Cyclones and storm surges in Bangladesh: Some mitigative measures

Bangladesh, with its repeated cycle of floods, cyclones, and storm surges, has proved to be one of the most disaster-prone areas of the world. During the years from 1797 to 1991, Bangladesh has been hit by 60 severe cyclones (mostly accompanied by storm surges). This paper gives a brief account of these disasters with particular reference to the wind speed, surge height, loss of life, and damage to crops and properties, etc.In order to protect the coastal areas of Bangladesh from cyclonic storm surges and floods, a major system of embankments was constructed during the 1960s and 1970s, but this is now in need of rehabilitation. The Cyclone Protection Project, which was approved by the World Bank in 1989, would rehabilitate some of the existing embankments, build new embankments, and construct roads. Locally available materials, indigenous technology, and cheap surplus manpower should be used in this project. A variety of fruit trees should be planted along the dikes and roads.To the south-western part of Bangladesh bordering the Bay of Bengal, lies the world's largest single mangrove tract, known as the Sunderban, which covers a total area of 571 500 ha. This mangrove forest is of extreme importance since it provides efficient protection to life and property against cyclones and storm surges. But due to deforestation, the width of the mangrove belt is being rapidly diminished. The author therefore lays emphasis on coastal afforestation.Absolute security against cyclone hazard is probably out of the question, but an effective cyclone warning response can definitely reduce loss of life and damage to property. The author discusses the current conditions for cyclone forecasting and warning in Bangladesh, and then puts forward some proposals for improving the Cyclone Preparedness Programme.     

Drought adaptation measures and their effectiveness at Barind Tract in northwest Bangladesh: a perception study

Natural Hazards - Drought is a natural calamity frequently occurs at Barind Tract in northwest Bangladesh and affects both the human and natural life. An initiative has been taken...     

Geochemistry of subsurface Late Quaternary ironstones in Rajshahi and Bogra Districts,Bangladesh: implications for genetic and depositional conditions

The present study deals with the geochemistry of Late Quaternary ironstones in the subsurface in Rajshahi and Bogra districts, Bangladesh with the lithological study of the boreholes sediments. Major lithofacies of the studied boreholes are clay, silty clay, sandy clay, fine to coarse grained sand, gravels and sands with (fragmentary) ironstones. The ironstones contain major oxides, Fe₂O₃* (* total Fe) (avg. 66.6 wt%), SiO₂ (avg. 15.3 wt%), Al₂O₃ (avg. 4.0 wt%), MnO (avg. 7.7 wt%), and CaO (avg. 3.4 wt%). These geochemical data imply that the higher percentage of Fe₂O₃* along with Al₂O₃ and MnO indicate the ironstone as goethite and siderite, which is also validated by XRD data. A comparatively higher percentage of SiO₂ indicates the presence of relative amounts of clastic quartz and manganese-rich silicate or clay in these rocks. These ironstones also have significant amounts of MnO (avg. 7.7 wt%) suggesting their depositional environments under oxygenated condition. Chemical data of these ironstones suggest that the source rock suffered deep chemical weathering and iron was mostly carried in association with the clay fraction and organic matter. Iron concretion was mostly formed by bacterial build up in swamps and marshes, and was subsequently embedded in clayey mud. Within the coastal environments, the water table fluctuates and goethite and siderite with mud and quartz became dry and compacted to form ironstone.

