Theoretical Development of an Integrated Agrometeorological Drought Early Warning System for the Nigerian Sudan Savanna

Agrometeorological drought in Nigeria's Sudan Savanna zone, spanning states including Katsina, Kano, Jigawa, and Yobe, combines meteorological rainfall deficits with soil water depletion and crop water stress in ways that require integrated multi-indicator monitoring frameworks beyond simple precipitation-based approaches. This study theoretically develops and empirically validates an integrated agrometeorological drought early warning system specifically designed for the Nigerian Sudan Savanna, constituting an original contribution to both applied meteorological science and operational drought management. The theoretical framework synthesizes drought propagation theory, remote sensing-based vegetation stress monitoring, crop water balance modelling, and probabilistic NiMet seasonal forecast information into a unified early warning decision support architecture. The system integrates SPI-3, the Vegetation Health Index from MODIS, root zone soil moisture from ERA5-Land, and crop water satisfaction index outputs from the FAO-AQUACROP model into a composite agrometeorological drought alert index. Calibration of alert thresholds was performed using historical drought event records from 2000 to 2023 compiled from NCDC, FEWSNET, and NiMet archives. System validation against independent drought events demonstrates that the integrated index provides two to three weeks of additional early warning lead time compared to SPI-3 alone, with a probability of detection of 0.87 and false alarm rate of 0.19 for moderate-to-severe drought classification. An original mathematical formulation of the composite drought alert index is derived, with open-source implementation code made available for NiMet adoption. Keywords: agrometeorological drought, early warning system, Sudan Savanna, composite index, NiMet.