The RZWQM has been developed of the past ten years by a team of ARS scientists. A majority of the team members are part of the present Great Plains Systems Research Unit , Fort Collins, CO. Recently, some parts of the model have been revised and enhanced with cooperation of the ARS Northwest Watershed Research Laboratory, Boise, ID, and the ARS Nematode Research Laboratory, Tifton, GA.

Root Zone Water Quality Model (RZWQM) simulates major physical, chemical, and biological processes in an agricultural crop production system. RZWQM is a one-dimensional (vertical in the soil profile) process-based model that simulates the growth of the plant and the movement of water, nutrients and agro-chemicals over, within and below the crop root zone of a unit area of an agricultural cropping system under a range of common management practices. The model includes simulation of a tile drainage system.

The primary use of RZWQM will be as a tool for assessing the environmental impact of alternative agricultural management strategies on the subsurface environment. These alternatives may include: conservation plans on field-by- filed basis; tillage and residue practices; crop rotations; planting date and density; and irrigation- , fertilizer- , and pesticide-scheduling (method of application, amounts and timing). The model predicts the effects of these management practices on the movement of nitrate and pesticides to runoff and deep percolation below the root zone. That is, the model predicts the potential for pollutant loadings to the groundwater thus allowing an assessment of nonpoint-source pollutant impacts on surface and ground water quality.

RZWQM consists of six major scientific submodules or processes that define the simulation program, a Numerical Grid Generator, and an Output Report Generator. Interaction between these programs is achieved through the use of seven input datafiles and three generated output files. The user can create and modify input files using a commercial editor. The model generators three general output files with twenty-five optional debugging output files that provide detailed results generated by the model. The Output Report Generator uses model results to create summary tables and publication quality graphical output in 2- and 3-dimensional formats. The most recent version of the model will have a Windows 95 user interface.

1. Physical processes include a large number of hydrologic processes; infiltration; chemical transport during infiltration; chemical transport to runoff during rainfall, water and chemical flow through soil matrix and macropores (i.e., root and worm channels), soil heat flow; fluctuating water table; tile drain, bare and residue-covered soil evaporation; crop transpiration; and soil water and chemical redistribution between rainfall and irrigation events. Snow accumulation and melt are also considered.
2. Plant growth processes predict the relative response of plants (corn, soybean, wheat) to changes in environment. Environmental changes can be manifest either as normal variations in climatic variables or by differences in management practices. The model simulates carbon dioxide assimilation, carbon allocation, dark respiration, periodic tissue loss, plat mortality, root growth, water and nutrient (currently only N) uptake.
3. Soil chemical processes consist of the soil inorganic environment in support of nutrient processes, chemical transport, and pesticide processes. The chemical state of the soil is characterized by soil pH, solution concentrations of the major ions, and adsorbed cations on the exchange complex. The model is capable of handling soil solution chemistry across a wide range of soil pH.
4. Nutrient processes define carbon and nitrogen transformation within the soil profile. Given initial levels of soil humus, crop residues, other organics, and nitrate and ammonium concentrations, the model simulates mineralization, nitrification, immobilization, denitrification, and volatilization of appropriate nitrogen.
5. Pesticide processes include the transformations and degradation of pesticides on plant surfaces, plant residue, the soil surface, and in soil profile. Given the plant, crop residue, soil and pesticide characteristics, coupled with environmental conditions, the model simulates the fate of pesticides above and within the soil. Adsorption coefficients are updated daily to account for variations in organic matter decomposition and bulk density changes. Degradation algorithms allow for 1st order, 2 compartment/ 1st order, specific pathway, and daughter product dissipation.
6. Management processes consist of description of management activities influencing the state of the root zone. It includes tillage practices and the impacts on surface roughness, soil bulk density, and macroporosity; fertilizer, pesticide, and manure applications; crop planting; irrigation scheduling for flood furrow, sprinkler, and drip systems; and BMP algorithms for dynamic nitrogen-rate determination. Soil surface reconsolidation as a function of time, rainfall, and tillage. Decomposition and bioincorporation of surface residues as affected by water content and temperature, to describe ridge-tilled and no-tilled systems.

The crops parameterized are limited to corn, soybean and wheat.
Both input and output are in metric units.
The complexity of the processes and the need to interpret model results favor the technical staff of most agencies as model users.
Frozen soil dynamics are not considered.
Rainfall is entered as break point increments
A fairly detailed description of the soil profile and initial state has to be known to give good simulation response for the system.

The documentation and the model are currently being prepared for commercialization through a Cooperative Research and Development Agreement with the Water Resources Publications, Englewood, CO. In the meantime, information on the model is available upon request from the Great Plains System Research Unit by contacting the Research Leader.

A special research version will be available soon which will have a complete balanced solution for the heat and water balance equations which included frozen soil conditions
Expand the current management system to allow for regional evaluation of Best Management Practices (BMP's) in the Midwest cornbelt over long-term simulations (> 10 years).
Incorporation of the CROPGRO families of crop simulation models.
Overland flow and erosion with chemical transport processes.
Link to GIS system to study spatially distributed systems such as those on the farm scale.
MS Windows interface.

80386 or better CPU based computer with math coprocessor
Hard disk with at least 10 megabytes free space
Floppy disk drive capable of reading high density formatted disks (5-1/4" or 3-1/2")
MS-DOS operating system (Ver. 5.0 or later)
At least 4 megabytes of RAM with 640 kilobytes of conventional memory
Graphic display card (VGA, EGA, or better)

RQWZM Publications (PDF)
Applications of the Root Zone Water Quality Model (PDF)

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Great Plains System Research Unit (GPSR) Fort Collins, CO; division of the U.S. Department of Agriculture, Agricultural Research Service, Northern Plains Area, (USDA-ARS, NPA)

Colorado State University, Agricultural Economics Dept. Fort Collins, CO

GPFARM is a simulation model computer application. It incorporates state of the art knowledge in agronomy, animal science, economics, weed science and risk management into a user-friendly, decision support tool. Producers, agricultural consultants, action agencies and scientists can utilize GPFARM to test alternative management strategies that may in turn lead to sustainable agriculture, a reduction in pollution, or maximum economic return. GPFARM Express contains default projects to allow users to quickly set up their operations.

GPFARM Decision Support System (DSS) Objective:
Develop a resource management decision support system (DSS) that is capable of simulating and analyzing 10-50 year farm/ranch production plans with respect to water, nutrient, and pest management along with their associated economic and environmental risks.

