cost early warning system (EWS) to detect in real time the hazard level of a stream in an ungauged basin. The EWS indicates whether it is safe or not for pedestrians to cross a flooded street, based on certain criteria used to assess the hazard level of the torrent. A hydrological and hydraulic model calculates the flow, velocity and water level in all cross sections along the stream. The model uses only real-time measurements of rain gauges and topographic survey data to determine the hazard level. Finally, a wireless sensor network sends the alert to a web platform and warns the community in real time.
      PubDate: 2018-03-07
      DOI: 10.1007/s11069-018-3249-4
  • Prediction of open stope hangingwall stability using random forests
    • Authors: Chongchong Qi; Andy Fourie; Xuhao Du; Xiaolin Tang
      Abstract: The prediction of open stope hangingwall (HW) stability is a crucial task for underground mines. In this paper, a relatively novel technique, the random forest (RF) algorithm, is introduced for the prediction of HW stability. The objective of this study is to verify the feasibility of the RF algorithm on HW stability prediction and investigate the relative importance of influencing variables. The training and verification of RF models were conducted on a dataset from the literature and a total of 115 HW cases were analysed. Thirteen influencing variables were selected as the inputs with the HW stability being selected as the output. The dataset was randomly divided into the training set and the testing set. Fivefold cross-validation was used as the validation method, and the grid search method was used for the hyper-parameters tuning. Performance measures were chosen to be the confusion matrix, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). The results show that the RF algorithm had great potential for the prediction of HW stability. AUC values achieved by the optimum RF model on the training set and the testing set were 0.884 and 0.873, respectively, indicating that the optimum RF model was excellent at predicting HW stability. The stope design method was found to be the most sensitive variable among all variables evaluated, with an importance score of 0.168 out of 1. The RQD and HW height also had a strong influence on the stability of an open stope HW.
      PubDate: 2018-03-06
      DOI: 10.1007/s11069-018-3246-7
  • Integration of multi-parametric fuzzy analytic hierarchy process and GIS
           along the UNESCO World Heritage: a flood hazard index, Mombasa County,
    • Authors: Yves Hategekimana; Lijun Yu; Yueping Nie; Jianfeng Zhu; Fang Liu; Fei Guo
      Abstract: Flood is a natural hazard affecting human life and ecosystem globally causing catastrophic disasters. Most flood-induced socioeconomic losses are exacerbated by unabated urban development, population upsurge, unregulated municipal systems, and indiscriminate land use. Therefore, implementation of a flood prediction system can potentially help mitigate flood-induced consequences. In this study, a framework of multi-criteria analysis incorporating geographic information system, fuzzy analytic hierarchy process, and bivariate statistics-based methods was developed for flood hazard index determination. Flood-prone areas were identified based on six factors (hydrological aspects and land cover): elevation, aspect, slope, flow accumulation, rainfall, and land cover map. To generate a flood hazard index, each one of the factors was classified into five categories: very low, low, moderate, high, and very high; the factors were then combined and processed using the proposed methodology. Obtained overall maps have been adjusted with socioeconomic data such as gross domestic product to relate the flood exposure to economic and demographic factors in Mombasa County, Kenya. Results suggest that the County is largely dominated by areas with a high flood hazard index due to its location and shoreline. Fort Jesus, the UNESCO World Heritage site, is currently under high risk of flood as shown by the flood hazard index, while most of the shoreline is at very high risk of flooding.
      PubDate: 2018-03-05
      DOI: 10.1007/s11069-018-3244-9
  • Observation of surface and atmospheric parameters using “NOAA 18”
           satellite: a study on earthquakes of Sumatra and Nicobar Is regions for
           the year 2014 ( M  ≥ 6.0)
    • Authors: Venkatanathan Natarajan; Philip Philipoff
      Abstract: Analysing pre-earthquake signals using satellite technology are getting importance among the scientific community, since round-the-clock survey for the wider region is possible compared to ground-based monitoring techniques. Several scientists are involved in various satellites and ground-based technologies to decode the complex physical mechanism of the earthquake process since 1980. They involved in measuring anomalous variations using space-based methodologies like EM signals, SAR interferometry, GPS for ionospheric sounding, satellite gravimetry, atmospheric sounding, Outgoing Longwave Radiation (OLR), radon gas and seismo-tectonic clouds. In this paper, the authors have considered surface latent heat flux (SLHF) and OLR satellite data for detailed analysis of earthquakes took place during the year 2014 in Sumatra and Nicobar Is regions. At the surface and atmospheric interface, the anomalous variations in SLHF were observed prior to the occurrence of the earthquake. Similarly, anomalous variations in OLR have been observed 3–30 days prior to the big earthquakes and it is measured above the cloud level. From the analysis, the author has found that variations in the SLHF and OLR flux can be utilized as efficient tools to identify the impending big earthquakes. SLHF and OLR variation level can give us a clue about the probable magnitude of earthquakes and also about earthquake preparation zones. Hence, by correlating the above-mentioned parameters, it is potential to key out the impending earthquakes with reasonable accuracy.
