Understanding the extent of interactions between groundwater and surface water through major ion chemistry and multivariate statistical techniques

Abstract

Abstract The present work examines the possible use of major ion chemistry and multivariate statistical techniques as a rapid and relatively cost‐effective method of identifying the extent of groundwater and surface water (GW–SW) interaction in an urban setting. The original hydrogeochemical dataset consists of groundwater ( n = 114), stream water ( n = 42) and drain water ( n = 24) samples, collected twice in a year for the pre‐ and post‐monsoon seasons, for three successive years along an 8 km reach of the Delhi segment of River Yamuna, India. The dynamic and similar seasonal changes of hydro‐geochemical facies and major ion trends of river, drain and groundwater samples indicate the existence of an empirical relationship between GW and SW. Results of both R‐ and Q‐mode factor and cluster analyses highlight multi‐scale control of the fluid exchange distributions, with distinct seasonal alteration in mode and extent of GW–SW interaction, namely, the influence of the mixing zones between urban river and groundwater and the pattern of groundwater flow through the river bed. Hierarchical cluster analysis (HCA) of sampling locations efficiently illustrates different groups that comprise samples severely influenced by contaminated surface water downstream and the upstream fresh water samples. These results substantiate the strong exchange processes between GW and SW all along the stretch. The study shows that the combination of an empirical and statistical relationship between different ionic species and sampling locations can provide greater confidence in identifying the extent of GW–SW interaction/exchange processes. Copyright © 2008 John Wiley & Sons, Ltd.