Regional groundwater flow modelling of Upper Chaj Doab of Indus Basin, Pakistan using finite element model (Feflow) and geoinformatics

A 3-D finite element model (Feflow) has been used for regional groundwater flow modelling of Upper Chaj Doab in Indus Basin, Pakistan. The thematic layers of soils, landuse, hydrology, infrastructure and climate were developed using Geographic Information System (GIS). The numerical groundwater flow model is developed to configure the groundwater equipotential surface, hydraulic head gradient and estimation of the groundwater budget of the aquifer. Integration of GIS with groundwater modelling and satellite remote sensing capabilities has provided an efficient way of analysing and monitoring groundwater status and its associated land conditions. The Arcview GIS software is used as additive tool to develop supportive data for numerical groundwater modelling, integration and presentation of image processing and modelling results.
The groundwater behaviour of the regional model shows a gradual decline in watertable from year 1999 onward. The persistent dry condition and high withdrawal rates play an influential role in lowering down the groundwater levels. Different scenarios were developed to study the impact of extreme climatic conditions (drought/flood) and variable groundwater abstraction on the regional groundwater system. The results of the study provide useful information regarding the behaviour of aquifer in order to organize management schemes on local and regional basis to monitor future groundwater development in the area.     

Flooding and its relationship with land cover change,population growth,and road density

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.     

Temporal changes in trace elements in brown soil and soybean after long-term fertilization

In agricultural production, specific elements in soil and plants are very important for the soil quality and plant productivity. Trace elements and rare earth elements enter in agri-environment by the application of fertilizers and, through anthropogenic activities, pose important health impacts even at low concentration due to non-biodegradable nature with long half-life. The micro nutrients are essential for human body in a quantity most of less than 100 mg/day. The nutritional element uptake by plants is regulated by availability of the required elements and element accumulation ability of the plants. Therefore, this study was aimed to investigate the accumulation of trace and rare earth elements after long-term application of different fertilizers in soil and soybean uptake. The inorganic fertilizers (NKP) and pig manure were applied to maize-maize-soybean rotation in Alfisols (brown) soil since 1979. Atomic emission spectrometry along with inductively coupled plasma technique was applied to determine trace and rare earth elements. The accumulation pattern of trace elements (TEs) observed in soil was Ni > Co > Se > Mo and rare earth elements (REEs) was found as La > Nd > Tb > Y > Pr > Gd > Er > Yb > Lu. In soybean stem, the TE and REE concentrations were Se > Ni > Co > Mo and Pr > Gd > Er > Yb > Tb > Nd > Lu > La > Y, respectively. Elemental concentrations in the seed samples were Ni > Se > Mo > Co and Pr > Gd > Er > Yb > Tb > Nd > Lu > Y > La. The seed of soybean accumulated Co, Mo, Ni, Gd, Pr, Er, Lu, and Tb more than the stem. Higher concentrations of Se, Nd, Y, and Yb were found in soil. These elements were higher in soybean stem followed by the seed. However, these elements are within safe toxic level and light pollution level.     

Evaluation of arid and semi-arid ecotypes of guar (Cyamopsis tetragonoloba L.) for salinity (NaCl) tolerance

The germplasm of 15 guar (Cyamopsis tetragonoloba L.) ecotypes was collected from different stressed ecozones of Pakistan to study the morphogenetic parameters under various levels of salt stress. The experiment was laid out in completely randomized design with three repeats and three treatments, i.e. 3, 9 and 15 dS m⁻¹ in 135 pots lined with polythene bags. The results showed that salt stress had considerable effect on plant height, root length, roof fresh and dry weights, shoot fresh and dry weights and seed yield per plant. However, ecotype/accession 281/3 and 239/2 performed better than others at higher salinity levels.     

Influence of water stress and exogenous glycinebetaine on sunflower achene weight and oil percentage

The study was carried out to assess whether exogenously applied glycinebtaine has any role in reducing the adverse effects of water stress on sunflower achene yield and oil contents. Two sunflower lines, Gulshan-98 and Suncross were subjected to water stress at the vegetative and reproductive stages of plant growth. Three levels of glycinebtaine (0, 50 and 100 mM) were applied before sowing (seed treatment) and at the time of initiation of stress at the vegetative and reproductive stages. A marked adverse effect of water stress on 100-achene weight and achene oil contents were observed in both sunflower lines. Exogenous supply of glycinebtaine was not effective in alleviating the adverse effects of water stress on achene oil percentage. Foliar spray of glycinebtaine, however, significantly reduced the negative effects of water stress on achene weight. Seed treatment with either level of glycinebtaine was not effective in increasing the 100-achene weight and achene oil percentage under both normally irrigated and water stress conditions. The sunflower line, Suncross produced higher oil yield than that of Gulshan-98.     

