Planning & Management

Oral

395027 - Integrating predictive information into an agro-economic model to guide agricultural planning

Monday, June 4
10:30 AM - 12:00 PM
Location: Greenway GH

Seasonal climate forecasts can inform long-range planning, including water resources utilization and allocation; however, quantifying the value of this information on the economy is often challenging. For rain-fed farmers, skillful season-ahead predictions may lead to superior planning, as compared to business as usual strategies, resulting in additional benefits or reduced losses. In this study, regional-level probabilistic precipitation forecasts of the major rainy season in Ethiopia are fed into an agro-economic model, adapted from the International Food Policy Research Institute, to evaluate economic outcomes (GDP, poverty rates, etc.) as compared with a no-forecast approach. Based on forecasted conditions, farmers can select various actions: adjusting crop area and crop type, purchasing drought-resistant seed, or applying additional fertilizer. Preliminary results favor the forecast-based approach, particularly through reduced losses in dry years. Various farmer risk-taking levels are also explored.

Ying Zhang, PhD

Postdoc
Johns Hopkins University

My research is centered on using systems-based approaches to guide decision-making in water-related activities to foster benefits and reduce risks.The scope of my research embraces multi-disciplines of climate science, hydrology, environment, energy, social science, economics, management, and policy, etc. My graduate research specifically aims to provide predictive information and use it to guide decision-making for water utilization and management, such as agricultural planning and reservoir operation, particularly in developing countries.

Presentation(s):

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Donghoon Lee

PhD Candidate
University of Wisconsin-Madison

Presentation(s):

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Paul James. Block, PhD

Assistant Professor
University of Wisconsin - Madison

Presentation(s):

Send Email for Paul Block


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