# Property:Extended model description

From CSDMS

This is a property of type Text.

M

"meanderpy" is a Python module that implements a simple numerical model of meandering, the one described by Howard & Knutson in their 1984 paper "Sufficient Conditions for River Meandering: A Simulation Approach" (https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/WR020i011p01659). This is a kinematic model that is based on computing migration rate as the weighted sum of upstream curvatures; flow velocity does not enter the equation. Curvature is transformed into a 'nominal migration rate' through multiplication with a migration rate (or erodibility) constant; in the Howard & Knutson (1984) paper this is a nonlinear relationship based on field observations that suggested a complex link between curvature and migration rate. In the 'meanderpy' module we use a simple linear relationship between the nominal migration rate and curvature, as recent work using time-lapse satellite imagery suggests that high curvatures result in high migration rates (Sylvester et al., 2019). +

B

C

S

K

--- WHEN USING THIS CODE FOR YOUR RESEARCH, PLEASE CITE: ---<br>
Neely, A., Bookhagen B., Burbank, D.W. (2017): An automated knickzone selection algorithm (KZ-Picker) to analyze transient landscapes: Calibration and validation, JGR Earth Surface, doi:10.1002/2017JF004250
available at: http://onlinelibrary.wiley.com/doi/10.1002/2017JF004250/full
<br>
---
The Matlab-based scripts extract several topometrics at the catchment scale based on log area/log slope and chi plots. Topometrics include: steepness index, theta, steepness index with adjusted theta for each drainage basin, specific stream power, curvature, local relief, and others. Detrended and normalized chi-squared plots are used to identify river knickpoints. Output is written as GeoTIFF files, shapefiles, and CSV files.
Additional information, examples, and tutorials are provided on the github page. +

S

M

2D marsh evolution model focused on pond dynamics. Channels are static features. Tidal transport is not directly simulated. Includes the effect of man-made ditches (i.e., localized subsidence).
It has companion website with pre-loaded simulations to be used by end-users. +

2

S

D

C

3D cellular model simulating delta evolution in coarse grained river dominated systems (e.g. a gravel fan delta). +

A 2D or 3D model of carbonate sediment production and transport that generates high-frequency platform top auto and allocycles as well as various aspects of large scale platform geomtry +

L

A Landlab implementation of the Barnes et al. (2014) lake filling & lake routing algorithms, lightly modified and adapted for Landlab by DEJH. This component is designed as a direct replacement for the LakeMapper as existing pre-Aug 2018, and provides a suite of properties to access information about the lakes created each time it is run. Only significant difference is the way the lakes are coded: this component uses the (unique) ID of the outlet node, whereas DepressionFinderAndRouter uses one of the pit node IDs. Note also this component does not offer the lake_codes or display_depression_map options, for essentially this reason. Use lake_map instead for both. It also uses a much more Landlabbian run_one_step() method as its driver, superceding DepressionFinderAndRouter’s map_depressions().
A variety of options is provided. Flow routing is route-to-one in this implementation, but can be either D4 (“steepest”) or D8 on a raster. The surface can be filled to either flat or a very slight downward incline, such that subsequent flow routing will run over the lake surface. This incline is applied at machine precision to minimize the chances of creating false outlets by overfill, and note that the gradient as calculated on such surfaces may still appear to be zero. The filling can either be performed in place, or on a new (water) surface distinct from the original (rock) surface. For efficiency, data structures describing the lakes and their properties are only created, and existing flow direction and flow accumulation fields modified, if those flags are set at instantiation +

A Lithology is a three dimensional representation of material operated on by Landlab components. Material can be removed through erosion or added to through deposition. Rock types can have multiple attributes (e.g. age, erodibility or other parameter values, etc). +

N

A Python tool for extracting and/or plotting data from the NEXRAD (WSR-88D) Doppler weather radar network operated by the US National Weather Service. This can be used for inputs to models that require a meteorologic component. +