Two-dimensional development of the dynamic coupled consolidation scaled boundary finite-element method for fully saturated soils

The scaled boundary finite-element method is a powerful tool used to analyse far-field boundary soil–structure interaction problems. In this paper, the method is extended to include Biot's coupled consolidation in order to deal with fully saturated soil as a two-phase medium. The advantages of this method are explained in this paper. The detailed formulation considers the general two-dimensional (2D) analysis case, accounting for body forces and surface tractions in both bounded and unbounded media.     

STUDY OF MORPHOLOGICAL CHANGE OF THE KUSHIYARA AND MONU RIVERS BY REMOTE SENSING

The Kushiyara and Monu rivers are two of the major river systems in the northeast region of Bangladesh. Analyzing satellite images of the Kushiyara and Monu rivers between 1990 and 1997, it was found that significant changes occurred at five distinct locations; i.e., Ahmadpur, Monumukh, Raysrr, Kaprangibari and Telibil. The amount of change was measured as 168.34 ha by using a plani-meter. Transportation of sediment was the major contributing factor of morphological change. The total average sediment concentration of Kushiyara and Monu rivers was found to be 16889.6 ppm per year during the study period by applying the Engelund and Hansen equation approach. Protection work has been suggested at the vulnerable locations.     

Geochemical assessment of Paleocene limestones of Sinn El-Kaddab Plateau,South Western Desert of Egypt,for industrial uses

The present work assesses the potential industrial uses of Paleocene limestone deposits, Garra Formation in Sinn El-Kaddab Plateau, South Western Desert of Egypt, based on their mineralogy and geochemical characteristics. Eighty-six limestone samples collected from ten stratigraphic columnar sections were analyzed using X-ray diffraction (XRD) and X-ray fluorescence (XRF) techniques. Petrographically, Garra limestone deposits consist dominantly of benthic foraminiferal wackestone and packstone microfacies. The XRD data revealed dominance of low-Mg calcite as essential carbonate mineral in the studied limestone. The bulk rock XRF results revealed CaO (29.28–55.75%) with an average of 52.74%. The CaO exhibits a strong negative correlation with MgO, SiO₂, TiO₂, Al₂O₃, and moderate negative correlation with Fe₂O₃ which indicates that the contribution of these elements is mainly due to detrital input. On the other hand, Al₂O₃ and Na₂O contents exhibit significant negative correlation with loss of ignition (LOI) wt% indicating their incorporation within terrigenous matrix. The average Sr content attains 1297 ppm indicating deposition in temperate marine environment. The average molar CaCO₃% values of bulk samples have been computed for individual columnar sections to determine the purity status of Garra limestone deposits. They range from impure (CaCO₃%?=?79.92%) to high-pure (CaCO₃%?=?97.76%) limestone. Therefore, Garra limestone deposits have extremely valuable uses in a wide spectrum of industrial applications including Portland cement, steel, ceramics, whiting, chemical uses, paper, and feed stuff.     

Prediction of river bank erosion and protection works in a reach of Chenab River,Pakistan

The impacts of floods on river bank erosion are generally significant in the alluvial river reaches. This paper presents the prediction of the river bank erosion along the right bank in the reach of Chenab River (starting from downstream of Marala Barrage) where excessive erosion had been reported. The bank erosion is predicted due to flow/flood events of 2010 by coupling the output from the two-dimensional numerical model to the excess shear stress approach. The predicted bank erosion was compared with the one estimated from Landsat images. The Landsat ETM+ images were processed in the ArcGIS software to assess the external bank erosion. The results show that the excess shear stress approach underpredicts the bank erosion. Therefore, the erodibility coefficient was modified by forcing the best agreement between predicted and estimated (i.e., from Landsat images) bank erosion which was used for further analysis. The results reveal that coupling the output from the numerical model to the excess shear stress approach (by modifying the erodibility coefficient) predicts the river bank erosion with a reasonable level of accuracy, thus helpful to identify the locations for the protection works. The predicted river bank erosion presents good coefficient of determination (R²) of 0.82 when compared with the estimated bank erosion from Landsat images. The findings of the present study will help to implement the river protection works at the identified locations in the selected reach of River Chenab and will also act as a guideline for similar river reaches.     

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

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.