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A list of all pages that have property "Extended model description" with value "Program for backwater calculations in open channel flow". Since there have been only a few results, also nearby values are displayed.

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  • Model:Kudryavtsev Model  + (Models the temporal and spatial distributiModels 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.d surface and mean active layer thickness.)
  • Model:RAFEM  + (Morphodynamic river avulsion model, designed to be coupled with CEM and SEDFLUX3D)
  • Model:Mrip  + (Mrip consists of a matrix representing theMrip 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. slope of the bed, thus creating feedback.)
  • Model:NearCoM  + (NearCoM predicts waves, currents, sedimentNearCoM 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.tion module and sediment transport module.)
  • Model:River Network Bed-Material Sediment  + (Network-based modeling framework of Czuba Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to bed-material sediment transport.</br></br>This code is capable of reproducing the results (with some work by the end user) described in the following publications:</br></br>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.</br></br>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.</br></br>Gran, K.B., and J.A. Czuba, (2017), Sediment pulse evolution and the role of network structure,</br>Geomorphology, 277, 17-30, doi:10.1016/j.geomorph.2015.12.015.</br></br>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.</br></br>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:</br></br>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. </br></br>And an application to Clear Creek/Tushar Mountains in Utah is described in:</br></br>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.</br></br>Note: the application code and data files for Murphy et al., 2019 are included in the repository as example files.</br></br>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:</br></br>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.</br></br>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.f the code instead of this Matlab version.)
  • Model:Nitrate Network Model  + (Network-based modeling framework of Czuba Network-based modeling framework of Czuba and Foufoula-Georgiou as applied to nitrate and organic carbon on a wetland-river network.</br></br>This code is capable of reproducing the results (with some work of commenting/uncommenting code by the end user) described in the following publication:</br></br>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:10.1002/2017WR021859.4(2), 1312-1337, doi:10.1002/2017WR021859.)
  • Model:Pllcart3d  + (Nonlinear three dimensional simulations of miscible Hele-Shaw flows using DNS of incompressible Navier-Stokes and transport equations.)
  • Model:Oceananigans.jl  + (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.)
  • Model:CMFT  + (One dimensional model for the coupled longOne 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.30 min, simulation length about 100 years.)
  • Model:OTEQ  + (One-Dimensional Transport with EquilibriumOne-Dimensional Transport with Equilibrium Chemistry (OTEQ):</br>A Reactive Transport Model for Streams and Rivers</br></br>OTEQ is a mathematical simulation model used to characterize the fate and transport of waterborne solutes in streams and rivers. The model is formed by coupling a solute transport model with a chemical equilibrium submodel. The solute transport model is based on OTIS, a model that considers the physical processes of advection, dispersion, lateral inflow, and transient storage. The equilibrium submodel is based on MINTEQ, a model that considers the speciation and complexation of aqueous species, acid-base reactions, precipitation/dissolution, and sorption.</br></br>Within OTEQ, reactions in the water column may result in the formation of solid phases (precipitates and sorbed species) that are subject to downstream transport and settling processes. Solid phases on the streambed may also interact with the water column through dissolution and sorption/desorption reactions. Consideration of both mobile (waterborne) and immobile (streambed) solid phases requires a unique set of governing differential equations and solution techniques that are developed herein. The partial differential equations describing physical transport and the algebraic equations describing chemical equilibria are coupled using the sequential iteration approach. The model's ability to simulate pH, precipitation/dissolution, and pH-dependent sorption provides a means of evaluating the complex interactions between instream chemistry and hydrologic transport at the field scale.</br></br>OTEQ is generally applicable to solutes which undergo reactions that are sufficiently fast relative to hydrologic processes ("Local Equilibrium"). Although the definition of "sufficiently fast" is highly solute and application dependent, many reactions involving inorganic solutes quickly reach a state of chemical equilibrium. Given a state of chemical equilibrium, inorganic solutes may be modeled using OTEQ's equilibrium approach. This equilibrium approach is facilitated through the use of an existing database that describes chemical equilibria for a wide range of inorganic solutes. In addition, solute reactions not included in the existing database may be added by defining the appropriate mass-action equations and the associated equilibrium constants. As such, OTEQ provides a general framework for the modeling of solutes under the assumption of chemical equilibrium. Despite this generality, most OTEQ applications to date have focused on the transport of metals in streams and small rivers. The OTEQ documentation is therefore focused on metal transport. Potential model users should note, however, that additional applications are possible.that additional applications are possible.)
