ABSTRACT:

Model stream avulsion as random walk

ABSTRACT:

DHSVM is a distributed hydrology model that was developed at the University of Washington more than ten years ago. It has been applied both operationally, for streamflow prediction, and in a research capacity, to examine the effects of forest management on peak streamflow, among other things.

ABSTRACT:

DR3M is a watershed model for routing storm runoff through a Branched system of pipes and (or) natural channels using rainfall as input. DR3M provides detailed simulation of storm-runoff periods selected by the user. There is daily soil-moisture accounting between storms. A drainage basin is represented as a set of overland-flow, channel, and reservoir segments, which jointly describe the drainage features of the basin. This model is usually used to simulate small urban basins. Interflow and base flow are not simulated. Snow accumulation and snowmelt are not simulated.

Input Parameters:
aily precipitation, daily evapotranspiration, and short-interval precipitation are required. Short-interval discharge is required for the optimization option and to calibrate the model. These time series are read from a WDM file. Roughness and hydraulics parameters and sub-catchment areas are required to define the basin. Six parameters are required to calculate infiltration and soil-moisture accounting. Up to three rainfall stations may be used. Two soil types may be defined. A total of 99 flow planes, channels, pipes, reservoirs, and junctions may be used to define the basin.

Output Parameters:
The computed outflow from any flow plane, pipe, or channel segment for each storm period may be written to the output file or to the WDM file. A summary of the measured and simulated rainfall, runoff, and peak flows is written to the output file. A flat file containing the storm rainfall, measured flow (if available), and simulated flow at user selected sites can be generated. A flat file for each storm containing the total rainfall, the measured peak flow (if available), and the simulated peak flow for user-selected sites can be generated.

Process:
The rainfall-excess components include soil-moisture accounting, pervious-area rainfall excess, impervious-area rainfall excess, and parameter optimization. The Green-Ampt equation is used in the calculations of infiltration and pervious area rainfall excess. A Rosenbrock optimization procedure may be used to aid in calibrating several of the infiltration and soil-moisture accounting parameters. Kinematic wave theory is used for both overland-flow and channel routing. There are three solution techniques available: method of characteristics, implicit finite difference method, and explicit finite difference method. Two soil types may be defined. Overland flow may be defined as turbulent or laminar. Detention reservoirs may be simulated as linear storage or using a modified-Puls method. Channel segments may be defined as gutter, pipe, triangular cross section, or by explicitly specifying the kinematic channel parameters alpha and m.

ABSTRACT:

Calculates the flow velocity and depth based on the gradually varied flow equation of an open channel.

ABSTRACT:

GEOtop accommodates very complex topography and, besides the water balance integrates all the terms in the surface energy balance equation. For saturated and unsaturated subsurface flow, it uses the 3D Richards’ equation. An accurate treatment of radiation inputs is implemented in order to be able to return surface temperature.
The model GEOtop simulates the complete hydrological balance in a continuous way, during a whole year, inside a basin and combines the main features of the modern land surfaces models with the distributed rainfall-runoff models.
The new 0.875 version of GEOtop introduces the snow accumulation and melt module and describes sub-surface flows in an unsaturated media more accurately. With respect to the version 0.750 the updates are fundamental: the codex is completely eviewed, the energy and mass parametrizations are rewritten, the input/output file set is redifined.
GEOtop makes it possible to know the outgoing discharge at the basin's closing section, to estimate the local values at the ground of humidity, of soil temperature, of sensible and latent heat fluxes, of heat flux in the soil and of net radiation, together with other hydrometeorlogical distributed variables. Furthermore it describes the distributed snow water equivalent and surface snow temperature.
GEOtop is a model based on the use of Digital Elevation Models (DEMs). It makes also use of meteorological measurements obtained thought traditional instruments on the ground. Yet, it can also assimilate distributed data like those coming from radar measurements, from satellite terrain sensing or from micrometeorological models.

ABSTRACT:

Glimmer is an open source (GPL) three-dimensional thermomechanical ice sheet model, designed to be interfaced to a range of global climate models. It can also be run in stand-alone mode. Glimmer was developed as part of the NERC GENIE project (www.genie.ac.uk). It's development follows the theoretical basis found in Payne (1999) and Payne (2001). Glimmer's structure contains numerous software design strategies that make it maintainable, extensible, and well documented.

