Interaction of lake-groundwater levels using cross-correlation analysis: A case study of Lake Urmia Basin, Iran

Abstract

Lake Urmia (LU) is the second largest hypersaline lake in the world. Lake Urmia's water level has dropped drastically from 1277.85 m to 1270.08 m a.s.l (equal to 7.77 m) during the last 20 years, equivalent to a loss of 70% of the lake area. The likelihood of lake-groundwater connection on the basin-scale is uncertain and understudied because of lack of basic data and precise information required for physically-based modeling. In this study, cross-correlation analysis is applied on a various time-frames of water level of the lake and groundwater levels (2001–2018) recorded in 797 observation wells across 17 adjacent aquifers. This provides insightful information on the lake-groundwater interaction. The cross-correlation coefficient between the monthly water level of lake and observations wells (rGW−L) and the difference of these two variables (Hf) was calculated for different time-frames. The values of rGW−L (ranged −0.69 to 0.97) and Hf (ranged −53 m to 293 m) indicated the significant role of time-frames of observed dataset on dynamic behavior of lake-groundwater interaction, and exchange fluxes in the study setting. Results suggested two opposing behaviors in lake-groundwater interaction of the study system mainly arise from anthropogenic activity (overexploitation of groundwater for irrigation) and aquifer type (unconfined/pressurized): three out of 17 adjacent aquifers are feeding by the LU and act as “gaining aquifers” (located in northern half of LU) and others discharging into the LU and act as “losing aquifers”. This study aimed to provide easy-to-obtain insights into LGWI in the complex setting of LU Basin. It can be considered a preliminary step towards a deeper understanding of the interaction through physically-based analysis and modeling.