Dynamics of surface water resource management towards fulfilling agricultural irrigation

Background: The dynamics of surface water resources and their influence on agriculture irrigation in Kano State, Nigeria, 2015-2025, are displayed in this research. This study aims to examine the influence of surface water availability changes on irrigation potential in semi-arid catchment. With looming uncertainty concerning water scarcity, particularly in Northern Nigeria, spatial-temporal dynamics of the surface water are critical to sustainable agriculture planning. Current studies have used satellite-based indices to monitor changes in water bodies and emphasized that such changes must be associated with climatic factors and land use patterns for irrigation development decision-making. Methods: Remote sensing data, including Normalized Difference Water Index (NDWI) from Landsat and Sentinel data, and rainfall data from the CHIRPS dataset, were used for the study. Spatiotemporal modeling methodology was used that included NDWI trend analysis, NDWI–rainfall relation, overlay with cover of cultivated land, and zonal statistics at the Local Government Area (LGA) level. Findings: Findings show that there is general surface wetness expansion in the southern and central regions of Kano State owing to enhanced irrigation activities, heightened water holding capacity, and possible aquifer recharge. Conclusion: The study concludes that water resource management in Kano must be specially crafted to overcome localized climatic stress conditions and spatial hydrological imbalance to facilitate sustainable irrigation under semi-arid conditions.Ground-truth verification is however absent, which limits the accuracy of surface wetness estimates, and future incorporation of field-based hydrological observations is recommended. The findings present actionable advice for policymakers on improving irrigation strategy formulation and adaptive water management in semi-arid climates. Novelty/Originality of this article: This research integrates satellite-based NDWI for the first time with rain anomaly and land use overlays to determine water body dynamics and their agricultural implications at sub-regional scales.