Abstract
A process-based crop model equipped with seasonal climate forecasts has been typically used to expect crop yields before or in the middle of the growing period. In this work, to consider the farmers’ risk-aversion behavior, we slightly shifted the typical focus to the risk associated with a crucial farming decision in a rainfed paddy rice field, the transplanting timing. Using a simple crop model and a semi-parametric weather generator, we tested hypothetical and real sets of climate forecasts for the rice field under nutrient deficiency in Lao People's Democratic Republic (PDR). Results showed that the first climatic risk in the study field was an occational dry conditions, and the traditional timing of transplanting seemed to minimize the worst effect of potential dry conditions. It was found that the transplanting timing needs to be 5–10 days earlier than the farming tradition when fertility stress delays foliage development. The tests with hypothetical climate forecasts suggest that duration of a potential dry condition needs to be reliably forecasted to manage the climatic risk by adjusting the transplanting timing. The yield simulations for the 2015 El-Niño event also implcate that adjusting the transplanting timing could effectively reduce the potential impact of dry climate at a cost of slightly reduced yield expectation. This study exemplifies how to explicitly assess the climatic risk associated with the farming decision using ready-to-use climate data and a simple crop model.
| Original language | English |
|---|---|
| Article number | 107073 |
| Journal | Agricultural Water Management |
| Volume | 256 |
| DOIs | |
| State | Published - 2021.10.1 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
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SDG 13 Climate Action
Keywords
- Crop response to water and fertility stresses
- Risk minimization
- Stochastic downscaling
- Transplanting timing
Quacquarelli Symonds(QS) Subject Topics
- Earth & Marine Sciences
- Agriculture & Forestry
- Environmental Sciences
- Geophysics
- Geology
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