Tools To Assist Decision-Making - Details
| Name of supporting tool: |
Lamb Planner (WA version 2nd edition) non electronic wheel planner |
| Developer(s): | Mandy Curnow, Peter Robson, Sandra Brown, ASHEEP group (Esperance) |
| Aims/use: | It sets out the key management operations in the sheep breeding year so that farmers can make informed choices on timing and activities to improve lambing percentages. |
| Key features: | Provides the latest best practice advice regarding ewe and ram nutrition, condition score targets, reproductive management and lambing guidelines. |
| Audience: | Farmers, extensionists, students. |
| Regions, scale, time of year: | WA version and Eastern States versions available. |
| Types of decisions: | Joining time, FWEC (faecal worm egg count) timing, teasing and nutritional decisions. |
| Strengths/limitations: | NA |
| Inputs: | Joining date or lambing date |
| Outputs: | Dates of all important actions needed for improving lambing percentages. |
| Expertise/system r'quts: | Basic hand held wheel device |
| Availability/status: |
Free to all growers and students. Further information is provided under "pasture management" at www.agric.wa.gov.au (pasture management) |
| Contact: | Available from district offices or P. Fumagalli, Tel: (08) 98928444, Email: pfumagalli@agric.wa.gov.au |
| Name of supporting tool: |
Green Feed Budget Calculator (sheep) |
| Developer(s): | Mandy Curnow, David Weaver, Mike Hyder |
| Aims/use: | To provide an electronic calculation of sheep feed budgets at a paddock scale during the 'green' season with a number of different scenarios. |
| Key features: | 1. Calculates stocking rates for a particular paddock. 2. Calculates sheep numbers for a range of paddock objectives. 3. Gives an estimate of deferment time during autumn. 4. Strip grazing stocking calculations. 5. Supplementary feed calculator during autumn. |
| Audience: | Farmers using PGR (pasture growth rate) and FOO (feed on offer) estimates, agricultural college students, development officers, consultants giving feeding advice. |
| Regions, scale, time of year: | Annual based pastures all year, perennials during spring, sheep and grain belt in WA; paddock; pasture growing season (not dry feed season). |
| Types of decisions: | Stocking rates, strip grazing, supplementary feeding |
| Strengths/limitations: | Relies on accurate assessment of green feed in the paddock. Not suited to very grassy pastures in beef areas. Not for use during summer and dry pasture. |
| Inputs: | Feed on Offer, PGRs, stock numbers and class, paddock area. |
| Outputs: | Stocking rates for a particular paddock for a range of paddock objectives. Supplementary feed calculator during autumn. |
| Expertise/system r'quts: | Basic computer skills; Windows 95 or better, CD-ROM, Mac version available. |
| Availability/status: | Package of explanatory notes and computer disk available for $15 from Department of Agriculture, Albany,Ph: 98928422; Further information is provided under "pasture management" at www.agric.wa.gov.au ( pasture management) |
| Contact: | Mandy Curnow, Dept of Agriculture and Food Western Australia, 444 Albany Hwy, Albany 6325, Email: mcurnow@agric.wa.gov.au |
| Name of supporting tool: |
MIDAS |
| Developer(s): | David Morrison and Dr. Ross Kingwell, although valuable assistance was provided by a host of collaborators. |
| Aims/use: | Further research, economic scenario planning. |
| Key features: | The MIDAS computer models represent the economics and biology of farming in the grain and sheep belts of Western Australia. |
| Audience: | Extensionists, researchers and consultants. |
| Regions, scale, time of year: | There are versions of MIDAS in working order for the eastern wheatbelt, central wheatbelt, south coast and Great Southern. |
| Types of decisions: | The model is run to try to identify robust results which can be extended to groups of farmers. For example, MIDAS has been used to assess optimal rotational changes in response to changes in the prices of commodities (such as sheep meat, wool and grains) and inputs (such as fertiliser, fuel and labour) taking account of the interactions between componentes of a farming system". |
| Strengths/limitations: | [Expired] |
| Expertise/system r'quts: | For more detailed information is available under ‘MIDAS??™ at www.agric.wa.gov.au (MIDAS) |
| Availability/status: | Not for individual use |
| Name of supporting tool: |
Pasture Watch & Pastures from Space |
| Developer(s): | Dr. Steve Gherardi , Department of Agriculture, G Mata, CSIRO and Fairport Technologies |
| Aims/use: | To provide real time pasture information and a range of tools to make grazing decisions. |
| Key features: | Pastures from Space web site- pasture growth rates at farm scale, Pasture Watch - decision tool for pasture budgeting, pasture grazing planner. |
| Audience: | Any landholder |
| Regions, scale, time of year: | Southern Australia agricultural areas during the growing season. |
| Types of decisions: | Grazing pressure, stocking rate, deferment times. |
| Strengths/limitations: | Weekly predictions of PGR (pasture growth rate) provided. |
| Inputs: | Paddock names, animals class and number, FOO (feed on offer) estimates. |
| Outputs: | Stocking rates etc. |
| Expertise/system r'quts: | Digitised farm map, internet access. |
| Availability/status: | $500 -$750 annually |
| Contact: | Dr Steve Gherardi, Dept of Agriculture and Food Western Australia, South Perth, Tel: (08) 9368 3333, Email: sgherardi@agric.wa.gov.au or Fairport Technologies 1800 500 195, Email: www.fairport.com.au/PastureWatch |
| Name of supporting tool: |
Profile Calculator (Measure as you grow wool) |
| Developer(s): | Andrew Peterson |
| Aims/use: | To manage wool fibre profile throughout the growing season. |
| Key features: | Pictorial representation of your wool fibre profile, calculations of fleece value and estimated clean fleece weight. |
| Audience: | Wool producers |
| Regions, scale, time of year: | Southern Australia agricultural areas during the growing season. |
| Types of decisions: | Adjustment of feed regimes to match fibre diameter targets. |
| Strengths/limitations: | Windows 98 or better, some glitches on some computers. |
| Inputs: | Fibre diameter and length of wool profile throughout season. |
| Outputs: | Fibre profile and predicted fleece value. |
| Expertise/system r'quts: | Basic Computer skills |
| Availability/status: | By request |
| Contact: | Andrew Peterson, Dept of Agriculture and Food Western Australia, South Perth, Tel: (08) 9368 3333, Email: apeterson@agric.wa.gov.au |
| Name of supporting tool: |
Fleece Calculator |
| Developer(s): | Johan Greeff |
| Aims/use: | The is a decision support tool for Merino wool producers for measuring profitability of carrying out in-shed testing of fibre diameter. |
| Key features: | This is based on the fact that sheep that produce more and finer wool than their contemporaries will tend to continue to produce more and finer wool during their lifetime in the flock. |
| Audience: | Wool producers |
| Regions, scale, time of year: | Anytime or region |
| Types of decisions: | Whether to in-shed test ewe flock to achieve wool breeding objectives. |
| Inputs: | The size of the breeding ewe flock, the number of replacement hogget ewes available, the average fleece weight, average fibre diameter and clean yield of hogget and mature ewes in the flock. |
| Outputs: | Amount of profit due to testing ewe flock over 10 years. |
| Expertise/system r'quts: | Access to the Department of Agriculture??™s web site. |
| Availability/status: | Further information is provided under "fleece calculator " at www.agric.wa.gov.au (fleece calculator ) |
| Contact: | Johan Reef, Tel: (08) 9821 3333, Email: greeff@agric.wa.gov.au |
| Name of model: |
Anthracnose Tracer |
| Developer(s): | Dr. Moin Salam, Dr. Art Diggle, Mr. Geoff Thomas and Dr. Mark Sweetingham |
| Aims/use: | To estimate spatio-temporal dispersion of anthracnose in lupins in a paddock from infected seeds. |
| Key features: | Based on detected level of seed infection, the model shows the expected loss of crop population due to anthracnose. |
| Audience: | Farmers, consultants, advisers |
| Regions, scale, time of year: | Broadacre agriculture; Paddock; During seed selection |
| Types of decisions: | Whether to use the seed for sowing; fungicide decisions |
| Strengths/limitations: | Strength: Gives good prediction of anthracnose spread from infected seeds and also from infected blue lupins along the fence; gives a pictorial (spatial) view. Limitations: Users would require special skills and software to run this model. |
| Inputs: | Weather/climate information of the concerned location (daily max and min temperature, hourly rainfall, wind speed and wind direction); level (%) of seed infection. |
| Outputs: | Percent loss of lupin population due to anthracnose infection in a paddock. |
| Expertise/system r'quts: | More than basic computer skills; requires Mathematica software and relatively large RAM. |
| Availability/status: | On request; users can ask for an output from contact person; Released 2001. Development on-going. |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
APSIM (Agricultural Production Systems Simulator) |
| Developer(s): | APSRU (Agricultural Production Systems Research Unit) |