Z

A ``ZoneTaxon`` is composed of members of a lower taxonomic level that each exists within a ``Zone`` object. Taxonomic rank is not considered by this class despite the use of the term, 'speciation', which is used herein to generally describe creation of a child taxon object.
All zones of the taxon can be obtained with the attribute, ``zones`` that are the objects that manage the geographic aspect of taxon member populations. The total geographic extent of all populations is depicted by the ``range_mask`` attribute. The zones of a ZoneTaxon instance are created and updated using a ``ZoneController``. At model time steps, the connectivity of zones over time is obtained using attributes of the ``Zone`` object.
The evolution of this taxon type is carried out in two stages during a model time step. In the first stage, the zones of the taxon are updated as the result of zone connectivity between the prior and current step in the method, ``_update_zones``. This method is the primary implementation of taxon dispersal and it is called in a stage prior to other evolutionary processes so that all taxa are positioned in their landscape locations prior to the other processes.
In the second stage, processes are carried out in methods that are readily expanded or overridden when needed. The primary methods of second stage macroevolution are ``_evaluate_dispersal``, ``_evaluate_speciation``, and ``_evaluate_extinction``. The evaluate dispersal method is intended to modify dispersal conducted in the first stage and it has no effect unless it is expanded or overridden to have an effect. Processes other than those listed above can be called by expanding or overridding the ``_evolve`` method.
The taxon is allopatric when it is associated with/exists within multiple zones (signifying multiple member populations). A timer is started when a taxon becomes allopatric. Allopatric speciation occurs once the timer reaches or exceeds the ``time_to_allopatric_speciation`` initialization parameter. If the initialization parameter, ``persists_post_speciation`` is True (default), a child taxon is created in each zone except one zone (the largest by area) that becomes the sole zone of the taxon. If ``persists_post_speciation`` is set to False, a child taxon is created in each and every zone, and the parent no longer occupies any zones, and therefore the parent taxon is no longer extant.
Extinction occurs when the taxon is no longer associated with any zones. This occurs when zones in the prior time step do not overlap zones in the current time step, signifying the geographic range of the taxon is no more. A taxon can become no longer extant also when the taxon speciates and ``persists_post_speciation`` is False signifying that the parent taxon has evolved into multiple taxon distinct from the original taxon.

D

A cellular automaton model for simulating the development of aeolian dune landscapes under the influence of vegetation and biota (parabolic dunes, blowouts, foredunes, nebkha dunes). +

S

A component to generate a sequence of spatially resolved storms over a grid, following a lightly modified version (see below) of the stochastic methods of Singer & Michaelides, Env Res Lett 12, 104011, 2017, & Singer et al., Geosci. Model Dev., accepted, 10.5194/gmd-2018-86.
The method is heavily stochastic, and at the present time is intimately calibrated against the conditions at Walnut Gulch, described in those papers. In particular, assumptions around intensity-duration calibration and orographic rainfall are "burned in" for now, and are not accessible to the user. The various probability distributions supplied to the various run methods default to WG values, but are easily modified. This calibration reflects a US desert southwest "monsoonal" climate, and the component distinguishes (optionally) between two seasons, "monsoonal" and "winter". The intensity-duration relationship is shared between the seasons, and so may prove useful in a variety of storm-dominated contexts.
The default is to disable the orographic rainfall functionality of the component. However, if orographic_scenario == 'Singer', the component requires a 'topographic__elevation' field to already exist on the grid at the time of instantiation.
The component has two ways of simulating a "year". This choice is controlled by the 'limit' parameter of the yield methods. If limit == 'total_rainfall', the component will continue to run until the total rainfall for the season and/or year exceeds a stochastically generated value. This method is directly comparable to the Singer & Michaelides method, but will almost always result in years which are not one calendar year long, unless the input distributions are very carefully recalibrated for each use case. If limit == 'total_time', the component will terminate a season and/or year once the elapsed time exceeds one year. In this case, the total rainfall will not correspond to the stochastically generated total. You can access the actual total for the last season using the property `(median_)total_rainfall_last_season`.
Note that this component cannot simulate the occurrence of more than one storm at the same time. Storms that should be synchronous will instead occur sequentially, with no interstorm time. This limitation means that if enough storms occur in a year that numstorms*mean_storm_duration exceeds one year, the number of simulated storms will saturate. This limitation may be relaxed in the future.
The component offers the option to modify the maximum number of storms simulated per year. If you find simulations encountering this limit too often, you may need to raise this limit. Conversely, it could be lowered to reduce memory usage over small grids. However, in increasing the value, beware - the component maintains two limit*nnodes arrays, which will chew through memory if the limit gets too high. The default will happily simulate grids up to around 50 km * 50 km using the default probability distributions.