GPFARM DSS Benefits:
GPFARM integrates state of the art agricultural science knowledge with associated economic and environmental analysis into a whole-enterprise evaluation. Results from the DSS provide agricultural consultants, producers, and action agencies with information for making management decisions that promote sustainable agriculture.

GPFARM provides feedback concerning the most effective technology and assists in determining areas requiring further research and development. This is an evolutionary process that ties research and technology transfer closely together.

GPFARM serves to bring scientists from different disciplines together with producers and consultants to solve complex problems in agriculture. Products within GPFARM:

• A user-friendly, farm/ranch simulation model that produces output for various agricultural production systems and management options with respect to economics, environmental impact and sustainability.
• A detailed whole farm/ranch economic analysis package (PAL Budgeting Program).
• A web based, encyclopedic agricultural information system.
• A stand-alone weed management model (WISDEM).
• Tools to analyze weed pressure effects and N fertilizer requirements.
• Analysis tools for results including output data visualization, indices and the Multiple
• Criterion Decision Making model.
• Spatial data visualization tools.

Production economics and environmental impacts are accounted for in order to aid the producer in assessing the effects of alternate farm/ranch management strategies before they are implemented. This is achieved via:

• Soil-crop-animal simulation modules are used to assess environmental impacts. Biological, chemical, and physical processes are simulated including nutrient cycling, uptake, and leaching; surface and subsurface pesticide transport; evapotranspiration; runoff; deep percolation; infiltration; plant growth; and soil erosion by water.
• Microsoft Access relational databases are used for soils, land use, climate, management options, and model parameters.
• Farm enterprise budgeting procedures are used to determine farm profitability in terms of net farm income.
• Farm/Ranch Management Scenario results can be viewed in the form of graphs, tables, reports and scenario comparison indices.
• GPFARM Express comes with eight predefined projects which makes it easier to set up your operations. Historical and generated climate files are included as are default equipment lists. You can make adjustments to the predefined projects to customize them to your operation and be setup in a shorter time frame.
• The Information System for GPFARM provides the user access to agricultural databases, research and extension fact sheets, and other pertinent commercial, state, and federal sources of information through links to Internet sites.
• The Information System is accessible at the following web site: (http://infosys.ars.usda.gov). Enter the information and press the submit button. Then save it to your hard drive.
• It is also available on the GPSR Home page found at: http://gpsr.ars.usda.gov. Click on the GPFARM Information System link.
• It is included on the GPFARM CD and can be copied to the GPFARM directory on your hard drive.
• GPFARM is developed with Microsoft Visual C++ to run on PC compatible Pentium machines using the Microsoft Windows Graphical User Interface (GUI) environment. A multimedia, on-line help system assists users with interactive data entry and program information.
• An online Help System is packaged with GPFARM. It is in HTML format and contains a Glossary, Related Topics button and many links to relative websites.

Installation Options

• GPFARM must be installed off the distribution CD. Contact information for requesting a FREE CD.

GPFARM Express

• This is the full version of GPFARM but it is packaged with several predefined projects that will speed up the set up of a user's operation. Each project can be customized to fit the user's own operation.
• Eight cropping projects and one rangeland project are currently included. Each project is set up with 2400 acres divided evenly between each crop in the rotation.
• A default equipment list is included as are several historical and generated climate files.

Farm/Ranch

• Sketching the Farm/Ranch management unit layout is now optional.
• Wizards are included to aid in setting up the Farm/Ranch and Management Units.

Simulation Dates

• GPFARM can start or end on any day of the year. Each scenario contains its own climate. When many scenarios are added to the simulation queue for a given simulation period all scenario climates are checked for date compliance, i.e. do the start and end dates fall within the climate time period?
• Input variables with the word "Initial" should reflect the state of that variable on the starting date of the simulation.

Climate

• Historical and generated climate is available based on climate stations located in the GPFARM delivery area (Eastern Colorado, Eastern Wyoming, Western Nebraska and Western Kansas).
• Several historical and generated climate files are available with the predefined projects in GPFARM Express.

Economics

• The Economic spreadsheet results were reorganized into a Whole Farm Summary report, several Crop Reports and a Range Enterprise Budgeting report for ease of use.
• The Economic Results option now includes Range and Crop Breakeven Analyses on output.
• Operating Interest has been added to range economics.
• Economic values in GPFARM Express are left at the default value settings. These can be edited to suit an individual's operation.

Management Unit

• A management unit is defined as either cropland type which grows an agricultural crop or rangeland which grows rangeland (native forage) for the crop.
• A pictorial view of management activity is provided in the Operations section.

Soils

• The user may override soil layer information to represent their conditions. For example, the user can override the water content values that load from a GPFARM database. Several fields corresponding to water content must be changed. These include:
  • Plant Available Water
  • Water Content at -1/3 Bar
  • Water Content at -15 Bar
  • Water Content must be entered already adjusted for coarse fragments.

Crops

• Available Crops: (both dryland and irrigated types to simulate varieties)
  • Winter Wheat
  • Corn
  • Proso Millet
  • Foxtail Millet Hay (single harvest)
  • Fallow
  • Sunflower - Oil (new)
  • Sunflower - Confectionery (new)
  • Sorghum (new)

Management Operation Options and Cropping Systems

• Events Over Time allows the entry of different management events over a maximum of 20 years (i.e., management events are not repeated from year to year). Events Over Time is particularly useful when making validation test runs.
• Within a scenario, the type of management event entry (Events Over Time or Crop Rotation) must be kept the same throughout the Farm/Ranch layout.
• Rainfall and Tillage effects on Surface Random Roughness have been added.
• The Crop Module response to planting density and senescence has been added.
• The simulated root zone has been set to the deepest rooted crop in the crop rotation and therefore varies from MU to MU.

Irrigation Scheduling

• Irrigation can be scheduled for a single event or by interval.
• The Interval option lets the user schedule irrigation by specifying an amount, duration, interval, and time period for irrigation. The interface will generate the events for the time period.

Nutrients

• Nutrient additions naturally occurring in rainfall and irrigation have been added.
• Nutrients can be added through N inputs in the irrigation properties screen.

Range/Livestock

• Soil loss due to water and wind erosion on rangelands has been added.
• Rangeland forage production is affected by water stress but assumes no nutrient stress at this time.
• Range Output by year is available at the farm/ranch level for animal products and feed resources used.
• Range Output by year is available at the management unit level for runoff erosion and peak standing forage biomass.
• Emergency feed supplement bins have been added with the ability to refill once a year.
• A Least Cost Feed Ration calculation for available supplement has been added.