| Aims/use: | Model of crop growth. Can be used for rotations, mixtures or weeds. Can be sued to produce outputs for any part of the system (e.g. soil water, breakdown of residues). |
| Key features: | Daily time-step calculations of crop growth based on potential assimilate production modified by nitrogen or water stress. |
| Audience: | Researchers and modellers (potential to produce secondary or tertiary products or outputs for farmers or advisers). |
| Regions, scale, time of year: | International--has been validated for WA, eastern Australia and Africa; point, scale up to paddock; anytime as can generate outputs for any part of the system. |
| Types of decisions: | Crop production under different seasons, environments and management. |
| Strengths/limitations: | Flexible outputs from a detailed simulation model. Requires time to set up input files and expertise to run the model. |
| Inputs: | Daily rainfall, radiation, max/min temp, soil parameters, crop parameters, residue parameters, management information. |
| Outputs: | Almost unlimited. Any of the aspects that are modelled: crop growth, quality, soil water, nitrate leaching, residue breakdown, weather information. |
| Expertise/system r'quts: | Need to be a licensed user and to have expertise/training to run the model; Windows-based PC. |
| Availability/status: | Available from APSRU as licensed user; Version 2.1 released October 2001. |
| Contact: | APSRU |
| Name of model: |
Blackleg Sporacle |
| Developer(s): | Drs. Moin Salam, Ravjit Khangura, Art Diggle and Martin Barbetti |
| Aims/use: | To predict the time of onset of blackleg spore maturity. |
| Key features: | Forecast status of the maturity of blackleg fruiting bodies on canola stubble; forecast onset of blackleg ascospore shower in the region. |
| Audience: | Farmers, consultants, advisers |
| Regions, scale, time of year: | Broadacre agriculture; district/region; 1 to 2 months before seeding time. |
| Types of decisions: | Sowing, fungicide decision |
| Strengths/limitations: | Good prediction of maturity of spores (fruiting bodies); not yet been related to yield loss. |
| Inputs: | Daily weather data (max and min temperatures and rainfall). |
| Outputs: | Status of maturity of spores and time of arrival of first ascospore showers (in relation to blackleg in canola) in the region. |
| Expertise/system r'quts: | Basic computer skills; compatible with Excel 5 or better. |
| Availability/status: | Forecasts are provided in PestFax and on the Department of Agriculture website (www.agric.wa.gov.au); released 2002. Development on-going. Available on request. Search for "plant disease forecast 2006" on the Dept of Agriculture and Food Western Australia or click the hyperlink www.agric.wa.gov.au/cropdisease |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902 Email: msalam@agric.wa.gov.au |
| Name of model: |
Blackspot Manager |
| Developer(s): | Dr. Moin Salam, Ms Jean Galloway, Dr. Art Diggle and Mr. Bill MacLeod |
| Aims/use: | Estimate development and spread of blackspot in field peas. |
| Key features: | Taking history of field peas in a region, the model shows to what extent the blackspot may spread in the region. |
| Audience: | Farmers, consultants, advisers |
| Regions, scale, time of year: | Broadacre agriculture; District/region; Any time, would be best during paddock selection decision making. |
| Types of decisions: | Paddock selection; enables management of blackspot through manipulating time of sowing. |
| Strengths/limitations: | Strength: Gives good prediction of blackspot spread in fieldpeas. Limitations: Users would require special skills and software to run this model. |
| Inputs: | Weather/climate information of the location (daily max and min temperature, hourly rainfall, wind speed and wind direction); paddock history (field peas only) in the region. |
| Outputs: | Extent and intensity of blackspot spread. |
| Expertise/system r'quts: | More than basic computer skills; requires Mathematica software and relatively large RAM. |
| Availability/status: | On request; users can ask for an output from contact person; Released a preliminary version in 2002. Development on-going. Available from the Dept of Agriculture and Food Western Australia website(www.agric.wa.gov.au) and search for "plant disease forecast 2006" or click the hyperlink www.agric.wa.gov.au/cropdisease |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
Blackleg Risk Appraisal Tool (BRAT) |
| Developer(s): | Dr. Moin Salam, Dr. Ravjit Khangura, Mr. Paul Carmody, Dr. Art Diggle and Dr. Martin Barbetti |
| Aims/use: | A tool for assessing the risk associated with the onset of ascospore showers coinciding with the most susceptible stage of canola. |
| Key features: | Blackleg Risk Appraisal Tool. Tracks down the status of the maturation of blackleg fruiting bodies on canola stubble; forecast onset of blackleg ascospore shower in a selected district or region; guides sowing time and fungicide interactions. |
| Audience: | Consultants and growers |
| Regions, scale, time of year: | All; District/region; Preseason |
| Types of decisions: | Sowing time vs blackleg risk |
| Strengths/limitations: | Modification of Blackleg Sporacle into a user-friendly tool. |
| Inputs: | Daily weather data (max and min temperatures and rainfall). |
| Outputs: | Projected date on beginning of ascospore showers. |
| Expertise/system r'quts: | Basic spreadsheet; MS Excel-based |
| Availability/status: | Available from the Dept of Agriculture and Food Western Australia website(www.agric.wa.gov.au) and search for BRAT or www.agric.wa.gov.au/cropdisease. |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902 Email: msalam@agric.wa.gov.au |
| Name of model: |
BYDV Risk Forecast |
| Developer(s): | Debbie Thackray , Art Diggle and Roger Jones, with GRDC funding |
| Aims/use: | To predict risk of yield loss from barley yellow dwarf virus (BYDV) spread in cereals in different areas of the WA grainbelt. |
| Key features: | A computer simulation model predicts when aphids are expected to start arriving in cereal crops, incidence of BYDV spread by them and yield losses from BYDV damage. Maps on an internet site (www.agric.wa.gov.au/bydv) illustrate model predicted risk on a shire basis. |
| Audience: | Farmers and advisers, researchers, students. |
| Regions, scale, time of year: | Internet based forecasts are for each shire in the medium and high annual rainfall zones of WA. Forecasts are issued in late April each year. Model can be run for any location in WA grainbelt with daily rainfall and temperature data available and anytime from mid-April onwards. |
| Types of decisions: | Risk forecasts assist users in making their own decisions about the need for early-season insecticide spray applications to control the aphids spreading BYDV. Information on insecticides and spray timing is also provided on the internet site. |
| Strengths/limitations: |
The forecasts give a good indication of when aphids are first likely to be in the crop and whether or not control is worthwhile. This replaces the need for, or enhances, crop inspections for aphids early in the growing season. This is useful because considerable virus spread can occur when only a few aphids are visible in the crop and these aphids are hard to find unless searches are done very thoroughly. A limitation is that currently inputting climate data to do model runs is time consuming, so for the internet forecasts they are only done for one location in a shire, although for different sowing dates. In the future we hope to automate model runs and perhaps make the model itself available over the internet. |
| Inputs: | For the model: sowing date, and daily rainfall and temperature data. For the internet forecasts: sowing date, then look for your location on the map. |
| Outputs: | From the model: start of aphid immigration, BYDV incidence, yield loss from BYDV damage. From the internet site: yield loss from BYDV damage for each shire, for a range of sowing dates. |
| Expertise/system r'quts: | Internet forecasts: Familiarity with internet navigation. Usual system requirements for internet use. Model: Ability to follow simple instructions and a little familiarity with typing information into boxes. Model is built using “Stella” software, but user does not need to be familiar with it. |
| Availability/status: | Forecasts available each growing season in late April through internet site: www.agric.wa.gov.au/bydv. Model not currently available, except through direct contact with Debbie Thackray . In the future, we hope to automate climate data retrieval and make the model available on the internet or on a CD. |
| Contact: | Debbie Thackray, Tel: (08) 6488 7574; Email: djthack@clima.uwa.edu.au |
| Name of model: |
CMV Risk Forecast |
| Developer(s): | Debbie Thackray , Art Diggle and Roger Jones, with GRDC funding. |
| Aims/use: | To predict risk of yield loss from cucumber mosaic virus (BYDV) spread in lupins in different areas of the WA grainbelt. |
| Key features: | A computer simulation model predicts when aphids are expected to start arriving in lupin crops, incidence of CMV spread by them from infected seed and yield losses from CMV damage. Maps on an internet site illustrate model predicted risk on a shire basis. |
| Audience: | Farmers and advisers, researchers, students. |
| Regions, scale, time of year: |
Internet based forecasts are for each shire in the medium and high annual rainfall zones of WA. Forecasts are issued in late April each year.
