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The catastrophic flooding in Derna, Libya, in September 2023, following Cyclone Daniel, resulted in extensive loss of life and critical infrastructure destruction. This research systematically analyzes the multiple failures that worsened the disaster, with particular attention to Early Warning Systems (EWS) and vital service infrastructure performance. Through a mixed-methods survey of residents (n=300) and advanced statistical analyses, including structural equation modeling (SEM) and regression analysis, we identified a cascade of systemic failures originating from a critically deficient EWS. Results reveal that while 60% of respondents were aware of warning systems, only 15% had received any preparedness training, and a mere 14% of the population received a timely and comprehensible warning. An SEM model (CFI=0.95, RMSEA=0.04, SRMR=0.03) delineated a failure cascade in which institutional shortcomings in meteorological forecasting (β=0.72, p<.001) and the subsequent collapse of the Abu Mansour and Al-Bilad dams precipitated sequential failures in power, communications, water, and medical services. Regression analysis identified road conditions (β=0.38, p<.001) and the timeliness of warnings (β=0.29, p<.001) as the primary predictors of evacuation difficulty, accounting for a high proportion of variance (R²=0.77, p<.001). Communication networks were severely compromised, with 60% of respondents experiencing outages exceeding 72 hours. Statistically significant associations were found; prior flood experience positively influenced risk perception (χ² (2) =18.4, p<0.01, Cramer's V=0.18), and receiving a warning was strongly associated with its perceived timeliness (χ² (1) =145.2, p<0.001, Cramer's V=0.45). This "predictable surprise" resulted from fragile infrastructure and socio-institutional failures in the "last mile" of warning delivery. Integrated risk governance combining robust infrastructure with community-centered systems is essential. Increasing the proportion of residents receiving timely warnings from 14% to 80% could significantly reduce potential casualties during future disasters.