Regional-scale identification of groundwater-surface water interaction using hydrochemistry and multivariate statistical methods, Wairarapa Valley, New Zealand

Abstract

Abstract. Identifying areas of interaction between groundwater and surface water is crucial for effective environmental management, because this interaction is known to influence water quantity and quality. This paper applies hydrochemistry and multivariate statistics to identify locations and mechanisms of groundwater-surface water interaction in the pastorally dominated Wairarapa Valley, New Zealand. Hierarchical Cluster Analysis (HCA) and Principal Components Analysis (PCA) were conducted using site-specific median values of Ca, Mg, Na, K, HCO3, Cl, SO4 and electrical conductivity from 22 surface water sites and 246 groundwater sites. Surface water and groundwater monitoring sites were grouped together in three of the seven clusters identified by HCA, with the inference made that similarities in hydrochemistry indicate groundwater-surface water interaction. PCA indicated that the clusters were largely differentiated by total dissolved solids concentration, redox condition and ratio of major ions. Shallow aerobic groundwaters, located in close proximity to losing reaches of rivers, were grouped with similar Ca-HCO3 type surface waters, indicating potential recharge to aquifers from these river systems. Groundwaters that displayed a rainfall-recharged chemical signature with higher Na relative to Ca, higher Cl relative to HCO3 and an accumulation of NO3 were grouped with neighbouring surface waters, suggesting the provision of groundwater base flow to these river systems and the transfer of this chemical signature from underlying aquifers. The hydrochemical techniques used in this study did not reveal groundwater-surface water interaction in some parts of the study area, specifically where deep anoxic groundwaters, high in total dissolved solids with a distinct Na-Cl signature, showed no apparent link to surface water. The drivers of hydrochemistry inferred from HCA and PCA are consistent with previous measurements of 18O, water age and excess air. Overall, this study has shown that multivariate statistics can be used as a rapid method to identify groundwater-surface water interaction at a regional scale using existing hydrochemical datasets.