Model can be run for any location in the WA grainbelt with available daily rainfall and temperature data and anytime from mid-April onwards. |
| Types of decisions: | Risk forecasts assist users in making their own decisions about the need for sourcing uninfected seed or using pre-sowing cultural control measures to decrease CMV spread by aphids. Information on these methods and how they work is also provided on the internet site. Knowing how much yield might be lost can also assist users in decisions about the economic benefit of other crop inputs. |
| Strengths/limitations: |
The forecasts give a good indication of when aphids are first likely to be in the crop and whether or not control is worthwhile. This replaces the need for, or enhances, crop inspections for aphids early in the growing season. This is useful because considerable virus spread can occur when only a few aphids are visible in the crop and these aphids are hard to find unless searches are done very thoroughly. The simulation model also makes it easier for users to understand the implications of sowing seed with a range of different infection levels and how altering sowing date can affect the risk of spread. A limitation is that currently inputting climate data to do model runs is time consuming, so for the internet forecasts they are only done for one location in a shire, although for a range of sowing dates. In the future we hope to automate model runs and perhaps make the model itself available over the internet. |
| Inputs: |
For the model: level of seed infection, sowing date, and daily rainfall and temperature data. For the internet forecasts: level of seed infection, sowing date, then look for your location on the map. |
| Outputs: |
From the model: start of aphid immigration, CMV incidence, yield loss from CMV damage, CMV infection in seed at harvest. From the internet site: yield loss from CMV damage for each shire, for a range of sowing dates. |
| Expertise/system r'quts: |
Internet forecasts: Familiarity with internet navigation. Usual system requirements for internet use. Model: Ability to follow simple instructions and a little familiarity with typing information into boxes. Model is built using “Stella” software, but user does not need to be familiar with it. |
| Availability/status: |
Forecasts available each growing season in late April through internet site: [Expired] www.agric.wa.gov.au/cmv. Model not currently available, except through direct contact with Debbie Thackray . In future, we hope to automate climate data retrieval and make model available on the internet or on a CD. |
| Contact: | Debbie Thackray, Tel: (08) 6488 7574; Email: djthack@clima.uwa.edu.au |
| Name of model: |
e-VarietyProfiler |
| Developer(s): | Dr. Moin Salam, Kawsar Salam, Blakely Paynter, Graham Walton, Geoff Thomas, Kedar Adhikari, Harmohinder Dhammu and Greg Shea |
| Aims/use: | To assist growers with choosing a variety to suit their circumstances. |
| Key features: | It collates scattered information from the Crop Variety Sowing Guide and other sources, such as agronomic trials, and arranges that information in profiles of physical characteristics, disease risk, abiotic stresses, herbicide tolerance and yield. It also provides and opportunity to obtain potential net return from a variety in a given location. Users can compare up to six varieties side by side at a time. |
| Audience: | Growers, Consultants |
| Regions, scale, time of year: | The current version of the profiler includes varieties of five crops for Western Australia- 53 wheat, 24 barley, 14 oats, 15 lupins and 37 canola. |
| Types of decisions: | Variety selection/comparison |
| Strengths/limitations: | Strength:A quick way to compare crop varieties. Limitation: Need MS-Excel software to run. |
| Inputs: | Location, crop varieties |
| Outputs: | Varietal characteristics and gross return. |
| Expertise/system r'quts: | Windows 98, Windows XP, Microsoft 97 or onwards |
| Availability/status: | Free cd, eVarietyProfiler can be downloaded from dept's web page: http://agric.wa.gov.au/ search for e-variety profiler |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
e-Variety Guide for Stripe Rust |
| Developer(s): | Dr. Moin Salam, Ms Megan Collins, Dr. Art Diggle and Dr. Rob Loughman |
| Aims/use: | To select right variety for stripe rust |
| Key features: | This estimator compares the economic return of two varieties by Agzone. It takes account of potential yields and the risk of stripe rust in each Agzone, as well as the costs of chemical control, the cost of changing variety and wheat prices. |
| Audience: | Consultants and advisers |
| Regions, scale, time of year: | Wheat belt; AgZone/Independent; During seed selection (harvesting). |
| Types of decisions: | What variety be used for next season |
| Strengths/limitations: | Easy to use tool; it does not consider effect of stem and leaf rust; so care should be taken while using this. |
| Inputs: | Virtually nothing; but user can change the default values. |
| Outputs: | Net returns from variety A and B |
| Expertise/system r'quts: | Basic computer skills; Compatible with Excel 5, 95, 97 & 98 on Windows and Macintosh systems (untested for later versions, but should work). |
| Availability/status: | On diskette or electronically; Released 2002; updated Feb 2003 |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
Resistance and Integrated Management model(RIM) |
| Developer(s): | Dr David Pannell, Vanessa Stewart, Anne Bennett, Marta Monjardino, Carmel Schmidt and Professor Steven Powles. |
| Aims/use: | A decision tool for investigating the biological and economic impacts of weed management options for annual ryegrass. |
| Key features: | Allows the evaluation of different weed management technologies over a 10 year rotation. Through selecting different treatments can observe impact of weed numbers and $/ha returns over time. Simulation model incorporating biological and economic data on weed management. |
| Audience: | Farmers, agronomists, researchers all agri industry |
| Regions, scale, time of year: | NA |
| Types of decisions: | Broadacre agriculture - standard/default assumptions set for Eastern wheatbelt, designed so that can easily adjust key parameters for different regions; weeds/m2; $/ha - extrapolate to paddock/farm implications; Can use at any time - run workshops in Autumn/spring |
| Strengths/limitations: | Can readily observe the impact of incorporating or excluding various weed management techniques from integrated weed management strategies. Can see impact that these treatments have in year applied and is successive years of rotation. Easy to adjust parameters to "regionalise", Fantastic interactive workshop tool, Excellent for conducting sensitivity analysis. Weaknesses - assumptions based on "average expected outcome" - no year to year variation |
| Inputs: | To select treatments user enters an x; Can alter most assumptions to allow sensitivity analysis or to regionalise |
| Outputs: | Weeds/m2; Seed production/m2; $/ha; annualised $/ha over length of rotation and many more |
| Expertise/system r'quts: | Basic computer skills, some understanding of farming systems, innovative thinking; Excel 97 or better |
| Availability/status: | On request - Top Active Package or RIM package $55 inc GST; Released 1998; Updated Jan 2003 |
| Contact: | Vanessa Stewart, Tel: (08) 9081 3111, Dept of Agriculture and Food Western Australia, Merredin; Dr Rick Llewellyn, WAHRI (08) 9380 3419 |
| Name of model: |
Flowering Calculator |
| Developer(s): | Dr David Tennant |
| Aims/use: | A model to calculate flowering time for a selection of crops and varieties to ensure optimum flowering time and ultimately grain yield. |
| Key features: | Advanced graphical user interface makes it easy to show 'flowering window' limits for selected crops and varieties |
| Audience: | Department researchers and advisers; consultants |
| Regions, scale, time of year: | Grainbelt; Farm/shire; Start of season |
| Types of decisions: | Which variety and when to sow it? |
| Strengths/limitations: | Easy to use. Easy to understand outputs. At prototype stage. |
| Inputs: | Rainfall, temperatures, phenological information |
| Outputs: | Graphical displays of the flowering window with frost, temperature and flowering events; calculates and displays probabilities of temperature events and frost events. |
| Expertise/system r'quts: | Basic computer skills; Minimum system requirements: IBM-compatible PC with minimum specifications of Pentium 90, 16 Mb RAM, CD-ROM, 800x600 display, Windows 95. |
| Availability/status: | On request; on CD; Beta version available |
