1 dataset found
  1. Data from: Estimated spring crop yields using Flex Cropping Tool

    • geodata.nal.usda.gov
    • agdatacommons.nal.usda.gov
    • +1more
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    USDA ARS LTAR Walnut Gulch Experimental Watershed, Estimated spring crop yields using Flex Cropping Tool [Dataset]. https://geodata.nal.usda.gov/geonetwork/srv/api/records/459d2dba-a346-4e54-9750-ef3178c18f38
    Explore at:
    www:link-1.0-http--linkAvailable download formats
    Dataset provided by
    United States Department of Agriculturehttp://usda.gov/
    Agricultural Research Servicehttps://www.ars.usda.gov/
    Time period covered
    Nov 1, 2014
    Area covered
    Description

    Average estimated yields and associated CV values for current (2018) model runs. Based on work done by Harsimran Kaur et al in 2017. The following is from her thesis:

    Agro-ecological classes (AECs) of dryland cropping systems in the inland Pacific Northwest have been predicted to become more dynamic with greater use of annual fallow under projected climate change. At the same time, initiatives are being taken by growers either to intensify or diversify their cropping systems using oilseed and grain legume crops. The main objective of this study was to use a mechanistic model (CropSyst) to provide yield and soil water forecasts at regional scales which could compare fallow versus spring crop choices (flex/opportunity crop). Model simulations were based on historic weather data (1981-2010) as well as combined with actual year weather data for simulations at pre-planting dates starting in Dec. for representative years. Yield forecasts of spring pea, canola and wheat were compared to yield simulations using only weather of the representative year via linear regression analysis to assess pre-plant forecasts. Crop yield projections on pre-plant forecast date of Feb 1st had higher R2 with yield simulated using actual years weather data and lower CVs across the region as compared to forecasts based on historic weather data and other pre-season forecast dates (Dec. 1st and Jan. 1st). Therefore, Feb. 1st was considered the most reliable time to predict yield and other relevant outputs such as available water forecasts on a regional scale. Regional forecast maps of predicted spring crop yields and CVs showed ranges of 1 to 4367 kg/ha and 11 to 293% for spring canola, 72 to 2646 kg/ha and 11 to 143% for spring pea and 39 to 5330 kg/ha and 11 to 158% for spring wheat across study region for a representative year. These data combined with predicted available water after fallow and following spring crop yield as well as estimates of winter wheat yield reduction would collectively serve as information contributing to decisions related to crop intensification and diversification.

  2. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
USDA ARS LTAR Walnut Gulch Experimental Watershed, Estimated spring crop yields using Flex Cropping Tool [Dataset]. https://geodata.nal.usda.gov/geonetwork/srv/api/records/459d2dba-a346-4e54-9750-ef3178c18f38
Organization logoOrganization logo

Data from: Estimated spring crop yields using Flex Cropping Tool

Related Article
Explore at:
www:link-1.0-http--linkAvailable download formats
Dataset provided by
United States Department of Agriculturehttp://usda.gov/
Agricultural Research Servicehttps://www.ars.usda.gov/
Time period covered
Nov 1, 2014
Area covered
Description

Average estimated yields and associated CV values for current (2018) model runs. Based on work done by Harsimran Kaur et al in 2017. The following is from her thesis:

Agro-ecological classes (AECs) of dryland cropping systems in the inland Pacific Northwest have been predicted to become more dynamic with greater use of annual fallow under projected climate change. At the same time, initiatives are being taken by growers either to intensify or diversify their cropping systems using oilseed and grain legume crops. The main objective of this study was to use a mechanistic model (CropSyst) to provide yield and soil water forecasts at regional scales which could compare fallow versus spring crop choices (flex/opportunity crop). Model simulations were based on historic weather data (1981-2010) as well as combined with actual year weather data for simulations at pre-planting dates starting in Dec. for representative years. Yield forecasts of spring pea, canola and wheat were compared to yield simulations using only weather of the representative year via linear regression analysis to assess pre-plant forecasts. Crop yield projections on pre-plant forecast date of Feb 1st had higher R2 with yield simulated using actual years weather data and lower CVs across the region as compared to forecasts based on historic weather data and other pre-season forecast dates (Dec. 1st and Jan. 1st). Therefore, Feb. 1st was considered the most reliable time to predict yield and other relevant outputs such as available water forecasts on a regional scale. Regional forecast maps of predicted spring crop yields and CVs showed ranges of 1 to 4367 kg/ha and 11 to 293% for spring canola, 72 to 2646 kg/ha and 11 to 143% for spring pea and 39 to 5330 kg/ha and 11 to 158% for spring wheat across study region for a representative year. These data combined with predicted available water after fallow and following spring crop yield as well as estimates of winter wheat yield reduction would collectively serve as information contributing to decisions related to crop intensification and diversification.

Search
Clear search
Close search
Google apps
Main menu