     

Recent Sea Level and Sea Surface Temperature Trends Along the Bangladesh Coast in Relation to the Frequency of Intense Cyclones

Bangladesh, one of the most densely populated countries in the world, is a victim of frequent natural calamities like tropical cyclones, tornadoes, floods, storm surges and droughts. Now the sea level rise (SLR) has also been included in these natural calamities. The SLR is likely to have greater impact on that part of Bangladesh having low topography and a wide flood plain. Since 21% of the population lives in the low coastal belt, any increase in sea level will be a problem of ominous proportion for Bangladesh. Since the cyclogenesis enhances over the Bay of Bengal during May and November, the sea level and sea surface temperature (SST) trends of these two months have been analyzed and calculated. The results of the selected stations one in the eastern coast and another in the western coast of Bangladesh show that Bangladesh coastal sea level is rising in the same way as the global sea level, but the magnitude is quite different. The difference in the behavior of sea level rise along the Bangladesh coast and the global trend may be due to the tectonic activity such as subsidence of the land. The mean tide level at Hiron Point (in Sunderbans) has shown an increasing trend of about 2.5 mm/year in May and 8.5 mm/year in November. Similarly near Cox?s Bazar (in the eastern coast of Bangladesh) it has registered a positive trend of about 4.3 mm/year in May and 10.9 mm/year in November. Thus the increment in the sea level along the Bangladesh coast during cyclone months is much more pronounced. In coastal waters near Hiron Point the SST has registered an increasing trend of about 1°C in May and 0.5°C in November during the 14-year period from 1985?1998. Near Cox?s Bazar, SST has shown a rising trend of about 0.8°C in May and about 0.4°C in November during the same 14-year period. The magnitude of SST trend is slightly more along the west coast. Any change in the frequency and intensity of tropical cyclones will have far reaching implications in the South Asian region. The rise in SST in the cyclone months seems to be correlated with the frequency and intensity of tropical cyclones. During these months, an increasing trend in the frequency and intensity of severe cyclones has been observed.     

Flow and erosion at a bend in the braided Jamuna River

The braided Jamuna River frequently changes its courses.Sometimes the secondary channel in a braided river acts as a single thread meandering channel.In the present study an attempt has been made to investigate the flow patterns and to estimate the rate of bank erosion in a bend along the Jamuna River.The three dimensional(3D) flow velocities were measured using Acoustic Doppler Current Profiler(ADCP).It is found that the near bank velocity is amplified by 1.1 to 1.3 times as compared with the section averaged velocity.A dominant secondary current is found in the upstream bend.The evolution as well as decay of the secondary current is not as clear as it is found in the laboratory experiments.It is revealed from the analysis of the flow process that the causes of higher rate of erosion at the study bend are the oblique flow near bankline,six times amplified shear velocity than critical shear velocity near bankline and the secondary current which acts as a sediment transporting agent from the outer bank towards the inner bank or the sand bar.Based on the flow processes,a simplified erosion prediction model is developed and applied to estimate the rate of erosion at a selected bend.Finally the predicted results have been compared with the observed data at the bend and all the available data at other bends along the Jamuna River.     

Predictor selection for streamflows using a graphical modeling approach

Streamflows are influenced by various hydroclimatic variables in complex ways. Accurate prediction of monthly streamflows requires a clear understanding of the dependence patterns among these influencing variables and streamflows. A graphical modeling technique, employing conditional independence, is adopted in this study to quantify the interrelationships between streamflows and a suite of available hydroclimatic variables, and to identify a reduced set of relevant variables for parsimonious model development. The nodes in the undirected graph represent relevant variables, and the strengths of the connections among the variables are learnt from the data. The graphical modeling approach is compared to the state-of-the-art method for predictor selection based on partial mutual information. For a synthetic benchmark dataset and a watershed in southern Indiana, USA, the graphical modeling approach shows more discriminating results while being computationally efficient. Along with artificial neural networks and time series models, results of the graphical model are used for formulating a variational relevance vector machine to predict monthly streamflows and perform probabilistic classification of hydrologic droughts in the watershed being studied. The parsimonious models developed for prediction at different lead times performed as well as the non-parsimonious models during both the calibration and testing periods. Drought forecasting for the study watershed at 1-month lead time was performed using the two selected predictors—soil moisture and precipitation anomalies alone, and the model performance was evaluated. The graphical model shows promise as a tool for predictor selection, and for aiding parsimonious model development applications in statistical hydrology.     

