Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area,Iran   总被引：7，自引：4，他引：3  

Aminreza Neshat  Biswajeet Pradhan  Saied Pirasteh  Helmi Zulhaidi Mohd Shafri 《Environmental Earth Sciences》2014,71(7):3119-3131

Groundwater contamination from intensive fertilizer application affects conservation areas in a plain. The DRASTIC model can be applied in the evaluation of groundwater vulnerability to such pollution. The main purpose of using the DRASTIC model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, thereby disregarding the effects of pollution types and their characteristics. Thus, this technique must be standardized and be approved for applications in aquifers and particular types of pollution. In this study, the potential for the more accurate assessment of vulnerability to pollution is achieved by correcting the rates of the DRASTIC parameters. The new rates were calculated by identifying the relationships among the parameters with respect to the nitrate concentration in groundwater. The methodology was implemented in the Kerman plain in the southeastern region of Iran. The nitrate concentration in water from underground wells was tested and analyzed in 27 different locations. The measured nitrate concentrations were used to associate and correlate the pollution in the aquifer to the DRASTIC index. The Wilcoxon rank-sum nonparametric statistical test was applied to determine the relationship between the index and the measured pollution in Kerman plain. Also, the weights of the DRASTIC parameters were modified through the sensitivity analysis. Subsequently, the rates and weights were computed. The results of the study revealed that the modified DRASTIC model performs more efficiently than the traditional method for nonpoint source pollution, particularly in agricultural areas. The regression coefficients showed that the relationship between the vulnerability index and the nitrate concentration was 82 % after modification and 44 % before modification. This comparison indicated that the results of the modified DRASTIC of this region are better than those of the original method.  相似文献   

Conjunctive use of surface water and groundwater via the bank infiltration method     

Mohd Khairul Nizar Shamsuddin  Wan Nor Azmin Sulaiman  Saim Suratman  Mohamad Pauzi Zakaria  Kamarudin Samuding 《Arabian Journal of Geosciences》2014,7(9):3731-3753

The bank infiltration (BI) technique may be a viable option if the local climate, hydrological, and geological conditions are conducive. This study was specifically conducted to explore the possibility of using BI to source the polluted surface water in conjunction with groundwater. Three major factors were considered for evaluation: (1) investigation on the contribution of surface water through BI, (2) input of local groundwater, and (3) water quality characteristics of water supply. Initially, the geophysical method was employed to define the subsurface geology and hydrogeology, and isotope techniques were performed to identify the source of groundwater recharge and interaction between surface water and groundwater. The physicochemical and microbiological parameters of the local surface water bodies and groundwater were analyzed before and during water abstraction. Extracted water revealed a 5 %–98 % decrease in turbidity, as well as HCO₃ ⁺, SO₄ ^?, NO₃ ^?, Al, As, and Ca concentration reduction compared with those of Langat river water. However, water samples from test wells during pumping show high concentrations of Fe²⁺ and Mn²⁺. In addition, amounts of Escherichia coli, total coliform, and Giardia were significantly reduced (99.9 %). Pumping test results indicate that the two wells (DW1 and DW2) were able to sustain yields.  相似文献   

Modeling storm surges associated with super typhoon durian in South China Sea   总被引：1，自引：0，他引：1  

Kak Choon Loy  Prakash Chandra Sinha  Juneng Liew  Fredolin Tangang  Mohd Lokman Husain 《Natural Hazards》2014,70(1):23-37

Super typhoon Durian struck the central Philippines on November 30, 2006 and southern coast of Vietnam on December 5, 2006. The reported maximum wind exceeded 250 km/h, and the central pressure was 904 hPa during the peak of the system. The typhoon brought colossal damage, both in terms of lives and in terms of properties to the Philippines and Vietnam while Thailand and Malaysia were slightly affected. The energy from the high-velocity wind and central pressure drop resulted in the generation of storm surges along the coastal region of the Philippines including its surrounding islands as well as parts of southern Vietnam. In this paper, a numerical 2D model is used to study the oceanic response to the atmospheric forcing by 2006 super typhoon Durian in the coastal regions of the Philippines and Vietnam. The initial study of this model aims to provide some useful insights before it could be used as a coastal disaster prediction system in the region of South China Sea (SCS). The atmospheric forcing for the 2D model, which includes the pressure gradient and the wind field, is generated by an empirical asymmetrical storm model. The simulated results of storm surges due to typhoon Durian at two locations lie in the range of observed data/estimates published by the Joint Typhoon Warning Centre (JTWC).  相似文献   

Markov CA,Multi Regression,and Multiple Decision Making for Modeling Historical Changes in Kirkuk City,Iraq     

Najat Qader Omar  Mohd Sanusi S. Ahamad  Wan Muhd Aminuddin Wan Hussin  Narimah Samat  Siti Zubaidah Binti Ahmad 《Journal of the Indian Society of Remote Sensing》2014,42(1):165-178