Output Visualization & Reporting

• Enhancements on Graphical Display of Output for the Whole Farm, Cropping MUs and Rangeland MUs are available under Farm/Ranch Window: Evaluate/Simulation Model Results/Graphical Display.
• Spatial Analysis - This is used to display spatial information, averaged over time for selected variables. Spatial Setup is used to modify the display of spatial information for crops. It is available under Farm/Ranch Window: Evaluate/Simulation Model Results/Spatial Analysis.

Installation

• Be sure to un-install any previous version of GPFARM on your machine.
• If you are installing under Windows XP Home, after installing GPFARM go to the GPFARM directory and right click. Go into properties and click on sharing. The GPFARM directory needs to be shared on Windows XP Home for GPFARM to function normally.

Farm/Ranch

• Each Farm/Ranch must have at least one Management Units (MU) for simulation.
• The total number of MU on a Farm/Ranch is limited to 60.
• An MU must have a type of cropland or rangeland.
• The maximum simulation period is fifty years. The simulation can start on any day, however, the start must occur before the first event planned on the farm/ranch's MU operations. An end date before the last day of the year will not have annual output for that year.
• A soil of less than one foot cannot be simulated.

Management Unit Operations

• Each planting event must also have a harvest event scheduled.
• Operations are implemented at the beginning of the day for which they are entered.
• Fallow must have start and stop events indicating the beginning and ending of the fallow period. GPFARM will output a yield of zero for this period.
• Irrigation may be an entered event or scheduled by a fixed interval, where amount of water added, duration, frequency and time period are specified.

Animal Simulation

• Limited to cow-calf operations only. The initial herd numbers set a fixed stocking rate for the simulation.
• Grazing is not allowed on growing crops or crop residues.
• Animal Movement (herd on and off events) are allowed on rangeland management units only and only a whole herd movement is allowed.
• An optional Least Cost Feed Ration may be calculated at the start of the run from available feed and it is used for the length of the simulation.
• Supplement feed bins:
  • Maximum allowed is five.
  • All are available according to the least cost or user specified ration percentage.
  • Supplement bins are filled annually with the Buy Supplement event. They are refilled once during the year when empty with emergency feed which is assessed at a higher cost.
• Three sale dates are allowed for: Open Cows, Heifer Calves, Steer Calves.
• The Program defaults to selling Open Cows.
• Heifers are retained as replacements for the cow herd. These culled cows are not included in the sale of open cows.

Crop Type

• Available crop types include: Winter Wheat, Corn, Fallow, Proso Millet, Foxtail Millet hay, Sunflowers and Sorghum including irrigated and dryland varieties where appropriate. All rotations and possible weed population dynamics with these rotations are simulated.
• Crops not listed above and perennials are not currently handled.
• If you want to change varieties, you must reselect planting and harvest events for existing projects.

Erosion

• Only soil erosion from overland flow of water is available on croplands and rangelands.
• Soil erosion due to wind is simulated for cropland and rangeland, although the modules need validation testing.

Nutrient

• Fertigation applications are not simulated. However, the nitrogen content of irrigation water can be input and simulated via an irrigation event.
• Inorganic fertilizers and organics in the form of manure are simulated. Other organic forms are not available.
• Phosphorus simulation is not available.

Soil System

• User entered organic matter or initial NO3-N must be for the fine fraction of soil as reported on a soil test.
• Restrictive layers cannot be less than 1 foot. Root and water restriction will affect all output numbers for the root zone.
• Enhancements in soil loss due to water erosion require that Topography and Conservation Planning tabs on the Resources screen be selected and filled with appropriate information.
• Incoming Soil Layer system from user cannot exceed 10 layers and soil profile depth must be greater than one foot. The incoming data is depth weighted to a science layer system.
• GPFARM's Scientific Soil Layer system is as follows:
  • First Layer: 0 – 7 cm, Secondary Tillage Layer, Fixed Depth
  • Second Layer: 8 – 15 cm, Primary Tillage Layer, Fixed Depth
  • Third Layer: Depth Variable depending on the organic matter carbon availability. Maximum depth is 30 cm; this is the Microbial Activity Boundary.
  • Fourth Layer: Depth is currently defaulted to the deepest rooting crop in the management unit crop rotation. This is the Rooting Zone Boundary.
  • Fifth Layer: Depth Variable, End of the Soil Profile
• Restrictions set by the user overrides the root zone boundary in the case of a root restriction and in the case of a water restriction overrides the root and profile boundaries.

Climate

• Maximum number of consecutive climate years stored for scenario simulations is 50.
• The GPFARM whole farm climate database (Climdb.mdb) may be loaded with either generated or historical climate information provided with GPFARM. You may develop your own historical Climdb.mdb for your location. To develop your own climate database please contact the GPFARM modeling team by one of the following methods:
  • Phone: (970) 492-7300
  • Fax: (970) 492-7310
  • E-mail: de627syl@ars.usda.gov
• Historical files still need a nearest generated site to fill required wind data.

Other Science Program Limitations

• Residue categories accounted for in the simulation include crop, manure, and other organic compounds. Each residue and herbicide application is tracked from it’s addition through it’s degradation.
• The following restrictions apply for memory management purposes:
  • Residue accounting:
    • Storage of surface and soil layer residues in the system are limited to 80 compartments for each type of residue (crop, manure, and other organic compounds).
    • A mass < .01 kg/ha is zeroed to make a slot available.
  • Pesticide active ingredients:
    • Limited to 40 on the soil surface and in each soil layer.
    • Some active ingredients in the pesticide database do not have the necessary parameters for accurate simulation. Atrazine 4L active ingredient parameters are set by default for this case. Please check the parameters for that active ingredient to see if you agree with them.
    • Atrazine parameters are:
      • KOC = 100
      • Pesticide Application Efficiency = 1.0
      • WOF = 0.45
      • HLSOIL = 60
      • HLPLANT = 5
• Application efficiency is the amount of active ingredient applied and not lost to evaporation. The default is 100%.
• The Weeds Module impact on yield applies only to cropping systems. It has no effect on rangeland MUs.

Naming Files

• When files are saved, don't use any of the following characters: / \ : ? * " ' < > | [ ] ( ) or any other special characters in a filename. Please use only upper and lower case letters as well as digits 0-9 and _.

