Quantifying the uncertainty of lake-groundwater interaction using the forward uncertainty propagation framework: The case of Lake Urmia

Abstract

The interaction between a lake and groundwater has important implications to the quantity and quality of water in both environments. Quantification of lake-groundwater interaction (LGI) has been challenging in regions with limited in-situ data. LGI can be quantified by physically-based models, direct measurement of seepage, measurements of conservative chemical or isotopic tracers, and lake water balance. Despite the accuracy of the methods based on hydrochemical or isotopic measurements and analysis, they require extensive field data that are costly to collect in large lakes. Instead, the data required to quantify LGI by the lake water budget method can be obtained via typical ground measurements and satellite remote sensing. However, the influence on the estimated LGI imposed by the uncertainty associated with the other components of lake water budget (e.g., precipitation, evaporation, and inflow/outflow) is still poorly understood. In this study, we coupled a forward uncertainty propagation framework with the lake water budget to estimate the uncertainty of LGI using Latin-Hypercube sampling. We implemented the above framework in the hypersaline Lake Urmia (LU), located in the northwestern Iran, over five consecutive study periods between September 2017 and May 2020. The results revealed the exchange of flow from groundwater to the LU in all studied periods, ranging between 0.2 million cubic meters (MCM)/day and 7.6 MCM/day. The relative contribution of LGI in the water budget varied between 3% and 37%. The results of the uncertainty analysis further demonstrated that the cumulative probability of LGI < 0, which indicates flow direction from the LU to groundwater, was insignificant in all the study periods ranging between 0.001 and 0.35.