Environmental impact assessment on water quality deterioration caused by the decreased Ganges outflow and saline water intrusion in south-western Bangladesh

 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     

Synthesis of biochar from sugarcane filter-cake and its impacts on physiological performance of lettuce (<Emphasis Type="Italic">Lettuce sativa</Emphasis>) grown on cadmium contaminated soil

Soil contamination with cadmium has become major concern all over the world because of its adverse impacts on ecosystem health and agricultural land. Soil amendment with biochar may have varied effects on physical and chemical properties of soil. The objective of the study was to explore the impact of sugarcane filter-cake biochar on physiological performance and growth of lettuce in an aged soil. Four different doses (0, 1.5%, 3%, and 5%) of biochar were used in the soil and conditioned for 1 month. After this, lettuce seedlings were grown in the soil. The results showed that the biochar treatment improved the fresh and dry biomass of leaves and roots as well as plant height while diminished the bioavailability of cadmium from the soil. As compared to control, biochar significantly enhanced the chlorophyll content in lettuce leaves. Due to the biochar amendment, the oxidative stress decreased in lettuce shoots over the control. As compared to control, concentration of cadmium in lettuce significantly decreased after the application of biochar. It was concluded that biochar could mitigate the toxicity of cadmium in lettuce by altering the biochemical and physiological processes in cadmium contaminated soil.     

巴基斯坦地方地震台网的监控能力与可靠性

使用Bungum和Huseby方法对地方地震台网的监控能力和可靠性进行了分析。用震源位置的标准计算机码重新定位地震事件。由频率震级分布导出50％，90％和100％的累积监控能力阀值，对这些阀值23年内记录资料的监控能力水平作了估测。分析表明，在台网内发生的地震事件的台网100％监控能力水平为ML=1.7，从台网内固定实时震源对台网震源解精度作了分析。地震事件在台网内发生时，震中误差低于4km。最后讨论了地方地震台网连续运行期间影响监控能力的因素。     

PM10 Source Apportionment in Ahvaz,Iran, Using Positive Matrix Factorization

Source apportionment of particulate matter <10 µm in diameter (PM₁₀), having considerable impacts on human health and the environment, is of high priority in air quality management. The present study, therefore, aimed at identifying the potential sources of PM₁₀ in an arid area of Ahvaz located in southwest of Iran. For this purpose, we collected 24‐h PM₁₀ samples by a high volume air sampler. The samples were then analyzed for their elemental (Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, Pb, Se, Si, Sn, Sr, Li, Ti, V, Zn, Mo, and Sb) and ionic (NH, Cl^?, NO, and SO) components using inductively coupled plasma optical emission spectrometry and ion chromatography instruments, respectively. Eight factors were identified by positive matrix factorization: crustal dust (41.5%), road dust (5.5%), motor vehicles (11.5%), marine aerosol (8.0%), secondary aerosol (9.5%), metallurgical plants (6.0%), petrochemical industries and fossil fuel combustion (13.0%), and vegetative burning (5.0%). Result of this study suggested that the natural sources contribute most to PM₁₀ particles in the area, followed closely by the anthropogenic sources.     

Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region

Soil temperature (T _S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T _S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T _S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T _a), solar radiation (R _S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T _S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T _a, RH, R _S and P were reasonably correlated with T _S at various depths, but the most effective parameters influencing T _S at different depths were T _a and RH.     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.     