| Contact: | Dr Meredith Fairbanks, Tel: (08) 9441 8112 , Email: mfairbanks@agric.wa.gov.au |
| Name of model: |
NP Decide |
| Developer(s): | Mr Steve Burgess, Drs Art Diggle and Bill Bowden |
| Aims/use: | To address nitrogen and phosphorus fertiliser decisions |
| Key features: | Predicts fertiliser N P yield and dollar response surfaces for any yield potential and soil P and N status. Has a soil P calculator. Takes account of the effects of take-all on responses too different N sources. |
| Audience: | Consultants, advisers and farmers |
| Regions, scale, time of year: | Wheat growing areas; Paddock; Can be used both strategically and tactically (i.e. all year) |
| Types of decisions: | Fertiliser (NP) type, rate and timing for cereal crops |
| Strengths/limitations: | Handles N and P together, gives a two fertiliser matrix output. Has simple save and recall routines. Does not consider grain quality effects. |
| Inputs: | Soil type, soil P test, cropping history, yield potential, take-all severity, rainfall zone, costs and prices. |
| Outputs: | Two fertiliser rate matrix of yield, current returns and returns considering future value of phosphorus. |
| Expertise/system r'quts: | Basic computer skills; PC running Windows operating system. |
| Availability/status: | Available on floppy disk; Last update 1992 |
| Contact: | Dr Bill Bowden, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2190, Fax: (08) 9622 1902, Email: bbowden@agric.wa.gov.au |
| Name of model: |
OPTLIME |
| Developer(s): | Mr Andrew Sandison, Mr Michael O'Connell |
| Aims/use: | 1. To explore the chemical/biological and financial responses to managing soil acidity using lime. 2. To assess the impact or relative differences between different management strategies eg increased tolerance to acidity in the rotation, vs. management with topsoil or subsurface liming and wider range of options in the rotation. |
| Key features: | Allows input of soil parameters specific to situations. Allows wide range of options and the ability to change these options between two concurrent analyses. |
| Audience: | Development Officers, advisers and consultants and leading farmers |
| Regions, scale, time of year: | Productive agriculture, excluding horticulture enterprises. Best calibrated to grainbelt but includes pasture options and higher rainfall zone capability; Paddock scale application; Any time, but if used in conjunction or as a decision aid for lime purchases best used following harvest to early May. |
| Types of decisions: | Soil acidity management decisions including lime quantity and potentially crop decisions |
| Strengths/limitations: | Brings together a wealth of information that has been developed specifically for WA conditions. Outputs are dynamically linked and updated as factors in the scenario are altered. No viable competitor at present. Is not a lime recommendation tool but rather a decision aid. Calibrates to applications of lime within the "normal" range used under field conditions (i.e. 0-4 t/ha) per 5-10 years. |
| Inputs: | Annual rainfall, Soil description, 7 choices from sand to heavy clay, for three layers, Starting soil pH profile, Starting Al toxicity profile, % Gravel, Bulk density, pH buffering capacity, Lime Quality and cost, Transport and spreading costs, Costs associated with deep banding of lime, Up to a 10 year crop rotation chosen from 16 enterprises (rotation then extended to 25 yr time frame for analysis), Yield potential of crops/product (acidity non-limiting), Crop tolerance to acidity, Fertiliser/rate applied (can enter two fertilisers per yr), Lime applications to surface or choice of depths in any of the 25 years. |
| Outputs: | Results of analysis prepared for printing, Investment appraisal, Graphical representation of outputs as below, Limed soil pH profile (select up to 4 yrs from 25), Unlimed soil pH profile (select up to 4 yrs from 25), Effects of treatments on toxic Aluminium by soil layer, Relative yields with time. Annual and accumulated cash flow, Lime removal (separated into total, products, fertiliser and leached contributions), Fate of applied lime. |
| Expertise/system r'quts: | Workshop training; PC computer with Microsoft Excel (Needs to be more fully tested to identify situations where it does not run) |
| Availability/status: | Available on CD with pdf users manual after training in workshop; Released in October 2002, refinement continuing Link: [Expired] |
| Contact: | Mr Chris Gazey, Tel: (08) 9690 2000, Dept of Agriculture and Food Western Australia, Northam. |
| Name of model: |
Potential Yield Calculator (PYCAL) |
| Developer(s): | Dr David Tennant |
| Aims/use: | 1. To estimate stored soil water at the start of the growing season or at planting. 2. To forecast potential yield for a range of cereal, legume and oilseed crops as the season progresses and calculate potential yield at end of season. |
| Key features: | Estimates stored soil moisture at planting or at start of growing season; Charts rainfall received against expected decile rainfall totals or rainfall received in earlier years; Identifies planting opportunities using a planting rule that can be user modified to suit local conditions; Forecasts potential yield for crops as the season progresses; Calculates yield and water use efficiencies at the end of the growing season; Calculates likelihood of receiving rainfall to achieve target yields. |
| Audience: | Farmers, consultants, advisers |
| Regions, scale, time of year: | Grainbelt; Farm; At start of season and within season |
| Types of decisions: | Sowing, crop nutrition, pest control |
| Strengths/limitations: | Widely used through the Climate Risk and Yield Information Service and as a stand alone tool in SA, Vic and WA cropping districts. Decile data sets supplied though extensive are not exhaustive. While procedure is given for including data for new sites, data are not readily available and inclusion process is complex. Growing season is limited to April/may to Sept, Oct or Nov. No flexibility to include crops growing beyond Dec 31. Rainfall data files have to be created manually. |
| Inputs: | Your summer rainfall and seasonal daily rainfall; your expected or observed final yields |
| Outputs: | Potential yield; stored soil water; accumulated rainfall; current decile category; water use efficiency |
| Expertise/system r'quts: | basic computer skills; Minimum system requirements: IBM-compatible PC with minimum specifications of Pentium 90, 16 Mb RAM, CD-ROM, 800x600 display, Windows 95. |
| Availability/status: | Available on CD; Released: 1996. Updated: D. Tennant, Aug. 2002. Non-DAWA staff can purchase a copy of PYCAL from Dr Meredith Fairbanks, 9441 8112, Email: mfairbanks@agric.wa.gov.au |
| Relevant Links: | Climate Calculator |
| Contact: | Dr Meredith Fairbanks, Tel: (08) 9441 8112, Email: mfairbanks@agric.wa.gov.au |
| Name of model: |
ROOTMAP |
| Developer(s): | Dr Vanessa Dunbabin and Dr Art Diggle |
| Aims/use: | Simulates interactions between plant roots and the soil environment |
| Key features: | Produces an animated pictorial representation of the root systems and soil conditions |
| Audience: | Research workers performing detailed examinations of roots and their function |
| Regions, scale, time of year: | Any; <1 square metre; growing season |
| Types of decisions: | Choice of variety, any agronomic decision that affects soil conditions |
| Strengths/limitations: | Requires programming skill and lots of time |
| Inputs: | Detailed measurements of roots and soils |
| Outputs: | Detailed prediction of root growth, function and effects |
| Expertise/system r'quts: | C++ programming; Macintosh |
| Availability/status: | By negotiation; details published in Plant and Soil 2002 |
| Contact: | Dr Art Diggle, Tel: (08)9368 3669, Fax: (08)9374 3749, Email: adiggle@agric.wa.gov.au |
| Name of model: |
SPLAT |
| Developer(s): | Dr Bill Bowden, Ms Alex Edward |
| Aims/use: | To choose wheat cultivar and nitrogen rate within the context of seasonal variation |
| Key features: | Estimates yield, protein and dollar responses to nitrogen for different environmental and management scenarios. Yield potential in SPLAT comes from 80 to 100 year runs of the WA version of the APSIM simulation model for a factorial of cultivar, sowing time, soil type and location. Allowance is made for disease and weed levels in the crop. A single figure soil nitrogen status is entered. |
| Audience: | Consultants, advisers and farmers |
| Regions, scale, time of year: | Wheat growing areas; paddock; can be used strategically |
| Types of decisions: | Sowing date, cultivar choice and nitrogen level |