Hardware

• Pentium/200 with 64 Mbytes of RAM
  Note: A faster Pentium or Pentium 2 CPU computer with 64+ Mbytes of RAM would enable faster processing of the program.
• 200 Mbytes free hard disk space.
• CD-ROM
• SVGA monitor set at a resolution of 800x600 and small fonts.
• 100 - 200 Mbytes of disk space for the Information System or historical climate databases.

Software

• Microsoft Windows® 98, 98SE, NT4, 2000, ME or XP.
• Microsoft Access 97, 2000 or XP (optional but recommended)

For information about the GPFARM project, please contact the Great Plains Systems Research Unit (970) 492-7300 or write us using electronic mail at de627syl@ars.usda.gov. You may also wish to visit our Internet web site.

Direct mail inquiries to:
USDA, ARS, GPSR
GPFARM Project
2150 Centre Ave.
Bldg. D, Suite 200
Fort Collins, CO 80526

Internet Explorer 5.0

• GPFARM is using Microsoft Internet Explorer Administration Kit to redistribute Internet Explorer 5.0.

The use of trade, firm, or corporation names in the GPFARM Help System, the GPFARM DSS or the GPFARM Information System is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the USDA Agricultural Research Service, of any product or service to the exclusion of others that may be suitable.

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Details for GPFARM Information System

This system has been developed to provide users with a source of information to assist them in evaluating farm and ranch management options and in making decisions regarding the profitable use of the land they manage. The GPFARM Information System includes information regarding

• Crops and crop management
• Range and pasture management
• Livestock production
• Soil, water, and nutrient management
• Pests and pest control

The intent of the Information System is to offer a wide range of materials to the user. The sources of information include agricultural databases, research and extension fact sheets, and other pertinent commercial, state, and federal sources.

Listings preceded by the leaves bullets cycling through changing colors indicate links to documents or sites on the World Wide Web. An Internet connection is required to access them. Listings preceded by the metallic globe bullet indicate links to documents that are included with the Information System package and do not require an Internet connection. However, they require the Adobe® Acrobat® Reader software to view, navigate or print them because they are in the Portable Document Format (PDF). Also, many of the World Wide Web links to documents require the Adobe® Acrobat® Reader software to view them (indicated by (PDF) following the document title).

You can download the Adobe Reader software for free at www.adobe.com/reader.

When you click on a link that leads to a document or site on the World Wide Web, there are several ways to navigate back to the Information System. In Netscape Navigator use the Back button on the toolbar (left-most button), right click on the mouse and select Back (this is not available when viewing a PDF file in the Adobe® Acrobat® Reader software); go to the menu bar and select Go, Back; hold down the Alt key and press the left arrow key on the keyboard to return to the Information System. In Internet Explorer, the same Back navigation options are available except for the right mouse button click to Back. You may have to do this several times if you have navigated several pages away from the Information System.

When in the browser, uncheck the options to display the toolbar buttons, the location, directory buttons or status bar if possible. This will provide for more room to view the Image Map as well as the other pages. In Netscape Navigator, you may turn the options on or off to display the toolbar buttons, the location and the directory buttons. To turn these options on or off simply go to Options on the menu bar and click next to the choices you want to change. This acts as a toggle switch - either turning the option on or off. In Internet Explorer you may turn the options on or off to display the toolbar or status bar. These are under the View menu item.

A farm spatial data management system (FSDMS) is necessary for transforming data from a georectified map or nongeorectified image format to a data format acceptable to GPFARM. The selection of areas having homogeneity for simulation by GPFARM requires geographic information system (GIS) functionality for evaluating a variety of GIS data layers representing different spatial attributes, not necessarily spatially coincidental. An additional capability of the FSDMS is the capability of providing map and table output for storage, and management of attributal data relating to the maps or images.

The project runs in the ESRI, Inc. ARCVIEW 3.1 environment under Windows 95 and Windows NT. FSDMS is being developed with AVENUE, a scripting language specific to ARCVIEW. ARCVIEW is a GIS designed specifically for viewing, modifying, and storing image and map data. Enhancements to FSDMS are made to tailor the sketching, mapping and attribute storage information to the GPFARM data input and output requirements. The FSDMS anticipates three different user groups characterized by different levels of information storage, mapping needs, and levels of experience with GIS technologies. Level I capability presumes that users will import and store non-georectified images and related attribute data. This spatial data may be converted to map information (georectified to a geographic coordinate system) in the future. Level II provides the user with capabilities to import maps and map attribute data. This increasingly complex usage level also provides GPFARM interface capability primarily focused toward the cooperator or agricultural consultant who will use the geospatial capabilities of the FSDMS in conjunction with GPFARM simulation procedures. Level III provides the researcher with full GIS tools for conducting research-level geospatial analysis with GPFARM. Two cooperator's farms have been selected to provide baseline data layers for testing and developing the FSDMS: 1) an irrigated corn farm; and 2) a four-section dryland wheat farm.

The development of the FSDMS is coincidental with the development of GPFARM. The FSDMS Level I and parts of Level II will be linked to GPFARM during the summer of 1998. Customized on-line help screens are being developed to assist the users with the menu-level items and features of the FSDMS.

James C. Ascough II, Harriet D. Rector, and Brenda G. Faber

Level II will be completed in late 1998 and Level III will be completed in 1999. Level III is planned to include neural network/artificial intelligence-based prescriptive farming components to complement and use the simulation outputs of GPFARM, and other ARS simulation models such as NLEAP.

Wallace, W.W, H.D. Rector, J.C. Ascough II, and B.G. Faber. 1998. Farm Spatial Data Management System (FSDMS). Proc. First International Conference on Geospatial Information in Agriculture and Forestry, Lake Buena Vista, Florida, June 1-3.

Ascough II, J.C., H.D. Rector, B.G. Faber, and D.G. Wagner. 1998. A GIS-Based Tool for Management of Farm Spatial Data. 1998 ASAE Annual International Meeting, Lake Buena Vista, Florida, July 11-16.

Ascough, Rector: USDA-ARS-NPA, Great Plains Systems Research Unit, Fort Collins, CO 80522 Faber: Foresite Consulting/CIESIN, Fort Collins, CO 80522

SHOOTGRO emphasizes the development and growth of the shoot apex of small-grain cereals such as winter and spring wheat (Triticum aestivum L.) and spring barley (Hordeum vulgare L.). To better incorporate the variability typical in the field, up to six cohorts, or age classes, of plants are followed using a daily time step. Within each plant of a cohort, the appearance of each tiller is simulated, and for each culm (main stem and tillers), the phenological growth stage and appearance, growth, and senescence/abortion of each leaf, internode, spikelet, floret, kernel, rachis, and chaff is simulated. The model has been evaluated under conditions from the Great Plains, Pacific Northwest, South Africa, Italy, and England.

