Regional Cooperation in Flood Management in the Ganges-Brahmaputra-Meghna Region: Bangladesh Perspective

Bangladesh is known to behighly vulnerable to floods. Frequent floods have put enormous constraints on its development potential. Unfortunately, the frequency of high intensity floods is on the rise. So far the country has struggled to put a sizeable infrastructure in place to prevent flooding in may parts of the country with limited success. In recent times, it was found that losses of lives and valuable assets could be significantly minimized by implementing non-structural measures including the improvement of flood forecasting and warning system. The existing flood forecasting and warning capacity of Bangladesh could be more effective if real-timedata could be acquired from upstreamareas within the Ganges-Brahmaputra-Meghna (GBM) catchment, where runoff is generated. In order to do so, Bangladesh needs to foster an effective regional cooperationwith the other GBM regional countries of India, Nepal, and Bhutan. This article examines how GBM regional cooperation could be useful towards managing floods in Bangladesh in particularand the region in general.     

Rainfall–runoff modelling and water balance analysis for Al-Hindiyah barrage,Iraq using remote sensing and GIS

Investigation of rainfall–run-off modelling is an important subject to develop any available means to water supply, which maintains human life such as run-off harvesting method. This study aims to analyse and understand the rainfall–run-off relationship in a part of Babil city, Iraq. Curve number which is a function of land use, soil texture, soil moisture and land slope is used in this study. Remote sensing and GIS are used to analyse the data and to produce the run-off depth map for the study area. Then, the run-off depth is used with rainfall to investigate the relationship between them using linear correlation. This study showed a strong linear relationship between rainfall and run-off (R² = 0.992). It indicates that in the absence of rainfall data, run-off data can be used to estimate rainfall amount. Also, the study revealed through water balance analysis that there is an average monthly change in storage.     

Whistler observations of magnetospheric electric field in the night side plasma-sphere at low latitude

Whistlers recorded at low latitude ground stations of Gulmarg, Nainital and Varanasi were used to infer the east-west component of electric field on the nightside plasmasphere atL=1.2, 1.12, and 1.07 during magnetic storm periods. The method of measuring electric field from the observed cross-L motions of whistler ducts within the plasma-sphere, indicated by changes in nose frequency of whistlers has been outlined. The nose frequencies of the non-nose whistlers under consideration have been deduced from Dowden-Allocock linear Q-technique. The results show eastward electric fields of 0.7 mVm^–1 in the equatorial plane of Gulmarg and 0.3 mVm^–1 in the equatorial plane of Nainital in the premidnight local time sector. Near midnight, there is a sharp transition from eastward field to a westward electric field of 0.2–0.7 mV m^–1 for Gulmarg, 0.3–0.5 mV m^–1 for Nainital and 0.1–0.3 mVm^–1 for Varanasi.     

An integrated GIS-based approach for geohazards risk assessment in coal mines

From the viewpoint of safety in underground coal mining, the most suitable mining panel is the one with minimum geological structures, the right machinery, and equipment selection, trained employee, and proficient stope management. Since the ground parameters are uncontrollable and inherent uncertainties exist, a high percent of risk will usually accompany the underground coal mining activities. The main purpose of this study is to present a geological–geotechnical risk assessment model for identification of high risk-prone areas in underground coal mines using an integrated GIS-geostatistics system. Tabas as the first mechanized and largest underground coal mine in Iran was selected as a case study in this study. Gas content of coal seam, Coal Mine Roof Rating (CMRR), initial in situ stress state, fault throw, and orientation were selected as hazard/risk factors. For estimating the amount of coal seam gas content, CMRR and initial in situ stress in unsampled areas and providing the prediction maps, geostatistics module in ArcGIS was used. Rock engineering system–interaction matrix method was used for attribute weight assignment. Next, the attribute layers were weighted, rated, and overlaid to create a final map of geohazards risk. The analysis results of final risk map indicate that about 45% of under study area is prone to high to very high geohazards risk. Comparison of the results with experiences obtained during the early part of the mine and mined-out panels showed generally good agreement with promising ideas. This highlights the potential application of the GIS-based approach for hazards detection and geohazards risk assessment in underground coal mines.     

