Integrated approach for identification of potential groundwater zones in Seethanagaram Mandal of Vizianagaram District,Andhra Pradesh,India

Identifying a good site for groundwater exploration in hard rock terrain is a challenging task. In hard rocks, groundwater occurs in secondary porosity developed due to weathering, fracturing, faulting, etc., which is highly variable within short distance and contributing to near-surface inhomogeneity. In such situations topographic, hydrogeological and geomorphological features provide useful clues for the selection of suitable sites. Initially, based on satellite imagery, topographical, geomorphological and hydrogeological features, an area of about 149 km² was demarcated as a promising zone for groundwater exploration in the hard rock tract of Seethanagaram Mandal, Vizianagaram District, Andhra Pradesh, India. A total of 50 Vertical Electrical Soundings (VES) were carried out using Wenner electrode configuration. An interactive interpretation of the VES data sharpened the information inferred from geomorphological and hydrogeological reconnaissance. Ten sites were recommended for drilling. Drilling with Down-The-Hole Hammer (DTH) was carried out at the recommended sites down to 50 to 70 m depths. The interpreted VES results matched well with the drilled bore well lithologs. The yields of bore wells vary from 900 to 9000 liters per hour (lph).     

Deciphering potential groundwater zone in hard rock through the application of GIS

Remote Sensing and Geographic Information System has become one of the leading tools in the field of hydrogeological science, which helps in assessing, monitoring and conserving groundwater resources. It allows manipulation and analysis of individual layer of spatial data. It is used for analysing and modelling the interrelationship between the layers. This paper mainly deals with the integrated approach of Remote Sensing and geographical information system (GIS) to delineate groundwater potential zones in hard rock terrain. The remotely sensed data at the scale of 1:50,000 and topographical information from available maps, have been used for the preparation of ground water prospective map by integrating geology, geomorphology, slope, drainage-density and lineaments map of the study area. Further, the data on yield of aquifer, as observed from existing bore wells in the area, has been used to validate the groundwater potential map. The final result depicts the favourable prospective zones in the study area and can be helpful in better planning and management of groundwater resources especially in hard rock terrains.     

Rice is a major exposure route for arsenic in Chakdaha block,Nadia district,West Bengal,India: A probabilistic risk assessment

The importance or otherwise of rice as an exposure pathway for As ingestion by people living in Bengal and other areas impacted by hazardous As-bearing groundwaters is currently a matter of some debate. Here this issue is addressed by determining the overall increased cancer risk due to ingestion of rice in an As-impacted district of West Bengal. Human target cancer health risks have been estimated through the intake of As-bearing rice by using combined field, laboratory and computational methods. Monte Carlo simulations were run following fitting of model probability curves to measured distributions of (i) As concentration in rice and drinking water and (ii) inorganic As content of rice and fitting distributions to published data on (i) ingestion rates and (ii) body weight and point estimates on bioconcentration factors, exposure duration and other input variables. The distribution of As in drinking water was found to be substantially lower than that reported by previous authors for As in tube wells in the same area, indicating that the use of tube well water as a proxy for drinking water is likely to result in human health risks being somewhat overestimated. The calculated median increased lifetime cancer risk due to cooked rice intake was 7.62 × 10⁻⁴, higher than the 10⁻⁴–10⁻⁶ range typically used by the USEPA as a threshold to guide determination of regulatory values and similar to the equivalent risk from water intake. The median total risk from combined rice and water intake was 1.48 × 10⁻³. The contributions to this median risk from drinking water, rice and cooking of rice were found to be 48%, 44% and 8%, respectively. Thus, rice is a major potential source of As exposure in the As-affected study areas in West Bengal and the most important exposure pathway for groups exposed to low or no As in drinking water.     

