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

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


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...
Overcoming basis risk in agricultural index insurance using crop simulation modeling and satellite crop phenology
Hesamı Afshar, Mehdı; Foster, Timothy; P. Higginbottom, Thomas; Parkes, Ben; Hufkens, Koen; Mansabdar, Sanjay; Ceballos, Francisco; Kramer, Berber (2021-04-19)
Extreme weather causes substantial damage to livelihoods of smallholder farmers globally and are projected to become more frequent in the coming decades as a result of climate change. Index insurance can theoretically help farmers to adapt and mitigate the risks posed by extreme weather events, providing a financial safety net in the event of crop damage or harvest failure. However, uptake of index insurance in practice has lagged far behind expectations. A key reason is that many existing index insurance p...
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Extreme flooding has become more prevalent due to climate change and has been causing extensive damage, loss of property, and fatalities around the world. Levees are often constructed to prevent inundation in floodplains and urban areas. Flood mitigation efforts during extreme floods include forcing a breach in the levee at a strategic location to avoid flooding at target locations. A well-known example of engineered levee breaches along the Mississippi River is the New Madrid Floodway at Birds Point, contr...
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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: