A Probabilistic Framework to Estimate Lake-Groundwater Interaction
Abstract
The interaction between lakes and groundwater (GW) has important implications to the quantity and quality of water in both environments. However, its quantification has been challenging in regions with limited in-situ data. The lake-GW interaction 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 first three methods, they require extensive field data that are costly to collect in large lakes. Instead, the lake water budget method requests data that can be obtained via ground synoptic stations and remote sensing data. Despite simplicity, the uncertainty associated with the input data and the estimated lake-GW interaction is still poorly understood. In this study, we employed a forward uncertainty propagation framework with Latin-Hypercube sampling to estimate the uncertainty of the lake-GW exchange. We implemented the above framework in the hypersaline Lake Urmia (LU), located in northwestern Iran, over five periods between September 2017 to May 2020. The results witnessed exchange of flow from groundwater to LU in all studied periods, ranging between 0.3 MCM/day and 9 MCM/day. Also, the share of the lake-GW interaction in the water budget varied between 3% and 37%. The results of the uncertainty analysis further demonstrated that the probability of LU being fed by GW is significant in the majority of the periods ranging from 99% to 65%.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.H55J0848C