Application of GIS for the identification and demarcation of selective heavy metal concentrations in the urban groundwater

Groundwater is the most appropriate and widely used source of drinking water, which is increasingly threatened by pollution from industrial and agricultural activities. To check the severity of the problem, 156 groundwater samples were collected from various depths (60-110 ft) of 52 different localities in Faisalabad city, the third largest metropolis in Pakistan, and analyzed for the metals (Zn, Cu, Cd, Ni, Pb, Mn and Fe) concentration in 2009. Quantification was done by using Flame Atomic Absorption Spectrophotometer technique and the results were compared with WHO standards for drinking water quality. Results showed that the levels of Cu, Mn and Fe were below the WHO standards while the concentrations of Zn, Cd, Ni and Pb were above the recommended levels of safe drinking water. Correlation analysis among the occurrence of these heavy metals revealed a highly significant and positive correlation of Mn with Zn and Fe. A significant and positive correlation of Cd was also found with Cu and groundwater depth showing that there is strong association between Cu-Cd pair and that the Cd concentration varies with depth of groundwater in the study area. Regional patterns of heavy metals occurrence were mapped using Geographical Information System (GIS) for the identification and demarcation of risk areas. The concentration maps may be used by policymakers of the city to mitigate groundwater pollution.     

Future change in the frequency of warm and cold spells over Pakistan simulated by the PRECIS regional climate model

Climate change caused by anthropogenic activities has generated a variety of research focusing on investigating the past climate, predicting the future climate and quantifying the change in climate extreme events by using different climate models. Climate extreme events are valuable to evaluate the potential impact of climate change on human activities, agriculture and economy and are also useful to monitor the climate change on global scale. Here, a Regional Climate Model (RCM) simulation is used to study the future variations in the temperature extreme indices, particularly change in frequency of warm and cold spells duration over Pakistan. The analyses are done on the basis of simulating two 30 years simulations with the Hadley Center’s RCM PRECIS, at a horizontal resolution of 50 km. Simulation for the period 1961–1990 represents the recent climate and simulation for the period 2071–2100 represents the future climate. These simulations are driven by lateral boundary conditions from HadAM3P GCM of Hadley centre UK. For the validation of model, observed mean, maximum and minimum temperatures for the period 1961–1990 at all the available stations in Pakistan are first averaged and are then compared with the PRECIS averaged grid-box data. Also the observed monthly gridded data set of Climate Research Unit (UK) data is used to validate the model. Temperature indices in the base period as well as in future are then calculated and the corresponding change is observed. Percentile based spatial change of temperature shows that in summer, increase in daily minimum temperature is more as compared to the increase of daily maximum temperature whereas in winter, the change in maximum temperature is high. The occurrence of annual cold spells shows significantly decreasing trend while for warm spells there is slight increasing trend over Pakistan.     

Geochemistry of the limestone of Mortas Formation and related terra rossa,Seydisehir, Konya,Turkey

The purpose of this study was to determine and evaluate the geochemical characteristics of the limestone of the Upper Cretaceous Mortas Formation and related terra rossa in a 50 km² area which is located 20 km south of the city of Seydisehir, Central Anatolia, by using data obtained from the ICP-MS analysis of randomly collected 42 samples of limestone and 18 samples of the terra rossa.The limestone of the Mortas Formation is composed of fossilliferous, gray-cream colored, medium to thick bedded, partially dolomitic carbonate rocks, and generally has dismicrite, intrapelmicrite composition. It includes the largest bauxite reservior in Turkey and has many occurences of terra rossa formation on it. According to mean distance, the Ba, Be, Hg, Mo, Nb, Sb and Th concentrations in the limestones overlying and underlying the bauxite deposits are different, but the main oxides, REE and other trace elements are same. In factor analysis, the first component reflects relative enrichment of clay against to CaO contents of the limestone, the second component corresponds to the degree of dolomitization. The PAAS-normalized REEs pattern for the Mortas Formation limestone samples illustrate similar main features as seawater.The terra rossa soils in the study area are considered to be highly weathered and weakly mature soil with respect to their generally low Al₂O₃ (21%), but high CaO (2%) contents, and their alteration indices. The element ratios in the terra rossa and limestone show that in the process of the transformation from limestone to terra rossa, Ba, Si, Ti, Al and Fe were enriched together by staying in-situ. Except Ce, all lanthanides show similar behavior, but the HREE, which were richer in limestone, were consumed fast relative to the LREE during soil formation. The association and the enrichment of Co, Cu, Cr, Ni and Pb as well as Ba, Zr, Ga, Nb and Rb in soil relative to the limestone are interpreted as being resulted from eolian transportation. Ca, Au, Hg, Sr, Se, Sb, Mo, Ag, U, Cd and Na were found to be the most mobile elements during pedogenic transformation. According to main oxide composition ratios of the limestone and terra rossa, the soils were described as representing a well washed soil completing the leaching and accumulation phase, but not totally completing the silicate weathering phase. In the processes of soil formation, 97.76% of the limestone was washed away; only 2.24% of limestone was deposited as soil. Therefore, 61 times mass reduction was realized.     

