This paper deals with an environmental impact assessment of low water flow in the river Ganges during a dry period at the
Khulna and Mongla port areas in south-western Bangladesh. Large-scale surface water withdrawal in India after commissioning
the Farakka Barrage causes a drastic fall in the Ganges low-flow condition within the Bangladesh territory during every dry
period. The average lowest discharge in the Ganges is 552 m3/s, which is about 73% less than that in the pre-Farakka time. This has caused the deterioration of both surface and groundwater
quality of the study area. Salinity is the principal cause of water quality degradation in the area. Present observation shows
that the surface water of the area is sulphate-chloride dominated, which signifies high salinity whereas the groundwater is
categorized as of medium to high salinity. To maintain the Rupsa River's maximum salinity below 1000 μS/cm the discharge in
the Ganges should be ∼1500 m3/s, whereas that at Garai basin is ∼10 m3/s. If this present situation continues it will be a crippling blow to the environment of the area in the long term. An integrated
multidisciplinary approach to hydrogeological research is urgently required to salvage the area from further deterioration.
Received: 9 August 1999 · Accepted: 8 March 2000 相似文献
The release of metals during weathering has been studied in order to assess its geochemical controls and possible effects
on environmental health in Bangladesh. A total of 27 soil samples and 7 surface water samples were collected from four locations
covering three major regions in the country. Results show that weathering effects are a strong function of climatic conditions.
Surface waters are typically enriched in Al, Mg, Ca, Na, K, As, Ba, Cr, Cu, Ni, Pb and Zn. The solubility of metal ions, organometallic
complexes, co-precipitation or co-existence with the colloidal clay fraction are the main processes that lead to metal enrichment
in lake and reservoir water. Aluminium concentrations exceed World Health Organization (WHO) drinking-water standards in all
samples, and in two regions, arsenic concentrations also significantly exceed WHO standards. The elevated levels of As indicate
that arsenic contamination of water supplies in Bangladesh is not confined to groundwater.
Received: 4 June 1999 · Accepted: 17 August 1999 相似文献
In this paper, a two-dimensional, vertically integrated hydrodynamic model is developed taking into account entrained air bubbles during storm surges as well as incorporating inverted barometer, and river and land dynamics. The model is specifically designed for the coastal region of Bangladesh. A nested scheme method with a fine mesh scheme (FMS), capable of incorporating the complex coastline and all major offshore islands accurately, nested into a coarse mesh scheme (CMS) covering up to 15° N latitude in the Bay of Bengal is used. To incorporate the small and big offshore islands in the Meghna estuarine region with its complex coastline accurately, a very fine mesh scheme (VFMS) is again nested into the FMS. Along the northeast corner of the VFMS, the Meghna river discharge is taken into account. The coastal and island boundaries are approximated through proper stair steps. The model equations are solved by a semi-implicit finite difference technique using a staggered C-grid. A stable appropriate tidal condition over the model domain is generated by applying tidal forcing with the four major tidal constituents M2, S2, K1, and O1 along the southern open boundary of the CMS. This tidal regime is introduced as the initial state of the sea for nonlinear interaction of tide and surge. The model is applied to simulate water levels due to the interaction of tide and surge associated with the cyclones April 1991 and Aila at different coastal and island locations along the coast of Bangladesh. The results are found to be quite satisfactory with root mean square error of ~0.50 m as calculated for both the storm events. Tests of sensitivities on water levels are carried out for air bubbles, offshore islands, river discharge, inverse barometer, and grid resolution. The presence of air bubbles increases simulated water levels a little bit in our model, and the contribution of air bubbles in increasing water level is found around 2 %. Further, water levels are found to be influenced by offshore islands, river discharge, inverse barometer as well as grid resolution. 相似文献
Meso-scale characteristics of disturbances that bring about atmospheric disasters in pre- and mature monsoon seasons in Bangladesh
are analyzed. Several types of meteorological instruments capable of observations with high temporal and spatial resolutions
were introduced for the first time in this area to capture the meso-scale structure of rainfall systems. We installed an automatic
weather station (AWS) and several automatic raingauges (ARGs) and utilized the weather radar of Bangladesh Meteorological
Department (BMD). From the radar image in the summer of 2001 (16–18 July), a striking feature of the systematic diurnal variation
in this area was elucidated. In these 3 days, the diurnal evolutions of convective activity were remarkably similar to each
other, implying that this pattern can be understood as a typical response of local cloud systems to the diurnal variation
of insolation under some summer monsoon situations. The ARG data show the difference in characteristics of rainfall between
pre- and mature monsoon seasons. The short intense downpour tends to occur more frequently in the pre-monsoon season than
in the mature monsoon season. The pre-monsoon rainfall also has clear diurnal variation with a peak that is more strongly
concentrated in time. In the northern part the rainfall peak is found in between midnight and early morning, while it is observed
in the daytime in central to western parts of the country. Two disaster cases caused by meso-scale disturbances are analyzed.
