GRASS GIS - Simulation Models
Current Topics: erosion modelling, hydrological modelling, floodplain analysis,
Erosion modelling: ANSWERS - r.answers
- The acronym for Areal Non-point Source Watershed Environmental Response
Simulation model. This event-oriented, distributed parameter model is
designed for erosion, sediment and water quality control planning on
complex, agricultural watersheds.
- It should normally be distributed in your GRASS-package. Note: ANSWERS is
written in C and FORTRAN, and will require a C compiler and a FORTRAN
compiler such as f77.
page at Purdue
- GRASS man page r.answers
Erosion modelling: AGNPS 5.0
- AGricultural Non-Point Source (AGNPS) is a distributed parameter model
developed by Agricultural Research Service (ARS) scientists and engineers. It
predicts soil erosion and nutrient transport/loadings from agricultural
watersheds for real or hypothetical storms i.e., it's an event-based model.
Erosion modeling is built upon the USLE applied on a storm basis; thus, it uses
the EI-index for single storm events. Its hydrology is based on the Soil
Conservation Service Curve Number technique. AGNPS uses another ARS developed
model named CREAMS to predict nutrient/pesticide and soil particle size
generation and interaction. Here is a AGNPS Page.
Some help about using AGNPS can be found here.
Note: AGNPS 5.0 is written in C.
- GRASS man pages: r.agnps50.input,
- Bragadin, G.L., Franchini, M., Morgagni, A., Todini, E. (1993): Agricultural
non-point source nutrient loadings estimated by means of an extended version
of AGNPS. The Bidente-Ronco case study - Part I. INGEGNERIA AMBIIENTALE,
Vol.22, Nr.9, S. 455
- Mitchell, J.K., Engel, B.A., Srinivasan,R., Wang, S.S.Y. (1993): Validation of AGNPS
for Small Watersheds Using an Integrated AGNPS/GIS System. WATER RESOURCES
BULLETIN- AMERICAN WATER RESOURCES ASSOCIATION, Vol.29, Nr.5, S. 833
- Robert Alton Young, C.A. Onstad, D.D. Bosch, W.P. Anderson. (1989)
AGNPS: A nonpoint-source pollution model for evaluating agricultural
watersheds. Jour. of Soil and Water Conservation. v44, n2. ISSN 0022-4561
- Srinivasan, R. and B.A. Engel, (1991), A Knowledge Based Approach
to Extract Input Data From Gis, ASAE Paper No. 91-7045, American
Society of Agricultural Engineers, St. Joseph, Michigan.
- Srinivasan, R. and B.A. Engel, (1991), GIS: A Tool For Visualization
and Analyzation, ASAE Paper No. 91-7574, ASAE, St. Joseph, Michigan.
- Srinivasan, R., Engel, B.A., Wright, J.R., Lee, J.G.(1994):
The Impact of GIS-derived Topographic Attributes on the Simulation of
Erosion Using AGNPS. APPLIED ENGINEERING IN AGRICULTURE , Vol.10,
Nr.4, S. 561
Erosion modelling: KINEROS - r.kineros
Rainfall-runoff modelling: TOPMODEL - r.topmodel
- TOPMODEL is a rainfall-runoff model that bases its distributed
predictions on an analysis of catchment topography. The model predicts
saturation excess and infiltration excess surface runoff and subsurface
stormflow. Since the first article was published about the model in 1979
there have been many different versions. The idea has always
been that the model should be simple enough to be modified by the user so
that the predictions conform as far as possible to the user's perceptions
of how a catchment works. The distributed outputs from the model
help in such assessments.
- TOPMODEL page at
- GRASS man page r.topmodel
- GRASS man page r.topidx
- TopModel Bibliography
Storm water runoff: r.water.fea
- r.water.fea is an interactive program that allows the user to simulate
storm water runoff analysis using the finite element numerical technique.
Infiltration is calculated using the Green and Ampt formulation. r.water.fea
computes and draws hydrographs for every basin as well as at stream junctions
in an analysis area. It also draws animation maps at the basin level. The
software is available within GRASS 4.x/5.x.
developed at University of Oklahoma by Dr. B.E. Vieux
- GRASS man page r.water.fea
Hydrologic modelling: r.hydro.CASC2D
page at University of Connecticut
- r.hydro.CASC2D is a physically-based, distributed, raster
hydrologic model which simulates the hydrologic response of a watershed
subject to a given rainfall field. Input rainfall is allowed to vary in
space and time. Major components of the model include interception,
infiltration, and surface runoff routing. Interception is a process whereby
rainfall is retained by vegetation. Interception is estimated using an
empirical three parameter model. Infiltration is the process whereby
rainfall or surface water is pulled into the soil by capillary and
gravity forces. The Green and Ampt equation with four parameters is applied
to model the event-based infiltration. For continuous soil moisture
accounting, redistribution of soil moisture can also be simulated whenever
the non-intercepted rainfall intensity falls below the saturated hydraulic
conductivity of the soil. The redistribution option requires two more soil
hydraulic parameters. Excess rainfall becomes surface runoff and is routed
as overland flow and subsequently as channel flow. The overland flow routing
formulation is based on a two-dimensional explicit finite difference (FD)
technique, while two different FD techniques, one explicit and
one implicit, provide options for routing one-dimensional channel flow.
