32-29 Risk Analysis in Growing Season Length for Kansas, USA.

Poster Number 128

See more from this Division: Students of Agronomy, Soils and Environmental Sciences (SASES)
See more from this Session: Symposium-- National Student Research Symposium Poster Contest
Monday, October 22, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
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Sriram Perumal1, Aavudai Anandhi1 and Charles Rice2, (1)Kansas State University, Manhatten, KS
(2)Agronomy, Kansas State University, Manhattan, KS
Poster Presentation
  • Sriram ASA Poster 2012VFinal.pdf (595.8 kB)
  • In Kansas, agriculture continues to be a significant contributor to the state’s economic well-being with rain-fed production (e.g. sorghum and wheat crops) contributing its share. Agricultural production system is inherently a risky activity in rain-fed areas where uncertainty in agro-climatic conditions affects production and profits. Understanding the role of risk and risk aversion in these systems, by reliable prediction of the uncertain variables is needed to develop technological and policy interventions that help reduce risk. Adaptation strategies such as synchronization of dates of cultivation practices and developing crop varieties with the changing climate have been used to reduce risk. Although the importance of risk has been widely recognized by researchers and policymakers, there is a dearth of quantitative information on risk. Hence, the objective of this study is to provide quantitative information on uncertain agro-meteorological indicators (AMI) such as growing season length (GSL), last spring freeze (LSF) and first fall freeze (FFF) used in many adaptation strategies to reduce risk. The analysis is carried for 23 centennial stations spread across Kansas.

    There are a number of methods available in literature to estimate these AMI. In this study, the LSF is the last day in March through May with Tmin < 0° C for the last time until fall. The FFF is the day in September through November with Tmin< 0° C for the first time since spring and GSL is calculated as the difference between FFF and LSF. The risk in these AMIs is estimated using cumulative probability functions and exceedence probabilities.

    Results show there is about One month difference in LSF, FFF and GSL  across the state. In general North West Kansas (Oberlin) or west central (Tribune) has the latest LSF, earliest FFF and shortest GSL. South east (Sedan, Independence, Columbus) has the earliest LSF, latest FFF and longest GSL. At 50%, 75% and 90% probability level (1) LSF occurs latest on or before May 5, 12 and 17 respectively; (2) LSF occurs earliest on or before April 4, 11, 15 respectively; (3) FFF occurs earliest on or after Oct 6, Sep 27 and 20 respectively; (4) FFF occurs latest on or after Nov 1, Oct 23 and 15 respectively; (5) shortest GSL is about 210, 218 and 224 days respectively; (6) longest GSL is about 238, 245 and 254 days respectively.

    See more from this Division: Students of Agronomy, Soils and Environmental Sciences (SASES)
    See more from this Session: Symposium-- National Student Research Symposium Poster Contest
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