Although they occurred in the same season, the structures of the cloud systems were largely different from each other. The
disturbance brought about tornadoes on 14 April 2004, consisting of many spherical cloud systems of approximately 20 km size.
On the other hand, another one that caused the tragic river water transport accident on 23 May 2004 had meso-scale rain band
structure. The latter case was captured by the AWS located at Dhaka. Sudden changes in temperature, wind and pressure were
observed clearly, showing the typical structure of convective rain bands. 相似文献
A long-term (1948 to 2012) trend of precipitation (annual, pre-monsoon, monsoon, and post-monsoon seasons) in Bangladesh was analyzed in different regions using both parametric and nonparametric approaches. Moreover, the possible teleconnections of precipitation (annual and monsoon) variability with El Niño/Southern Oscillation (ENSO) episode and Indian Ocean Dipole (IOD) were investigated using both average and individual (both positive and negative) values of ENSO index and IOD. Our findings suggested that for annual precipitation, a significant increasing monotonic trend was found in whole Bangladesh (4.87 mm/year), its western region (5.82 mm/year) including Rangpur (9.41 mm/year) and Khulna (4.95 mm/year), and Sylhet (10.12 mm/year) and Barisal (6.94 mm/year) from eastern region. In pre-monsoon, only Rangpur (2.88 mm/year) showed significant increasing trend, while in monsoon, whole Bangladesh (3.04 mm/year), Sylhet (7.17 mm/year), and Barisal (6.94 mm/year) showed similar trend. In post-monsoon, there was no significant trend. Our results also revealed that the precipitation (annual or monsoon) of whole Bangladesh and almost all of the spatial regions did not show any significant correlation with ENSO events, whereas the average IOD values showed significant correlation only in monsoon precipitation of western region. The individual positive IODs showed significant correlation in whole Bangladesh, western region, and its two divisions (Rajshahi and Khulna). So, in the context of Bangladesh climate, IOD has the more teleconnection to precipitation than that of ENSO. Our findings indicate that the co-occurrence of ENSO and IOD events may suppress their influence on each other.
Biosorption is a promising technology for the removal of heavy metals from industrial wastes and effluents. In the present study, biosorption of Pb2+, Cu2+, Fe2+ and Zn2+ onto the dried biomass of Eucheuma denticulatum (Rhodophyte) was investigated as a function of solution pH, contact time, temperature and initial metal ion concentration. The experimental data were evaluated by Langmuir, Freundlich, Temkin and Dubinin–Radushkevich isotherm models. The sorption isotherm data followed Langmuir and Freundlich models, and the maximum Langmuir monolayer biosorption capacity was found as 81.97, 66.23, 51.02 and 43.48 mg g?1 for Pb2+, Cu2+, Fe2+ and Zn2+, respectively. The sorption kinetic data followed pseudo-second-order and intraparticle diffusion models. Thermodynamic study revealed feasible, spontaneous and endothermic nature of the sorption process. Fourier transform infrared analysis showed the presence of amine, aliphatic, carboxylate, carboxyl, sulfonate and ether groups in the cell wall matrix involved in metal biosorption process. A total of nine error functions were applied in order to evaluate the best-fitting models. We strongly suggest the analysis of error functions for evaluating the fitness of the isotherm and kinetic models. The present work shows that E. denticulatum can be a promising low-cost biosorbent for removal of the experimental heavy metals from aqueous solutions. Further study is warranted to evaluate its potential for the removal of heavy metals from the real environment. 相似文献
We develop multiple step ahead prediction models of river flow for locations in Tasmania (Australia) for decision support in aquaculture. In predicting river flows for multiple days ahead, we first statistically determine the maximum input lags of rainfall and river flow. We then use machine learning techniques in building models. In multiple step ahead prediction, we consider both static and dynamic approaches. In dynamic approach, one day prediction is served as input to two days ahead prediction. The experimental results demonstrate that, in general, a dynamic approach provides better accuracy in multiple day’s ahead prediction. For Duck Bay location using dynamic approach, support vector regression performs best over linear regression, M5P and multilayer perceptron. However, at Montagu Bay location, we find that M5P performs best over methods. We find that multiple step ahead prediction of river flow for each location requires modelling of lags with associated machine learning techniques. 相似文献