This study investigated the relationship between near-surface lithology and the spatial variability of As concentrations using
sediment grain-size analysis and electromagnetic induction survey in the southeast Bangladesh. It has been observed that the
aquifers overlain by finer sediments have higher concentrations of As in groundwater, whereas As concentrations are remarkably
low in aquifers having permeable sandy materials or thinner silt/clay layer at the surface. The near-surface lithology acts
as a controlling factor for spatial distributions of groundwater As within the very shallow depths (<15 m). Shallow alluvial
aquifers can provide low-As drinking water in many areas of the country when tube wells are properly installed after investigation
of the overlying near-surface sediment attributes and hydraulic properties. 相似文献
Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve-receiver operating char-acteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC＞90％)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the per-iod between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72％between 2000 and 2017,while the PG rate increased by 51.68％over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks. 相似文献
Arsenic (As) is a toxic and carcinogenic metalloid that causes various hazards to human health. Phytofiltration is a more eco-friendly and green approach than chemoremediation, or other traditional technologies, for removing As from aquatic environments. Recently, Micranthemum umbrosum was shown as a promising candidate for phytofiltration of inorganic As species. This work examines the potential application of M. umbrosum to phytofiltration of organic As species, such as monomethylarsonic acid (MMAA, CH5AsO3) and dimethylarsinic acid (DMAA, C2H7AsO2), from oxic water environments. M. umbrosum plants were grown in two test concentrations of MMAA and DMAA, or a control, in a hydroponic experiment. After seven days, leaves accumulated 90 ± 3.2 and 48 ± 1.6 µg As g?1 (oven dry basis) from 1 µg As mL?1 of water added from MMAA and DMAA, respectively. Bioconcentration factor values and translocation factor values were always greater than 1.0, indicating that M. umbrosum was a good As accumulator and that leaves accumulated significantly higher amounts of As than stems and roots. Analysis of macro- and micronutrient data showed that M. umbrosum had higher resistance to organic As treatments than the control. These results confirm the potential application of M. umbrosum for phytofiltration of organic As from contaminated oxic water environments. 相似文献
Experimental modeling is used to study the geometry and evolution of inversion structures. Two main types of inversion structures are analyzed:
1. (1) structures formed by fault-propagation folding; and
2. (2) structures formed by fault-bend folding on listric faults.
Fault-propagation inversion structures initially develop as broad drape folds with possible fault breakthrough during an early extensional phase. Syn-extensional strata deposited in the hanging wall typically thicken away from the fault. Compressional reactivation results in reversal of slip on the master and secondary faults, their rotation to shallower dips, and the development of a compressional fault-propagation fold. Key features of the fault-propagation fold are basinward thickening of syn-extensional units and resulting steep dips of the front limb of the structure. Fault-bend inversion structures initiate as rollover folds within extensional half-graben. Deformation is primarily localized along a system of antithetic faults. Syn-extensional strata typically thicken across the fault but also thin basinward away from the fault. During compression, the extensional rollover folds are folded into compressional fault-bend folds. Key features of this structure are thinning of syn-extensional units into the basin. Inversion of more symmetric graben results in a doubly-convex geometry of syn-extensional units. These observations of bed geometry and thickness provide predictive models for interpreting the geometries of inversion structures in areas of poor data quality. 相似文献
Hydrologic models of irrigated lands generally adopt either a basin-scale or a root-zone perspective. While basin-wide macro-scale models rely on the aggregation of important spatial and temporal data across large areas, micro-scale root-zone models depend on the definition of rigid boundaries around the zone of plant–soil–water interaction. In reality, irrigation management decisions are made on a field by field basis and can interact across field boundaries. This paper first describes a shallow water table model, based on deforming finite element (DFE) framework, to characterize the near-surface field-to-field hydrologic response to various irrigation and drainage management regimes along a gently sloping alluvial fan. The model is then enhanced through changing geometry of a fluctuating water table below a series of irrigated fields. Such an enhancement also offers computational flexibility relative to the saturated–unsaturated models commonly used in micro-scale studies. The model is designed with the alluvial fan aquifers of California’s western San Joaquin Valley as reference systems. 相似文献
Southern Bangladesh’s irrigation and drinking water is threatened by saline intrusion. This study aimed to establish an irrigation water quality index (IWQI) using a geostatistical model and multivariate indices in Gopalganj district, south-central Bangladesh. Groundwater samples were taken randomly (different depths) in two seasons (wet-monsoon and dry-monsoon). Hydrochemical analysis revealed groundwater in this area was neutral to slightly alkaline and dominating cations were Na+, Mg2+, and Ca2+ along with major anions Cl? and HCO3?. Principal component analysis and Gibbs plot helped explain possible geochemical processes in the aquifer. The irrigation water evaluation indices showed: electrical conductivity (EC) >750 µS/cm, moderate to extreme saline; sodium adsorption ratio (SAR), excellent to doubtful; total hardness (TH), moderate to very hard; residual sodium bicarbonate, safe to marginal; Kelly’s ratio >1; soluble sodium percentage (SSP), fair to poor; magnesium adsorption ratio, harmful for soil; and IWQI, moderate to suitable. In addition, the best fitted semivariogram for IWQI, EC, SAR, SSP, and TH confirmed that most parameters had strong spatial dependence and others had moderate to weak spatial dependence. This variation might be due to the different origin/sources of major contributing ions along with the influence of variable river flow and small anthropogenic contributions. Furthermore, the spatial distribution maps for IWQI, EC, SSP, and TH during both seasons confirmed the influence of salinity from the sea; low-flow in the major river system was the driving factor of overall groundwater quality in the study area. These findings may contribute to management of irrigation and/or drinking water in regions with similar groundwater problems. 相似文献
This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation. 相似文献
Bangladesh is one of the topmost climate vulnerable countries in the world where the riverine island (char) dwellers are the most victims of climate change. Climate finance is perceived as the key instruments to address the issues related to climate change impacts and improve the livelihood resilience of the rural people. This article examines the role of climate finance governance at the vulnerable hazard-prone chars in Bangladesh. Climate finance adaptation governance has been assessed through measuring the climate service intervention, behavioral changes and impacts at the local level. The study reveals that the mechanism of climate finance in Bangladesh is good enough, but implementation is not satisfactory. It also observed that there is a lack of participatory governance for disaster management, and there is no direct contribution of climate finance governance in the village level which causes to fail the existing implementation strategy. The study suggests that a riverine island-based long-term development program should be implemented through ensuring effective monitoring system so that climate finance governance can contribute a lot and improve the food security and livelihood resilience of char dwellers.