重庆老龙洞地下河不同部位水体、表层沉积物有机氯农药含量及组成研究

为研究重庆老龙洞地下河不同部位水体、表层沉积物有机氯农药分布特征,用气相色谱-微池电子捕获检测器(GC-μECD)分析了样品中OCPs含量。结果表明:研究区水样、表层沉积物中OCPs检出率均为100 %,其浓度在时间上存在季节差异,水体中OCPs、DDTs、HCHs含量丰水期小于枯水期,而在表层沉积物中则表现为OCPs、HCHs丰水期大于枯水期,DDTs丰水期小于枯水期;在空间上则表现为水体中有机氯农药总体下游大于上游,而沉积物中则与之相反。通过对比可知,岩溶洞穴环境由于缺乏光照,空气流动缓慢,生物活动不频繁,使水体中的HCHs不易降解,沉积物中的HCHs不易重新释放而浓度高于洞外。枯水期由于洞内流速较小且变幅不大,水体中的DDTs大量沉积因而其浓度低于洞口,而丰水期洞口因受大量雨水的稀释作用DDTs反而低于洞内的含量;洞内沉积物中的DDTs则因洞内环境恒定不易重新释放和枯水期水体中的大量沉积而一直高于洞外。洞穴环境、不同污水汇入对水体中DDTs和表层沉积物中DDTs、HCHs的组成结构均有不同程度的影响,而对水体中HCHs的组成结构影响不大。此外,地下河不同部位污染源的输入对有机氯污染物的组成结构也有影响。与国内外水体及表层沉积物中HCHs、DDTs相比较,研究区水体、表层沉积物中HCHs、DDTs浓度分别处于中等和偏高水平。      

Malachite Green Adsorption onto Chitosan Coated Bentonite Beads: Isotherms,Kinetics and Mechanism

The removal of Malachite green (MG) from aqueous solutions by cross‐linked chitosan coated bentonite (CCB) beads was investigated and the CCB beads were characterized by Fourier Transform Infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS) and X‐ray diffraction (XRD) analysis. Solubility and swelling tests were performed in order to determine the stability of the CCB beads in acidic solution, basic solution and distilled water. The amount of MG adsorbed was shown to be influenced by the initial pH of the solution, contact time and the initial MG concentration. A kinetic study indicated that a pseudo‐second‐order model agreed well with the experimental data. From the Langmuir isotherm model, the maximum adsorption capacity of MG was found to be 435.0 mg g^–1. Desorption tests were carried out at different concentrations of EDTA, H₂SO₄ and NaOH. However, all desorbing solutions showed zero recovery of MG at all concentrations.     

Potential of support vector regression for prediction of monthly streamflow using endogenous property

In the recent past, a variety of statistical and other modelling approaches have been developed to capture the properties of hydrological time series for their reliable prediction. However, the extent of complexity hinders the applicability of such traditional models in many cases. Kernel‐based machine learning approaches have been found to be more popular due to their inherent advantages over traditional modelling techniques including artificial neural networks(ANNs ). In this paper, a kernel‐based learning approach is investigated for its suitability to capture the monthly variation of streamflow time series. Its performance is compared with that of the traditional approaches. Support vector machines (SVMs) are one such kernel‐based algorithm that has given promising results in hydrology and associated areas. In this paper, the application of SVMs to regression problems, known as support vector regression (SVR), is presented to predict the monthly streamflow of the Mahanadi River in the state of Orissa, India. The results obtained are compared against the results derived from the traditional Box–Jenkins approach. While the correlation coefficient between the observed and predicted streamflows was found to be 0·77 in case of SVR, the same for different auto‐regressive integrated moving average (ARIMA) models ranges between 0·67 and 0·69. The superiority of SVR as compared to traditional Box‐Jenkins approach is also explained through the feature space representation. Copyright © 2009 John Wiley & Sons, Ltd.