Improving the Performance of Index Insurance Using Crop Models and Phenological Monitoring

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2021-03-01

Author

Afshar, Mahdı Hesamı
Higginbottom, Thomas P.
Parkes, Ben
Hufkens, Koen
Mansabdar, Sanjay
Ceballos, Francisco
Kramer, Berber

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Extreme weather events cause considerable damage to the livelihoods of smallholder farmers globally. Whilst index insurance can help farmers cope with the financial consequences of extreme weather, a major challenge for index insurance is basis risk, where insurance payouts correlate poorly with actual crop losses. We analyse to what extent the use of crop simulation models and crop phenology monitoring can reduce basis risk in index insurance. Using a biophysical process-based crop model (Agricultural Production System sIMulator (APSIM)) applied for rice producers in Odisha, India, we simulate a synthetic yield dataset to train non-parametric statistical models to predict rice yields as a function of meteorological and phenological conditions. We find that the performance of statistical yield models depends on whether meteorological or phenological conditions are used as predictors and whether one aggregates these predictors by season or crop growth stage. Validating the preferred statistical model with observed yield data, we find that the model explains around 54% of the variance in rice yields at the village cluster (Gram Panchayat) level, outperforming vegetation index-based models that were trained directly on the observed yield data. Our methods and findings can guide efforts to design smart phenology-based index insurance and target yield monitoring resources in smallholder farming environments.

URI

https://hdl.handle.net/11511/92605

Journal

REMOTE SENSING

DOI

https://doi.org/10.3390/rs13050924

Collections

Department of Civil Engineering, Article

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Improving performance of index insurance using crop models and phenological monitoring Afshar, Mahdı Hesamı ; Parkes, Ben; Hufkens, Koen; Ceballos, Francisco (2020-05-04) Extreme weather events pose significant risks to the livelihoods of smallholder farmers across Asia and Africa. Weather index-based insurance provides a potential solution to mitigate risks caused by crop failures, providing farmers with a payout in the event of a poor harvest. It also reduces costs relative to traditional indemnity insurance by eliminating the need for resource-intensive, in-situ assessment of losses. However, one challenge associated with weather index-based insurance is basis risk – wher...
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Citation Formats

M. H. Afshar et al., “Improving the Performance of Index Insurance Using Crop Models and Phenological Monitoring,” REMOTE SENSING, vol. 13, no. 5, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/92605.