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Mokhtar Ernieza Suhana Pradhan Biswajeet Ghazali Abd Halim Shafri Helmi Zulhaidi Mohd 《Natural Hazards》2017,87(2):1125-1146
Natural Hazards - Discharge is traditionally measured at gauge stations located at discrete positions along the river course. When the volume of water discharge is higher than the river bank,... 相似文献
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Lawal Billa Hamid Assilzadeh Shattri Mansor Ahmed R. Mahmud Abdul H. Ghazali 《Central European Journal of Geosciences》2011,3(3):309-317
Observed rainfall is used for runoff modeling in flood forecasting where possible, however in cases where the response time of the watershed is too short for flood warning activities, a deterministic quantitative precipitation forecast (QPF) can be used. This is based on a limited-area meteorological model and can provide a forecasting horizon in the order of six hours or less. This study applies the results of a previously developed QPF based on a 1D cloud model using hourly NOAA-AVHRR (Advanced Very High Resolution Radiometer) and GMS (Geostationary Meteorological Satellite) datasets. Rainfall intensity values in the range of 3–12 mm/hr were extracted from these datasets based on the relation between cloud top temperature (CTT), cloud reflectance (CTR) and cloud height (CTH) using defined thresholds. The QPF, prepared for the rainstorm event of 27 September to 8 October 2000 was tested for rainfall runoff on the Langat River Basin, Malaysia, using a suitable NAM rainfall-runoff model. The response of the basin both to the rainfall-runoff simulation using the QPF estimate and the recorded observed rainfall is compared here, based on their corresponding discharge hydrographs. The comparison of the QPF and recorded rainfall showed R2 = 0.9028 for the entire basin. The runoff hydrograph for the recorded rainfall in the Kajang sub-catchment showed R2 = 0.9263 between the observed and the simulated, while that of the QPF rainfall was R2 = 0.819. This similarity in runoff suggests there is a high level of accuracy shown in the improved QPF, and that significant improvement of flood forecasting can be achieved through ‘Nowcasting’, thus increasing the response time for flood early warnings. 相似文献
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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
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Ernieza Suhana Mokhtar Biswajeet Pradhan Abd Halim Ghazali Helmi Zulhaidi Mohd Shafri 《Arabian Journal of Geosciences》2018,11(21):682
Water discharge is the main parameter in hydraulic modeling for flood hazard assessment. However, the unavailability of data on discharge and observed river morphologies resulted in erroneous calculations and irregularities in flood inundation mapping. The objectives of this study are (i) to investigate uncertainties of hydraulic parameters (width, cross-sectional depth, and channel slope) used in discharge equation and (ii) to examine the influence of estimate discharge on water extent and flood depth with different boundary conditions on interferometric synthetic aperture radar (IFSAR) and modified IFSAR DEMs. Sensitivity analysis was conducted with the Monte Carlo simulation method to generate random data combinations. Bjerklie’s equation was used to calculate discharge based on the three variables, and Manning’s n was substituted into the Hydrologic Engineering Center River Analysis System (HEC-RAS) model. TerraSAR-X was used to distinguish existing flood water bodies and normal water extent. The uncertainty of the combined variables was assessed with the likelihood measures such as F-statistic, mean absolute error, root mean square error, and Nash–Sutcliffe efficiency which compares observed and predicted inundated area as well as flood water depth simulated using the HEC-RAS model. 相似文献
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ABSTRACTA model fusion approach was developed based on five artificial neural networks (ANNs) and MODIS products. Static and dynamic ANNs – the multi-layer perceptron (MLP) with one and two hidden layers, general regression neural network (GRNN), radial basis function (RBF) and nonlinear autoregressive network with exogenous inputs (NARX) – were used to predict the monthly reservoir inflow in Mollasadra Dam, Fars Province, Iran. Leaf area index and snow cover from MODIS, and rainfall and runoff data were used to identify eight different combinations to train the models. Statistical error indices and the Borda count method were used to verify and rank the identified combinations. The best results for individual ANNs were combined with MODIS products in a fusion model. The results show that using MODIS products increased the accuracy of predictions, with the MLP with two hidden layers giving the best performance. Also, the fusion model was found to be superior to the best individual ANNs. 相似文献