M

A landform evolution model operating at the drainage basin or larger scale. Recent model development has targeted planetary applications. +

C

A length-, and time-averaged representation of coastal system elements including the inner shelf, shoreface, surfzone, inlet, inlet shoals, and estuary channels and tidal flats. The multi-line nature of the morphodynamic model allows it to represent large-scale sediment transport processes with a combination time-average physics empirical relationships. A major use is to represent the interactions between system components to develop with changes in large scale forcing such as accelerated sea level rise, changes in river sediment input (ie. dams), changes in estuary tide prisms (ie. dikes) and the like. +

M

A marsh column model designed to (ultimately) be inserted beneath spatially distributed marsh sedimentation models. Tracks surface biomass, subsurface root mass, carbon accumulation and decay (includes both labile and refractory carbon), inorganic sediments, and sediment compaction. +

L

A model to explore how increasingly tall valley walls constrain the river lateral erosion and promote vertical incision. Each run is unique as a random walk controls the lateral migration of the channel. To store and compare repeated runs with identical parameters, there is a built in system to save the results of each run.
This model is used to illustrate the wall feedback concept proposed by Malatesta, Prancevic, Avouac; 2017; JGR Eath-Surface; doi:10.1002/2015JF003797 +

A

A module that calculates the evolution of a gravel bed river under an imposed cycled hydrograph. +

T

A multi-dimensional numerical model for sediment transport based on the two-phase
flow formulation is developed. With closures of particle stresses and fluid-particle interaction,
the model is able to resolve processes in the concentrated region of sediment
transport and hence does not require conventional bedload/suspended load assumptions.
The numerical model is developed in three spatial dimensions. However, in this version,
the model is only validated for Reynolds-averaged two-dimensional vertical (2DV) formulation
(with the k − epsilon closure for carrier flow turbulence) for sheet flow in steady and
oscillatory flows. This numerical model is developed via the open-source CFD library of
solvers, OpenFOAM and the new solver is called twoPhaseEulerSedFoam. +

G

A multi-element (N, P, Si, C), multi-form (particulate, dissolved, organic, inorganic) set of biogeochemical sub-models that predicts annual river exports to the coast as a function of basin-aggregated natural and human impact characteristics; GNE is a generic framework used to run the basin models. +

O

A numerical method to analyse a vertical succession of strata and identify the most cyclical arrangement of constituent facies using an optimised transition probability matrix approach +

L

A parallel 3D numerical code that can be used to model various thermomechanical geodynamical processes such as mantle-lithosphere interaction for rocks that have visco-elasto-plastic rheologies. The code is build on top of PETSc and the current version of the code uses a marker-in-cell approach with a staggered finite difference discretization. +

S

A primitive equation ocean general circulation model based on the Bryan--Semtner--Cox formulation and designed to give good performance on clusters of workstations and massively parallel machines using the PVM message passing library. +

D

A process-response model simulating the evolution and stratigraphy of fluvial dominated deltaic systems in two dimensions, based on simple approximations of erosion and deposition. The model is called DELTASIM, and was initially presented by Overeem et al. (2003) as AQUATELLUS. DELTASIM has several improvements, the main algorithm has been revised and the output can be presented as probabilistic output. +

L

P

A python code for modeling the dense endmember of pyroclastic density currents (PDCs) generated either by impulsive column collapse or sustained fountaining eruptions. Dense, particle rich PDC is modeled as solid-fluid mixture driven by gravity analogous to the granular flow models of Iverson and Denlinger (2001). Flow movement over real topography is realized by using a digital elevation model (DEM) file as one of the model inputs. Other model inputs include simulation time, flow density and viscosity, x and y coordinates (or longitude and latitude) of the source, among others, which are input to the model either using a config file or via command line arguments. +

H

A series of tools for extracting a network of hilltops from a landscape, computing curvature, slope and aspect over variable length scales from high resolution topography and performing hillslope traces from hilltops to valley bottoms to sample hilltop curvature, mean hillslope gradient and hillslope length. See Hurst et al. (2012) for full description. +

