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Assessing climate risks in rainfed farming using farmer experience, crop calendars and climate analysis

Published online by Cambridge University Press:  29 April 2015

U. B. NIDUMOLU ,
P. T. HAYMAN ,
Z. HOCHMAN ,
H. HORAN ,
D. R. REDDY ,
G. SREENIVAS  and
D. M. KADIYALA
U. B. NIDUMOLU*
Affiliation:
CSIRO Agriculture Flagship, Adelaide Laboratories, Gate 4, Waite Rd, Urrbrae, SA 5064, Australia
P. T. HAYMAN
Affiliation:
South Australian Research and Development Institute (SARDI), Hartley Grove Road, Urrbrae, SA 5064, Australia
Z. HOCHMAN
Affiliation:
CSIRO Agriculture Flagship, EcoSciences Precinct, 41 Boggo Rd, Dutton Park, QLD 4102, Australia
H. HORAN
Affiliation:
CSIRO Agriculture Flagship, EcoSciences Precinct, 41 Boggo Rd, Dutton Park, QLD 4102, Australia
D. R. REDDY
Affiliation:
PJTS Agricultural University, Rajendranagar, Hyderabad, India
G. SREENIVAS
Affiliation:
PJTS Agricultural University, Rajendranagar, Hyderabad, India
D. M. KADIYALA
Affiliation:
ICRISAT, Patancheru, Hyderabad, India
*
*To whom all correspondence should be addressed. Email: uday.nidumolu@csiro.au
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Summary

Climate risk assessment in cropping is generally undertaken in a top-down approach using climate records while critical farmer experience is often not accounted for. In the present study, set in south India, farmer experience of climate risk is integrated in a bottom-up participatory approach with climate data analysis. Crop calendars are used as a boundary object to identify and rank climate and weather risks faced by smallhold farmers. A semi-structured survey was conducted with experienced farmers whose income is predominantly from farming. Interviews were based on a crop calendar to indicate the timing of key weather and climate risks. The simple definition of risk as consequence × likelihood was used to establish the impact on yield as consequence and chance of occurrence in a 10-year period as likelihood. Farmers’ risk experience matches well with climate records and risk analysis. Farmers’ rankings of ‘good’ and ‘poor’ seasons also matched up well with their independently reported yield data. On average, a ‘good’ season yield was 1·5–1·65 times higher than a ‘poor’ season. The main risks for paddy rice were excess rains at harvesting and flowering and deficit rains at transplanting. For cotton, farmers identified excess rain at harvest, delayed rains at sowing and excess rain at flowering stages as events that impacted crop yield and quality. The risk assessment elicited from farmers complements climate analysis and provides some indication of thresholds for studies on climate change and seasonal forecasts. The methods and analysis presented in the present study provide an experiential bottom-up perspective and a methodology on farming in a risky rainfed climate. The methods developed in the present study provide a model for end-user engagement by meteorological agencies that strive to better target their climate information delivery.

Type
Climate Change and Agriculture Research Papers
Information
The Journal of Agricultural Science , Volume 153 , Issue 8 , November 2015 , pp. 1380 - 1393
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Copyright
Copyright © Cambridge University Press 2015 

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