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.     

Modelling the vulnerability of groundwater to contamination in an unconfined alluvial aquifer in Pakistan

The area of Thal Doab is located in the Indus Basin and is underlain by a thick alluvial aquifer called the Thal Doab aquifer (TDA). The TDA is undergone intense hydrological stress owing to rapid population growth and excessive groundwater use for livestock and irrigated agricultural land uses. The potential impact of these land uses on groundwater quality was assessed using a DRASTIC model in a Geographic Information System environment. Seven DRASTIC thematic maps were developed at fixed scale and then combined into a groundwater vulnerability map. The resultant vulnerability index values were grouped into four zones as low, moderate, high and very high. The study has established that 76% of the land area that is underlain by the TDA has a high to very high vulnerability to groundwater contamination mainly because of a thin soil profile, a shallow water table and the presence of soils and sediments with high hydraulic conductivity values. In addition, only 2 and 22% of the total area lie in low and moderate vulnerability zones, respectively. The outcomes of this study can be used to improve the sustainability of the groundwater resource through proper land-use management.     

Prevailing trends of climatic extremes across Indus-Delta of Sindh-Pakistan

This study examines the variability and change in the patterns of climatic extremes experienced in Indus-Delta of Sindh province of Pakistan, comprising regions of Karachi, Badin, Mohenjodaro, and Rohri. The homogenized daily minimum and maximum temperature and precipitation data for a 36-year period were used to calculate 13 and 11 indices of temperature and precipitation extremes with the help of RClimDex, a program written in the statistical software package R. A non-parametric Mann–Kendall test and Sen’s slope estimates were used to determine the statistical significance and magnitude of the calculated trend. Temperatures of summer days and tropical nights increased in the region with overall significant warming trends for monthly maximum temperature as well as for warm days and nights reflecting dry conditions in the study area. The warm extremes and nighttime temperature indices showed greater trends than cold extremes and daytime indices depicting an overall warming trends in the Delta. Historic decrease in the acreage of major crops and over 33% decrease in agriculture credit for Sindh are the indicators of adverse impacts of warmer and drier weather on Sindh agriculture. Trends reported for Karachi and Badin are expected to decrease rice cultivation, hatching of fisheries, and mangroves forest surrounding these cities. Increase in the prevailing temperature trends will lead to increasingly hotter and drier summers resulting to constraints on cotton, wheat, and rice yield in Rohri and Mohenjodaro areas due to increased crop water requirements that may be met with additional groundwater pumping; nonetheless, the depleted groundwater resources would have a direct impact on the region’s economy.     

Chromium uptake by giant reed under rhizobacterial inhibition

The role of rhizospheric microbes of giant reed (Arundo donax L.) in Cr uptake from hydroponic culture was investigated. The control group was exposed to Cr in range of 25–100 mg L^?1 containing a control itself (with no metal addition). The experimental group received same Cr treatments, but in addition was exposed to antibiotic treatment in order to inhibit rhizospheric bacteria. The range of Cr accumulated in the roots was 3–7.65 mg L^?1; in stem it ranged 2.15–42.4 mg kg^?1; while in leaves, the range of Cr content was 13.7–15 mg kg^?1. Overall, Cr uptake in A. donax (without rhizobacterial inhibition) was root < leaf < stem. However, the amount of Cr uptake in plants with rhizobacterial inhibition was significantly less (~4.6-folds in 100 mg L^?1 Cr treatment) than those without such inhibition clearly highlighting that rhizobacterial inhibition decreased the Cr uptake. The experimental results clearly demonstrated that the inhibition of the rhizobacterial populations had great influence on the Cr uptake. However, Cr uptake could not be completely inhibited as some metal uptake was observed after the rhizobacterial inhibition although it was significantly less than the Cr uptake of plants without such inhibition.     