Simulating urban growth in a megalopolitan area using a patch‐based cellular automata

Although traditional cellular automata (CA)‐based models can effectively simulate urban land‐use changes, they typically ignore the spatial evolution of urban patches, due to their use of cell‐based simulation strategies. This research proposes a new patch‐based CA model to incorporate a spatial constraint based on the growth patterns of urban patches into the conventional CA model for reducing the uncertainty of the distribution of simulated new urban patches. In this model, the growth pattern of urban patches is first estimated using a developed indicator that is based on the local variations in existing urban patches. The urban growth is then simulated by integrating the estimated growth pattern and land suitability using a pattern‐calibrated method. In this method, the pattern of new urban patches is gradually calibrated toward the dominant growth pattern through the steps of the CA model. The proposed model is applied to simulate urban growth in the Tehran megalopolitan area during 2000–2006–2012. The results from this model were compared with two common models: cell‐based CA and logistic‐patch CA. The proposed model yields a degree of patch‐level agreement that is 23.4 and 7.5% higher than those of these pre‐existing models, respectively. This reveals that the patch‐based CA model simulates actual development patterns much better than the two other models.     

An investigation of near surface wind speed trends in arid and semiarid regions of Iran

Wind plays an important role on the ecosystems and hydrological cycles besides other meteorological parameters such as temperature, precipitation, sunshine, and relative humidity. It strongly affects evapotranspiration, especially in arid and semiarid regions where there are serious problems in regard to water resource management. Evaluating the wind speed trend can provide good information for future agricultural planning. This study was conducted in order to investigate the wind speed trends over 24 synoptic meteorological stations located in arid and semiarid regions of Iran from 1975 to 2005. Near-surface wind speed was trended by nonparametric Mann–Kendall test spatially and temporally in three time scales (annual, seasonal, and monthly). Then, Sen’s slope estimator was used to determine the amount of the changes; furthermore, 10-year moving average low-pass filter was applied to show general trends. Finally, the smoothed time series derived from the mentioned filter were classified in three clusters for each time series and then mapped to show their spatial distribution pattern. Results showed insignificant and significant, increasing and decreasing trends during the surveyed time. Wind speeds in less than 50 % of stations changed statistically in all time scales, and in most cases, the frequency of the upward trends was more than that of downward ones. The spatial distribution of significant wind speed showed that the increase mostly occurred in eastern part. Clustering gave us the turning point around 1990. Clearly, when clusters were mapped, they indicated the same pattern as the Z value maps derived from Mann–Kendall test which meant that the outputs of the mentioned method confirmed the other one. As the wind speed trends in different stations likely to follow the previous evapotranspiration (ET₀) trend results in Iran, it confirms that wind speed was an effective parameter on ET₀, even though other parameters should be considered too.     

Chromium Removal through Biosorption and Bioaccumulation by Bacteria from Tannery Effluents Contaminated Soil

Four bacterial isolates (two resistant and two sensitive to chromium) were isolated from soil contaminated with tannery effluents at Jajmau (Kanpur), India, and were identified by 16S rDNA gene sequencing as Stenotrophomonas maltophilia, Exiguobacterium sp., Pantoea sp., and Aeromonas sp. Biosorption of chromium by dried and living biomasses was determined in the resistant and sensitive isolates. The effect of pH, initial metal concentration, and contact time on biosorption was studied. At pH 2.5 the living biomass of chromium resistant isolate Exiguobacterium sp. ZM‐2 biosorbed maximum amount of Cr⁶⁺ (29.8 mg/g) whereas the dried biomass of this isolate biosorbed 20.1 mg/g at an initial concentration of 100 mg/L. In case of chromate sensitive isolates, much difference was not observed in biosorption capacities between their dried and living biomasses. The maximum biosorption of Cr³⁺ was observed at pH 4.5. However, biosorption was identical in resistant and sensitive isolates. The data on chromium biosorption were analyzed using Langmuir and Freundlich isotherm model. The biosorption data of Cr⁶⁺ and Cr³⁺ from aqueous solution were better fitted in Langmuir isotherm model compared to Freundlich isotherm model. Metal recovery through desorption was observed better with dried biomasses compared to the living biomasses for both types of chromium ions. Bioaccumulation of chromate was found higher in chromate resistant isolates compared to the chromate sensitive isolates. Transmission electron microscopy confirmed the accumulation of chromium in cytoplasm in the resistant isolates.