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Impact of lake basin morphometry and mixing on Arctic lake water isotope composition

Mahar, Isabelle F 1 ; Cluett, Allison 2 ; Thomas, Elizabeth 3

1 Barnard College, Columbia University
2 University at Buffalo
3 University at Buffalo

Lake water isotope proxies are used to infer past climate changes. However, among modern lakes within a single region experiencing the same climate, summer lake water isotope compositions vary strongly. We previously hypothesized that this difference in isotope composition was due to differences in lake summer residence time, which, in lakes with similar catchment sizes, is controlled largely by lake volume (Cluett & Thomas, 2020). We use sensitivity tests of idealized lake basins in the PRYSM lake water environment model (Dee, et al., 2018; Morrill et al., 2019) to test this hypothesis. Furthermore, we assess whether changing morphological parameters of a lake basin, including volume, surface area, and geometry, changes the average summer isotope composition, the signal recorded by many proxies.

We ran 19 simulations of the PRYSM model, holding climate and precipitation isotope forcings constant between runs. We used 39 years of climate data at daily resolution from the ERA-Interim Reanalysis dataset, and tuned the model parameters to match observations in a small lake on western Greenland. The only parameters that we changed between simulations were lake volume, surface area, and geometry. We focused simulations on two simplified lake geometries: rectangular prisms and cones. For the rectangular prisms, we held the volume constant but changed surface area and depth. Then, we ran several sensitivity tests with cones, in which we held one variable (e.g., volume) constant, but changed other variables (e.g., surface area and depth). Using the constant-volume simulations with rectangular prisms and the full suite of simulations with cones, we can assess whether summer lake water isotope composition changes with any individual morphometric parameter.

We find that surface area impacts average summer surface water isotope composition more strongly than volume. Lakes with the same surface area but different volumes have very similar summer isotope compositions. On the other hand, lakes with the same volume but different surface area have different summer isotope compositions: lakes with large surface areas tend to be depleted compared to lakes with small surface areas. We then examine the processes causing these observed differences in our simulations. Prior to isothermal mixing, large-surface-area lakes retain more isotopically depleted runoff during the spring melt period in the surface layer than the small-surface-area lakes. This is significant because when the large-surface-area lakes mix vertically following the spring melt period, the depleted surface water mixes through the entire lake. Consequently, these lakes more effectively incorporate spring melt into the water column and the lake water remains relatively depleted throughout the rest of the ice-free season. Small-surface-area lakes retain a smaller volume of spring runoff in the surface layer, and a greater proportion of the spring melt is flushed out of the lake basin. When these lakes then mix vertically, only a small amount of depleted surface water is mixed through the entire lake, and the lake water remains relatively enriched throughout the rest of the ice-free season.

In our sensitivity test results, it is clear that lake volume does not explain seasonal lake water isotope variability, rather, the lake surface area is the most important variable controlling lake water summer isotope composition. The summer isotope composition in lakes with large surface area tends to reflect mean annual precipitation, whereas lakes with small surface area are biased towards summer precipitation.

Cluett, A. A., & Thomas, E. K. (2020). Resolving combined influences of inflow and evaporation on western Greenland lake water isotopes to inform paleoclimate inferences. Journal of Paleolimnology, 1–18.

Dee, S. G., Russell, J. M., Morrill, C., Chen, Z., & Neary, A. (2018). PRYSM v2. 0: A proxy system model for lacustrine archives. Paleoceanography and Paleoclimatology, 33(11), 1250–1269.

Morrill, C., Meador, E., Livneh, B., Liefert, D. T., & Shuman, B. N. (2019). Quantitative model-data comparison of mid-Holocene lake-level change in the central Rocky Mountains. Climate Dynamics, 53(1/2), 1077–1094 https://doi.org/10.1007/s00382-019-04633-3