Characterizing site response in the Attock Basin,Pakistan, using microtremor measurement analysis

The Attock Basin is situated close to the northwest of Pakistan. Recent seismic event of October 2015 (7.5M_w) near the Pakistan Afghanistan border has proved that the area of interest is seismically active and triggered a series of aftershocks of magnitude even greater than 6.5M_w. This seismic activity has posed danger to the future of the people and infrastructure especially to the northwestern part of the country. Therefore, site response analysis is essential for estimating local site conditions in response to seismic events. Ambient noise recordings were made at 50 sites within urban and semi-urban settlements in the Attock Basin to analyze the site response of the small but densely populated basin. At each of these sites, the fundamental frequency of the soft sediments (f ₀), the amplitude (A ₀) of corresponding H/V spectral ratios, the thickness of soft sediment (H) lying over competent lithology, and the soil vulnerability index (K _g) were studied. Results were correlated with sparsely available borehole data to enhance the credibility of the study conducted for microzonation and predicting the site response to earthquake seismicity in the Attock Basin. The soil vulnerability index was found to range from moderate to high. Results clearly showed that the study area exhibits low to moderate fundamental frequency with greater soft sediment thicknesses distributed throughout the study area. Moreover, higher impedance contrasts were found at most of the sites within the central part of the Attock Basin, thus reflecting a moderate to high susceptibility of damage in those regions in response to seismic events.     

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.

     

A regional groundwater-flow model for sustainable groundwater-resource management in the south Asian megacity of Dhaka,Bangladesh

The water resources that supply most of the megacities in the world are under increased pressure because of land transformation, population growth, rapid urbanization, and climate-change impacts. Dhaka, in Bangladesh, is one of the largest of 22 growing megacities in the world, and it depends on mainly groundwater for all kinds of water needs. The regional groundwater-flow model MODFLOW-2005 was used to simulate the interaction between aquifers and rivers in steady-state and transient conditions during the period 1981–2013, to assess the impact of development and climate change on the regional groundwater resources. Detailed hydro-stratigraphic units are described according to 150 lithology logs, and a three-dimensional model of the upper 400 m of the Greater Dhaka area was constructed. The results explain how the total abstraction (2.9 million m³/d) in the Dhaka megacity, which has caused regional cones of depression, is balanced by recharge and induced river leakage. The simulated outcome shows the general trend of groundwater flow in the sedimentary Holocene aquifers under a variety of hydrogeological conditions, which will assist in the future development of a rational and sustainable management approach.

     

Inversion of Gravity Data for Imaging of a Sediment-basement Interface: A Case Study in the Northwestern Part of Bangladesh

Gravity data collected by the Geological Survey of Bangladesh are processed and interpreted for imaging of a sediment-basement interface over the northwestern part of Bangladesh. The observed gravity data are processed for discriminating gravitational fields contributed subtly from the shallow basement topographic feature with the twelve nodal piecewise cubic polynomial–based finite–element approach. In spectral analysis, the presence of a widely spread shallow basement feature has been detected and interpretation of gravity data using a two-dimensional gravity inversion technique indicates that its depth ranges from 0.041 km to 0.570 km relative to ground surface. In the northern part of the study area, the inferred basement configuration shows a general depression of the basement in the Takurgaon-Panchagar and Lalmonirhat districts and reaches a maximum depth of about 0.570 km. In the Nilphamari district and its southwestern part, the basement occurs at the most shallow depth due to its upliftment. However, the estimated sediment-basement interface depths are compared with the borehole and other geophysical interpretative information and are found to be consistent.     

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.     

Stable isotope dynamics of groundwater interactions with Ganges river

Groundwater depletion has been an emerging crisis in recent years, especially in highly urbanized areas as a result of unregulated exploitation, thus leaving behind an insufficient volume of usable freshwater. Presently Ganges river basin, the sixth largest prolific fluvial system and sustaining a huge population in South Asia, is witnessed to face (i) aquifer vulnerability through surface waterborne pollutant and (ii) groundwater stress due to summer drying of river as a result of indiscriminate groundwater abstraction. The present study focuses on a detailed sub-hourly to seasonally varying interaction study and flux quantification between river Ganges and groundwater in the Indian subcontinent which is one of the first documentations done on a drying perennial river system that feeds an enormous population. Contributing parameters to the total discharge of a river at its middle course on both temporal and spatial scale is estimated through three-component hydrograph separation and end-member mixing analysis using high-resolution water isotope (δ¹⁸O and δ²H) and electrical conductivity data. Results from this model report groundwater discharge in river to be the highest in pre-monsoon, that is, 30%, whereas, during post-monsoon the contribution lowers to 25%; on the contrary, during peak monsoon, the flow direction reverses thus recharging the groundwater which is also justified using annual piezometric hydrographs of both river water and groundwater. River water-groundwater interaction also shows quantitative variability depending on river morphometry. The current study also provides insight on aquifer vulnerability as a result of pollutant mixing through interaction and plausible attempts towards groundwater management. The present study is one of the first in South Asian countries that provides temporally and spatially variable detailed quantification of baseflow and estimates contributing parameters to the river for a drying mega fluvial system.