Prediction of pore-water pressure response to rainfall using support vector regression

Nonlinear complex behavior of pore-water pressure responses to rainfall was modelled using support vector regression (SVR). Pore-water pressure can rise to disturbing levels that may result in slope failure during or after rainfall. Traditionally, monitoring slope pore-water pressure responses to rainfall is tedious and expensive, in that the slope must be instrumented with necessary monitors. Data on rainfall and corresponding responses of pore-water pressure were collected from such a monitoring program at a slope site in Malaysia and used to develop SVR models to predict pore-water pressure fluctuations. Three models, based on their different input configurations, were developed. SVR optimum meta-parameters were obtained using k-fold cross validation and a grid search. Model type 3 was adjudged the best among the models and was used to predict three other points on the slope. For each point, lag intervals of 30 min, 1 h and 2 h were used to make the predictions. The SVR model predictions were compared with predictions made by an artificial neural network model; overall, the SVR model showed slightly better results. Uncertainty quantification analysis was also performed for further model assessment. The uncertainty components were found to be low and tolerable, with d-factor of 0.14 and 74 % of observed data falling within the 95 % confidence bound. The study demonstrated that the SVR model is effective in providing an accurate and quick means of obtaining pore-water pressure response, which may be vital in systems where response information is urgently needed.     

Control of river stage on the reactive chemistry of the hyporheic zone

We examined the influence of river stage on subsurface hydrology and pore water chemistry within the hyporheic zone of a groundwater‐fed river during the summer baseflow period of 2011. We found river stage and geomorphologic environment to control chemical patterns in the hyporheic zone. At a high river stage, the flux of upwelling water in the shallow sediments (>20 cm) decreased at sample sites in the upper section of our study reach and increased substantially at sites in the lower section. This differential response is attributed to the contrasting geomorphology of these subreaches that affects the rate of the rise and fall of a river stage relative to the subsurface head. At sites where streamward vertical flux decreased, concentration profiles of a conservative environmental tracer suggest surface water infiltration into the riverbed below depths recorded at a low river stage. An increase in vertical flux at sites in the lower subreach is attributed to the movement of lateral subsurface waters originating from the adjacent floodplain. This lateral‐moving water preserved or decreased the vertical extent of the hyporheic mixing zone observed at a low river stage. Downwelling surface water appeared to be responsible for elevated dissolved organic carbon (DOC) and manganese (Mn) concentrations in shallow sediments (0–20 cm); however, lateral subsurface flows were probably important for elevated concentrations of these solutes at deeper levels. Results suggest that DOC delivered to hyporheic sediments during a high river stage from surface water and lateral subsurface sources could enhance heterotrophic microbial activities. Copyright © 2013 John Wiley & Sons, Ltd.     

Acoustic evidence of a submarine slide in the deepest part of the Arctic,the Molloy Hole

The western Svalbard continental margin contains thick sediment sequences with areas known to contain gas hydrates. Together with a dynamic tectonic environment, this makes the region prone to submarine slides. This paper presents results from geophysical mapping of the deepest part of the high Arctic environment, the Molloy Hole. The mapping includes multibeam bathymetry, acoustic backscatter and sub-bottom profiling. The geophysical data reveal seabed features indicative of sediment transport and larger-scale mass wasting. The large slide scar is here referred to as the Molloy Slide. It is located adjacent to the prominent Molloy Hole and Ridge system. The slide is estimated to have transported >65 km³ of sediments over the deep axial valley of the Molloy Ridge, and further into the Molloy Hole. A unique feature of this slide is that, although its run-out distance is relatively short (<5 km), it extends over an enormous vertical depth (>2,000 m) as a result of its position in a complex bathymetric setting. The slide was most likely triggered by seismic activity caused by seafloor spreading processes along the adjacent Molloy Ridge. However, gas-hydrate destabilization may also have played a role in the ensuing slide event.     

Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment

The extensive use of pesticides for increasing the agricultural production is affecting the quality of groundwater. The objectives of this article are to (i) develop pesticide relative leaching ranks for well sites, (ii) develop maps for human health risks due to pesticide applications, and (iii) identify the most significant parameters in pesticide simulations for groundwater vulnerability assessment. The methods include (i) development of acifluorfen relative leaching ranks for 25 well sites using ArcPRZM‐3, (ii) development of health risk maps using model simulated maximum dissolved bentazon concentrations on the basis of USA drinking water quality guidelines, (iii) sensitivity analysis for 14 ArcPRZM‐3 input parameters using the Plackett–Burman method. ArcPRZM‐3 is a user‐friendly system for spatial modeling of pesticide leaching from surface to groundwater. Thirteen acifluorfen relative leaching potential ranks were developed in which the pesticide leaching decrease from 1 to 13. The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. The ArcPRZM‐3 system could be efficiently applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.