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Publication Date
15 April 2019

Seasonal and Interannual Patterns and Controls of Hydrological Fluxes in an Amazon Floodplain Lake With a Surface‐Subsurface Process Model

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Floodplain lakes represent important aquatic ecosystems, and field‐based estimates of their water budgets are difficult to obtain, especially over multiple years. We examine the hydrological fluxes for an Amazon floodplain lake connected to the Solimões River using a process‐based hydrologic model. Water exchanges between the river and lake agree well with field estimates, including the timing of different hydrological phases. However, beyond available field data, modeling results show that the seven simulated years all differed from each other. These interannual differences were caused by the interplay between phases when water levels were rising with river‐water flowing into the lake (RWRI), versus rising with lake‐water flowing out to the river (RWLO). This exchange determines the river‐water content in the lake (CL). Maximum CL occurred before river levels peaked because local catchment contributions can be sufficient to push lake‐water out to the river, even as river levels rise. Numerical experiments show that the seasonal distribution of local rainfall, local catchment size, and interannual variability in both climate and river stage can contribute to differing dynamics of CL in a floodplain lake. Their impacts vary among phases: river‐rise dominates the RWRI, whereas local hydrological processes dominate the RWLO and receding‐water phases. Intermediate‐to‐long‐term rainfall accumulation controls CL during the RWLO phase, whereas annual precipitation accumulation is important for CL during low water. Our model generalizes beyond limited available field studies and offers the potential to better understand floodplain lakes in other areas and how regional versus local changes in climate may affect their hydrological dynamics.

“Seasonal And Interannual Patterns And Controls Of Hydrological Fluxes In An Amazon Floodplain Lake With A Surface‐Subsurface Process Model”. 2019. Water Resources Research 55: 3056-3075. doi:10.1029/2018WR023897.
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