Soil Index for crop insurance
There are two frequent overarching challenges relating to the provision of high-quality data for agricultural insurance: 1) data availability and 2) data quality.
For 1), to make high-quality data available for agricultural insurance purposes, governments have important roles to play in establishing a framework for data collection, auditing, financing and management.
For 2), even if data for agricultural insurance purposes is available, its quality is often not high enough, which has critical consequences for farmers.
This crop insurance product utilizes soil moisture conditions for pay-outs instead of only rainfall (this will include yield and germination insurance). The soil moisture is determined using satellites, soil moisture probes, and DTS (distributed temperature sensing) in 2 pilot locations (Districts) in Northern Ghana. We also propose using a crop model (e.g. DSSAT, AquaCrop) as a way of tailoring the service to particular conditions (e.g. soil type, crop type). This facilitates the down-scaling of soil moisture data from satellites, interpolating DTS measurements in the vertical direction, and provide a way to identify crop-specific thresholds on which to base the insurance index.