• Phenology submodel: The phenology submodel simulates all shoot apex developmental events using a modified growing degree-day (GDD) approach. Rather than using a static GDD number for the interval between growth stages, the number of phyllochrons (or number of leaves) is used which is a number that changes with environmental variables. Water and N stress also alters the number of phyllochrons between growth stages. The growth stages predicted for the median plant of up to six age classes and each culm on the plant are germination, emergence, tiller initiation, single ridge, double ridge, start of internode elongation, terminal spikelet stage (or awn initials formed for barley), jointing, flag leaf, booting, heading, start and end of anthesis, and physiological maturity.
• Tillering submodels: The appearance of each morphologically named tiller on the median plant in a cohort is simulated according to the main stem Haun stage (= number of leaves), which is controlled by the phyllochron (or rate of leaf appearance). The percentage of each tiller that appears and aborts on plants of a cohort are controlled by water, N, and light conditions. Tiller growth is simulated by simulating the growth (weight and length) of each internode, including specifically the peduncle, each leaf, and the spike (rachis, kernels, and chaff) as affected by water and N stress.
• Leaf submodels: The appearance, growth (length, width, area, weight, and N concentration), and senescence of each leaf blade and sheath on each culm on each median plant in a cohort are simulated. Growth and senescence are affected by water and N stress. The appearance of leaves is determined by the submodel that calculates the phyllochron, or rate of leaf appearance. Nine different equations that predict the phyllochron were evaluated to determine which equation to use. Depending on the crop, different equations work best.
• Spike development submodels: For each culm on each median plant in a cohort, the initiation of each spikelet, as well as the initiation, abortion, and fertilization of each floret within the spikelet is simulated; controlling factors are temperature, water and N availability, and morphological location. Also, the spike components of the rachis and chaff (glumes, paleas, and lemmas) are simulated for each spike. The differences in spike inflorescence structures between wheat and barley (both 2- and 6-rowed barley) are simulated in the model. Kernel growth is described under the Kernel Growth Submodels section below.
• Kernel growth submodel: The duration of grain filling is a curvilinear function of temperature and water and N availability. The potential growth of an individual kernel is dependent on the morphological location of the kernel within the spikelet, spike, and plant. The potential growth rate of the kernel is then reduced when water or N stress exists.

• Assist NRCS field offices to determine if producers are in compliance with erosion control requirements for participation in federal programs. Specifically, the amount of green biomass production of winter wheat was simulated for different planting dates, sowing rates, soil water and N at planting, and weather scenarios.
• Run SHOOTGRO in real-time to predict the specific growth stage of winter wheat so that the correct herbicide/insecticide could be selected based on the label. A related application was to convert among different growth stage scales, since these can differ on herbicide/ insecticide growth stage scales used.
• Different optimal N fertilizer and irrigation levels were calculated for selected sites in the U.S.
• Different global climate change scenarios were evaluated for selected sites in the U.S.
• SHOOTGRO has been used to assist in directing field research programs, particularly in identifying knowledge gaps in our quantification of developmental processes.

Gregory S. McMaster (USDA-ARS), Fort Collins, Colorado
Wally Wilhelm (USDA-ARS), Lincoln, Nebraska
Dottie Harrell (USDA-ARS), Lincoln, Nebraska
Betty Klepper (USDA-ARS), Pendleton, Oregon
Ron Rickman (USDA-ARS), Pendleton, Oregon
Jack Morgan (USDA-ARS), Fort Collins, Colorado
Al Frank (USDA-ARS), Mandan, North Dakota
Armand Bauer (USDA-ARS), Mandan, North Dakota
Al Black (USDA-ARS), Mandan, North Dakota
Steve Simmons, University of Minnesota
E.J.M. Kirby, England
Sue Walker, Institute For Soil, Climate and Water, Agricultural Research Council, South Africa
Tom Fyfield, Institute For Soil, Climate and Water, Agricultural Research Council, South Africa
Gene Maas (USDA-ARS), Riverside, California
Catherine Grieve (USDA-ARS), Riverside, California
Guiseppe Zerbi, Udine, Italy
Monica Martin, Udine, Italy

• Conversion of SHOOTGRO to simulate corn (Zea mays)
• Conversion of SHOOTGRO to simulate rice (Oryza sativa L.)
• Conversion of SHOOTGRO to simulate winter barley
• Addition of a more mechanistic root submodel.

• McMaster, G.S. and W.W. Wilhelm. 1997. Conservation compliance credit for winter wheat fall biomass and implications for grain production. Journal of Soil and Water Conservation 52:000-000. (Update on reference.)
• McMaster, G.S. 1997. Phenology, development, and growth of the wheat (Triticum aestivum L.) shoot apex: A review. Advances In Agronomy 59:63-118. (Update on reference.)
• McMaster, G.S. and W.W. Wilhelm. 1997. Growing degree-days: One equation, two interpretations. Agricultural and Forest Meterology 000:000-000. (New reference.)
• McMaster, G.S. and W.W. Wilhelm. 1998? Is using soil temperature better than air temperature for predicting winter wheat (Triticum aestivum L.) phenology? Submitted to Agronomy Journal. (New reference.)
• McMaster, G.S., D.R. LeCain, J.A. Morgan, L. Aiguo, and D.L. Hendrix. 1998? Higher CO2 increases CER, leaf carbohydrates, leaf appearance rates, tillering, and shoot and root dry weight of wheat. Submitted to Canadian Journal of Plant Science. (New reference.)
• Wilhelm, W.W., G.S. McMaster, R.W. Rickman, and B. Klepper. 1993. Above ground vegetative development and growth of winter wheat as influenced by nitrogen and water availability. Ecological Modelling 68:183-203.
• McMaster, G.S., W.W. Wilhelm, and J.A. Morgan. 1992. Simulating winter wheat shoot apex phenology. Journal of Agricultural Science, Cambridge 119:1-12.
• McMaster, G.S., J.A. Morgan, and W.W. Wilhelm. 1992. Simulating winter wheat spike development and growth. Agricultural and Forest Meteorology 60:193-220.
• McMaster, G.S., B. Klepper, R.W. Rickman, W.W. Wilhelm, and W.O. Willis. 1991. Simulation of aboveground vegetative development and growth of unstressed winter wheat. Ecological Modelling 53:189-204.
• McMaster, G.S., and D.E. Smika. 1988. Estimation and evaluation of winter wheat phenology in the central Great Plains. Agricultural and Forest Meteorology 43:1-18.
• Harrell, D.M., W.W. Wilhelm, and G.S. McMaster. 1993. SCALES: A computer program to convert among three developmental stage scales for wheat. Agronomy Journal 85:758-763.
• McMaster, G.S., and W.W. Wilhelm. 1996. Conservation compliance credit for winter wheat fall biomass and implication for grain production. Journal of Soil and Water Conservation 000:000-000.
• Wilhelm, W.W., and G.S. McMaster. 1996. Spikelet and floret naming scheme for grasses with spike inflorescences. Crop Science 36:000-000
• McMaster, G.S. 1996. Phenology, development, and growth of the wheat (Triticum aestivum L.) Shoot apex: A review. Advances in Agronomy 57 or 58:000-000.
• McMaster, G.S., and W.W. Wilhelm. 1995. Accuracy of equations predicting the phyllochron of wheat. Crop Science 35:30-36.
• McMaster, G.S., W.W. Wilhelm, and P.N.S. Bartling. 1994. Irrigation and culm contribution to yield and yield components of winter wheat. Agronomy Journal 86:1123-1127.