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Suriati Ghazali 《Area》2003,35(2):183-194
The importance of social capital in both rural and urban communities is an often-published topic. By representing the operation of social capital networks, this paper explores the persistence of informal rotating credit in the livelihoods of low-income, urban households in Penang, Malaysia. It highlights the function of such credit and the ways in which it benefits poor women and their households. This paper suggests that informal credit reduces the probability of being poor, and the returns to household investment in social capital are higher for the poor than for the population at large. The downside of such social capital is also discussed. The paper concludes that informal credit is enhanced in the urban settings due to the increase in income opportunities, especially for women. 相似文献
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Sammen Saad Sh. Mohamed T. A. Ghazali A. H. Sidek L. M. El-Shafie A. 《Natural Hazards》2017,87(1):545-566
The study of dam-break analysis is considered important to predict the peak discharge during dam failure. This is essential to assess economic, social and environmental impacts downstream and to prepare the emergency response plan. Dam breach parameters such as breach width, breach height and breach formation time are the key variables to estimate the peak discharge during dam break. This study presents the evaluation of existing methods for estimation of dam breach parameters. Since all of these methods adopt regression analysis, uncertainty analysis of these methods becomes necessary to assess their performance. Uncertainty was performed using the data of more than 140 case studies of past recorded failures of dams, collected from different sources in the literature. The accuracy of the existing methods was tested, and the values of mean absolute relative error were found to be ranging from 0.39 to 1.05 for dam breach width estimation and from 0.6 to 0.8 for dam failure time estimation. In this study, artificial neural network (ANN) was recommended as an alternate method for estimation of dam breach parameters. The ANN method is proposed due to its accurate prediction when it was applied to similar other cases in water resources.
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Since 2003, the permanent failure of the scan line corrector (SLC) of the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor has seriously limited the scientific applications and usability of ETM+ data. While a number of methods have been conducted to fill the regular un-scanned locations in ETM+ SLC-off images, only a few researches have been developed to recover the large gap areas in such images. In this study, an innovative gap filling method has been introduced to reconstruct the large gap locations in SLC-off images via multi-temporal auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two auxiliary fill images in parallel using the multiple linear regression (MLR) model in two successive steps. In the first step, almost half the gap locations have been recovered using the MLR model, then in the second step a weighted multiple linear regression (WMLR) algorithm is proposed to recover the remaining missing values. The simulated and actual case studies show that the proposed approach may provide a powerful tool for recovering the large gaps in SLC-off images, especially when there is a long time interval between the auxiliary fill images and the target SLC-off image. 相似文献
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S. M. Hamza Amimul Ahsan M. A. Imteaz T. A. Mohammad A. H. Ghazali A. R. M. Shariff 《Arabian Journal of Geosciences》2017,10(7):168
Safeguarding groundwater from pollution is largely a global political decision. These decisions are basically supported by DRASTIC (D=Depth to water, R=Recharge, A=Aquifer media, S=Soil media, T=Topography, I=Impact of vadose zone, C=Hydraulic conductivity) analysis. Furthermore, water quality index (WQI) is an effective tool for groundwater quality evaluation and management. This study identifies the relationship between these two indices [i.e., pollution vulnerability index (PVI) and WQI]. The DRASTIC index of the study area was found to be from 60.4 to 178 characterized by very low, low, medium high, and very high vulnerability constituting of 12.88, 24.38, 34.11, 21.99, and 6.63% of the study area, respectively. In addition, the WQI of the area according to the analyzed parameters is between 10.19 and 55.63. It was established that a good correlation (61%) was found to exist between the two indices; which may be an indication that most pollutants present in the groundwater are likely due to anthropogenic activities on the land surface. 相似文献