PRELIMINARYATTEMPTS TOWARDS ARSENIC RISK MAPPING AND ASSESSMENT OF RIVER-AQUIFER-SEDIMENT INTERACTION DYNAMICS

Abstract

Environmental exposure to arsenic and its detrimental health effects have turned out to be progressively evident over the most recent couple of years. Arsenic contamination in groundwater is of expanding concern in view of its toxicity and widespread occurrence and is presently a worldwide epidemic. Contamination has been found in Argentina, Mexico, Chile, China, Vietnam, Hungary, Bangladesh and India. In India, the issue of arsenic emerges due to an awful blend of 3 factors: an arsenic source present in the aquifer, its mobilization and intrusion into the ground water & the utilization of arsenic-rich water for drinking purposes. Central Ground Water Board (CGWB) investigated and revealed that West Bengal, Assam, Bihar, Uttar Pradesh, Chhatisgarh, Jharkhand and Manipur are being affected by arsenic contamination (> 0.05 mg/L). Assessment can be done by analytic studies on samples collected at the site under consideration and other secondary factors which have an indirect impact on the infestation and increase in the concentration of arsenic. Usage of secondary data by reviewing and analyzing it, has proved to provide a cost-effective way of conducting cross-locale correlations, comprehending conditions which are specific to districts, to ascertain the trends, and portraying the present circumstance. It is to complement the primary data collection. Availability of this information in a scattered manner makes interpretation cumbersome for a user. Having an information system for Arsenic in the form of Risk/Hazard maps, would, however, help the government bodies, researchers, Non Governmental Organizations and volunteers to identify the severity of the As-crisis and also help to implement better planning and management of As-affected areas. An attempt has been made to prepare a framework for the database component of the proposed risk-map-based information system for arsenic in the state of Uttar Pradesh, India. With the combination of different secondary attributes with primary data, a comprehensive database can be prepared. Quantitative hazard mapping can be done by screening and inputting primary and secondary data, with the help of different geo-statistical models. PRELIMINARY ATTEMPTS TOWARDS ARSENIC RISK MAPPING AND ASSESSMENT OF RIVER-AQUIFER-SEDIMENT INTERACTION DYNAMICS ix Many co-variates can be utilized to fulfill this objective, few of them being subsurface geology, population, ground water abstraction volumes, water supply sources, water quality and extreme events (floods and droughts). Preliminarily mapping of state of the art arsenic concentrations in all districts of UP was done which showed maximum concentrations in districts with Himalayan rivers/tributaries and progression of infestation from east towards west in the upper districts. Charts and graphs can be prepared to depict the chronology of the dependence of arsenic concentration on the additional attributes. For the interaction study, samples of Ganga river water, nearby shallow and deep ground water, river bed sediments and bank sediments were collected during the low flow period (March-April) from the monitoring locations at Uttarakhand - Rishikesh, Haridwar, Uttar Pradesh - Garhmukteshwar, Kanpur, Varanasi and Ballia symbolizing Upper and Middle Ganga river reaches. The following parameters were determined : Temperature, pH, EC, DO, TDS, TOC, cations (Na+, K+, Ca2+, Mg2+), anions (F-, Cl-, NO3 -, SO4 2-, SiO4 2-, PO4 3-), total dissolved arsenic, iron and manganese. Water quality data was collected and assembled to : 1. Provide information to more fully comprehend the extent, magnitude, and source of arsenic in ground water along the Ganges; 2. Compute the mechanisms that control arsenic concentrations; and 3. Assess the effect of river sediment on arsenic concentrations. Correlation analyses were done using Pearson’s statistical tool using Intelluctus Statistics Analyzer, to understand the influence of groundwater chemistry on arsenic contamination. Factor analysis and ANOVA were done using SPSS Statistics 24, to find out the dominating factors governing the groundwater chemistry, and spatial variability of arsenic concentrations along the stretch covered in the study, respectively. The correlations and factors were comprehensively analyzed to throw light on the interaction dynamics