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This page provides a simple browsing interface for finding entities described by a property and a named value. Other available search interfaces include the page property search, and the ask query builder.

List of results

Model:EstuarineMorphologyEstimator + (See article: https://doi.org/10.3390/rs10121915)
Model:MARSSIM V4 + (See documentation and published papers using MARSSIM)
Model:Landlab + (See documentation at: http://landlab.readthedocs.org)
Model:ISSM + (See https://issm.jpl.nasa.gov/)
Model:TIN-based Real-time Integrated Basin Simulator (tRIBS) + (See https://tribshms.readthedocs.io/en/latest/)
Model:FUNWAVE + (See manual)
Model:SPHYSICS + (See manual)
Model:REF-DIF + (See manual version3)
Model:STWAVE + (See manual, is uploaded)
Model:Glimmer-CISM + (See paper)
Model:Nitrate Network Model + (See readme file with the source file download or related publication by J. A. Czuba.)
Model:River Network Bed-Material Sediment + (See readme file with the source file download or related publications by J. A. Czuba.)
Model:AquaTellUs + (See references.)
Model:RiverMUSE + (See the associated published paper: https://doi.org/10.1086/684223 and the readme file for parameter descriptions.)
Model:TOPOG + (See website, too many to describe: http://www-data.wron.csiro.au/topog/)
Model:HydroTrend + (See: *Kettner, A.J., and Syvitski, J.P.M., … See:*Kettner, A.J., and Syvitski, J.P.M., 2008. HydroTrend version 3.0: a Climate-Driven Hydrological Transport Model that Simulates Discharge and Sediment Load leaving a River System. Computers & Geosciences, Special Issue.More details about the long term sediment routine that is incorporated in the Hydrotrend:*Syvitski, J.P.M., Milliman, J.D., 2007. Geology, 115, 1-19..M., Milliman, J.D., 2007. Geology, 115, 1-19.)
Model:FwDET + (See: Version 2.0: Cohen et al. (2019), The … See:Version 2.0: Cohen et al. (2019), The Floodwater Depth Estimation Tool (FwDET v2.0) for Improved Remote Sensing Analysis of Coastal Flooding. Natural Hazards and Earth System Sciences (NHESS) Version 1.0: Cohen, S., G. R. Brakenridge, A. Kettner, B. Bates, J. Nelson, R. McDonald, Y. Huang, D. Munasinghe, and J. Zhang (2017), Estimating Floodwater Depths from Flood Inundation Maps and Topography. Journal of the American Water Resources Association (JAWRA):1–12. Water Resources Association (JAWRA):1–12.)
Model:1DBreachingTurbidityCurrent + (See: Eke, E., Viparelli, E., and Parker, G., 2011. Field-scale numerical modeling of breaching as a mechanism for generating continuous turbidity currents. Geosphere, 7, 1063-1076. Doi: 10.1130/GES00607.1)
Model:Cliffs + (Shallow-water equations)
Model:GPM + (Shallow-water equations for fluid flow Separate equations for wave propagation Shield's criterion and transport capacity criterion for clastic transport (similar to SEDSIM) Sigle-phase flow in porous media for vertical and 3D compaction options.)
Model:BRaKE + (Shear stress-driven fluvial erosion, primarily modulated by bed erodibility, critical bed shear stress, block delivery, and block size.)
Model:Alpine3D + (Snow settling, temperature diffusion, snow saltation and suspension, snow metamorphism, terrain radiation.)
Model:DepthDependentDiffuser + (Soil flux is calculated at the product of diffusivity, a characteristic transport depth, and an exponential velocity profile based on total soil depth.)
Model:2DFLOWVEL + (Solves the non-linear, depth-averaged conservation equations, using finite difference scheme of Koutitas (1988))
Model:TreeThrow + (Species specific, logistic growth equation for individual trees. Sediment flux for each tree fall a function of sediment volume, transport distance, and hillslope angle. Sediment volume and transport distance a function of tree diamter.)

Model:WAVEWATCH III ^TM + (Spectral action balance equation.)

Model:IncrementalDebrisFlowVolumeAnalyzer + (Standard flow routing and uniform sampling principles are used to govern the processes of this model.)
Model:CarboCAT + (Subsidence rates Production rates CA rules, number of seed neighbours etc)
Model:HexWatershed + (Terrain analysis. One equation is the resolution of a hexagon can be estimated using its area instead of edge length.)
