Accurate prediction of bedload transport is crucial for designing hydraulic structures in sediment-prone, data-scarce regions, such as the Moroccan Al Haouz region. This study develops and validates an integrated predictive modeling framework to quantify sediment flux and deposition height for a 100-year flood at a road-stream crossing on the El Bahja River. The approach uses a chain of tools, including HEC-HMS, HEC-RAS, ArcGIS, and an S-shaped granulometric model, to calibrate and compare twelve well-known sediment transport equations, ensuring robust and accurate predic-tions. Validation against field measurements confirms the framework's reliability and identifies six models (Parker and Klingeman, Camenen and Larson, Ribberink, Smart and Jaeggi, Watanabe, and Meyer-Peter and M & uuml;ller) that employ a threshold-based methodology. These models estimate a specific sediment discharge of 0.14 m(3) s(-1) m(-1 )and an accumu-lation level of 1.01 m, closely matching field data. The primary novelty of this work is the integrated validation of a multi-model framework under extreme conditions, an approach that is seldom documented. The key practical outcome is a robust selection framework for the most reliable sediment transport equations, supporting informed model selection for resilient infrastructure design in the High Atlas and comparable semi-arid regions, thereby advancing Sustainable Develop-ment Goal 6 (Clean Water and Sanitation).