This paper presents a novel hybrid deterministic-stochastic river morphodynamics numerical modeling approach that integrates a two-dimensional (2D) hydrodynamic model (deterministic) with a bed morphodynamic model (deterministic) and a bank erosion model (Markovian stochastic). The model solves the 2D Shallow Water Equations and the standard k-epsilon turbulence model. Bedload transport is estimated using the Meyer-Peter and Muller formula, and bed evolution is solved using the Exner Equation. The Markovian stochastic bank erosion model uses a new method to evaluate bank erosion risk. The approach was applied to a meander bend cutoff event in the Maiqu River on the Tibetan Plateau. Sixteen different bank-material critical shear stress cases were considered, representing highly erodible banks to resistant banks. Ten statistical realizations were performed for each case with different bank-material erodibility to obtain ensemble-averaged results. Flow field and bed evolution in the cutoff channel suggest that the model can successfully simulate bank erosion processes during the cutoff channel evolution, and bank topographic irregularities are reasonably captured. A newly introduced calibration parameter, the ratio of mesh size to the coupling period between the bank erosion model and the hydrodynamic & morphodynamic model, is not as intuitive as the erosion resistance calibration parameters used by the traditional bank erosion model. The proposed approach necessitates estimating the size of a typical slump failure, or 10-30% of the cutbank height, to set the size of the computational mesh.

The complex interactions among soil, vegetation, and site hydrologic conditions driven by precipitation and tidal cycles control biogeochemical transformations and bi-directional exchange of carbon and nutrients across the terrestrial-aquatic interfaces (TAIs) in the coastal regions. This study uses a highly mechanistic model, ATS-PFLOTRAN, to explore how these interactions impact the material exchanges and carbon and nitrogen cycling along a TAI transect in the Chesapeake Bay region that spans zones of open water, coastal wetland and upland forest. Several simulation scenarios are designed to parse the effects of the individual controlling factors and the sensitivity of carbon cycling to reaction constants derived from laboratory experiments. Our simulations revealed a hot zone for carbon cycling under the coastal wetland and the transition zones between the wetland and the upland. Evapotranspiration is found to enhance the exchange fluxes between the surface and subsurface domains, resulting in higher dissolved oxygen concentration in the TAI. The transport of organic carbon decomposed from leaves provides additional source of organic carbon for the aerobic respiration and denitrification processes in the TAI, while the variability in reaction rates mediated by microbial activities plays a dominant role in controlling the heterogeneity and dynamics of the simulated redox conditions. This modeling-focused exploratory study enabled us to better understand the complex interactions of various system components at the TAIs that control the hydro-biogeochemical processes, which is an important step towards representing coastal ecosystems in larger-scale Earth system models.

Wildfires can induce an abundance of vegetation and soil changes that may trigger higher surface runoff and soil erosion, affecting the water cycling within these ecosystems. In this study, we employed the Advanced Terrestrial Simulator (ATS), an integrated and fully distributed hydrologic model at watershed scale to investigate post-fire hydrologic responses in a few selected watersheds with varying burn severity in the Pacific Northwest region of the United States. The model couples surface overland flow, subsurface flow, and canopy biophysical processes. We developed a new fire module in ATS to account for the fire-caused hydrophobicity in the topsoil. Modeling results show that the watershed-averaged evapotranspiration is reduced after high burn severity wildfires. Post-fire peak flows are increased by 21-34% in the three study watersheds burned with medium to high severity due to the fire-caused soil water repellency (SWR). However, the watershed impacted by a low severity fire only witnessed a 2% surge in post-fire peak flow. Furthermore, the high severity fire resulted in a mean reduction of 38% in the infiltration rate within fire-impacted watershed during the first post-fire wet season. Hypothetical numerical experiments with a range of precipitation regimes after a high severity fire reveal the post-fire peak flows can be escalated by 1-34% due to the SWR effect triggered by the fire. This study implies the importance of applying fully distributed hydrologic models in quantifying the disturbance-feedback loop to account for the complexity brought by spatial heterogeneity.