Model:WRF + (The WRF-ARW core is based on an Eulerian s … The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations, cast in flux (conservative) form, using a mass (hydrostatic pressure) vertical coordinate. Prognostic variables for this solver are column mass of dry air (mu), velocities u, v and w (vertical velocity), potential temperature, and geopotential. Non-conserved variables (e.g. temperature, pressure, density) are diagnosed from the conserved prognostic variables. The solver uses a third-order Runge-Kutta time-integration scheme coupled with a split-explicit 2nd-order time integration scheme for the acoustic and gravity-wave modes. 5th-order upwind-biased advection operators are used in the fully conservative flux divergence integration; 2nd-6th order schemes are run-time selectable.6th order schemes are run-time selectable.)
Model:BITM + (The dynamics of erosion and deposition are … The dynamics of erosion and deposition are schematized with a relationship, which represents a diffusion scheme that changes the bottom elevation at a rate linearly proportional to the difference between the current and the equilibrium profile, defined by the Dean's equation, and then redistributes the removed or deposited material in equal parts between the contiguous inshore and offshore locations. The phenomenon of overwash is schematized assuming that the first shoreface element of the barrier island is eroded of a quantity, which is related to the frequency of hurricanes and severe storms and to the difference between the maximum elevation of the barrier and the mean sea level.elevation of the barrier and the mean sea level.)
Model:DELTA + (The equations are from Albertson et al. (1950) and Syvitski et al. (1988).)
Model:CEM + (The evolution of the coastline is governed … The evolution of the coastline is governed by a continuity equation; the rate of horizontal shoreline change in the local cross-shore direction is proportional to the divergence of alongshore sediment flux. Alongshore sediment transport is computed via the common CERC formula, which relates alongshore sediment flux to breaking-wave approach angle and breaking wave height. Breaking-wave characteristics in each shoreline location are calculated by starting with the deep-water height and propagation direction (obtained for each time slice from the input wave file), and refracting and shoaling the waves over assumed shore-parallel contours until breaking occurs. The CERC equation also involves an empirical constant K, which can be configured by the model user. Other equations for sediment flux can easily be substituted. See Ashton and Murray (2006a) for details.See Ashton and Murray (2006a) for details.)
Model:AR2-sinuosity + (The geometry of a channel centerline is re … The geometry of a channel centerline is represented as a direction series using a second-order autoregressive formulation. The governing equation istheta(i) = b_1*theta(i-1) + b_2*theta(i-2) + epsilon(i)where theta is the channel direction, i is the centerline node index, b_1 and b_2 are coefficients, and epsilon is a random disturbance drawn from a normal distribution with a mean of zero.a normal distribution with a mean of zero.)
Model:OverlandFlow + (The key algorithms and parameters are described in length the Geoscientific Model Development paper by Adams et al., (2017).)
Model:SPACE + (The key equations and parameters are described in Shobe et al (2017, Geoscientific Model Development).)
Model:DeltaClassification + (The key methods used are: 1) Feature normalization and principal component analysis 2) Spatial clustering using GEOSOM algorithm 3) Hierarchical agglomerative clustering to built nested clusters)
Model:CVPM + (The key parameters are temperature; density; heat capacity; thermal conductivity; porosity; volume fractions of ice, unfrozen water, and air; degree of water saturation; pore-water solute type and concentration; particle radii.)
Model:1D Particle-Based Hillslope Evolution Model + (The key physical parameters are the hillsl … The key physical parameters are the hillslope length and height, as well as a parameter which specifies the underlying asymmetry in the particle dynamics. The process of determining these parameters is described in the simulation section of a corresponding paper (which can be accessed here: https://arxiv.org/abs/1801.02810).d here: https://arxiv.org/abs/1801.02810).)
Model:Quad + (The key physical parameters are: (1) the s … The key physical parameters are: (1) the sediment unit-flux, defined as the sediment input from the river network in units of volume per unit width. (2) The average water discharge per unit width. (3) The basement slope on top of which the delta develops. (4) The base-level curve. The key equations are a sediment mass balance and the boundary conditions dictated by diffusive transport (i.e., the sediment flux is proportional to the local bed slope through the fluvial diffusivity). To first order calculations, we assume the fluvial diffusivity to be half the water discharge per unit width (they both have the same units). More accurate expressions for the fluvial diffusivity can be found in Paola 2000 and Lorenzo-Trueba et al.2009. Paola 2000 and Lorenzo-Trueba et al.2009.)
Model:Meander Centerline Migration Model + (The key physical parameters of the model a … The key physical parameters of the model are the aspect ratio deal with hydraulics (geometry of the river cross section, Shields number, grain size) and geomorphology (erodibility of the floodplain surface). The model solves for the equations of Ikeda et al. JFM 1981 and Zolezzi and Seminara JFM 2001. See Bogoni et al. WRR 2017 for details.1. See Bogoni et al. WRR 2017 for details.)