  • Model:OTIS  + (One-Dimensional Transport with Inflow and One-Dimensional Transport with Inflow and Storage (OTIS): A Solute Transport Model for Streams and Rivers</br></br>OTIS is a mathematical simulation model used to characterize the fate and transport of water-borne solutes in streams and rivers. The governing equation underlying the model is the advection-dispersion equation with additional terms to account for transient storage, lateral inflow, first-order decay, and sorption. This equation and the associated equations describing transient storage and sorption are solved using a Crank-Nicolson finite-difference solution.</br></br>OTIS may be used in conjunction with data from field-scale tracer experiments to quantify the hydrologic parameters affecting solute transport. This application typically involves a trial-and-error approach wherein parameter estimates are adjusted to obtain an acceptable match between simulated and observed tracer concentrations. Additional applications include analyses of nonconservative solutes that are subject to sorption processes or first-order decay. OTIS-P, a modified version of OTIS, couples the solution of the governing equation with a nonlinear regression package. OTIS-P determines an optimal set of parameter estimates that minimize the squared differences between the simulated and observed concentrations, thereby automating the parameter estimation process.tomating the parameter estimation process.)
  • Model:OpenFOAM  + (OpenFOAM (Open Field Operation and Manipulation) is a toolbox for the development of customized numerical solvers, and pre-/post-processing utilities for the solution of continuum mechanics problems, including computational fluid dynamics.)
  • Model:OTTER  + (Optimization Technique in Transient EvolutOptimization Technique in Transient Evolution of Rivers (OTTER). This models a 1D river profile while incorporating a algorithm for dynamic channel width. The channel width algorithm dynamically adjusts channel geometry in response to values of water discharge, rock-uplift/erosion, and sediment supply. It operates by calculating the current shear stress (no wide channel assumption), the shear stress if channel width is slightly larger, and shear stress for a slightly narrower channel. Using these values, erosion potential is calculated for all three scenarios (no change in width, slightly wider, slightly narrower) and the one that generates the maximum erosion rate dictates the direction of channel change. See Yanites, 2018 JGR for further information.Yanites, 2018 JGR for further information.)
  • Model:OrderID  + (OrderID is a method that takes thickness and facies data from a vertical succession of strata and tests for the presence of order in the strata)
  • Model:GeoClaw  + (Originally developed for modeling tsunami Originally developed for modeling tsunami generation, propagation, and inundation. Also used for storm surge modeling and overland flooding (e.g. dam break problems). Uses adaptive mesh refinement to allow much greater spatial resolutions in some regions than others, and to automatically follow dynamic evolution of waves or floods. Uses high-resolution finite volume methods that robustly handle wetting and drying. The package also includes tools for working with geophysical data including topography DEMs, earthquake source models for tsunami generation, and observed gauge data. The simulation code is in Fortran with OpenMP for shared memory parallelization, and Python for the user interface, visualization, and data tools. interface, visualization, and data tools.)
  • Model:PHREEQC  + (PHREEQC implements several types of aqueouPHREEQC implements several types of aqueous models: two ion-association aqueous models (the Lawrence Livermore National Laboratory model and WATEQ4F), a Pitzer specific-ion-interaction aqueous model, and the SIT (Specific ion Interaction Theory) aqueous model. Using any of these aqueous models, PHREEQC has capabilities for (1) speciation and saturation-index calculations; (2) batch-reaction and one-dimensional (1D) transport calculations with reversible and irreversible reactions, which include aqueous, mineral, gas, solid-solution, surface-complexation, and ion-exchange equilibria, and specified mole transfers of reactants, kinetically controlled reactions, mixing of solutions, and pressure and temperature changes; and (3) inverse modeling, which finds sets of mineral and gas mole transfers that account for differences in composition between waters within specified compositional uncertainty limits.pecified compositional uncertainty limits.)