Health risk assessment of nitrate exposure in groundwater of rural areas of Gonabad and Bajestan,Iran

Prolonged exposure to excessive levels of nitrate through drinking water is a potential risk for human health. The current research reports the analytical results and associated health risk for water quality in term of nitrate in 39 groundwater samples during January 2018 in rural areas of Gonabad and Bajestan, Iran. Nitrate concentrations ranged from 1.8 to 82.2 and from 5.5 to 84.3 mg/L for Gonabad and Bajestan, respectively. In this work, the potential risk to human health was determined using the hazard quotient (HQ) for three age groups including adults, children and infants. Comparison of HQs among the 39 sampling sites showed that the rural areas in Bajestan had higher HQs than Gonabad. Among the studied groups, infants exposed to a higher risk than children and adults. The results also indicated that the health of individuals from nitrate exposure in most of the groundwater studied was not acceptable and most of the consumers were in danger from current nitrate concentrations. Therefore, there is an urgent need for enforcing effective plans to improve groundwater quality and to better manage and control probable nitrate contaminated sources.     

Bearing capacity of soft soil model treated with end-bearing bottom ash columns

Granular column technique is a soil improvement method used to increase the bearing capacity of a soft soil area by replacing the soil with a group of granular column materials. The by-product utilisation is a worldwide interest for sustainable infrastructure development. Bottom ash, which is a combustion deposit derived from coal burning, is a potential by-product that could be used alternatively to sand or aggregate as a green granular column material. This research is to study the potential use of the bottom ash column-improved soft clay by conducting a series of small-scale physical modelling test. The bearing capacity behaviour and failure mode of soft clay improved with end-bearing group of bottom ash columns with and without geotextile encasement are investigated. The bearing capacity of soft clay is significantly enhanced by the inclusion of bottom ash columns; that is, 239% of bearing capacity improvement is observed with only 13% of improvement area. The bulging of the bottom ash column is transferred to buckling failure with higher bearing capacity when the bottom ash column is encased by geotextile. The outcome of this research leads to the usage of bottom ash by-product as a granular column material in sustainable soil improvement technique.     

A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data

The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.     

An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes

Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operator split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Although developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.     

Testing Nano-Powder and Fused-Glass Mineral Reference Materials for In Situ Rb-Sr Dating of Glauconite,Phlogopite, Biotite and Feldspar via LA-ICP-MS/MS

Reference materials (RMs) with well-characterised composition are necessary for reliable quantification and quality control of isotopic analyses of geological samples. For in situ Rb-Sr analysis of silicate minerals via laser ablation inductively coupled plasma tandem mass spectrometry (LA-ICP-MS/MS) with a collision/reaction cell, there is a general lack of mineral-specific and matrix-matched RMs, which limits wider application of this new laser-based dating technique to certain minerals. In this work, pressed nano-powder pellets (NP) of four RMs, GL-O (glauconite), Mica-Mg (phlogopite), Mica-Fe (biotite) and FK-N (K-feldspar), were analysed and tested for in situ Rb-Sr dating, complemented by isotope dilution (ID) MC-ICP-MS Rb-Sr analyses of GL-O and Mica-Mg. In addition, we attempted to develop alternative flux-free and fused ‘mineral glasses’ from the above RMs for in situ Rb-Sr dating applications. Overall, the results of this study showed that among the above RMs only two NP (Mica-Mg-NP and GL-O-NP) were suitable and robust for in situ dating applications. These two nano-powder reference materials, Mica-Mg-NP and GL-O-NP, were thus used as primary RMs to normalise and determine Rb-Sr ages for three natural minerals: MDC phlogopite and GL-O glauconite grains, and also Mica-Fe-NP (biotite). Our in situ analyses of the above RMs yielded Rb-Sr ages that are in good agreement (within 8%) of published ages, which suggests that both Mica-Mg-NP and GL-O-NP are suitable RMs for in situ Rb-Sr dating of phlogopite, glauconite and biotite. However, using secondary RMs is recommended to monitor the quality of the obtained ages.