| Strengths/limitations: | The determination of yield potential for different seasons, sowing dates, soil types and locations (superceded by WA Wheat) is interacted with nitrogen rate effects and dose response curves are given for dollars, yield, protein and screenings. A comparative output between species and a seasonal probability analysis is given. The nitrogen input is a single figure and only one fertiliser nitrogen availability is considered. |
| Inputs: | Location, cultivar, sowing date, soil type, weed history |
| Outputs: | Comparative gross margin graphs for different seasonal decile ratings. Yield, protein and screenings response curves |
| Expertise/system r'quts: | Basic computer skills; Microsoft Excel operating under Macintosh of Windows system |
| Availability/status: | Available on floppy disk or via email; released 2000 |
| Contact: | Dr Bill Bowden, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2190, Fax: (08) 9622 1902, Email: bbowden@agric.wa.gov.au |
| Name of model: |
Yield Calculator |
| Developer(s): | Dr David Tennant |
| Aims/use: | 1. To estimate stored soil water at the start of the growing season or at planting. 2. To forecast yield for a range of cereal crops as the season progresses and calculate yield at the end of the season 3. Can be used to quantify a technology trend. |
| Key features: |
Estimates stored soil moisture at planting or at start of growing season; forecasts yield for crops as the season progresses based on a stress index and previous yields; calculates yield trends in terms of kg/ha/year. |
| Audience: | Farmers, consultants, advisers |
| Regions, scale, time of year: |
Calibrated for all Australian wheatbelt shires; can be calibrated using farm yields ( 10 years or more); at start of season and within season. |
| Types of decisions: | Provides information on yield probabilities. |
| Strengths/limitations: |
Strengths - widespread application; can be used across Australian grainbelt; predicts actual yields (if time series of yields and rainfall is available); works best in water-limiting regions. Limitations - requires a sequence of yields from which to derive the parameters. |
| Inputs: |
Daily rainfall, past yields, soil type, location-specific parameters. |
| Outputs: |
Predicted yields through the season compared to yields from all other years of modelled runs, plant available soil moisture up to sowing. |
| Expertise/system r'quts: |
Basic computer skills; Windows-compatible computer running Microsoft Excel. |
| Availability/status: |
Under development. Alpha version available on request |
| Contact: |
Dr David Tennant, Ph: 9368 3287, Email: dtennant@agric.wa.gov.au; or Dr Meredith Fairbanks, Ph: 9441 8112, Email: mfairbanks@agric.wa.gov.au |
| Name of model: |
Select Your Nitrogen(SYN) |
| Developer(s): | Drs Art Diggle and Bill Bowden |
| Aims/use: | Select Your Nitrogen - a quantitative expert system to address soil nitrogen issues and their effects on yield, quality and dollars in broadscale cropping systems. |
| Key features: | Major emphasis on effects of rotation, tillage, soil type and rainfall on soil nitrogen availability and it's impact on yield, quality (oil%, protein%) and dollars for non legume crops. It can handle segregations of cereals. Pulls together all previous WA nitrogen research and models (NAVAIL, RONSON, SPLAT). |
| Audience: | Consultants, advisers and farmers |
| Regions, scale, time of year: | Broadacre non-legume cropping systems; Paddock; Can be used both strategically and tactically (i.e. all year) |
| Types of decisions: | Rotation, varietal choice, tillage and nitrogen fertiliser timing, sources and rates. |
| Strengths/limitations: | Handles all crop nitrogen issues except foliar uptake. A comparative output format is used. Requires the input of a yield potential (SPLAT and WA Wheat do this better but are not as good on nitrogen availability issues) |
| Inputs: | Soil, rainfall, cultivar and fertiliser menus can be adjusted by the user. Costs and prices can be adjusted. Rotation phases come in from menus and yields, harvest indices and pasture composition have to be estimated. |
| Outputs: | Soil and nitrogen "availability", yield protein/oil and dollar returns. Sensitivity analyses on responses to rate of fertiliser, timing of fertiliser and yield potential. |
| Expertise/system r'quts: | Basic computer skills; Microsoft Excel '97 or better |
| Availability/status: | Available on a CD with users' manual as pdf; released October 2002. Updated May 2003 |
| Contact: | Dr Bill Bowden, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2190, Fax: (08) 9622 1902, Email: bbowden@agric.wa.gov.au |
|
Name of model: |
TACT |
| Developer(s): | Mr Steve Robinson and Dr Doug Abrecht |
| Aims/use: | Critical information for assessing risks associated with sowing wheat |
| Key features: | Climate analysis using heuristic rules and simulations of wheat yield and development |
| Audience: |
Agriculturalists with 'risky' questions |
| Regions, scale, time of year: | All regions, but wheat simulation best in low rainfall eastern wheatbelt; point (scaled to paddock/lmu); anytime, strategic or tactical issues, depends on question and information required. |
| Types of decisions: | Assessing rainfall and temperature dependant risks eg sowing opportunities/ rain during haymaking or shearing, frost risk, high temperature risk. Assessing impact of wheat sowing strategies on yield prospects given soil type and season to date rainfall. |
| Strengths/limitations: | Easy to use. Season to date capability in yield simulation, distribution of differences compared to difference in distributions for assessing the impact of sowing decisions. Does not work well outside the eastern wheatbelt or on lighter soils. |
| Inputs: | Current season (season to date) and historical daily weather data (max and min temperatures, rainfall, radiation) OR daily rainfall and average daily max min temperature and radiation. |
| Outputs: | Graphs and tables of probability of outcomes/ yield distributions |
| Expertise/system r'quts: | Basic computer skills; PC with MS DOS capability. |
| Availability/status: | On request as foreign order; self expanding archive on 3.5 floppy or email; released 1992, updated 1996. |
| Contact: | Dr Doug Abrecht, Tel: (08) 9081 3106, Mobile: 0427934648 Email: dabrecht@agric.wa.gov.au |
| Name of model: |
WA Wheat |
| Developer(s): | Dr James Fisher and Mr Craig Scanlan |
| Aims/use: | Enables users to predict the impact of particular combinations of season and management on wheat yield, protein content and the leakage of water and nitrate beyond the root zone for locations and soil types across the WA wheatbelt |
| Key features: | We have used a validated simulation model, APSIM, to produce a database of information on wheat production in Western Australia for different combinations of season, soil type and management. The database has a powerful interface that enables data to be filtered and presented in a wide range of graphs. Data relating to production, quality, phenology, crop stresses, rainfall, water leakage and nitrate leaching can be displayed. Data can easily be exported to a spreadsheet for further analyses. |
| Audience: | Farmers, consultants, advisers, researchers |
| Regions, scale, time of year: | Wheatbelt; paddock; planning for the coming season. Regional/district analyses. Limited application within a season. |
| Types of decisions: | Time of sowing, N fertiliser application (timing and rate), variety selection. Likely outcomes given historical seasons. |
| Strengths/limitations: | Strengths: contains over 12 million datapoints, has broad application across the wheatbelt, has a wide range of outputs. Limitations: based on fixed runs of the model, limited flexibility to analyse a specific situation, data for wheat only. |
| Inputs: | Select options from a fixed database. |
| Outputs: | Wheat production, quality, phenology, crop stresses, rainfall, water leakage and nitrate leaching. Distributions, frequencies, time series, x-y plots. Data can be exported to a spreadsheet for further analyses. |
| Expertise/system r'quts: | Familiarity with Windows-type of programs. Intermediate to high skill in creating and interpreting graphs; PC running Windows operating system with at least 64 MB RAM and a Pentium processor. |
| Availability/status: | To be distributed via CD-ROM.; Released May 2003. A second edition of the database is being developed as part of the "National Whopper Cropper" project. |
| Contact: | Dr James Fisher, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2125, Fax: (08) 9622 1902, Email: jsfisher@agric.wa.gov.au |
| Name of model: |
MUDAS |
| Developer(s): | Dr Ross Kingwell |