  • Model:PIHM  + (PIHM is a multiprocess, multi-scale hydrolPIHM is a multiprocess, multi-scale hydrologic model where the major hydrological processes are fully coupled using the semi-discrete finite volume method. PIHM is a physical model for surface and groundwater, “tightly-coupled” to a GIS interface. PIHMgis which is open source, platform independent and extensible. The tight coupling between GIS and the model is achieved by developing a shared data-model and hydrologic-model data structure.model and hydrologic-model data structure.)
  • Model:PISM  + (PISM is a hybrid shallow ice, shallow shelPISM is a hybrid shallow ice, shallow shelf model. PISM is designed to scale with increasing problem size</br>by harnessing the computational power of supercomputing systems and by leveraging the scalable software libraries that have been developed by the high-performance computing research community. The model combines two shallow (small depth-to-width ratio) stress balances, namely the shallow-ice approximation (SIA) and the shallow-shelf approximation (SSA), which are computationally efficient schemes to simulate ice flow by internal deformation and ice-stream flow, respectively. In PISM, deformational velocities from the SIA and sliding velocities from the SSA are weighted and averaged to achieve a smooth transition from shearing flow to sliding flow.sition from shearing flow to sliding flow.)
  • Model:PRMS  + (PRMS is a modular-design modeling system that has been developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff, sediment yields, and general basin hydrology)
  • Model:PSTSWM  + (PSTSWM is a message-passing benchmark codePSTSWM is a message-passing benchmark code and parallel algorithm testbed that solves the nonlinear shallow water equations on a rotating sphere using the spectral transform method. It is a parallel implementation of STSWM to generate reference solutions for the shallow water test cases.olutions for the shallow water test cases.)
  • Model:ParFlow  + (ParFlow is an open-source, object-orientedParFlow is an open-source, object-oriented, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.rological code ARPS and the NCAR code WRF.)
  • Model:PIHMgis  + (Physically-based fully-distributed hydroloPhysically-based fully-distributed hydrologic models try to simulate hydrologic state variables in space and time while using information regarding heterogeneity in climate, land use, topography and hydrogeology. However incorporating a large number of physical data layers in the hydrologic model requires intensive data development and topology development and topology definitions.)
  • Model:TreeThrow  + (Plot scale, spatially implicit model of tree throw on hillslopes. We couple an existing forest growth model with a couple simple equations for the transport of sediment caused by tree fall.)
  • Model:PotentialEvapotranspiration  + (Potential Evapotranspiration Component calPotential Evapotranspiration Component calculates spatially distributed potential evapotranspiration based on input radiation factor (spatial distribution of incoming radiation) using chosen method such as constant or Priestley Taylor. Ref: Xiaochi et. al. 2013 for 'Cosine' method and ASCE-EWRI Task Committee Report Jan 2005 for 'PriestleyTaylor' method.</br>Note: Calling 'PriestleyTaylor' method would generate/overwrite shortwave & longwave radiation fields.ite shortwave & longwave radiation fields.)
  • Model:STVENANT  + (Predicts 1D, unsteady, nonlinear, gradually varied flow)
  • Model:FlowAccumulator  + (Provides the FlowAccumulator component whiProvides the FlowAccumulator component which accumulates flow and calculates drainage area. FlowAccumulator supports multiple methods for calculating flow direction. Optionally a depression finding component can be specified and flow directing, depression finding, and flow routing can all be accomplished together. routing can all be accomplished together.)