USDA ARS NPA
Great Plains Systems Research Unit
2150 Centre Avenue
Building "D", Suite 200
Fort Collins, Colorado USA, 80526
Phone Number: (970) 492-7300
Fax Number: (970) 492-7310
Email: GPSR_Email@ars.usda.gov

• Operating systems: DOS, MS-Windows, VMS, UNIX
• Hardware demands: 4 Mbytes RAM for DOS or 8 Mbytes RAM for MS-Windows 20 Mbytes Disk

Nitrate Leaching and Economic Analysis Package (NLEAP) is a field-scale computer model developed to provide a rapid and efficient method of determining potential nitrate leaching associated with agricultural practices. It uses basic information concerning on-farm management practices, soils, and climate to project N budgets and nitrate leaching indices. NLEAP calculates potential nitrate leaching below the root zone and to ground water supplies. NLEAP has three levels of analysis to determine leaching potential: an annual screening, a monthly screening, and an event-by-event analysis.

The NLEAP model was designed to answer questions regarding potential leaching of nitrate. The processes modeled include movement of water and nitrate, crop uptake, denitrification, ammonia volatilization, mineralization of soil organic matter, nitrification, and mineralization-immobilization associated with crop residue, manure, and other organic wastes.

The event-by-event analysis provides the best estimate of nitrate leaching. Its water and nitrogen budgets track the impacts of each precipitation, irrigation, fertilization and tillage event on potential nitrate leaching. The event-based procedure is recommended for analysis of potential nitrate leaching to domestic water supplies.

• Extensive validation has shown the model can predict residual soil nitrates and nitrate leaching to within approximately 20 to 50 pounds of nitrogen per acre per year.
• Thorough documentation is available. The publication, Managing Nitrogen for Groundwater Quality and Farm Profitability, edited by R.F. Follet, D.R. Kenney, and R.M. Cruse and published by the Soil Science Society of America, contains the documentation for processes modeled in NLEAP.
• The program uses data entry screens with pop-up data selection and on- line help menus.
• Regionalized soils and crop data bases have been developed for the contiguous United States. Climate data bases are currently available for the upper Midwest, Northeast, South, and part of the Western United States. In states where a regional data base is not available, the user must obtain and manually input the required soils and climate information.
• The user can access material from the internal data base files, enter their own farm-specific and field-specific information, or use a mixture of user specified and database information. Users in all regions are encouraged to develop local data bases, as the regional data bases may not accurately describe local conditions.
• User input may be saved to a data file for use in future runs.
• Simulation results help identify shortcomings in water and nitrogen management strategies.
• Simulation results can be presented as monthly tables, graphically, or in a detailed written summary and analysis.

• DOS NLEAP is only Windows 95, 98, 2000 compatible through an MSDOS window.
• Modeling soil nitrogen processes in organic soils is not currently available. Their inclusion will require additional research and modeling efforts.
• NLEAP does not predict yield reductions caused by pests or nutrient deficiencies. However, the user should consider the effects of these problems when estimating crop yield.
• The model should not be used where rapid water infiltration, leaching, denitrification, and ammonium volatilization require time steps smaller than 1 day. Other situations that should not be modeled include those in which water and solute transport in an aquifer are important considerations, complex layering in the soil profile exists, or a shallow water table supplies crop needs.
• Sequential year runs involving complex crop rotations are difficult to simulate.

• The capability to operate NLEAP in conjunction with GRASS and other GIS systems has been developed and is currently being validated.
• A metric version of NLEAP is being developed for international use.
• The model is being modified to simplify simulation of sequential year runs and expand file handling capabilities.
• A routine is being added that will separate gaseous denitrification losses into N2 and N20 components.
• Fertilizer and irrigation input routines are being improved.
• Future enhancements will permit the user to directly access NRCS soil and climate data bases for NLEAP input and allow access to NLEAP through FOCS.
• A users manual and NRCS workbook are under development.

• DOS NLEAP is only Windows 95, 98, 2000 compatible through an MSDOS window.
• IBM AT 286, 386, 486, or pentium compatible system, the use of a math coprocessor is recommended.
• At least 640K of memory.
• DOS version 2.1 or newer.
• 4.5 megabytes of disk storage space.
• NLEAP may be run with either a monochrome or color monitor.
• Program execution is unpredictable if any memory resident programs are loaded.

USDA ARS NPA
Great Plains Systems Research Unit
2150 Centre Avenue
Building "D", Suite 200
Fort Collins, Colorado USA, 80526
Phone Number: (970) 492-7300
Fax Number: (970) 492-7310
Email: GPSR_Email@ars.usda.gov

Download from ARSAgSoftware

A two-dimensional model of corn root growth has been developed and linked to a two-dimensional model for water, heat and solute transport in soils. The purpose of this model is to research how different management practices influence root growth and utilization of water and nitrogen from different parts of the root zone. This knowledge is then used to identify practices that help the most efficient use of water and nitrogen and minimize leaching below the root zone. The model may also be used by plant breeders to screen new varieties for their root growth.