| Aims/use: | Represent a typical whole-farm system, including economic and biological components. Also includes tactical management. |
| Key features: | Optimal farm plan for profit maximisation |
| Audience: | Researchers |
| Regions, scale, time of year: | Various; farm; anytime |
| Types of decisions: | Enterprise mix, rotation selection, flock size and composition |
| Strengths/limitations: | Strengths: Includes interactions between enterprises and activities, profit maximisation. Limitation: Requires good understanding of farm system modelled and knowledge of linear programming. |
| Inputs: | No further inputs for existing model (except updates) |
| Outputs: | Optimal farm plan, economics of different activities |
| Expertise/system r'quts: | Knowledge of linear programming, considerable training to use the model; MS-dos based. |
| Availability/status: | On request; users can ask for an output from contact person; In use |
| Contact: | Dr Ross Kingwell, Economic Services, Dept of Agriculture and Food Western Australia |
| Name of model: |
IMAGINE |
| Developer(s): | Don Cooper, Dr Amir Abadi |
| Aims/use: | Provides financial analysis of alternative land uses, Provides financial analysis of alternative land uses. |
| Key features: | Can include long rotation crops, such as trees and allows spatial configuration within a paddock, for example, an alley farming scenario. |
| Audience: | Researchers |
|
Regions, scale, time of year |
Any paddock; any time |
| Types of decisions: | Choice of rotation |
| Strengths/limitations: | Strengths: Allows spatial configuration of different crops within a paddock. Includes spatial and temporal interactions. Not limited to any region. Limitations: User must enter all data for the particular crops they want to assess. |
| Inputs: | All production values, costs prices for the crop |
| Outputs: | Financial indicators, such as Net Present Value, Annual Equivalent Return. |
| Expertise/system r'quts: | Good computer skills; Windows 2000 or better. |
| Availability/status: | On request; In use. |
| Contact: | Dr Amir Abadi, Email: aabadi@agric.wa.gov.au, Economic Services, Dept of Agriculture and Food Western Australia |
| Name of model: |
Regional Farm Model |
| Developer(s): | Mr Michael O'Connell |
| Aims/use: | Tracks different whole farm financial outcomes to unfolding seasonal conditions |
| Key features: | Predicts profit, cash and net worth outcomes |
| Audience: | Advisers - for regional intelligence |
| Regions, scale, time of year: | All; Whole farm. Scale up to region; Monthly - event driven. |
| Types of decisions: | Advice on enterprise selection, stock sales, input management, financial impact. |
| Strengths/limitations: | Easy "quick and dirty" appraisal of how farm businesses might be travelling. Representation of any region/district depends on 'representative' inputs in structuring the model. |
| Inputs: | Farm business physical and financial benchmarks, regional statistics |
| Outputs: | Predicts profit, cash surplus, and change in net worth for a representative farm. Can scale up to gross value impact on the region. |
| Expertise/system r'quts: | Basic spreadsheet. Minor prior exposure to farm business financials.; Microsoft Excel |
| Availability/status: | On request; Released 2002. Updating representative regional models is on-going. |
| Contact: | Regional economists, Dept of Agriculture and Food Western Australia |
| Name of model: |
STEP |
| Developer(s): | Caroline Peek, Anne Bennett, Allan Herbert, Dave Rogers |
| Aims/use: | Simulate the costs of making the transition from one farming system to another |
| Key features: | Whole Farm Development Budget |
| Audience: | Consultants, farmers, researchers |
| Regions, scale, time of year: | Any; whole farm; a planning tool that can be used any time |
| Types of decisions: | How you will make the transition |
| Strengths/limitations: | No preset figures |
| Inputs: | All costs |
| Outputs: | Detailed budget |
| Expertise/system r'quts: | Medium Excel skills; Excel 95 + |
| Availability/status: | Available on CD; Jul-03 |
| Contact: | Caroline Peek, Dept of Agriculture and Food Western Australia, Geraldton, WA 6525, Tel: (08) 9956 8519, Email: cpeek@agric.wa.gov.au |
| Name of model: |
Lime and Nutrient Calculator |
| Developer(s): | Drs James Fisher, Art Diggle and Bill Bowden |
| Aims/use: | To estimate the acidification and removal of nutrients associated with broadacre rotations. |
| Key features: | Available in either printed or electronic (Excel) format; acidification and nutrient removal related to production, leaching and acidifying fertilisers; covers broadacre crops, hay, wool and meat production; values for macro and micro nutrients. |
| Audience: | Farmers, consultants, advisers |
| Regions, scale, time of year: | Broadacre agriculture; paddock; fertiliser ordering and long-term planning. |
| Types of decisions: | Quantity of ameliorants need to maintain the status quo. |
| Strengths/limitations: |
Strengths: Good information source for nutrient contents; simple mechanics; covers wide range of nutrients and products. Limitations: based on average values only; simple relationships; does not indicate change in pH or nutrient status; value given needs to be adjusted for efficiency in order to get an application rate. |
| Inputs: | Information on location, broad soil-type, products harvested, fertiliser application (from menus) |
| Outputs: | Quantity of removal as lime equivalents or amount of nutrient (as total and per year); how quantities are apportioned between product removal, leaching and acidifying fertilisers. |
| Expertise/system r'quts: | Basic computer skills; assistance with interpretation may be required; Compatible with Excel 95, 97 & 98 on Macintosh and Windows systems (untested for later versions, but should work). |
| Availability/status: | Package of explanatory notes, printed calculator and computer disk available from TopCrop (c/-Department of Agriculture Northam, Ph: 9690 2000); Released 1998, one update since (1999) |
| Contact: | Dr James Fisher, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483 Northam 6401. Tel: (08) 9690 2125, Fax: (08) 9622 1902, Email: jsfisher@agric.wa.gov.au |
| Name of model: |
Potassium In Agricultural Systems Model (KASM) |
| Developer(s): | Mr Craig Scanlan and Dr Bill Bowden |
| Aims/use: | A soil-crop model that allows users to assess short and long term potassium (K) nutrition of agricultural production systems. |
| Key features: |
KASM is a simulation model operating on a weekly time-step. This means that at the end of each week, KASM adds rainfall for that week, applies any products the user has specified for that week and calculates crop growth for the week. This process is repeated for a one year period. This type of model gives enormous flexibility to the user, and the capacity to test the model thoroughly against individual trials. |
| Audience: |
Advisers, farmers, researchers |
| Regions, scale, time of year: | Broad-acre agricultural systems in WA; annual |
| Types of decisions: |
Advice on K fertiliser applications and long-term planning. KASM is ideal for working out directional changes to strategies when conditions change. It has been developed to address the questions of “how much ?”, “how often ?” and “when ?” for K nutrition of broad-acre grain crops in Western Australia. |
| Strengths/limitations: | Strengths - able to address individual situations, in terms of soil types, fertiliser strategies and yield and price expectations; provides both short-term and long-term analyses. KASM has been rigorously tested against Department of Agriculture trial data and by ‘sensibility analysis??™ by the developers, researchers with field experience in potassium response, and by agribusiness professionals who have experience in potassium nutrition at a farm-scale. Limitations - calculates growth in response to K status of the crop only. Other agronomic constraints such as soil moisture, pH, aluminium, nitrogen supply or phosphorus supply do not affect crop growth in each time-step. The model is best suited to light soils in WA. Care should be taken in adapting the model to other environments. |
| Inputs: | Paddock history, fertiliser applications, Colwell K test, rainfall all from menus, but with option for data to be entered by the user. |
| Outputs: | crop yield, changes soil K levels through time, K removal and leaching, distribution of K through the soil profile. |
| Expertise/system r'quts: | Basic computer skills; Windows-compatible computer running Microsoft Excel 2000/2002/XP or better, CD-ROM. |