      PubDate: 2018-03-03
      DOI: 10.1007/s11069-018-3242-y
  • Riverine flood assessment in Jhang district in connection with ENSO and
           summer monsoon rainfall over Upper Indus Basin for 2010
    • Authors: Bushra Khalid; Bueh Cholaw; Débora Souza Alvim; Shumaila Javeed; Junaid Aziz Khan; Muhammad Asif Javed; Azmat Hayat Khan
      Abstract: Pakistan has experienced severe floods over the past decades due to climate variability. Among all the floods, the flood of 2010 was the worst in history. This study focuses on the assessment of (1) riverine flooding in the district Jhang (where Jhelum and Chenab rivers join, and the district was severely flood affected) and (2) south Asiatic summer monsoon rainfall patterns and anomalies considering the case of 2010 flood in Pakistan. The land use/cover change has been analyzed by using Landsat TM 30 m resolution satellite imageries for supervised classification, and three instances have been compared, i.e., pre-flooding, flooding, and post-flooding. The water flow accumulation, drainage density and pattern, and river catchment areas have been calculated by using Shutter Radar Topography Mission digital elevation model 90 m resolution. The standard deviation of south Asiatic summer monsoon rainfall patterns, anomalies and normal (1979–2008) has been calculated for July, August, and September by using rainfall data set of Era interim (0.75° × 0.75° resolution). El Niño Southern Oscillation has also been considered for its role in prevailing rainfall anomalies during the year 2010 over Upper Indus Basin region. Results show the considerable changing of land cover during the three instances in the Jhang district and water content in the rivers. Abnormal rainfall patterns over Upper Indus Basin region prevailed during summer monsoon months in the year 2010 and 2011. The El Niño (2009–2010) and its rapid phase transition to La Niña (2011–2012) may be the cause of severity and disturbances in rainfall patterns during the year 2010. The Geographical Information System techniques and model based simulated climate data sets have been used in this study which can be helpful in developing a monitoring tool for flood management.
      PubDate: 2018-03-03
      DOI: 10.1007/s11069-018-3234-y
  • A model for assessing iceberg hazard
    • Authors: Grant R. Bigg; T. E. Cropper; Clare K. O’Neill; Alex K. Arnold; A. H. Fleming; R. Marsh; V. Ivchenko; Nicolas Fournier; Mike Osborne; Robin Stephens
      Abstract: With the polar regions opening up to more marine activities but iceberg numbers more likely to increase than decline as a result of global warming, the risk from icebergs to shipping and offshore facilities is increasing. The NW Atlantic iceberg hazard has been well monitored by the International Ice Patrol for a century, but many other polar regions have little detailed climatological knowledge of the iceberg risk. Here, we develop a modelling approach to assessing iceberg hazard. This uses the region of the Falklands Plateau and its shipping routes for a case study, but the approach has general geographical applicability and can be used for assessing iceberg hazard for routes or fixed locations. The iceberg risk for a number of locations selected from the main shipping routes in the SW Atlantic is assessed by using an iceberg model, forced by the output from a high-resolution ocean model. The iceberg model was seeded with icebergs around the edge of the modelled region using a number of scenarios for the seeding distribution, based on a combination of idealised, modelled and observed iceberg fluxes from the Southern Ocean. This enabled us to determine measures of iceberg risk linked to a mix of starting location and the likelihood of icebergs being encountered in such a position. For our study area, the main area of iceberg risk is linked to the East Falklands Current, but small, yet nonzero, risk covers much of the east and north of the region.
      PubDate: 2018-03-02
      DOI: 10.1007/s11069-018-3243-x
  • Reconstruction and post-event analysis of a flash flood in a small
           ungauged basin: a case study in Slovak territory
    • Authors: Veronika Bačová Mitková; Pavla Pekárová; Dana Halmová; Pavol Miklánek
      Abstract: Flash floods are one of the major natural hazards occurring in small streams with a negative effect on the country as well as on human lives. Heavy rainfall occurred on July 20, 2014 and July 21, 2014 and caused severe surface water flooding and a flash flood in the Malá Fatra National Park (Slovakia). The most affected was Vrátna Valley with the Varínka stream. This study presents a reconstruction and post-event analysis of a flash flood on small ungauged basin located in this protected area of Slovakia. The reconstruction included hydraulic terrain measurements on estimating the flood’s culmination and documenting the flood’s development. The measurements were taken at three cross sections of the Varínka stream. This paper is focused mainly on post-event analysis of the Varínka stream in two profiles: Stráža (gauged profile) and Tiesňavy (ungauged cross section). Subsequently, the extremeness of the flash flood was preliminary evaluated. Results of the post-event analysis showed that the July 2014 flood was not the highest flood in this area despite its catastrophic consequences. By studying historical materials, we came to the conclusion that in the past (e.g. in 1848 or 1939) some devastating floods in this area had occurred, which had disastrous consequences for the population. The second part of the study is focused on comparing this flash flood with three major floods which have occurred in Slovak territory since 1998. The first flood occurred on the 20th of July, 1998 on the Malá Svinka stream, and the two others are floods which occurred on the 7th of June, 2011 in the Small Carpathian Mountains: on the Gidra stream in Píla village and on the Parná stream in Horné Orešany village. Such comparison of flash floods from different geographical regions and different rainfall events can provide comprehensive information about their regimes, threats and disastrous effects.
      PubDate: 2018-03-02
      DOI: 10.1007/s11069-018-3222-2
School of Mathematical and Computer Sciences
Heriot-Watt University
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