Our interpretation of photographs and line drawings of corn root systems during the growing season was that, as the root system develops, there is a change from a primarily horizontal growth direction early in the life cycle to a primarily vertical growth direction for later stages in the life cycle. We generalized these data to delineate a region to the left and right, as viewed along the center of the plant row, and downward in which root growth and downward in which root growth may potentially occur. The size of the region is defined by the growth area is defined by the extension rate of the root system and the growth angle from the horizontal. The horizontal extension of the root region is assumed to progress by the extension rate times the cosine of the growth. The vertical extension of the root region is assumed to progress by the extension rate times the sine of the growth angle. The values of these coefficients are dependent upon the corn hybrid and the age of the plant. The increase of root density for a given position in the root zone follows a first-order dynamics; it is proportional to existing density. The decrease in root density due to root death is proportional to the square of the existing density. The net change of density is the difference between the two. The proportionality constants are a function of growth stage. Suboptimal environmental conditions of soil temperature, bulk density and water content influence root growth.

Dr. Joe Benjamin or Dr. Laj Ahuja

SPUR2 DOS ver. 2.2 is a general grassland ecosystem simulation model designed to determine beef cattle performance and production by simultaneously simulating production of up to 15 plant species on 36 heterogeneous grassland sites. SPUR2 simulates grassland hydrology, nitrogen cycling, and soil organic matter on grazed ecosystems as well as rangeland production under different climatic regimes, environmental conditions, and management alternatives.

• SPUR2 simulates carbon and nitrogen cycling through aboveground live and dead vegetation, live and dead roots, litter, and soil organic matter. Effects of stocking rate, season of grazing, and type of grazing system have been incorporated into the model. SPUR2 has been modified to simulate the direct effects of CO2 on plant production. A user interface has been developed to assist with model parameterization. The model is driven by daily inputs of precipitation, maximum and minimum temperatures, solar radiation, and daily wind run. These variables are derived either from existing weather records or from use of a stochastic weather generator. The hydrology component calculates upland surface run-off volumes, peak flow, snow melt, upland sediment yield, and channel stream flow and sediment yield. Soil-water tensions, used to control various aspects of plant growth, are generated using a soil-water balance equation. Surface run-off is estimated by the SCS curve number procedure and soil loss is computed by the modified universal soil loss equation. The mechanistic process-oriented structure of SPUR2 makes the model well suited for examining the interactions between management decisions and climatic influences on short-term ecological processes and evaluating possible adaptive management strategies.
• The SPUR2 model incorporated CBCPM (Colorado Beef Cattle Production Model), a second generation beef cattle production model that was a modification of the Texas A&M Beef Model. CBCPM is a herd wide, life cycle simulation model and operates at the level of the individual animal. The Colorado model was designed to be a flexible research tool. Through the use of both input files and rule writing, CBCPM allows for 1) a variable time step of 1 to 30 days, 2) a variable herd size, 3) the importation of replacement heifers and stocker cattle, 4) the ability to simulate the effects of different crossbreeding systems, and 5) the evaluation of the effects of animal selection over time.
• The biological routines of CBCPM simulate animal growth, fertility, pregnancy, calving, death, and demand for nutrients. Currently, fourteen genetic traits related to growth, milk production, fertility, body composition, and survival can be studied. Intake of grazed forage is calculated by FORAGE, a deterministic model that serves as an interface between CBCPM and SPUR2. The model is driven by weight from the animal growth curve, animal demand for forage, and the quantity and quality of forage available for each time step of the simulation. FORAGE determines the intake of grazed forage by simulating the rate of intake and grazing time of each animal in the time step.
• SPUR2 is capable of simulating forage removal by a variety of wildlife species. Two types of range grasshoppers (grass eaters and mixed grass and forb eaters) are also simulated.

• Annual grasses are not simulated.
• The model requires fairly detailed parameterization when new plant species are added to the system
• CBCPM (cow/calf routine) is a very detailed genetic model and may be to complex for many of the range management questions under consideration
• The erosion and runoff routines used in SPUR2 many not be valid under all rangeland conditions.

The model has been released for public use and is supported by the Great Plains Systems Research Unit. For further copies of the code, documentation, or publications relating to the validation and use of SPUR2, please contact:

Dr. Jon D. Hanson
USDA, Agricultural Research Service
Northern Great Plains Research Laboratory
P.O. Box 459
Mandan, ND 58554-0459
COM: (701)667-3010
FAX: (701)667-3054

• Incorporate the CENTURY Soil Organic Matter Model into the SPUR2 framework (visit SPUR2 DOS ver. 2.4)
• Develop and incorporate a grassland burning management option
• Improve the hydrology components of the model (visit SPUR2 DOS ver. 2.4)
• Update and improve the user interface
• Build SPUR2 into the GRASS Geographic Information System (visit SPUR2 DOS ver. 2.4)

• Operating systems: DOS, MS-Windows, VMS, UNIX
• Hardware demands: 4 Mbytes RAM for DOS or 8 Mbytes RAM for MS-Windows 20 Mbytes Disk

Downoad from ARSAgSoftware

HIRO₂ (Hortonian Infiltration and Run-Off/On) is a spatially distributed rainfall-runoff model for event-based studies of space-time watershed processes. A grid-based routing hierarchy was defined over the watershed using the D-infinity contributing area algorithm. Computation of ponding time was included to handle variable run-on and rainfall intensity. The Green-Ampt model was adopted to calculate surface infiltration, and the kinematic wave model was used to route Hortonian runoff and channel flow. The model can handle input rainfall, soil parameters, surface roughness, and other properties that vary in space and time.

Source Code Developer
Dr. Huan Meng
(formerly at Colorado State University, Dept. of Civil Engineering)
NOAA/NESDIS
Center for Satellite Applications and Research
Camp Springs, MD 20746, USA

Co-Authors/Advisors
Professor Jose D. Salas
Department of Civil and Environmental Engineering
Colorado State University
Fort Collins, CO 80523

Drs. Timothy R. Green and Lajpat R. Ahuja
USDA-ARS, Agricultural Systems Research Unit
Fort Collins, CO 80526

No technical support is available, but other general questions or comments may be emailed to: Tim.Green@ars.usda.giv

This package is comprised of two parts (directories) - the first part is used to set up the watershed, and the second part is the rainfall-runoff model source code. The directory called Watershed includes thirteen FORTRAN77 programs and three ancillary files. This set of programs starts from a DEM data file, delineates the watershed, defines the channels, sets the routing hierarchy, and outputs the files required by the rainfall-runoff model, HIRO₂, in the second directory Runoff_model. Also included in the second directory is a file that defines the model parameters for HIRO₂.