| Availability/status: | Available on CD including users' manual, technical notes and sample rainfall files; released June 2005. |
| Contact: | Dr Bill Bowden, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483 Northam WA 6401. Tel: (08) 9690 2000, Email: bbowden@agric.wa.gov.au |
| Name of model: |
Farm Energy Calculator |
| Developer(s): | Dr. Moin U. Salam, Dr. Glen P. Riethmuller, Nicolyn Short, Tim Maling, Jodie Bowling, Dr. James S Fisher |
| Audience: | Consultants, advisers and farmers |
| Regions, scale, time of year: | Broadacre cropping systems; Paddock; Can be used both strategically and tactically (i.e. all year) |
| Types of decisions: | Assess the energy usage of farm management options for the crop and animal components of a farm enterprise; compare fuel use under various farm management options (eg. tillage, sowing, hay production, harvesting, crop/sheep monitoring etc.), soil types, crops and paddocks for the crop and livestock components of the farm |
| Strengths/limitations: | The farm energy (fuel) calculator was tested under real-world conditions. Results showed the calculator predicted well what the farmer recorded for spraying, spreading, seeding, raking and stacking, and slightly overestimated harvesting, baling and mowing operations. Calculator is designed only for broadacre cropping. |
| Inputs: | Multiple pasture and cropping paddocks, crop type, machinery types, spraying regime, cultivation, haymaking, distance to delivery, crop/sheep monitoring. |
| Outputs: | Total fuel usage/cost, breakdown of fuel usage for each paddock/management option |
| Expertise/system r'quts: | Basic computer skills; Microsoft Excel '97 or better |
| Availability/status: | Available on a CD |
| Contact: | Dr Moin Salam, Centre for Cropping Systems, Dept of Agriculture and Food Western Australia, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
DAMCAT4 |
| Developer(s): | Mr. Darren Farmer and Dr. Neil Coles. |
| Aims/use: | Windows update of Damcat program developed by the department in the late 75's to design dam and catchments for water supplies based on expected monthly demand. |
| Key features: | Design of catchment and dam size for different climate and demand variables. |
| Audience: | advisers, farmers, research workers. |
| Regions, scale, time of year: | Southwest dryland agriculture; paddock; can be used both strategically and tactically (i.e. all year). |
| Types of decisions: | Stocking rate. |
| Strengths/limitations: | Design period or ARI ( Average Recurrence Interval) restricted. Cost of construction. |
| Inputs: | Rainfall, evaporation and demand. |
| Outputs: | Dam and catchment size. |
| Expertise/system r'quts: | Basic computer skills; any modern computer. |
| Availability/status: | For more information and updates please refer to the Dept of Agriculture and Food Western Australia web site: http://www.agric.wa.gov.au (search for Farm Water or DAMCAT). |
| Contact: | For development contact: Mr Darren Farmer, for general information contact: FarmWaterInfo@agric.wa.gov.au |
| Name of model: |
Dam-Volume Calculator |
| Developer(s): | Mr. Darren Farmer and Dr. Neil Coles |
| Aims/use: | Determines the amount of water remaining in a dam and calculates its potential supply reliability based on a given demand and evaporation. |
| Key features: | Derives supply vs. demand and identifies length of time water will last for given demand with no rainfall. |
| Audience: | Advisers, farmers, research workers. |
| Regions, scale, time of year: | Southwest dryland agriculture; paddock; can be used both strategically and tactically (i.e. all year). |
| Types of decisions: | The program is expected to provide an adequate indication of existing farm water supplies and dam capacity. |
| Strengths/limitations: | The methods used in the Dam Volume Calculator program assumes that the situation being calculated can be approximated by a regular geometry. They do not allow for gully dams, irregular geometry, variable batter slope or other issues that might affect accurate volume calculator. |
| Inputs: | Standard volume equation (prismoidal formula). |
| Outputs: | The volume for square, rectangular and circular dam shapes from basic measurements. It also provides an indication of capacity lost to sedimentation and evaporation when appropriate data are provided. |
| Expertise/system r'quts: | Basic computer skills; any modern computer. |
| Availability/status: | For more information and updates please refer to the Dept of Agriculture and Food Western Australia web site:http://www.agric.wa.gov.au(search for Farm Water or Dam Volume). |
| Contact: | For development contact : Mr Darren Farmer, for general information contact: FarmWaterInfo@agric.wa.gov.au |
| Name of model: |
RAINTANK2 |
| Developer(s): | Mr. Darren Farmer and Dr. Neil Coles. |
| Aims/use: | Simple program to determine optimum roof area and tank size for rainwater collection to meet nominated demand and reliability of supply. |
| Key features: | Provides optimum raintank size for available roof areas. |
| Audience: | advisers, farmers, research workers. |
| Regions, scale, time of year: | Southwest dryland agriculture; paddock; Can be used both strategically and tactically (i.e. all year). |
| Types of decisions: | Drinking rate-600L/day. |
| Strengths/limitations: | Restricted to 600L/day demand. Being upgraded. |
| Inputs: | Rainfall and demand. |
| Outputs: | Raintank size or roof area required. |
| Expertise/system r'quts: | Basic computer skills; any modern computer. |
| Availability/status: |
For more information and updates please refer to the Dept of Agriculture and Food Western Australia web site: http://www.agric.wa.gov.au(search for Farm Water or Rain Tank). |
| Contact: | For development contact: Mr Darren Farmer, for general information contact: FarmWaterInfo@agric.wa.gov.au |
| Name of model: |
AgET |
| Developer(s): | Dr Rob Argent, Uni. Melb. |
| Aims/use: | Comparison of recharge under different soil-crop combinations. |
| Key features: | Easy to use, default data files for whole agricultural region come with the software. |
| Audience: | Development officers, advisers, consultants, landcare professionals. |
| Regions, scale, time of year: | Whole agricultural region, regional soils files currently under development; paddock (strictly speaking an infinitesimal point in a flat, uniform landscape); any time. |
| Types of decisions: | Awareness raising, landcare planning |
| Strengths/limitations: | Easy to use, easy to abuse - relativities between predicted recharge numbers usually adequate, requires calibration to give "correct" values. |
| Inputs: | All inputs supplied, user selects location to load climate data & soil/crop to load parameters. |
| Outputs: | Relative water balance under different management for selected area. |
| Expertise/system r'quts: | Basic knowledge of agricultural systems; Windows 95 or better. |
| Availability/status: | AgET Released 1999, now version 2.1, user support from Paul Raper. |
| Contact: | Dr Paul Raper, Hydrologist, Dept of Agriculture and Food Western Australia, Bunbury, Tel: (08) 9780 6255, Email: praper@agric.wa.gov.au |
| Name of model: |
CATCHER |
| Developer(s): | Dr Rob Argent, Uni. Melb. |
| Aims/use: | Determine first pass water balance for farm or catchment. |
| Key features: | Uses AgET output files. |
| Audience: | Development officers, advisers, consultants, Landcare professionals. |
| Regions, scale, time of year: | Whole ag region; paddock, farm or small catchment; any time. |
| Types of decisions: | Awareness raising, landcare planning. |
| Strengths/limitations: | Relies on AgET output, no run off, run on or other lateral water flow, no groundwater discharge. |
| Inputs: | AgET output plus proportion of farm-catchment under each soil-crop combination. |
| Outputs: | Relative water balance under different management for selected area. |
| Expertise/system r'quts: | General knowledge of water in agricultural catchments; Windows 95 or better. |
| Availability/status: | Catcher Draft version 1.1, some known bugs. |
| Contact: | Dr Paul Raper, Hydrologist, Dept of Agriculture and Food Western Australia, Bunbury, Tel: (08) 9780 6255, Email: praper@agric.wa.gov.au |
| Name of model: |
Flowtube Model |
| Developer(s): | Dr Rob Argent, Uni. Melb. |
| Aims/use: | Predict area with shallow water table under different management scenarios. |
| Key features: | 2D slice down a hillslope or catchment. |
| Audience: | Hydrologists, consultants, Landcare professionals (maybe). |
| Regions, scale, time of year: | Whole Agricultural region, a range of examples are available for download; catchment or hillslope; any time. |
