排序方式： 共有21条查询结果，搜索用时 15 毫秒
11.
Narges Palizdan Yashar Falamarzi Yuk Feng Huang Teang Shui Lee Abdul Halim Ghazali 《Theoretical and Applied Climatology》2014,117(3-4):589-606
Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982–2011 were examined at the 95 % level of significance using the regional average Mann–Kendall (RAMK) test and the regional average Mann–Kendall coupled with bootstrap (RAMK–bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km?×?5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations. 相似文献
12.
This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level fluctuation during the 1971–2013 period. Two new methods including nonparametric hybrid wavelet Mann–Kendall test and ?en’s methodology have been used to determine potential trends in the variables and their dominant periods. The results showed significant decreasing trends in the water level and streamflow series, moderate decreasing trend in the rainfall and relative humidity series, and increasing trends in the observed temperature data. The 8- , 12-month, and 2-year periods were detected as the dominant periods of the variables in monthly, seasonal, and annual timescales, respectively. The results from the interaction analysis revealed that the main factor influencing the water level at UL is decreasing trend in the streamflow series. Both the monthly series of UL’s water level and the streamflow series of the stations indicated two start points of significant decreasing trend in 1973 and 1998. Furthermore, a comparative analysis among the applied methods indicated a good agreement between the results of hybrid wavelet Mann–Kendall test and ?en’s trend analyzing method. 相似文献
13.
Phuong Thao Thi Ngo Mahdi Panahi Khabat Khosravi Omid Ghorbanzadeh Narges Kariminejad Artemi Cerda Saro Lee 《地学前缘(英文版)》2021,12(2):505-519
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies. 相似文献
14.
Narges?PalizdanEmail author Yashar?Falamarzi Yuk?Feng?Huang Teang?Shui?Lee 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(4):853-877
The main purpose of this study was to determine the most dominant periodic components that affect the annual and seasonal precipitation trends in each homogenous rainfall region in the Langat River Basin, Malaysia for the period 1982–2011. Performing this research could be essential because in the previous studies on detection of trend in Malaysia, the details of variations of different time scales and the periodic responsible for the observed trends were not investigated. Using discrete wavelet transform (DWT) coupled with Mann–Kendall at the regional scale for the first time particularly in the context of Malaysia is the contribution of this study. In order to form the homogenous rainfall regions, first the total annual and seasonal precipitation in each year was spatialized into 5 km × 5 km grids using the inverse distance weighting method. The obtained precipitation series for the grids were then grouped applying the Ward’s clustering method based on the similarity of precipitation time series. After allocating a cluster number to each grid, the boundary of the regions was formed in ArcGIS software. Following which, in each homogenous region the areal precipitation series were computed by the Thiessen polygon method. The Mann–Kendall (MK) test was used to detect trend and the DWT coupled with the MK test and the sequential MK analysis were then utilized in order to find out the time scale which affected the observed trend in each homogenous region. On annual scale, it was found that D1 (plus approximation) component in regions Annual Cluster1 (AC1) and AC2 was the periodic mode responsible for trends. On seasonal scale, in regions Northeast monsoon Cluster 1 (NC1), NC3, SC1 and Southwest monsoon Cluster 2 (SC2), D1 (with approximation), in regions NC4, Inter monsoon 1 Cluster 1 (I1C1), I1C2, Inter monsoon 2 Cluster 1 I2C1 and I2C2, Detail 2 (D2) (plus approximation) and in region NC2, Detail 3 (D3) (with approximation added) component were the most influential periodicity for trends. 相似文献
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16.
Fataneh Taghizadeh-Farahmand Forough Sodoudi Narges Afsari Najmieh Mohammadi 《Journal of Seismology》2013,17(4):1207-1221
The Kopeh-Dagh fold belts are among the most seismically active areas in Northeastern Iran, which build the northern part of the Alpine–Himalayan orogen in western Asia. They act as the abrupt northeastern limit to active deformation in Iran. We perform a combined P and S receiver function analysis to detect the major discontinuities within the lithosphere beneath Northeast Iran. Our results obtained from 12 short period and broadband seismological stations significantly map the lateral variations of the Moho boundary. Based on P receiver functions, we show that the Moho depth varies from ～43 km beneath the southern Kopeh-Dagh foreland basin to ～49 km below the northern part of the basin. S receiver functions reliably reveal an average Moho depth of ～50–55 km beneath the Kopeh-Dagh mountain range showing the regional shortening in response to the collision of Arabia with Eurasia. Furthermore, we observe clear conversions with negative polarity at ～8.5–9.5 s in S receiver functions, which could be related to the conversion at the lithosphere–asthenosphere boundary. This may show a relatively thin continental lithosphere of about 85–95 km beneath the Kopeh-Dagh implying that the lithosphere was influenced by geodynamical reworking processes in the past. 相似文献
17.
We consider the cosmological dynamics of a tachyon field localized on the extended DGP braneworld scenario. We present a detailed analysis of the critical points in the phase space of the model, their stability and late-time cosmological viability of the solutions. We study the luminosity distance behavior of this ?EDGP model and compare it with ΛCDM model. Also we show that the EDGP solutions in the presence of tachyon field can explain late time acceleration of the universe. 相似文献
18.
Narges Fathalian Seyedeh Somayeh Hosseini Rad Nasibeh Alipour Hossein Safari 《天文和天体物理学研究(英文版)》2022,(3):143-156
Here,we study the temperature structure of flaring and non-flaring coronal loops,using extracted loops from images taken in six extreme ultraviolet channels rec... 相似文献
19.
We reconsider the issue of cosmological dynamics in a DGP setup with a bulk scalar field. The ghost-free, normal branch of
this DGP-inspired braneworld scenario has the potential to realize a self-consistent phantom-like behavior. The roles played
by the bulk canonical scalar field on this phantom-like dynamics are explored. Within a dynamical system approach, the effective
phantom nature of the scenario is investigated with details. This analysis shows that there is a stable, late-time de Sitter
phase. 相似文献
20.
Taravatrooy Narges Nikoo Mohammad Reza Sadegh Mojtaba Parvinnia Mohammad 《Natural Hazards》2018,93(2):905-920
In many parts of Canada, limited data are available for hydrodynamic model inputs, and the ability to generate quality flood grids through 1D, 2D or 3D methods is nonviable. In this paper, the capability of simplified flood models, which rely solely on digital terrain models (DTMs), was explored to assess the quality and speed of their results. Results were validated against historic floods in two locations. Three non-physics-based simplified conceptual flood models were tested: (1) planar method, (2) inclined plane and (3) height above nearest drainage network (HAND) model. The accuracy and performance were evaluated using three criteria: inundation extent, water depth and computation time. Findings show that the HAND model is the best predictor of inundation extent, with Probability of Detection and Critical Success Index being higher than 0.90 in both study areas. Though the preprocessing time for the HAND model is lengthy, once completed, the time to simulate flooding at a variety of water levels is rapid, making this model the most suitable choice for web-based, on-demand flood inundation mapping. Knowledge of the fit of these flood models and associated uncertainty can be helpful to emergency managers such that they can better understand exposure and vulnerability while preparing flood response plans. 相似文献