Through a step function, a depression depth may be specified, below which no
overland flow will be routed.
- GRASS man page
SWAT hydrologic model
The Soil and Water Assessment Tool (SWAT) is the hydrologic model
used in the SWAT/GRASS linkage (USDA/Arnold and others, 1995). SWAT
is a continuous-time, basin-scale hydrologic model capable of
complex long-term simulations including hydrology, pesticide and
nutrient cycling, and erosion and sediment transport. It is a river basin scale model
developed to quantify the impact of land management practices in
large, complex watersheds. SWAT is a public domain model actively
supported by the USDA Agricultural Research Service at the
Grassland, Soil and Water Research Laboratory in Temple, TX.
Watershed Calculation: r.watershed
Floodplain Analysis: f.input etc.
- f.input reads the results of the HEC-2 Water Surface Profile model
and generates a vector map of water surface elevations at hydraulic
sections. The user supplies to f.input a vector map of the hydraulic
cross sections used in the HEC-2 model along with the HEC-2 model
- f.econ takes as input the results of f.wsurf along with a
user-supplied vector map of building sites and two ASCII files of
economic data. As output f.econ generates a vector map of total
damage to each building in the floodplain along with a summary ASCII
report of flood damages categorized by building types (residential,
public, ...) and damage type (structure or content). f.econ also
reports areal extent of flooding.
- f.reach provides floodwater statistics, including areal extent of
flooding, average flood depth, and volume of water, calculated on a
Landscape Analysis: r.le
Postscript documentation (check also the
related manual pages)
- Since the 1970s, with the availability of satellite data, there has
been an increasing interest in the structure of the earth on the scale of kilometers
or hundreds of kilometers.
Landscape ecology is a multi-disciplinary pursuit, involving geographers,
biologists, sociologists, remote sensors, and many others. The focus
of landscape ecology is on the dynamics and structure of the biosphere,
including human activities, on the scale of hundreds of meters to
kilometers (Risser et al. 1984; Forman and Godron 1986; Urban et al. 1987).
The science of landscape ecology expanded rapidly in the 1980s, and
methods for the quantitative analysis of landscape structure also were
developed (e.g. Mead et al. 1981; Gardner et al. 1987; Milne 1988;
Griffiths and Wooding 1988), yet there is no generally for the
quantitative analysis of landscape structure that will work within a
geographical information system (GIS).
The r.le programs have been designed to provide software for calculating
a variety of common quantitative measures of landscape structure. The
programs can be used to analyze the structure of nearly any landscape.
The r.le programs are designed for analyzing landscapes
composed of a mosaic of patches, but, more generally, these programs are
capable of analyzing any two-dimensional raster or array whose entries are
integer values. The r.le programs have options for controlling the shape,
size, number, and distribution of sampling areas used to
collect information about the landscape. Sampling area shapes can be
square, or rectangular with any length/width ratio or can be circular with
any radius. The size of sampling areas can be changed, so that the landscape
can be analyzed at a variety of spatial scales simultaneously.
Sampling areas may be distributed across the landscape in a random,
systematic, or stratified-random manner, or as a moving window. The r.le
programs can calculate a number of measures that produce single values as
output (e.g. mean patch size in the sampling area), as well as measures that
produce a distribution of values as output (e.g. frequency distribution of
patch sizes in the sampling area) (Table 1), and it is also possible to output tables of data about selected
attributes (e.g., size, shape, amount of perimeter) of individual patches, as
well as to make new maps of patch attributes. The programs include no
options for graphing or statistically analyzing the results of
the analyses. External software must be used.
Wildfire spread simulation: r.ros/r.spread/r.spreadpath
- This WIldfire SPread Simulation, WiSpS, package contains three GRASS
programs r.ros, r.spread and r.spreadpath
- r.ros (for wildfire spread simulation) - Generates three, or
four raster map layers showing 1) the base (perpendicular)
rate of spread (ROS), 2) the maximum (forward) ROS, 3) the
direction of the maximum ROS, and optionally 4) the maximum
potential spotting distance.
- r.spread - Simulates elliptically anisotropic spread on a
graphics window and generates a raster map of the cumulative
time of spread, given raster maps containing the rates of
spread (ROS), the ROS directions and the spread origins. It
optionally produces raster maps to contain backlink UTM
coordinates for tracing spread paths.
- r.spreadpath - Recursively traces the least cost path
backwards to cells from which the cumulative cost was
- GRASS man page
- GRASS man page
- GRASS man page