Road transport fuel consumption is strongly affected by pavement conditions and road infrastructure, whereas conventional normative approaches primarily consider vehicle characteristics and operating conditions while neglecting pavement friction and infrastructure-induced driving cycles. This study develops and validates an integrated physical–mechanistic model for predicting actual fuel consumption on high-category roads by combining vehicle energy-balance equations with pavement diagnostic parameters and infrastructure constraints. Unlike existing mechanistic or empirical approaches, the proposed framework explicitly incorporates pavement friction as a quantitative indicator of both skid resistance and road-related energy losses, enabling the simultaneous assessment of traffic safety and fuel efficiency within a unified engineering model. The methodology was applied to the A-350 Almaty–Taldykorgan highway using telemetry from 150 independent vehicle-route observations, 840 complete corridor transits, approximately 4.8 million CAN-GPS records, and 340 pavement friction measurements. The results indicate that actual fuel consumption exceeded normative values by an average of 9.2%, while a reduction in pavement friction below the regulatory threshold was associated with a substantial increase in fuel consumption, further amplified by pedestrian crossings and urban road sections. Model calibration and independent validation demonstrated that the proposed model achieved strong predictive performance (R² = 0.94; MAE = 1.8%) under the observed operating conditions. This study extends existing fuel consumption modeling by reinterpreting pavement friction as a dual-purpose engineering indicator for both safety assessment and energy-efficiency diagnostics. The proposed methodology provides a scientific basis for corridor-level pavement management and infrastructure-related fuel-efficiency assessment and provides a conceptual foundation for future integration into intelligent transportation systems, subject to broader multi-corridor and seasonal validation.

Spring floods represent one of the major natural hazards in snowmelt-dominated river basins of Central Asia. The Nura River basin in Central Kazakhstan is particularly vulnerable because of pronounced interannual runoff variability, limited reservoir regulation capacity, and the hydraulic connection between the Nura and Ishim river systems. This study aimed to provide an integrated basin-scale assessment of spring flood hazards and to identify key hydraulic constraints relevant to flood-risk management. The assessment was based on long-term hydrological observations covering periods of up to approximately 90 years. Extreme spring flood discharges and runoff volumes were estimated using the Kritsky–Menkel frequency-analysis method based on a three-parameter gamma distribution. The analysis was supplemented by assessment of reservoir storage capacities, floodplain topography, channel conveyance, and the Nura–Ishim bifurcation zone using cartographic, digital elevation, and engineering data. The adopted probability distribution was additionally evaluated against alternative flood-frequency models using goodness-of-fit and information criteria. For a 1% exceedance probability, the estimated maximum spring discharges were 752 m ³ /s at Sheshenkara, 1220 m ³ /s at Sergiopolskoye, and 2360 m ³ /s at Romanovskoye. The corresponding 1% spring flood volumes reacheNura River and the distributary system of the Nura–Ishim interfluve may begin at approximately 800 m ³ /s, with an estimated plausible range of 750–850 m ³ /s. The interfluve can store approximately 400 million m ³ of floodwater, whereas extreme inflow may reach about 350 million m ³ per day, compared with a downstream Ishimestimated plausible range of 750–850 m ³ /s. The interfluve can store approximately 400 million m ³ of floodwater, whereas extreme inflow may reach about 350 million m ³ per day, compared with a downstream Ishim conveyance capacity of approximately 100–150 million m ³ per day. The results demonstrate that extreme spring flood volumes cannot be managed effectively by reservoir regulation alone and that the Nura–Ishim interfluve plays a critical role in floodwater redistribution. Comparison with Austrian flood-risk management practice supports a transition from localized protection toward integrated basin-scale management combining structural measures, controlled retention areas, and spatial planning. The proposed measures include earth embankments with controlled overflow sections, riprap bank protection, and mobile water-filled barriers. auseuse the analysis combines pre- and post-regulation hydrological records and does not include formal non-stationary frequency analysis or detailed two-dimensional hydraulic modeling, the estimates should be interpreted as basin-scale planning values rather than precise local inundation predictions. The findings provide a quantitative basis for strategic flood-risk management and infrastructure resilience in snowmelt-dominated river systems of Central Asia.