Representing northern peatland microtopography and hydrology within the Community Land Model

Abstract

Abstract. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to represent the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. The new model provides improved predictive capacity for seasonal hydrological dynamics in northern peatlands, and provides a useful foundation for investigation of northern peatland carbon exchange.

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales

“…The peatland area fraction derived from the map of Yu et al (2010) cannot represent the local area providing water for fens. (4) For global applications, the effects of micro-relief were not represented in the model, although they have been shown to be an important regulator of the local hydrology cycle (Gong et al, 2012;Shi et al, 2015).…”

“…The simulated water table by ORCHIDEE-PEAT depends on water inflows from the surrounding non-peatland areas, and a water-routing analysis on subgrid scales can be included to improve the model performance for water table in the future (Ringeval et al, 2012;Stocker et al, 2014). Other studies have shown that microtopography exerts important influences on hydrological dynamics of peatlands; however, to capture the influence of microtopography on water table, high-resolution microtopographic feature and vegetation information are needed (Gong et al, 2013;Shi et al, 2015). The poor correspondence between simulated and observed energy fluxes was not completely unexpected, since ORCHIDEE-PEAT only calculates one energy budget for the whole grid cell and not for each soil tile/PFT present in the same grid cell.…”

Evaluating the Community Land Model in a pine stand with shading manipulations and <sup>13</sup>CO<sub>2</sub> labeling

“…However, to better quantify and reduce uncertainties arising from deficiencies in model process representation, parameters, driver data sets, and initial conditions, there has been significant effort to evaluate and to calibrate LSMs against site-scale ob-servations and experimental manipulations (Baldocchi et al, 2001;De Kauwe et al, 2014;Hanson et al, 2004;Ostle et al, 2009;Raczka et al, 2013;Richardson et al, 2012;Schaefer et al, 2012;Schwalm et al, 2010;Stoy et al, 2013;Williams et al, 2009;Zaehle et al, 2014). Further, model development from these focused site-scale studies, especially in close collaboration with experimentalists, can inform and prioritize new experiments and observations that are specifically designed to advance understanding of critical terrestrial ecosystems and processes (Shi et al, 2015).…”

“…CLM has been evaluated against observations from a wide range of sources, and these evaluations have resulted in improved model performance (Bauerle et al, 2012;Bonan et al, 2011Bonan et al, , 2012Koven et al, 2013;Lawrence et al, 2011;Mao et al, 2012aMao et al, , b, 2013Oleson et al, 2008;Randerson et al, 2009;Riley et al, 2011;Shi et al, 2011Shi et al, , 2013Shi et al, , 2015Thornton et al, 2007). Nevertheless, little attention has been paid to CLM's ability to replicate short-term manipulative experiments, which provide an avenue for exploring and validating model response to sudden, large changes in environmental drivers that control physiological and ecological responses (Amthor et al, 2001;Bonan et al, 2013;Shi et al, 2015). Processes operating over short timescales can have long-lived ecosystem consequences through indirect effects; e.g., stomatal conductance varies on timescales of hours or shorter, but indirect effects on site-level water balance through controls on transpiration can extend to annual timescales and beyond.…”

Assessing the Value of UAV Photogrammetry for Characterizing Terrain in Complex Peatlands

“…Consequently, including microtopographic information in carbon-balance models is often recommended as a means of improving model accuracies [6,[8][9][10][11]. Most commonly, microtopographic data are acquired via terrestrial surveys using real-time kinematic global navigation satellite system (RTK GNSS) equipment, which are capable of centimeter accuracies [12,13].…”