| Types of decisions: | Awareness raising, landcare planning, regional planning. |
| Strengths/limitations: | Strength is ease of use, main weakness is relating 2D length with shallow groundwater to catchment area (3D). |
| Inputs: | A transect of bores and time series of groundwater observations, recharge estimates a transect of bores and time series of groundwater observations. |
| Outputs: | Predictions of depth to groundwater over time. |
| Expertise/system r'quts: | Basic quantitative hydrology skills; Windows 95 or better. |
| Availability/status: | Flowtube Version 2.0, well supported, used nationally. |
| Contact: | Dr Paul Raper, Hydrologist, Dept of Agriculture and Food Western Australia, Bunbury, Tel: (08) 9780 6255, Email: praper@agric.wa.gov.au |
| Name of model: |
Leakage Calculator |
| Developer(s): | Mr Richard O'Donnell, Dr Paul Raper |
| Aims/use: | First pass & awareness raising of leakage in the farm landscape. Comparison of current & potential land uses to impact on leakage ('What Ifs?'). |
| Key features: | Uses representative locations throughout the wheatbelt to cover the range of climate & soils of the grain-growing areas of the South-west agricultural region. Produces actual and relative leakage volumes to highlight areas that may respond to recharge control strategies based on perennial plants. |
| Audience: | Developed for use in salinity management workshops run for landholder groups. All land managers, including people supporting them - CLCs, group coordinators, consultants etc. |
| Regions, scale, time of year: | Agricultural areas of WA; paddock; annual rainfall figures; uses average soil type x land use factors |
| Types of decisions: | How much/ what/ where to incorporate perennials in the landscape. |
| Strengths/limitations: | Useful as an awareness raising tool, allows user to look at options at paddock scale. Very simple to operate, assumes no prior knowledge of water balance principles, inputs can be supplied in hectares-cubic metres or in acres-cubic yards. Limitations: Provides average figures, so leakage driven by extreme rainfall events is not reflected in the results. Not strong confidence in figures when tested with farmer groups (no way of checking figures against actual leakage in the ground). Provides leakage estimates for individual soil- plant combinations but not for rotations. |
| Inputs: | Area of soil type x land use for each paddock. Typical areas are provided as a guide. |
| Outputs: | Leakage in mm, m3 and Good Sized Farm Dams (1 GSFD = 2000m3). Outputs are colour-coded for easy interpretation; colours have been tested on colour-blind subjects. Allows user to determine which soil type x land use has the greatest potential for leakage and which soil types are likely to respond most to changes in land use. |
| Expertise/system r'quts: | Very little expertise required, no prior knowledge assumed. Written in Excel 97, requires Windows operating system running on base level PC. |
| Availability/status: | Version 1 fully tested & available on web site |
| Contact: | Paul Raper, Tel: 08 9780 6255, Email: praper@agric.wa.gov.au |
| Name of model: |
Climate Calculator |
| Developer(s): | Dr David Tennant |
| Aims/use: | 1. Graph rainfall data and calculate rainfall statistics for a location to better understand climate risks in that area. 2. Analyse relationships between yields and parameters such as rainfall and the Southern Oscillation Index. |
| Key features: | Graphs rainfall for any year, displays rainfall to date and the possible rainfall finishes enabling users to get an idea of how wet or dry the season may be. Calculates rainfall deciles to put into PYCAL. Enables users to find climate events for example: wettest day on record and how many days are below 2°C to identify frost risks for a specific location. Analysis of relationships between yields and climate parameters. |
| Audience: | Farmers, consultants, advisers. |
| Regions, scale, time of year: | Grainbelt; farm; at start of season and within season, annual rainfall as well. |
| Types of decisions: | Identify climate risks, look at rainfall records, graph rainfall records. |
| Strengths/limitations: | Ability to graph rainfall from Jan- Dec and display possible rainfall decile finishes. Ability for users to get a better idea of climate risks for their locations by looking at historical data for chances of frost and dry years for example. Calculates summer rainfall and growing season deciles which can be put into PYCAL. Rainfall files have to be updated manually. |
| Inputs: | Rainfall records, temperatures records, APSIM or STIN yields. |
| Outputs: | Rainfall graphs, rainfall deciles, `chocolate wheels` for yield/climate relationships. |
| Expertise/system r'quts: | Basic computer skills; Minimum system requirements: IBM-compatible PC with minimum specifications of Pentium 90, 16 Mb RAM, CD-ROM, 800x600 display, Windows 95. |
| Availability/status: | Development; on-going Beta version available to DAWA staff only |
| Contact: |
Dr Meredith Fairbanks, Tel: (08) 9441 8112, Email: fairbanks@agric.wa.gov.au |
| Name of model: |
Agroforestry Calculator |
| Developer(s): | Mr Gavin White, Campbell White & Associates, on contract to DAWA. |
| Aims/use: | To estimate the profitability of a farm forestry project. |
| Key features: | Standard tree enterprise details included, from which appropriate variants can be created; allows incorporation of off-site productivity effects within the paddock. |
| Audience: | Farmers, consultants, advisers. |
| Regions, scale, time of year: | Any; paddock; anytime. |
| Types of decisions: | Whether to invest in a tree crop. |
| Strengths/limitations: | Linear, for user friendliness; only straight line land productivity trends; requires farm forestry knowledge to input correct values. |
| Inputs: | Paddock area, normal gross margin $/ha, area to be planted to trees, area affected by land degradation now and in future with/without project, when area degraded reaches equilibrium; option for skilled users to enter/edit tree-crop input quantity, price and yield details. |
| Outputs: | Financial indicators, such as Net Present Value, Benefit Cost Ratio and cashflow graph. |
| Expertise/system r'quts: | Basic computer skills; farm forestry expertise if editing tree crop enterprise information; Windows 95 or better. |
| Availability/status: | Available on DAWA web site or from contact; Released August 1999; enterprise updates added January 2002. |
| Important Links: | Farm Forestry toolbox (search for farm forestry toolbox in DAWA web page). |
| Contact: | Peter Eckersley, Dept of Agriculture and Food Western Australia, PO Box 1231, Bunbury 6231. Tel: (08) 9780 6204, Fax: (08) 9780 6136, Email: peckersley@agric.wa.gov.au |
| Name of model: |
Quarantine Significance Model (QUASIMODO) |
| Developer(s): | David Cook |
| Aims/use: | Exotic plant pest/disease outbreak simulation using base case of no government intervention. Expected damage estimate produced by the model provides a ceiling for eradication/control strategies in the event of a real incursion. |
| Key features: | Population diffusion model of pest spread incorporating satellite sites; central database containing plant industry time series gross value, export, type 2A output multiplier and area statistics; automated Markov chains. |
| Audience: | Government and industry stakeholders |
| Regions, scale, time of year: | Aggregated stochastic partial equilibrium model capable of simulating outbreaks affecting up to 25 crops. |
| Types of decisions: | Is eradication economically feasible? |
| Strengths/limitations: | Not user friendly; information on some parameters difficult to source; outputs are probability distributions, which can make communication of results to stakeholders difficult. |
| Inputs: | Probabilities of entry and establishment, induced average variable cost increments (attributable to pest in ‘live with??™ scenario), induced change in total revenue (incl. exports), minimum and maximum area occupied, population growth rate, minimum and maximum pest density per unit of area, probability of satellite outbreaks, population diffusion coefficient. |
| Outputs: | Distributions of expected damage over 10, 20 and 25 year time horizons. |
| Expertise/system r'quts: | Medium Excel skills; @Risk ‘Professional??™; knowledge of microeconomics and population spread functions would be advantageous. |
| Availability/status: | Upon request. |
| Contact: | David Cook, E-mail: dccook@agric.wa.gov.au ; Peter Eckersley, Email: peckersley@agric.wa.gov.au ; Andrew Reeves, Email: areeves@agric.wa.gov.au |
Page updated: 7 August 2009
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