Abstract: Violent flare-ups in herder–farmer conflict often appear suddenly, peak sharply, and dissipate unpredictably across communities. This project adapts rogue-wave dynamics—rare, high-amplitude events emerging from modulation instability in nonlinear systems—to explain and predict such outbreak patterns in Delta State. We model incident intensity as a nonlinear wave field coupled to slow-varying socio-environmental drivers (land use, market shocks, rainfall, policing). Using geocoded incident data (2010–2025), we will (i) test whether conflict clusters exhibit rogue-wave signatures, (ii) estimate conditions that precipitate “surge” events, and (iii) simulate targeted early-warning and response strategies. Outputs include an open dataset, a calibrated model, ward-level risk maps, and policy briefs for state actors and community stakeholders. Existing statistical or diffusion models struggle to capture sudden, high-amplitude incident spikes and their rapid spatial spillovers in Delta State. There is a need for a predictive, interpretable framework that identifies instability windows and guides timely prevention.
O et al. (Sat,) studied this question.