M

A stand alone model for an idealized transect across a marsh channel-and-platform. The model simulates morphological evolution from sub-tidal to millennial time scales. In particular, the model explores the effect that soil creep (of both vegetated and unvegetated mud) has on channel bank dynamics, e.g., bank slumping. The model is written in Matlab. +

P

A stochastic point model for tidal flat evolution to study the influence of tidal currents and wind waves on tidal flat equilibrium. +

B

A three-dimensional hydrodynamic multi-purpose model for coastal and shelf seas, which can be coupled to biological, re-suspension and contaminant models. Has been used in a variety of configurations from resolving grain-scale up to seasonal scale processes. Can be run with optional MPI parallelization or run-time visualization via PGPLOT. Programmed with the goal that the same executable can be used for all cases, by using allocatable arrays and cases defined via a single configuration file pointing to input data in files typically in the same directory. +

S

A three-dimensional two-phase flow solver, SedFoam-2.0, is presented for sediment transport applications. The solver is extended upon twoPhaseEulerSedFoam (https://csdms.colorado.edu/wiki/Model:TwoPhaseEulerSedFoam). In this approach the sediment phase is modeled as a continuum, and constitutive laws have to be prescribed for the sediment stresses. In the proposed solver, two different inter-granular stress models are implemented: the kinetic theory of granular flows and the dense granular flow rheology μ(I). For the fluid stress, laminar or turbulent flow regimes can be simulated and three different turbulence models are available for sediment transport: a simple mixing length model (one-dimensional configuration only), a k-ϵ and a k-ω model. The numerical implementation is first demonstrated by two validation test cases, sedimentation of suspended particles and laminar bed-load. Two applications are then investigated to illustrate the capabilities of SedFoam-2.0 to deal with complex turbulent sediment transport problems, such as sheet flow and scouring, with different combinations of inter-granular stress and turbulence models. +

C

A transect spanning three coastal ecosystems (bay-marsh-forest) evolves in yearly timesteps to show the evolution of the system. Geomorphic and carbon cycling processes allow for the exchange of material between the adjacent ecosystems. Each landscape unit is on the order of kilometers. Main geomorphic processes are featured in Kirwan et al. 2016 in GRL, and carbon processes track allochthonous and autocthonous carbon with time and depth. +

F

A turbulence-resolving numerical model for fine sediment transport in the bottom boundary layer is developed. A simplified Eulerian two-phase flow formulation for the fine sediment transport is adopted. By applying the equilibrium Eulerian approximation, the particle phase velocity is expressed as a vectorial sum of fluid velocity, sediment settling velocity and Stokes number dependent inertia terms. The Boussinesq approximation is applied to simplify the governing equation for the fluid phase. This model utilizes a high accuracy hybrid compact finite difference scheme in the wall-normal direction, and uses the pseudo-spectral scheme in the streamwise and spanwise directions. The model allows a prescribed sediment availability as well as an erosional/depositional bottom boundary condition for sediment concentration. Meanwhile, the model also has the capability to include the particle inertia effect and hindered settling effect for the particle velocity. +

W

A

ADCIRC is a system of computer programs for solving time dependent, free surface circulation and transport problems in two and three dimensions. These programs utilize the finite element method in space allowing the use of highly flexible, unstructured grids. Typical ADCIRC applications have included:
# modeling tides and wind driven circulation,
# analysis of hurricane storm surge and flooding,
# dredging feasibility and material disposal studies,
# larval transport studies,
# near shore marine operations. +

ALFRESCO was originally developed to simulate the response of subarctic vegetation to a changing climate and disturbance regime (Rupp et al. 2000a, 2000b). Previous research has highlighted both direct and indirect (through changes in fire regime) effects of climate on the expansion rate, species composition, and extent of treeline in Alaska (Rupp et al. 2000b, 2001, Lloyd et al. 2003). Additional research, focused on boreal forest vegetation dynamics, has emphasized that fire frequency changes – both direct (climate-driven or anthropogenic) and indirect (as a result of vegetation succession and species composition) – strongly influence landscape-level vegetation patterns and associated feedbacks to future fire regime (Rupp et al. 2002, Chapin et al. 2003, Turner et al. 2003). A detailed description of ALFRESCO can be obtained from the literature (Rupp et al. 2000a, 200b, 2001, 2002). The boreal forest version of ALFRESCO was developed to explore the interactions and feedbacks between fire, climate, and vegetation in interior Alaska (Rupp et al. 2002, 2007, Duffy et al. 2005, 2007) and associated impacts to natural resources (Rupp et al. 2006, Butler et al. 2007). +

