On the Uncertainty Induced by Pedotransfer Functions in Terrestrial Biosphere Modeling

Abstract

Terrestrial ecosystem and ecohydrological models are of paramount importance for understanding and quantifying the coupled water and carbon cycles. Despite their physics-based modeling approach, several sources of uncertainties affect the robustness of their predictions (e.g., Fisher et al., 2014;Zhou et al., 2018). Uncertainties include epistemic sources due to specific model formulations (e.g., Schwalm et al., 2019) and poorly known model parameters (e.g., Pappas et al., 2013) due to the lack of high fidelity in situ data at commensurate scales. One of the major processes that affects both the water and carbon cycles is the movement of water in the soil. Uncertainties involved in modeling soil water transport may impact key hydrological fluxes, such as runoff generation, groundwater recharge, and evapotranspiration, and, in turn, changes in water content in the root zone may influence vegetation dynamics, especially in areas with limited water availability.Most current generation ecohydrological and terrestrial ecosystem models simulate water movement in soils by solving either the 1-D or the 3-D Richards equation, adopting different numerical schemes (e.g., Farthing &

Macro- and micro-plastics change soil physical properties: a systematic review

“…Higher concentrations of MaP in this review tended to reduce K s , as reported previously by de Souza Machado et al (2018) and Guo et al (2022). Additionally, MaP reduced the soil infiltration rate and wetting front (Wen et al 2022).…”

“…Generally, K s is sensitive to soil bulk density (Araya and Ghezzehei 2019), suggesting that slight changes in it would greatly influence K s . With MaP and MiP, changes in K s were primarily driven by soil texture-associated structure and secondarily by plastic size distribution-associated water repellency (Wang et al 2020, Guo et al 2022. Soil water repellency is influenced primarily by soil physicochemical properties associated with organic matter content (Zema et al 2021).…”

“…These results complicate the prediction of possible changes in soil physical properties induced by plastics of different shapes and sizes, polymer types, or abundance. For example, it could amplify uncertainty when estimating net primary productivity in water-limited ecosystems with low permeability soils, due to information gaps regarding the effect of plastics on soil structure formation process and hydraulic properties , Paschalis et al 2022.…”

Local Controls on Near‐Surface Glacier Cooling Under Warm Atmospheric Conditions

“…We use the glacier component of the land‐surface model Tethys‐Chloris (Botter et al., 2021; Fatichi et al., 2012, 2021; Fugger et al., 2022; Fyffe et al., 2021; Mastrotheodoros et al., 2020; Paschalis et al., 2022) to model the surface energy balance across the glacier. The model simulates the energy fluxes of the ice/snow surface and subsurface, following: $$$R{n}_{\mathit{SNOW}}+Q{v}_{\mathit{SNOW}}+Qf{m}_{\mathit{SNOW}}-{H}_{\mathit{SNOW}}-L{E}_{\mathit{SNOW}}-{G}_{\mathit{SNOW}}-d{Q}_{\mathit{SNOW}}=0,$$$ …”

“…We use the glacier component of the land-surface model Tethys-Chloris (Botter et al, 2021;Fatichi et al, 2012Fatichi et al, , 2021Fugger et al, 2022;Fyffe et al, 2021;Mastrotheodoros et al, 2020;Paschalis et al, 2022) to model the surface energy balance across the glacier. The model simulates the energy fluxes of the ice/snow surface and subsurface, following:…”