ABSTRACT:

IceFlow simulates ice dynamics by solving equations for internal deformation and simplified basal sliding in glacial systems. It is designed for computational efficiency by using the shallow ice approximation for driving stress, which it solves alongside basal sliding using a semi-implicit direct solver. IceFlow is integrated with GRASS GIS to automatically generate input grids from a geospatial database.

ABSTRACT:

Predicts 1D, unsteady, nonlinear, gradually varied flow

Input parameters (ASCII):
Number of cross sections, Time (s) and space (m) descretisation steps, Chezy friction coefficient (m**1/2 s**-1), Period (s) and amplitude (m) of incoming waves, Number of time steps desired, Channel width at the Ith cross section (m), Still water depth (m)

Output parameters (ASCII):
water depths (m), water discharges (m3/s), free surface elevation with respect to the SWL (m)

ABSTRACT:

Landlab is a Python software package for creating, assembling, and/or running 2D numerical models. Landlab was created to facilitate modeling in earth-surface dynamics, but it is general enough to support a wide range of applications. Landlab provides three different capabilities:
(1) A DEVELOPER'S TOOLKIT for efficiently building 2D models from scratch. The toolkit includes a powerful GRIDDING ENGINE for creating, managing, and iterative updating data on 2D structured or unstructured grids. The toolkit also includes helpful utilities to handle model input and output.

(2) A set of pre-built COMPONENTS, each of which models a particular process. Components can be combined together to create coupled models.

(3) A library of pre-built MODELS that have been created by combining components together.

To learn more, please visit http://landlab.github.io

Input Parameters:
Because this is a toolkit for model building, there are no set input parameters. Rather, developers use the code to create their own models, with their own unique inputs.
The ModelParameterDictionary tool provides formatted ASCII input for model parameters. The I/O component also handles input of digital elevation models (DEMs) in standard ArcInfo ASCII format.

Output Parameters:
Gridding component provides ASCII and/or netCDF output of grid geometry.

ABSTRACT:

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.

ABSTRACT:

The Green-Ampt method of infiltration estimation.

ABSTRACT:

RHESSys 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.

ABSTRACT:

This process component is part of a spatially-distributed hydrologic model called TopoFlow, but it can now be used as a stand-alone model.

ABSTRACT:

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.

ABSTRACT:

Gridded water balance model using climate input forcings that calculate surface and subsurface runoff and ground water recharge for each grid cell. The surface and subsurface runoff is propagated horizontally along a prescribed gridded network using Musking type horizontal transport.

ABSTRACT:

An extension of the WBMplus (WBM/WTM) model. Introduce a riverine sediment flux component based on the BQART and Psi models.

ABSTRACT:

This dataset contains daily raw water treatment plant operational data and Oklahoma Mesonet weather data collected from 2011–2024. It includes inflow, pH, turbidity, alkalinity, alum dosage, and daily aggregated weather attributes such as TMAX, TMIN, humidity, and pressure. Data is provided in raw, pre-cleaning form for reproducibility.

ABSTRACT:

This HydroShare collection contains three resources. The two datasets in the collection were used in the study ‘Artificial Intelligence to Assist Small Water Treatment Plant Operations.’ The first dataset (Raw Data) contains historical water treatment and Oklahoma Mesonet weather records from 2011–2024 in unprocessed form. The second dataset (Cleaned Data) is the processed and merged version of the same data, cleaned for duplicates, and missing values were removed. Together, they provide a transparent data pipeline from raw input to AI-ready dataset for modeling alum dosing.

ABSTRACT:

This resource contains a Python script used to clean and preprocess the alum dosage dataset from a small Oklahoma water treatment plant. The script handles missing values, removes outliers, merges historical water quality and weather data, and prepares the dataset for AI model training.

ABSTRACT:

This dataset was developed to support research on predicting alum dosage in small water treatment plants. It combines daily plant records with weather data, including maximum temperature (TMAX). To make the data reliable for analysis and modeling, outliers and incorrect readings were carefully removed using logical and domain-based rules.

Records with clearly impossible or error values, such as extremely high or negative numbers, were deleted. Each variable was kept within realistic operating limits—for example, alum between 0 and 3500 mg/L, hardness between 5 and 1000 mg/L, and alkalinity between 2 and 1000 mg/L. Unusual readings like pH = 0.54 were also removed. Missing value rows were entirely removed from the dataset.

Through this cleaning process, the dataset became consistent, accurate, and ready for machine-learning models that can better predict chemical dosing and support safer, more efficient water treatment operations.