ANUGA is a hydrodynamic model for simulating depth-averaged flows over 2D surfaces. This package adds two new modules (operators) to ANUGA. These are appropriate for reach-scale simulations of flows on mobile-bed streams with spatially extensive floodplain vegetation.
The mathematical framework for the sediment transport operator is described in Simpson and Castelltort (2006) and Davy and Lague (2009). This operator calculates an explicit sediment mass balance within the water column at every cell in order to handle the local disequilibria between entrainment and deposition that arise due to strong spatial variability in shear stress in complex flows.
The vegetation drag operator uses the mathematical approach of Nepf (1999) and Kean and Smith (2006), treating vegetation as arrays of objects (cylinders) that the flow must go around. Compared to methods that simulate the increased roughness of vegetation with a modified Manning's n, this method better accounts for the effects of drag on the body of the flow and the quantifiable differences between vegetation types and densities (as stem diameter and stem spacing). This operator can simulate uniform vegetation as well as spatially-varied vegetation across the domain. The vegetation drag module also accounts for the effects of vegetation on turbulent and mechanical diffusivity, following the equations in Nepf (1997, 1999). +

ANUGA is a hydrodynamic modelling tool that allows users to model realistic flow problems in complex 2D geometries. Examples include dam breaks or the effects of natural hazards such as riverine flooding, storm surges and tsunami. The user must specify a study area represented by a mesh of triangular cells, the topography and bathymetry, frictional resistance, initial values for water level (called stage within ANUGA), boundary conditions and forces such as rainfall, stream flows, windstress or pressure gradients if applicable.
ANUGA tracks the evolution of water depth and horizontal momentum within each cell over time by solving the shallow water wave governing equation using a finite-volume method.
ANUGA also incorporates a mesh generator that allows the user to set up the geometry of the problem interactively as well as tools for interpolation and surface fitting, and a number of auxiliary tools for visualising and interrogating the model output.
Most ANUGA components are written in the object-oriented programming language Python and most users will interact with ANUGA by writing small Python scripts based on the ANUGA library functions. Computationally intensive components are written for efficiency in C routines working directly with Python numpy structures. +

Acronym1D is an add on to Acronym1R in that it adds a flow duration curve to Acronym1R, which computes the volume bedload transport rate per unit width and bedload grain size distribution from a specified surface grain size distribution (with sand removed). +

Acronym1R computes the volume bedload transport rate per unit width and bedload grain size distribution from a specified surface grain size distribution (with sand removed). +

AeoLiS is a process-based model for simulating aeolian sediment transport in situations where supply-limiting factors are important, like in coastal environments. Supply-limitations currently supported are soil moisture contents, sediment sorting and armouring, bed slope effects, air humidity and roughness elements. +

F

Allow for quick estimation of water depths within a flooded domain using only the flood extent layer (polygon) and a DEM of the area. Useful for near-real-time flood analysis, especially from remote sensing mapping.
Version 2.0 offers improved capabilities in coastal areas. +

A

Alpine3D is a model for high resolution simulation of alpine surface processes, in particular snow processes. The model can be forced by measurements from automatic weather stations or by meteorological model outputs (this is handled by the MeteoIO pre-processing library). The core three-dimensional Alpine3D modules consist of a radiation balance model (which uses a view factor approach and includes shortwave scattering and longwave emission from terrain and tall vegetation) and a drifting snow model solving a diffusion equation for suspended snow and a saltation transport equation. The processes in the atmosphere are thus treated in three dimensions and coupled to a distributed one dimensional model of vegetation, snow and soil model (Snowpack) using the assumption that lateral exchange is small in these media. The model can be used to force a distributed catchment hydrology model (AlpineFlow). The model modules can be run in a parallel mode, using either OpenMP and/or MPI. Finally, the Inishell tool provides a GUI for configuring and running Alpine3D.
Alpine3D is a valuable tool to investigate surface dynamics in mountains and is currently used to investigate snow cover dynamics for avalanche warning and permafrost development and vegetation changes under climate change scenarios. It could also be used to create accurate soil moisture assessments for meteorological and flood forecasting. +

W