HYDROLOGIC AND ISOTOPE MASS-BALANCE MODELING OF SMALL LAKE SYSTEMS AND IMPLICATIONS FOR RECONSTRUCTING HOLOCENE HYDROCLIMATE USING LACUSTRINE SEDIMENT OXYGEN ISOTOPE RECORDS

Hydrologic and isotope mass-balance models are essential for quantitatively interpreting lacustrine sediment oxygen stable isotope (d18O) records. Such records can provide evidence of past changes in lake level and precipitation-evaporation balance on timescales greater than the length of observational datasets, which are too short to capture the full range of climate variability. Here we present a coupled hydrologic and isotope mass-balance model adapted for small, closed-basin lake systems, which provides insight on lake sensitivity to changes in climate (e.g. air temperature, relative humidity, precipitation), and catchment hydrologic parameters (e.g. soil water capacity). The model is based on a system of differential equations that describe the hydrologic and isotopic balance of the lake and catchment water reservoirs. This MATLAB®-based model was applied to two lakes located in the semi-arid, drought prone region of eastern Washington and one lake located in the highlands of western Guatemala. Steady-state sensitivity experiments were conducted using constant averaged monthly climate input parameters and indicated that lake level and water d18O ratios vary strongly with changing drought-related climate variables, especially the amount and timing of precipitation. Catchment hydrologic parameters and lake infiltration and outseepage also had a major impact on the modeled variables. Model validation was achieved using 13 years of instrumental data (lake level, water d18O, weather station data) from the Washington lakes, and demonstrated the model’s capacity to accurately predict lake level and water/sediment d18O ratios in response to continuously variable hydrologic and environmental inputs to the catchment. These results support the applicability of the model to the interpretation of isotope records from these and similar systems, and ultimately will facilitate a better understanding of terrestrial hydroclimate variability on century to millennial time scales.