Property:Extended model description
From CSDMS
This is a property of type Text.
M
MPeat2D incorporates realistic spatial variability on the peatland and allows for more significant insights into the interplay between these complex feedback mechanisms. +
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Makes use of fast Delaunay triangulation and Voronoi diagram calculations to represent surface processes on an irregular, dynamically evolving mesh. Processes include fluvial erosion, transport and deposition, hillslope (diffusion) processes, flexural isostasy, orographic precipitation. Designed to model processes at the orogenic scale. Can be easily modified for other purposes by changing process laws. +
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Matlab® code for paleo-hydrological flood flow reconstruction in a fluvial channel: first-order magnitude estimations of maximum average flow velocity, peak discharge, and maximum flow height from boulder size and topographic input data (channel cross-section & channel bed slope). +
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Measure single reservoir performance using resilience, reliability, and vulnerability metrics; compute storage-yield-reliability relationships; determine no-fail Rippl storage with sequent peak analysis; optimize release decisions using determinisitc and stochastic dynamic programming; evaluate inflow characteristics. +
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Model describing the morphodynamic evolution of vegetated coastal foredunes. +
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Model for fluvial fan-delta evolution, originally described by Sun et al. (2002) and later adapted by Limaye et al. (2023). The model routes water and sediment across a grid from a single inlet and via a self-formed channel network, where local divergence in sediment flux drives bed elevation change. The model represents hydrodynamics using rules for flow routing and stress partitioning. At large scales, other heuristics determine how channels branch and avulse, distributing water and sediment. The original model, designed for fluvial fan-deltas that debouch into standing water, is extended to allow deposition of an alluvial fan in the absence of standing water.
References:
Limaye, A. B., Adler, J. B., Moodie, A. J., Whipple, K. X., & Howard, A. D. (2023). Effect of standing water on formation of fan-shaped sedimentary deposits at Hypanis Valles, Mars. Geophysical Research Letters, 50(4), e2022GL102367. https://doi.org/10.1029/2022GL102367
Sun, T., Paola, C., Parker, G., & Meakin, P. (2002). Fluvial fan deltas: Linking channel processes with large-scale morphodynamics. Water Resources Research, 38(8), 26-1-26–10. https://doi.org/10.1029/2001WR000284 +
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ModelE is the GISS series of coupled atmosphere-ocean models, which provides the ability to simulate many different configurations of Earth System Models - including interactive atmospheric chemsitry, aerosols, carbon cycle and other tracers, as well as the standard atmosphere, ocean, sea ice and land surface components. +
L
Models temperature of 1-D lake-permafrost system through time, given input surface temperature and solar radiation. Model is fully implicit control volume scheme, and cell size can vary with depth. Thermal conductivity and specific heat capacity are dependent on cell substrate (% soil and % ice) and temperature using the apparent heat capacity scheme where freezing/thawing occurs over a finite temperature range and constants are modified to account for latent heat. Lake freezes and thaws depending on temperature; when no ice is present lake is fully mixed and can absorb solar radiation. Upper 10 m substrate contains excess ice and, if thawed, can subside by this amount (lake then deepens by amount of subsidence). "Cell type" controls whether cell has excess ice, only pore space ice, or is lake water. +
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Models the temporal and spatial distribution of the active layer thickness and temperature of permafrost soils. The underlying approximation accounts for effects of air temperature, snow cover, vegatation, soil moisture, soil thermal properties to predict temperature at the ground surface and mean active layer thickness. +
R
M
Mrip consists of a matrix representing the sea floor (25x25 m at this time). Blocks in the matrix are picked up (or deposited) according to transport rules or equations (users choice) and moved with the flow. The user-determined flow is altered, depending on the height and slope of the bed, thus creating feedback. +
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NEMO is a state-of-the-art modelling framework. It is used for research activities and forecasting services in ocean and climate sciences. NEMO is developed by a European consortium with the objective of ensuring long term reliability and sustainability. NEMO includes three major components; the blue ocean (dynamics), the white ocean (sea-ice), the green ocean (ocean biogeochemistry). It also allows coupling through interfaces with atmosphere (through OASIS software), waves, ice-shelves, so as nesting through the adaptive mesh refinement software AGRIF. +
NearCoM predicts waves, currents, sediment transport and bathymetric change in the nearshore ocean, between the shoreline and about 10 m water depth. The model consists of a "backbone", i.e., the master program, handling data input and output as well as internal storage, together with a suite of "modules": wave module, circulation module and sediment transport module. +
R
Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to bed-material sediment transport.