Electrical analogy for modelling thermal regime and moisture distribution in sandy soils

The soil mass is subjected to temperature variation due to several human activities (viz. tanks storing heated fluids, buried cables and pipelines, air-conditioning ducts, disposal of nuclear and thermal power plant wastes etc.), which result in heat-induced migration of the moisture in it. Though several studies have been conducted in the past to investigate the mechanism of heat migration through the soil mass, a methodology for ‘real-time measurement of the variations in temperature, flux and moving moisture front, in tandem, with respect to space' has rarely been attempted. In this context, extensive laboratory investigations were conducted to measure real-time flux and temperature variations in the sandy soils, and the validation of results has been done by employing an equivalent electrical circuit programme, LTspice. Subsequently, a mathematical model PHITMDS (i.e. Prediction of Heat-Induced Temperature and Moisture Distribution in Soil) has been developed and its utility and efficacy, for predicting the depth-wise temperature and heat-induced moisture migration, due to evaporation, in terms of position of moving moisture front in the sandy soil has been critically discussed and demonstrated.     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

A comparative study of soil erosion modelling by MMF,USLE and RUSLE

The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area.     

Ecological model analysis of respiratory health risk factors by ambient air pollution in Lucknow,the capital City of Uttar Pradesh,India

Ambient air pollution, particularly in the urban environment of developing countries, has turned out to be a major health risk factor. We explore the compounded impact of age sensitivity, exposure, poverty, co-morbidity, etc., along with composite air pollution in determining morbidity and health burden of people in Lucknow, India. This cross-sectional study is confined to analyse respiratory health status across different socio-economic and geographic locations using n = 140 in-depth questionnaire method. We used mean daily ambient air pollution data of PM₁₀, PM_2.5, SO_2, and NO₂ for the 2008–2018 period. We used the ecological model framework to assess the risk at different hierarchical levels and compounded severity on a spatial scale. We also used Logistic regression model with log odds and odds ratio to analyze the association of risks outcomes with composite air pollution scores calculated using the principal component analysis method. There is a strong association of location-specific respiratory disease prevalence with an overall 32 percent prevalence. The prevalence of ecological model 1 (individual domain) is 4.3 percent, while ecological model 2 (community domain) has the highest prevalence at 32.4 percent. The logistic regression model shows that respiratory disease load is positively associated with age sensitivity (P < .001) and composite pollution level (P < .001). For another model with suffocation as the outcome variable, composite pollution level (P < .001) and exposure (P < .001) are positively associated. Optimum interventions are required at Ecological models 1, 2, and 3 levels for better respiratory health outcomes.

     

尼泊尔低喜马拉雅推覆带油源对比及油气成藏

尼泊尔低喜马拉雅推覆带油气苗来源不清极大地影响了该区油气勘探.在地质-地球物理综合调查的基础上,利用油气地球化学、碳同位素及生烃史模拟对尼泊尔代莱克地区油源和成藏过程进行了研究.结果表明:①尼泊尔代莱克地区油苗产于Padukasthan断裂,可分两期,第一期呈含油断层泥产出,氯仿沥青"A"为149～231 μg/g,RR.为0.81％,氯仿沥青"A"的δ13C相对较重(-26.24‰～-27.10‰),族组分具有正碳同位素序列,发黄绿色荧光,为典型的低熟煤成油,第二期呈液态油产出并遭受微生物降解,金刚烷IMD指数为0.33～0.45,R.为1.24％～1.53％,3,4-DMD含量46％～47％,全油δ13C为-29.50‰～-29.45‰,族组分碳同位素趋于一致,发蓝色荧光,为海相成因高熟油;②第一期油来源于Surkhet群的Melpani组和Gondwana群煤系烃源岩,为Ⅲ型有机质低熟阶段的产物,第二期来源于Surkhet群的Swat组浅海陆棚相黑色页岩,为Ⅱ1型有机质生油高峰的产物,两期油与Lakharpata群过成熟黑色泥岩和Siwalik群未熟泥岩没有亲缘关系;③尼泊尔低喜马拉雅推覆带具有"多源多期、推覆增熟、砂体控储、披覆控聚"的油气成藏模式,油气成藏过程可划分为沉积浅埋、构造圈闭形成、深埋油藏形成、气藏形成和晚期改造定型5个演化阶段;④尼泊尔低喜马拉雅推覆有利于Gondwana群、Surkhet群深埋增温、持续快速生烃和晚期成藏,对比邻区巴基斯坦的含油气盆地,尼泊尔低喜马拉雅推覆带及相邻类似地区具备良好的油气成藏条件.