UC Davis

Sri Lanka’s 2021 ban on agrochemicals – and subsequent country-wide rice yield loss – offers a rare opportunity to study the components of yield resiliency during system-wide transitions away from synthetic agricultural inputs. We combine a six-year Sentinel-2 satellite based remote sensing analysis with semi-structured farmer interviews to assess heterogeneous yield impacts, recovery rates and post-ban adaptation strategies among rice farms in Sri Lanka’s Anuradhapura District. Using Normalized Difference Red Edge (NDRE) and a panel of 100,000 pixels, we developed three tools for measuring rice farm productivity changes before, during and after the ban. In parallel, we analyzed farmer interview responses through partitioning-around-medoids cluster analysis to identify farm typologies linked to farm attributes, reported yield loss, and yield recovery times. Both methods found that farms with the lowest pre-ban productivity experienced the smallest relative yield losses and fastest recoveries. The two methods identified different categories of most impacted farmers: our remote sensing analysis pointed to the highest productivity farmers experiencing the largest yield loss and largest recovery, while our cluster analysis identified these impacts in the middle-resource farmer cluster. Interview data further indicated that crop rotation, access to large-scale irrigation resources, proximity to government extension, previous usage of organic farming practices, and participation in post-ban trainings were associated with greater yield resiliency. Our findings highlight the power of pairing land-scape level satellite remote sensing monitoring with targeted, resource-sensitive farmer interventions for supporting any future large-scale transitions away from agrochemicals.