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41.
Noor Azlinda Ahmad M. Fernando Z.A. Baharudin M. Rahman V. Cooray Ziad Saleh Joseph R. Dwyer Hamid K. Rassoul 《Journal of Atmospheric and Solar》2010,72(2-3):143-150
In this study, the first electric field pulse of cloud and cloud-to-ground discharges were analyzed and compared with other pulses of cloud discharges. Thirty eight cloud discharges and 101 cloud-to-ground discharges have been studied in this analysis. Pulses in cloud discharges were classified as ‘small’, ‘medium’ and ‘large’, depending upon the value of their relative amplitude with respect to that of the average amplitude of the five largest pulses in the flash. We found that parameters, such as pulse duration, rise time, zero crossing time and full-width at half-maximum (FWHMs) of the first pulse of cloud and cloud-to-ground discharges are similar to small pulses that appear in the later stage of cloud discharges. Hence, we suggest that the mechanism of the first pulse of cloud and cloud-to-ground discharges and the mechanism of pulses at the later stage of cloud discharges could be the same. 相似文献
42.
Javed Mallick Ram Karan Singh Mohammed A. AlAwadh Saiful Islam Roohul Abad Khan Mohamed Noor Qureshi 《Environmental Earth Sciences》2018,77(7):276
Landslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts. 相似文献
43.
The study aims to investigate the possible relationship between Niño 4 and Indian Ocean high longitude (IOHLN) with the Swan coastal river flow by constructing a regression model which predict streamflow patterns and which enables to obtain long time lead to forecasting, in a period when there was not much rainfall. Many streamflow forecast models use rainfall and runoff relationship, which is dependent on basin response time and hence cannot provide large forecasting lead time. For water resource management, this lead time of predictability is not capable for a long period of drying trend. Significant findings of this study suggest that Niño 4 and Indian Ocean high pressure longitude (IOHLN) can be used for forecasting of flow in Swan river. In this study not only qualitative forecast of Swan coastal river is presented based on the conditional probability, but also a quantitative forecast is done by combining Niño.4 and IOHLN indices using multiple regression, which shows enhancement over other climate indicators when used alone. The Conditional probability model correctly predict 7 years category of flow out of 8 years flow. 相似文献
44.
Alhani Israa Jamal Noor Mohd Jamaludin bin Md Al-Bared Mohammed Ali Mohammed Harahap Indra Sati Hamonangan Albadri Wael Mahmood 《Acta Geotechnica》2020,15(11):3075-3093
Acta Geotechnica - During the construction of pavements, gravelly soil is used as the main material in the base and sub-base layers. Predicting the deformation behaviour of gravelly soil has been... 相似文献