Near surface lithology and spatial variation of arsenic in the shallow groundwater: southeastern Bangladesh

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.     

Upscaling of the permeability by multiscale wavelet transformations and simulation of multiphase flows in heterogeneous porous media

We describe a new approach for simulation of multiphase flows through heterogeneous porous media, such as oil reservoirs. The method, which is based on the wavelet transformation of the spatial distribution of the single-phase permeabilities, incorporates in the upscaled computational grid all the relevant data on the permeability, porosity, and other important properties of a porous medium at all the length scales. The upscaling method generates a nonuniform computational grid which preserves the resolved structure of the geological model in the near-well zones as well as in the high-permeability sectors and upscales the rest of the geological model. As such, the method is a multiscale one that preserves all the important information across all the relevant length scales. Using a robust front-detection method which eliminates the numerical dispersion by a high-order total variation diminishing method (suitable for the type of nonuniform upscaled grid that we generate), we obtain highly accurate results with a greatly reduced computational cost. The speed-up in the computations is up to over three orders of magnitude, depending on the degree of heterogeneity of the model. To demonstrate the accuracy and efficiency of our methods, five distinct models (including one with fractures) of heterogeneous porous media are considered, and two-phase flows in the models are studied, with and without the capillary pressure.     

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.     

Study of the global and regional climatic impacts of ENSO magnitude using SPEEDY AGCM

ENSO is considered as a strong atmospheric teleconnection that has pronounced global and regional circulation effects. It modifies global monsoon system, especially, Asian and African monsoons. Previous studies suggest that both the frequency and magnitude of ENSO events have increased over the last few decades resulting in a need to study climatic impacts of ENSO magnitude both at global and regional scales. Hence, to better understand the impact of ENSO amplitude over the tropical and extratropical regions focussing on the Asian and African domains, ENSO sensitivity experiments are conducted using ICTPAGCM (‘SPEEDY’). It is anticipated that the tropical Pacific SST forcing will be enough to produce ENSO-induced teleconnection patterns; therefore, the model is forced using NINO3.4 regressed SST anomalies over the tropical Pacific only. SPEEDY reproduces the impact of ENSO over the Pacific, North and South America and African regions very well. However, it underestimates ENSO teleconnection patterns and associated changes over South Asia, particularly in the Indian region, which suggests that the tropical Pacific SST forcing is not sufficient to represent ENSO-induced teleconnection patterns over South Asia. Therefore, SST forcing over the tropical Indian Ocean together with air–sea coupling is also required for better representation of ENSO-induced changes in these regions. Moreover, results obtained by this pacemaker experiment show that ENSO impacts are relatively stronger over the Inter-Tropical Convergence Zone (ITCZ) compared to extratropics and high latitude regions. The positive phase of ENSO causes weakening in rainfall activity over African tropical rain belt, parts of South and Southeast Asia, whereas, the La Niña phase produces more rain over these regions during the summer season. Model results further reveal that ENSO magnitude has a stronger impact over African Sahel and South Asia, especially over the Indian region because of its significant impact over the tropical Atlantic and the Indian Ocean through Walker circulation. ENSO-induced negative (positive) NAO-like response and associated changes over Southern Europe and North Africa get significantly strong following increased intensity of El Niño (La Niña) in the northern (southern) hemisphere in the boreal winter (summer) season. We further find that ENSO magnitude significantly impacts Hadley and Walker circulations. The positive phase of ENSO (El Niño) overall strengthens Hadley cell and a reverse is true for the La Niña phase. ENSO-induced strengthening and weakening of Hadley cell induces significant impact over South Asian and African ITCZ convective regions through modification of ITCZ/monsoon circulation system.