  • Model:QDSSM  + (QDSSM is a 3D cellular, forward numerical QDSSM is a 3D cellular, forward numerical model coded in Fortran90 that simulates landscape evolution and stratigraphy as controlled by changes in sea-level, subsidence, discharge and bedload flux. The model includes perfect and imperfect sorting modules of grain size and allows stratigraphy to be build over time spans of 1000 to million of time spans of 1000 to million of years.)
  • Model:QTCM  + (QTCMs are models of intermediate complexity suitable for the modeling of tropical climate and its variability. It occupies a niche among climate models between complex general circulation models and simple models.)
  • Model:QUAL2K  + (QUAL2K (or Q2K) is a river and stream wateQUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987). Q2K is similar to Q2E in the following respects:</br>One dimensional. The channel is well-mixed vertically and laterally.</br>* Steady state hydraulics. Non-uniform, steady flow is simulated.</br>* Diurnal heat budget. The heat budget and temperature are simulated as a function of meteorology on a diurnal time scale.</br>* Diurnal water-quality kinetics. All water quality variables are simulated on a diurnal time scale.</br>* Heat and mass inputs. Point and non-point loads and abstractions are simulated.oint loads and abstractions are simulated.)
  • Model:StreamProfilerApp  + (QuickChi enables the rapid analysis of stream profiles at the global scale from SRTM data.)
  • Model:GSFLOW-GRASS  + (Quickly generates input files for and runs GSFLOW, the USGS integrated groundwater--surface-water model, and can be used to visualize the outputs of GSFLOW.)
  • Model:RCPWAVE  + (RCPWAVE is a 2D steady state monocromatic short wave model for simulating wave propagation over arbitrary bahymetry.)
  • Model:REF-DIF  + (REF/DIF is a phase-resolving parabolic refREF/DIF is a phase-resolving parabolic refraction-diffraction model for ocean surface wave propagation. It was originally developed by Jim Kirby and Tony Dalrymple starting in 1982, based on Kirby's dissertation work. This work led to the development of REF/DIF 1, a monochromatic wave model. of REF/DIF 1, a monochromatic wave model.)
  • Model:River Erosion Model  + (REM mechanistically simulates channel bed REM mechanistically simulates channel bed aggradation/degradation and channel widening in river networks. It has successfully been applied to alluvial river systems to simulate channel change over annual and decadal time scales. REM is also capable of running Monte Carlo simulations (in parallel to reduce computational time) to quantify uncertainty in model predictions.quantify uncertainty in model predictions.)
  • Model:RHESSys  + (RHESSys is a GIS-based, hydro-ecological mRHESSys is a GIS-based, hydro-ecological modelling framework designed to simulate carbon, water, and nutrient fluxes. By combining a set of physically-based process models and a methodology for partitioning and parameterizing the landscape, RHESSys is capable of modelling the spatial distribution and spatio-temporal interactions between different processes at the watershed scale.ifferent processes at the watershed scale.)
  • Model:ROMS  + (ROMS is a Free-surface, terrain-following,ROMS is a Free-surface, terrain-following, orthogonal curvilinear, primitive equations ocean model. Its dynamical kernel is comprised of four separate models including the nonlinear, tangent linear, representer tangent linear, and adjoint models. It has multiple model coupling (ESMF, MCT) and multiple grid nesting (composed, mosaics, refinement) capabilities. The code uses a coarse-grained parallelization with both shared-memory (OpenMP) and distributed-memory (MPI) paradigms coexisting together and activated via C-preprocessing.ogether and activated via C-preprocessing.)
  • Model:UMCESroms  + (ROMS is a Free-surface, terrain-following,ROMS is a Free-surface, terrain-following, orthogonal curvilinear, primitive equations ocean model. Its dynamical kernel is comprised of four separate models including the nonlinear, tangent linear, representer tangent linear, and adjoint models. It has multiple model coupling (ESMF, MCT) and multiple grid nesting (composed, mosaics, refinement) capabilities. The code uses a coarse-grained parallelization with both shared-memory (OpenMP) and distributed-memory (MPI) paradigms coexisting together and activated via C-preprocessing.ogether and activated via C-preprocessing.)