The cellular automata (CA) model is an important tool in land use change studies. Swift increases in population and long-term expectations of rapid urbanization have led to extensive land use change, and normal living conditions have affected the natural resources of the land. This paper highlights and analyzes the historical urban changes in Kirkuk City, Iraq, considering repeated changes undergone by the state such change as government infrastructures, wars, and economic blockade. In this paper, an integrated model, built-in multi regression model, and multi-criteria evaluation were considered to improve the representation of CA transition rules. Environmental and socioeconomic factors were used to produce Suitable Maps (SMs). These SMs were practicalities to create factor layers and weight usage, rating method process for variance expert decision-making groups, and geographic information systems for the periods 1984, 1990, 2000, and 2010. The roots of the equation (R²) values are compared and these values are chosen to produce a good model of suitable maps. The approach used in this study provides a mechanism for monitoring suitability maps in Kirkuk. Furthermore, the model Markov CA is implemented and evaluated. The results indicate that the model, its related concepts performs sufficiency  相似文献   

Latent-space inversion (LSI): a deep learning framework for inverse mapping of subsurface flow data     

Razak  Syamil Mohd  Jiang  Anyue  Jafarpour  Behnam 《Computational Geosciences》2022,26(1):71-99

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Nature,origin and evolution of a Late Pleistocene incised valley‐fill,Sunda Shelf,Southeast Asia          下载免费PDF全文

Faisal A. Alqahtani  Howard D. Johnson  Christopher A.‐L. Jackson  Mohd Rapi B. Som 《Sedimentology》2015,62(4):1198-1232

Understanding the stratigraphic fill and reconstructing the palaeo‐hydrology of incised valleys can help to constrain those factors that controlled their origin, evolution and regional significance. This condition is addressed through the analysis of a large (up to 18 km wide by 80 m deep) and exceptionally well‐imaged Late Pleistocene incised valley from the Sunda Shelf (South China Sea) based on shallow three‐dimensional seismic data from a large (11 500 km²), ‘merge’ survey, supplemented with site survey data (boreholes and seismic). This approach has enabled the characterization of the planform geometry, cross‐sectional area and internal stratigraphic architecture, which together allow reconstruction of the palaeo‐hydrology. The valley‐fill displays five notable stratigraphic features: (i) it is considerably larger than other seismically resolvable channel forms and can be traced for at least 180 km along its length; (ii) it is located in the axial part of the Malay Basin; (iii) the youngest part of the valley‐fill is dominated by a large (600 m wide and 23 m deep), high‐sinuosity channel, with well‐developed lateral accretion surfaces; (iv) the immediately adjacent interfluves contain much smaller, dendritic channel systems, which resemble tributaries that drained into the larger incised valley system; and (v) a ca 16 m thick, shell‐bearing, Holocene clay caps the valley‐fill. The dimension, basin location and palaeo‐hydrology of this incised valley leads to the conclusion that it represents the trunk river, which flowed along the length of the Malay Basin; it connected the Gulf of Thailand in the north with the South China Sea in the south‐east. The length of the river system (>1200 km long) enables examination of the upstream to downstream controls on the evolution of the incised valley, including sea‐level, climate and tectonics. The valley size, orientation and palaeo‐hydrology suggest close interaction between the regional tectonic framework, low‐angle shelf physiography and a humid‐tropical climatic setting.  相似文献   

Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia     

Sayang Mohd Deni  Abdul Aziz Jemain  Kamarulzaman Ibrahim 《Theoretical and Applied Climatology》2009,97(1-2):109-121

The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.  相似文献   

The spatial distribution of wet and dry spells over Peninsular Malaysia     

S. Mohd. Deni  A. A. Jemain  K. Ibrahim 《Theoretical and Applied Climatology》2008,94(3-4):163-173

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How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?     

Mohd Rizaludin Mahmud  Mazlan Hashim  Mohd Nadzri Mohd Reba 《Asia-Pacific Journal of Atmospheric Sciences》2017,53(3):375-384

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman’s correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d^-1). A strong relationship between GPM rainfall and error was found from heavy (~35 mm d^-1) to violent rain (160 mm d^-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.  相似文献   

Artificial neural network simulation for prediction of suspended sediment concentration in the River Ramganga,Ganges Basin,India     

Mohd Yawar Ali Khan  Fuqiang Tian  Faisal Hasan  Govind Joseph Chakrapani 《国际泥沙研究》2019,34(2):95-107

The relation between the water discharge (Q) and suspended sediment concentration (SSC) of the River Ramganga at Bareilly, Uttar Pradesh, in the Himalayas, has been modeled using Artificial Neural Networks (ANNs). The current study validates the practical capability and usefulness of this tool for simulating complex nonlinear, real world, river system processes in the Himalayan scenario. The modeling approach is based on the time series data collected from January to December (2008-2010) for Q and SSC. Three ANNs (T1-T3) with different network configurations have been developed and trained using the Levenberg Marquardt Back Propagation Algorithm in the Matlab routines. Networks were optimized using the enumeration technique, and, finally, the best network is used to predict the SSC values for the year 2011. The values thus obtained through the ANN model are compared with the observed values of SSC. The coefficient of determination (R2), for the optimal network was found to be 0.99. The study not only provides insight into ANN modeling in the Himalayan river scenario, but it also focuses on the importance of understanding a river basin and the factors that affect the SSC, before attempting to model it. Despite the temporal variations in the study area, it is possible to model and successfully predict the SSC values with very simplistic ANN models.  相似文献