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ARS Home » Pacific West Area » Boise, Idaho » Northwest Watershed Research Center » Research » Publications at this Location » Publication #379647

Research Project: Ecohydrology of Mountainous Terrain in a Changing Climate

Location: Northwest Watershed Research Center

Title: Ecohydrologic modelling in a deciduous boreal forest: Model evaluation for application in non-stationary climates

Author
item MARSHALL, ADRIENNE - University Of Idaho
item LINK, TIMOTHY - University Of Idaho
item Flerchinger, Gerald
item NICOLSKY, DIMITRY - University Of Alaska
item LUCASH, MELISSA - Portland State University

Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/19/2021
Publication Date: 6/15/2021
Citation: Marshall, A., Link, T., Flerchinger, G.N., Nicolsky, D., Lucash, M. 2021. Ecohydrologic modelling in a deciduous boreal forest: Model evaluation for application in non-stationary climates. Hydrological Processes. 35(6). Article e14251. https://doi.org/10.1002/hyp.14251.
DOI: https://doi.org/10.1002/hyp.14251

Interpretive Summary: Boreal forests in northern latitudes are changing rapidly with deterioration of permafrost, changes in forest composition, increased fire frequency, and rapid changes in hydrology in the wake of permafrost thaw. To better understand and anticipate these changes, a detailed one-dimensional simulation model of plant-snow-soil physics (SHAW model) was coupled with an areal permafrost simulation model (GIPL model). The coupled model was applied to a post-fire deciduous forest stand in interior Alaska over a 13-year period and reproduced observed soil moisture and temperature dynamics with reasonable accuracy. These findings illustrate that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this deciduous boreal region and can be used to simulate how changes in climate and vegetation cover might influence permafrost, hydrology, and vegetation shifts in these fragile ecosystems.

Technical Abstract: In upland boreal regions, deciduous forest types are likely to become increasingly prevalent in future climates with more frequent fire. Soil moisture may become increasingly important to growth limitations in these regions, and soil hydraulic parameters are critical for the simulation of soil moisture dynamics. To better identify appropriate soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically-based, one-dimensional ecohydrologic Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to a post-fire deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation (GLUE) parameterization, SHAW was able to reproduce interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 50 cm as low as 0.020. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures (root mean squared error) that minimize error in soil moisture simulation, with those that were designed to minimize the dependence of model performance on interannual climate variability. The latter case moderately decreases traditional model performance but is likely more suitable for climate change applications, for which it is critical that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterization, and (3) a novel model diagnostic objective function for parameter selection to improve applicability in non-stationary climates.