Environmental Engineering
G.R. Puno; R.C.C. Puno; I.V. Maghuyop
Abstract
BACKGROUND AND OBJECTIVES: Fine topographic information is a key input parameter for a detailed flood simulation and mapping. This study aimed to compare the accuracy statistics of the flood models developed using the digital elevation datasets with different resolutions from the light detection and ...
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BACKGROUND AND OBJECTIVES: Fine topographic information is a key input parameter for a detailed flood simulation and mapping. This study aimed to compare the accuracy statistics of the flood models developed using the digital elevation datasets with different resolutions from the light detection and ranging and interferometric synthetic aperture radar systems.METHODS: The study applied the Hydrologic Engineering Center-Hydrologic Modeling System and Hydrologic Engineering Center-River Analysis System models workable within the geographic information system to simulate and map flood hazards in Maapag Watershed. The models’ validity and accuracy were tested using the confusion error matrix, f-measurement, and the root means square error statistics.FINDINGS: Results show that using the light detection and ranging dataset, the model is accurate at 88%, 0.61, and 0.41; while using the interferometric synthetic aperture radar dataset, the model is accurate at 76%, 0.34, 0.53; for the error matrix, f-measurement, and root mean square error; respectively.CONCLUSION: The model developed using the light detection and ranging dataset showed higher accuracy than the model developed using the interferometric synthetic aperture radar. Nevertheless, the latter can be used for flood simulation and mapping as an alternative to the former considering the cost of model implementation and the smaller degree of accuracy residual error. Hence, flood modelers particularly from local authorities prefer to use coarser datasets to optimize the budget for flood simulation and mapping undertakings.
Environmental Management
G. R. Puno; R. C. Puno; I. V. Maghuyop
Abstract
BACKGROUND AND OBJECTIVES: The study involved developing a two-dimensional flood model to analyze the risk exposure of land use/land cover based on the generated flood hazard maps for the six return period scenarios in the Solana watershed.METHODS: The approach consisted of applying hydrologic and hydraulic ...
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BACKGROUND AND OBJECTIVES: The study involved developing a two-dimensional flood model to analyze the risk exposure of land use/land cover based on the generated flood hazard maps for the six return period scenarios in the Solana watershed.METHODS: The approach consisted of applying hydrologic and hydraulic numerical flood models and the suite of advanced geographic information systems and remote sensing technologies. The process involved utilizing a high-resolution digital elevation model and a set of high-precision instruments such as the real-time kinematic-global position system receiver, digital flow meter, deep gauge, and automatic weather station in collecting the respective data on bathymetry, river discharge, river depth, and rainfall intensity during a particular climatic event, needed for the model development, calibration and validation.FINDINGS: The developed two-dimensional flood model could simulate flood hazard with an 86% accuracy level based on the coefficient of determination statistics. The flood risk exposure analysis revealed that coconut is the most affected, with 31.3% and 37.1% being at risk across the 2-year and 100-year return period scenarios, respectively. Results also showed that rice and pineapple are at risk of flooding damage with the increasing rate of exposure by a magnitude of 42.9 and 9.3 across the 2-year and 100-year flood scenarios, respectively.CONCLUSION: The study highlighted the integration of the findings and recommendations in the localized comprehensive land use plan and implementation to realize the challenge of building a climate change proof and a flood-resilient human settlement in the urbanizing watershed of Solana.