  • Model:HydroRaVENS  + (RaVENS: Rain and Variable EvapotranspiratiRaVENS: Rain and Variable Evapotranspiration, Nieve, and Streamflow</br></br>Simple "conceptual" hydrological model that may include an arbitrary number of linked linear reservoirs (soil-zone water, groundwater, etc.) as well as snowpack (accumulation from precipitation with T<0; positive-degree-day melt) and evapotranspiration (from external input or Thorntwaite equation).</br></br>It also includes a water-balance component to adjust ET (typically the least known input) to ensure that P - Q - ET = 0 over the course of a water year.</br></br>Other components plot data and compute the NSE (Nash–Sutcliffe model efficiency coefficient).Nash–Sutcliffe model efficiency coefficient).)
  • Model:Landslides  + (Relative wetness and factor-of-safety are Relative wetness and factor-of-safety are based on the infinite slope stability model driven by topographic and soils inputs and recharge provided by user as inputs to the component. For each node, component simulates mean relative wetness as well as the probability of saturation based on Monte Carlo simulation of relative wetness where the probability is the number of iterations with relative wetness >= 1.0 divided by the number of iterations. Probability of failure for each node is also simulated in the Monte Carlo simulation as the number of iterations with factor-of-safety <= 1.0 divided by the number of iterations.y <= 1.0 divided by the number of iterations.)
  • Model:RouseVanoniEquilibrium  + (Rouse-Vanoni Equilibrium Suspended Sediment Profile Calculator)
  • Model:SLEPIAN Delta  + (Routines pertaining to the paper published as: doi: 10.1073/pnas.1206785109)
  • Model:SLEPIAN Alpha  + (Routines pertaining to the paper published as: doi: 10.1137/S0036144504445765)
  • Model:SLEPIAN Charlie  + (Routines pertaining to the paper published as: doi: 10.1111/j.1365-246X.2008.03854.x)
  • Model:SLEPIAN Echo  + (Routines pertaining to the paper published as: doi: 10.1016/j.acha.2012.12.001)
  • Model:SLEPIAN Bravo  + (Routines pertaining to the paper published as: doi: 10.1111/j.1365-246X.2006.03065.x)
  • Model:Plume  + (Run a hypopycnal sediment plume)
  • Model:Bing  + (Run a submarine debris flow)
  • Model:SBEACH  + (SBEACH is a numerical simulation model forSBEACH is a numerical simulation model for predicting beach, berm, and dune erosion due to storm waves and water levels. It has potential for many applications in the coastal environment, and has been used to determine the fate of proposed beach fill alternatives under storm conditions and to compare the performance of different beach fill cross-sectional designs.ferent beach fill cross-sectional designs.)
  • Model:SEDPAK  + (SEDPAK provides a conceptual framework forSEDPAK provides a conceptual framework for modeling the sedimentary fill of basins by visualizing stratal geometries as they are produced between sequence boundaries. The simulation is used to substantiate inferences drawn about the potential for hydrocarbon entrapment and accumulation within a basin. It is designed to model and reconstruct clastic and carbonate sediment geometries which are produced as a response to changing rates of tectonic movement, eustasy, and sedimentation The simulation enables the evolution of the sedimentary fill of a basin to be tracked, defines the chronostratigraphic framework for the deposition of these sediments, and illustrates the relationship between sequences and systems tracts seen in cores, outcrop, and well and seismic data.cores, outcrop, and well and seismic data.)
  • Model:SELFE  + (SELFE is a new unstructured-grid model desSELFE is a new unstructured-grid model designed for the effective simulation of 3D baroclinic circulation across river-to-ocean scales. It uses a semi-implicit finite-element Eulerian-Lagrangian algorithm to solve the shallow water equations, written to realistically address a wide range of physical processes and of atmospheric, ocean and river forcings. of atmospheric, ocean and river forcings.)