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Abstract Soil moisture and evapotranspiration (ET) are important components of boreal forest hydrology that affect ecological processes and land‐atmosphere feedbacks. Future trends in soil moisture in particular are uncertain. Therefore, accurate modeling of these dynamics and understanding of concomitant sources of uncertainty are critical. Here, we conduct a global sensitivity analysis, Monte Carlo parameterization, and analysis of parameter uncertainty and its contribution to future soil moisture and ET uncertainty using a physically based ecohydrologic model in multiple boreal forest types. Soil and plant hydraulic parameters and LAI have the largest effects on simulated summer soil moisture at two contrasting sites. In future scenario simulations, the selection of parameters and global climate model (GCM) choice between two GCMs influence projected changes in soil moisture and ET about as much as the projected effects of climate change in the less sensitive GCM with a late‐century, high‐emissions scenario, though the relative effects of parameters, GCM, and climate vary among hydrologic variables and study sites. Saturated volumetric water content and sensitivity of stomatal conductance to vapor pressure deficit have the most statistically significant effects on change in ET and soil moisture, though there is considerable variability between sites and GCMs. The results of this study provide estimates of: (a) parameter importance and statistical significance for soil moisture modeling, (b) parameter values for physically based soil‐vegetation‐atmosphere transfer models in multiple boreal forest types, and (c) the contributions of uncertainty in these parameters to soil moisture and ET uncertainty in future climates.
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Diagnosis of Atmospheric Drivers of High-Latitude Evapotranspiration Using Structural Equation Modeling
Evapotranspiration (ET) is a relevant component of the surface moisture budget and is associated with different drivers. The interrelated drivers cause variations at daily to interannual timescales. This study uses structural equation modeling to diagnose the drivers over an ensemble of 45 high-latitude sites, each of which provides at least several years of in situ measurements, including latent heat fluxes derived from eddy covariance flux towers. The sites are grouped by vegetation type (tundra, forest) and the presence or absence of permafrost to determine how the relative importance of different drivers depends on land surface characteristics. Factor analysis is used to quantify the common variance among the variables, while a path analysis procedure is used to assess the independent contributions of different variables. The variability of ET at forest sites generally shows a stronger dependence on relative humidity, while ET at tundra sites is more temperature-limited than moisture-limited. The path analysis shows that ET has a stronger direct correlation with solar radiation than with any other measured variable. Wind speed has the largest independent contribution to ET variability. The independent contribution of solar radiation is smaller because solar radiation also affects ET through various other drivers. The independent contribution of wind speed is especially apparent at forest wetland sites. For both tundra and forest vegetation, temperature loads higher on the first factor when permafrost is present, implying that ET will become less sensitive to temperature as permafrost thaws.
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- PAR ID:
- 10313988
- Date Published:
- Journal Name:
- Atmosphere
- Volume:
- 12
- Issue:
- 10
- ISSN:
- 2073-4433
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/atmos12101359
