Long-term patterns in the diets of Japanese temperate bassLateolabrax japonicus larvae and juveniles in Chikugo estuarine nursery ground in Ariake Bay, Japan

Larval and juvenile Japanese temperate bass (Lateolabrax japonicus) samples were collected from a wide range of spatial gradients (covering a distance of approximately 30 km) in Chikugo estuary, Ariake Bay, Japan over a period of 8 yr (1997–2004) in order to observe changes in diet. Gut contents were studied by separating, identifying, counting, and estimating the dry weight of prey organisms. Copepod samples were collected during each cruise to observe the numerical composition, abundance, and biomass in the estuary. Considerable spatial and temporal variations were observed in copepod distributions in ambient water and the diets of the fish. Two distinctly different copepod assemblages were identified in the estuary: One in the upper estuarine turbidity maximum (ETM), dominated by a single speciesSinocalanus sinensis and the other in the lower estuary consisting of a multispecies assemblage, dominated byOithona davisae, Acartia omorii, Paracalanus parvus, andCalanus sinicus. The gut content composition of the fish in the upper estuary was dominated byS. sinensis, while in the lower estuary, it consisted ofP. parvus, O. davisae, andA. omorii. Within the size group analyzed (13.0–27.0 mm SL), the smaller individuals were found to feed on a mixed diet composed of smaller prey. The diets gradually shifted to bigger prey composed predominantly ofS. sinensis for larger size groups. Greater proportions of empty guts were recorded in the smaller individuals and dropped with increasing fish size. Higher dry biomass of copepods in the environment, as well as higher dry weights of gut contents, were recorded in the upper estuary, indicating that the upper estuarine ETM areas are important nursery grounds for the early life stages of the Japanese temperate bass. The early life stages of the Japanese temperate bass are adapted to use the upstream nursery grounds and ascending to the nursery areas to useS. sinensis is one of the key survival strategies of the Japanese temperate bass in the Chikugo estuary.     

Seismo-stratigraphic and structural interpretation of seismic data of Titas gas field,Bengal basin,Bangladesh

In the present study, seismic interpretation has been carried out over Titas structure of Bengal basin, Bangladesh to figure out its seismo-stratigraphic and structural behavior. Seven well marked reflecting horizons (R-01 to R-07) have been identified within the Neogene sedimentary sequences using 18 seismic sections and well log data. A new seismic stratigraphy of Neogene sequences has been proposed for the Titas structure ruling out the traditional lithostratigraphy. The studied structure has been divided into 3 megasequences (MS1, MS2 and MS3). Reflector R-01 and R-03 represent the tops of the megasequence 2 (MS2) and megasequence 1 (MS1) respectively. These well marked reflectors are correlated with the top of the traditional litho-groups called Tipam and Surma. Reflectors R-02 and R-04 represent acoustic impedance boundaries within MS2 and MS1 due to lithological gradation. However, R-02 and R-04 are not considered as sequence/ formation boundaries because geologically these are not well defined. Reflectors R-05, R-06 and R-07 represent top of the gasbearing zones A, B and C that belongs to MS1. All these interfaces or reflectors are anti-form with a central long crestal zone. It forms a north-south trending semi-domal sub-surface anticlinal structure having a semi-dome shaped closure. The structure is asymmetric with steeper eastern flank and gentler western flank. The crestal region is essentially plain with discontinuous reflection. The semidomal nature of the anticline is in contrast to the neighboring narrow anticlines. Structural pattern suggests its development in relation to the NE-SW trending stress field due to convergence of Indian plate with Burmese plate. Structures of the shallower and deeper reflectors are formed at different phases of structural development.     

Geochemistry of ochreous precipitates from coal mine drainage in India

The deposition of ochreous is common by a consequence of acid mine drainage (AMD). The ochreous precipitated from the AMD sites around Tertiary coalfield of Assam, India were collected and characterized by X-ray diffractometry (XRD), Fe to S molar ratio, ammonium oxalate acid (pH 3.0) extraction, fourier-transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), scanning electron microscope (SEM) and transmission electron microscope (TEM). The ochreous mainly consists of goethite, schwertmannite, ferrihydrite and jarosite. Mineralogy of ochreous was controlled by the pH whereas formation of ferrihydrite was favored at high organic carbon content. Role of bacteria for the formation of secondary minerals was observed. Mobility of metals was controlled by the ochreous, and they were also retained during the process of phase transformation of poorly ordered iron-oxyhydroxysulfates into the stable forms.     

A long-term trend in precipitation of different spatial regions of Bangladesh and its teleconnections with El Niño/Southern Oscillation and Indian Ocean Dipole

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.

     

Simultaneous adoption of risk management strategies to manage the catastrophic risk of maize farmers in Bangladesh

GeoJournal - Risk and uncertainty are distinctive features of agricultural cultivation, which significantly affect the production and income. Risk management is an important way for farmers to...     

Flood susceptibility modelling using advanced ensemble machine learning models

Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods.Therefore, earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters.In this study, we applied and assessed two new hybrid ensemble models, namely Dagging and Random Subspace(RS) coupled with Artificial Neural Network(ANN), Random Forest(RF), and Support Vector Machine(SVM) which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin, the northern region of Bangladesh.The application of these models includes twelve flood influencing factors with 413 current and former flooding points, which were transferred in a GIS environment.The information gain ratio, the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors.For the validation and the comparison of these models, for the ability to predict the statistical appraisal measures such as Freidman, Wilcoxon signed-rank, and t-paired tests and Receiver Operating Characteristic Curve(ROC) were employed.The value of the Area Under the Curve(AUC) of ROC was above 0.80 for all models.For flood susceptibility modelling, the Dagging model performs superior, followed by RF,the ANN, the SVM, and the RS, then the several benchmark models.The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.     

Mineralogical changes during intense chemical weathering of sedimentary rocks in Bangladesh

Bangladesh is situated in a subtropical to tropical climatic zone. A recently weathered crust has developed on sedimentary bedrock (sandstone, siltstone, shale and claystones) of Tertiary–Quaternary age. Weathered samples were collected from 16 sections totaling 68 samples and were analyzed mineralogically. The main primary minerals identified in the weathered crust of sedimentary rocks are quartz, plagioclase, K-feldspar, biotite, muscovite, sparse carbonate and epidote. The secondary minerals are kaolinite, illite, chlorite, gibbsite and goethite. Weathering initiated along the grain boundaries and cleavage planes of the minerals, forming small cloudy materials which were very difficult to identify. In the advanced stage of weathering, these cloudy materials have turned into secondary minerals. In region 1, high rain fall (7100 mm/yr) and monsoonic climate resulted in a kaolinite–gibbsite–goethite suite through the weathering of feldspars and biotite. The occurrence of gibbsite in the relatively elevated lands of Sylhet and Fe-kaolinite throughout the study areas is indicative of a humid–tropical climate during formation of the weathered crust.     

Heavy metal biosorption potential of a Malaysian Rhodophyte (<Emphasis Type="Italic">Eucheuma denticulatum</Emphasis>) from aqueous solutions

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.     

Multiple step ahead river flow modelling for south east tasmanian aquaculture

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.