Neha Singh

Geochemical modelling, ionic ratio and GIS based mapping of groundwater salinity and assessment of governing processes in Northern Gujarat, India

In semi-arid/arid regions, groundwater is the major source of irrigation, drinking and industrial requirements, water salinity and shortage are major problems of concern. North Gujarat, India, is one such area where highly saline groundwater is generally ascribed to rapid increase of population, agriculture and industries induced decline in water table by unplanned abstraction of groundwater. However, no effort has been made to discriminate the natural and anthropogenic influences on groundwater salinity. In this brief background, the present study attempts to identify the factors and processes controlling the groundwater salinity in the area, based on ionic ratios in integration with various graphical methods, saturation indices and geographical information system. Na+/Ca2+ > 1 indicates the deficiency of Ca2+ possibly due to CaCO3 precipitation or ion exchange process. Na+/Cl− > 1 and \( {\text{SO}}_{4}{}^{2 - } /{\text{Cl}}^{ - } \gg 0.05 \) suggest salinization is mainly due to wastewater infiltration and/or due to irrigation water return flow. Sea water intrusion in coastal parts, vertical and lateral mixing of water and anthropogenic inputs are also responsible for salinization of groundwater. USSL diagram, Na%, sodium adsorption ratio, residual sodium carbonate and magnesium hazard indicate unsuitability of groundwater for irrigation purposes. To prevent groundwater salinization, appropriate measures need to be taken to control further indiscriminate exploitation of groundwater for irrigation.

Assessment of hydrogeochemistry and the quality of groundwater in 24-Parganas districts, West Bengal

AbstractHydrogeochemistry of an area helps in understanding the geological processes which control the chemistry of water and play an important role in determining the suitability of groundwater for various purposes. In the present study, an attempt has been made to understand the geological processes controlling the quality of water in a part of North and South 24-Parganas districts of West Bengal. 39 representative groundwater samples were collected from the study area and physico-chemical parameters were analyzed for all the samples. Schoeller and Durov diagram were used to understand the hydrochemical nature of water. Results obtained from water chemistry were used in the interpretation of controlling processes using different conventional graphs, and determining the quality of groundwater. Silicate weathering and ion exchange are the dominant processes controlling the chemistry of groundwater in the study area, where calcium and magnesium in the water are replaced by the sodium and potassium in the minerals from the host rock as chloro-alkaline indices are negative at most of the places. Saturation index was calculated to understand the mineralogy of the subsurface. The groundwater is oversaturated with iron containing minerals like Fe(OH)3, goethite, and hematite, while undersaturated with anhydrite and gypsum. The groundwater suitability was determined by calculating water quality index for drinking purpose; while SAR, and residual sodium carbonate indices for the agricultural purpose. The groundwater in the study area is not suitable for drinking, but can be used for other household use and in irrigation for agriculture.

Distributed Query Plan Generation Using Firefly Algorithm

A large number of queries are posed daily against the distributed databases spread across the globe. Query processing strategies are used to generate efficient query plans for these queries. The number of such query plans increases exponentially with the increase in the number of involved sites and relations accessed by the query. Further, this complexity increases if the data is fragmented and replicated across multiple sites. This problem, referred to as the distributed query plan generation DQPG problem, is a combinatorial optimization problem. An attempt has been made in this paper to solve this DQPG problem using the Firefly Algorithm FA, which is inspired by the flashing behaviour of fireflies in nature. The proposed FA based DQPG algorithm DQPGFA, aims to generate distributed query plans incurring minimum Query Proximity Cost QPC value. The experimental results show that DQPGFA, in comparison to the GA based DQPG algorithm DQPGGA, was able to select Top-K query plans that had a comparatively lesser average QPC value. Such generated query plans would, most likely, lead to an improvement in the query response time and thereby would result in effective and efficient decision making.

Distributed Query Plan Generation using Bacterial Foraging Optimization

In distributed database systems, relations are replicated and fragmented at multiple sites to ensure easy availability and greater reliability. This leads to an exponential increase in the possible alternatives available for selecting the set of sites, constituting a query plan, for processing. Computing the optimal query plans, from amongst all possible query plans, is a discrete combinatorial optimization problem. This Distributed Query Plan Generation (DQPG) problem has been addressed using Bacterial Foraging Optimization (BFO) in this paper. Here, a novel BFO based DQPG algorithm (DQPGBFO), which generates the Top-K distributed query plans having the minimum total query processing cost, has been proposed. Experimental comparison of DQPGBFO with the existing Genetic Algorithm (GA) based DQPG algorithm (DQPGGA) shows that the former is able to generate Top-K query plans that have a comparatively lower total cost of processing a distributed query. This, in turn, leads to a reduction in the query response time and thus aids in decision making.