This code is capable of reproducing the results (with some work by the end user) described in the following publications:
Czuba, J.A., and E. Foufoula-Georgiou (2014), A network-based framework for identifying potential synchronizations and amplifications of sediment delivery in river basins, Water Resources Research, 50(5), 3826–3851, doi:10.1002/2013WR014227.
Czuba, J.A., and E. Foufoula-Georgiou (2015), Dynamic connectivity in a fluvial network for identifying hotspots of geomorphic change, Water Resources Research, 51(3), 1401-1421, doi:10.1002/2014WR016139.
Gran, K.B., and J.A. Czuba, (2017), Sediment pulse evolution and the role of network structure,
Geomorphology, 277, 17-30, doi:10.1016/j.geomorph.2015.12.015.
Czuba, J.A., E. Foufoula-Georgiou, K.B. Gran, P. Belmont, and P.R. Wilcock (2017), Interplay between spatially-explicit sediment sourcing, hierarchical river-network structure, and in-channel bed-material sediment transport and storage dynamics, Journal of Geophysical Research - Earth Surface, 122(5), 1090-1120, doi:10.1002/2016JF003965.
As of 20 March 2019, additional model codes were added to the repository in the folder "Gravel_Bed_Dynamics" that extend the model to gravel bed dynamics. The new methods for gravel bed dynamics are described in:
Czuba, J.A. (2018), A Lagrangian framework for exploring complexities of mixed-size sediment transport in gravel-bedded river networks, Geomorphology, 321, 146-152, doi:10.1016/j.geomorph.2018.08.031.
And an application to Clear Creek/Tushar Mountains in Utah is described in:
Murphy, B.P., J.A. Czuba, and P. Belmont (2019), Post-wildfire sediment cascades: a modeling framework linking debris flow generation and network-scale sediment routing, Earth Surface Processes and Landforms, 44(11), 2126-2140, doi:10.1002/esp.4635.
Note: the application code and data files for Murphy et al., 2019 are included in the repository as example files.
As of 24 September 2020, this code has largely been converted to Python and has been incorporated into Landlab version 2.2 as the NetworkSedimentTransporter. See:
Pfeiffer, A.M., K.R. Barnhart, J.A. Czuba, and E.W.H. Hutton (2020), NetworkSedimentTransporter: A Landlab component for bed material transport through river networks, Journal of Open Source Software, 5(53), 2341, doi:10.21105/joss.02341.
This initial release is the core code, but development is ongoing to make the data preprocessing, model interface, and exploration of model results more user friendly. All future developments will be in the Landlab/Python version of the code instead of this Matlab version.
N
Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to nitrate and organic carbon on a wetland-river network.
This code is capable of reproducing the results (with some work of commenting/uncommenting code by the end user) described in the following publication:
Czuba, J.A., A.T. Hansen, E. Foufoula-Georgiou, and J.C. Finlay (2018), Contextualizing wetlands within a river network to assess nitrate removal and inform watershed management, Water Resources Research, 54(2), 1312-1337, doi:10.1002/2017WR021859. +
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Nonlinear three dimensional simulations of miscible Hele-Shaw flows using DNS of incompressible Navier-Stokes and transport equations. +
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Oceananigans.jl is designed for high-resolution simulations in idealized geometries and supports direct numerical simulation, large eddy simulation, arbitrary numbers of active and passive tracers, and linear and nonlinear equations of state for seawater. +
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One dimensional model for the coupled long-term evolution of salt marshes and tidal flats. The model framework includes tidal currents, wind waves, sediment erosion and deposition, as well as the effect of vegetation on sediment dynamics. The model is used to explore the evolution of the marsh boundary under different scenarios of sediment supply and sea level rise. Time resolution 30 min, simulation length about 100 years. +