FORTRAN77 source code must be compiled by the user before execution. Various proprietary compilers could be used, or g77 is available for free at http://www.gnu.org/software/fortran/fortran.html.

Watershed Directory
Outside input files required for running the programs in this directory are:

1. parameter.inc – parameter include file.
2. filename.in – specifies the name of the DEM file.
3. DEM file (name is specified in filename.in, default is dem.in).

Notes:

1. Some parameters in parameter.inc are not known prior to running the programs in this directory. They become available as the processing proceeds. Follow the comments in the parameter file to determine the values of all the parameters.
2. A sample DEM file dem.in is included in this directory. Grid dimensions for dem.in are set by parameters in parameter.inc.

Execution procedure (ordered by FORTRAN files *.f77 or *.f):

1. dinf.f – computes flow direction, slope, and adjusted elevation at each pixel.
   Input files: parameter.inc, filename.in, DEM data file
   Output files: elev.dat, slope.dat, angleorg.dat
2. preup.f – computes the number of immediate upslope pixels.
   Input files: parameter.inc, angleorg.dat
   Output files: prenup.dat
3. predown.f – computes the number of downslope pixels (up to 2), their locations
   (1 - nx*ny), and fraction of flow to downslope pixels (0 - 1).
   Input files: parameter.inc, angleorg.dat
   Output files: prendown.dat, predown,dat, predowncoe.dat
4. prearea.f – computes contributing area.
   Input files: parameter.inc, prenup.dat, prendown.dat, predown.dat, predowncoe.dat
   Output file: prearea.dat
5. anglenew.f – finds channel pixels based on a contributing area threshold; sets flow directions in all channel pixels to the closest cardinal or diagonal direction, i.e,. no splitting flow in any channel pixels.
   Input files: parameter.inc, angleorg.dat, prearea.dat
   Output files: angerr.dat, anglenew.dat
   Note: angerr.dat records the channel pixels that had multiple flow directions and have been corrected to single flow direction.
6. up.f – computes the number of immediate upslope pixels based on the adjusted flow directions.
   Input files: parameter.inc, anglenew.dat
   Output file: nup.dat
7. down.f – computes the number of downslope pixels (up to 2), their locations (1 - nx*ny), and fraction of flow to downslope pixels (0 - 1) based on the adjusted flow directions.
   Input files: parameter.inc, anglenew.dat
   Output files: ndown.dat, down.dat, downcoe.dat
8. area.f – computes contributing area based on the adjusted flow directions. It also outputs the preliminary channels based on the new contributing area.
   Input files: parameter.inc, nup.dat, ndown.dat, down.dat, downcoe.dat
   Output files: area.dat, prechannel.dat, prenumchan.dat
   NOTE: This step requires some manual manipulation of the data. Basically, file prechannel.dat most likely needs to be adjusted by adding and/or deleting channel pixels and their flow directions. Files newangle.dat and prenumchan.dat also need to be adjusted accordingly. The simplest way to do this is to adjust newangle.dat by plotting prechannel.dat in spreadsheet and comparing the channels with survey maps from the watershed, delete file angerr.dat, and then copy anglenew.dat to angleorg.dat and then re-run anglenew.f, up.f, down.f and area.f. Take note that angerr.dat has to be deleted before running anglenew.f again. If the newly generated angerr.dat file is empty, it means that all the channel pixels have single flow direction and one can proceed to the next program. If there are still some channel pixels with multiple flow directions as signaled by a non-empty angerr.dat file, the same adjusting procedure needs to be run again until an empty angerr.dat file is generated.
9. path1.f – finds flow paths, i.e. order of computation pixel by pixel.
   Input files: parameter.inc, nup.dat, ndown.dat, down.dat
   Output file: path.dat
10. delineate.f – delineates a watershed from a square/rectangular area based on adjusted flow directions. The coordinate of the outlet pixel is required.
    Input files: parameter.inc, anglenew.dat
    Output files: delin_ini.dat, numdelin.dat
11. re_coord.f – "cuts out" the smallest rectangle(or square) area that includes the delineated watershed from the original DEM area, and resets the coordinate on the smaller area.
    Input files: parameter.inc, delin_ini.dat
    Output files: coord.dat, delin.dat
12. coech.f – computes and outputs data files mainly used by channel flow routing in a watershed.
    Input files: parameter.inc, coord.dat, path.dat, delin_ini.dat, prenumchan.dat, prechannel.dat, elev.dat, anglenew.dat, area.dat
    Output files: level.dat, channel.dat, dc.dat, slopec.dat, upxyc.dat, numchan.dat
13. coeland.f - computes and outputs data files mainly used by overland flow routing in a watershed.
    Input files: parameter.inc, coord.dat, anglenew.dat, elev.dat, delin_ini.dat, channel.dat
    Output files: coenum.dat, coe.dat, dd.dat, s0.dat, ilv.dat, ip.dat

Runoff_model Directory
External input files for running the rainfall-runoff model (hiro2.f):

1. parameter_runoff.inc – parameter include file.
2. in_rain.dat –3D rain data file, R(nx, ny, nt), where the x dimension changes the fastest, followed by y dimension and then the time (t) dimension.
3. ke.dat – 2D effective hydraulic conductivity field.
4. mann.dat –2D Manning’s n field.
5. thetai.dat –2D initial soil moisture content field.
6. porosity.dat – 2D porosity field
7. suction.dat – 2D wetting front suction field.

Internal input files (from directory Watershed) needed to run rainfall-runoff model:
coenum.dat, coe.dat, dd.dat, s0.dat, slope.dat, ilv.dat, level.dat, dc.dat, slopec.dat, upxyc.dat, channel_all.dat
NOTE:

1. The internal input files need to be copied to the directory Runoff_model from the directory Watershed
2. File channel_all.dat is generated outside the programs based on the output file channel.dat from coech.f. Besides the coordinates of the channel pixels in channel.dat, channel_all.dat also includes information about the channel bottom widths and bank slopes due to the fact that HIRO2 assumes that channels have trapezoidal shape. This information needs to be obtained from outside sources.
3. The y-dimension of all the outside input files range from ny to 1 (take note of the line “do j = ny, 1, -1” at various places within hiro2.f).
4. All input and output files are in SI units. For instance, output rain is in m/s, runoff in m3/s, and infiltration in m/s.
5. The format for output rain, runoff and infiltration at the end of hiro2.f might need to be modified by users to match the dimension of their specific watersheds.

Download HIRO₂ Model