Hydrologic control of temporal variability in groundwater arsenic on the Ganges floodplain of Nepal

Autor: L. S. Smith, Tom H. Brikowski, A. Neku, Suresh Das Shrestha
Rok vydání: 2014
Předmět:
Zdroj: Journal of Hydrology. 518:342-353
ISSN: 0022-1694
DOI: 10.1016/j.jhydrol.2013.09.021
Popis: Elevated arsenic in groundwater affects some 100 million people in South Asia, yet mitigation efforts are hindered by persistent uncertainty about the proximal source of arsenic and mechanisms for its mobilization. At the core of this uncertainty are the relative roles of surficial organic clays vs. deeper aquifer matrix iron oxyhydroxides. Temporal variations in groundwater chemistry can serve to distinguish the contributions of these two sources, and such variation is especially pronounced in headwater areas of the Ganges floodplain immediately adjacent to the Himalayan foothills (e.g. the Terai of Nepal). Tubewells down to 50 m in the Terai commonly exhibit cyclical, temporally-correlated variation in dissolved arsenic, iron and other species. In Nawalparasi, the most arsenic-affected district, these wells tap thin (2 m) gray sand aquifers embedded in a thick (>50 m) sequence of organic clays. Monsoon recharge refreshes these aquifers, temporarily minimizing arsenic concentrations. Post-monsoon, average groundwater compositions exhibit increasing trends in water–rock interaction (higher TDS, with cation exchange to form increasingly Na–HCO 3 waters), arsenic and iron. This cycle can be repeated during dry-season precipitation events as well, revealing direct correlation between trends in degree of clay interaction (sodium fraction of major cations) and arsenic concentrations. During the year, reversals in vertical head gradient yield reversals in arsenic temporal trend, and downward gradients in the dry season correlate with increases in arsenic. Collectively these observations strongly support a model of reductive mobilization of arsenic from adjacent clays into aquifers, tempered by repeated flushing during periods of appreciable rainfall.
Databáze: OpenAIRE