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Impact of Land Cover Change on Urban Flooding and Hydraulic Performance of Kinalumsan River, Cebu City, Central Visayas, Philippines

Sep 2026 · Hydrology · 0 citations · 38 references

Abstract

Predicting flood dynamics in data-scarce urban catchments remains a major hydrological challenge, yet physically-based modeling is essential for design mitigation infrastructure. This study assessed the impact of land cover change on the hydrological response and hydraulic performance of the ungauged Kinalumsan River in Cebu City, Philippines, which frequently overflows during intense rainfall. To overcome the absence of historical gauge records, a short-term field monitoring campaign was conducted to capture discrete storm events for event-based calibration. Land cover maps from 1996 to 2023 were analyzed to evaluate spatiotemporal trends. A physically-based, coupled modeling framework was deployed: a HEC-HMS model utilized the Soil Conservation Service Curve Number (SCS-CN) method to simulate peak discharges under 10-, 25-, 50- and 100-year return periods, which subsequently drove a HEC-RAS (Version 6.6) 2D model to assess flood characteristics. The event-based calibration demonstrated good predictive performance, achieving Nash–Sutcliffe Efficiency (NSE) values of 0.96 (HEC-HMS) and 0.88 (HEC-RAS), indicating reliable simulation of the catchment’s response. Results show a steady increase in built-up areas, which contributed to higher peak discharges and expanded flood extents. Extreme rainfall events further amplified flood hazards, with the 100-year return period producing the widest inundation. The districts of Tisa and Punta Princesa located near the downstream portion of the Kinalumsan River consistently experienced the greatest exposure in both depth and velocity terms. Overall, the study demonstrates that integrating short-duration monitoring campaigns with coupled hydrologic–hydraulic modeling provides a scientifically defensible, highly transferable template for rapid flood hazard mapping and stormwater management in data-constrained developing regions. This cost-effective method of flood modelling can be upscaled to other cities where data is scarce including selection of nature-based solutions for the improvement of urban drainage and stormwater management for resilient cities.

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