Model:Erode + (The main equations are: Q = R * A^p Qs = Kf * (Q^m) * (S^n), 2D mass conservation equations for water and sediment)
Model:SWEHR + (The model couples the shallow water equati … The model couples the shallow water equations with the Green-Ampt infiltration model and the Hairsine-Rose soil erosion model. Fluid flow is also modified through source terms in the momentum equations that account for changes in flow behavior associated with high sediment concentrations. See McGuire et al. (2016, Constraining the rates of raindrop- and flow-driven sediment transport mechanisms in postwildfire environments and implications for recovery timescales) for a complete model description and details on the numerical solution of the governing equations.rical solution of the governing equations.)
Model:WDUNE + (The model is abstract. Refer to accompanyi … The model is abstract. Refer to accompanying paper and references therein: Barchyn TE, Hugenholtz CH. 2011. A new tool for modeling dune field evolution based on an accessible, GUI version of the Werner dune model. Geomorphology. Available from:http://dx.doi.org/10.1016/j.geomorph.2011.09.021Or, also, refer to original description of the model:Werner, BT. 1995. Eolian dunes: computer simulations and attractor interpretation. Geology 23, 1107-1110. Available from: http://dx.doi.org/10.1130/0091-7613(1995)023<1107:EDCSAA>2.3.CO;230/0091-7613(1995)023<1107:EDCSAA>2.3.CO;2)
Model:Badlands + (The model is mainly written in fortran and … The model is mainly written in fortran and is based on the following characteristics:- The finite volume approach from Tucker et al. (2001) based on the dual Delaunay-Voronoi framework is used to solve the continuity equation explicitly,- Node ordering is perform efficiently based on the work from Braun & Willett (2013),- A Hilbert Space-Filling Curve method algorithm (Zoltan) is used to partition the TIN-based surface into subdomains,- Drainage network partitioning is generated through METIS library.rtitioning is generated through METIS library.)
Model:Tracer dispersion calculator + (The model solves the elevation-specific eq … The model solves the elevation-specific equation of tracer mass conservation simplified for the case of an equilibrium bed. This simplification is appropriate in slowly varying non-equilibrium conditions at time scales up to 1-2 decades. Key physical parameters are the entrainment rate of particles in bedload transport, the average particle step length, the standard deviation of bed elevation change, the elevation of the maximum probability of particle entrainment, the probability functions of bed elevations and of particle entrainment in bedload transport.particle entrainment in bedload transport.)
Model:LateralVerticalIncision + (The model uses geometric laws that mimic the behaviour of Meyer-Peter Mueller (1948) sediment transport capacity laws as a function of slope and width.)
Model:Sedtrans05 + (The model uses hydrodynamics parameters, s … The model uses hydrodynamics parameters, sediment characteristics (median grain size, density, possibly pre-existing bedforms), and water characteristics (viscosity and density computed from salinity and temperature)It uses Grant and Madsen (1986) continental shelf bottom boundary layer theory. Five methods to predict sediment transport for non-cohesive sediments are offered: Einstein-Brown (Brown, 1950), Yalin (1963) and Van Rijn (1993) Engelund and Hansen (1967) and Bagnold (1963).lund and Hansen (1967) and Bagnold (1963).)
Model:CMIP + (The original dataset was created by the)
Model:PyDeCe + (The pyroclastic flow is treated as a two-c … The pyroclastic flow is treated as a two-component granular flow with >30% volume fraction of solids supported by excess pore fluid pressure in a laminar Newtonian fluid. This approach of modeling mass flows is adapted from the debris flow model of Iverson and Denlinger (2001). The model solves depth averaged mass and momentum conservation equations in 2D, with suitable source terms, to determine the thickness and velocity of the current at each point in time and space. The current is primarily driven by gravity and the motion of the current is opposed by friction and viscous resistance. A shear-rate dependent variable basal friction model is used to determine the basal friction as the flow evolves (Jop et al., 2006). A 1st order Godunov scheme with an HLLC Riemann solver is used to calculate the flux across cell interfaces (Toro, 2009) and the source terms are solved separately using an explicit Euler method.ed separately using an explicit Euler method.)
Model:SurfaceRoughness + (The surface normal vector for a given pixe … The surface normal vector for a given pixel are defined by fitting a 6-term polynomial surface to a set of DEM points within a user-specified radius of that pixel. A second user-defined neighborhood is used to then map out the local variability in the orientation of the surface normal vectors.orientation of the surface normal vectors.)