- Cabrera, J. and Lee, H.S.*, 2020. Flood risk assessment for Davao Oriental in the Philippines using geographic information system‐based multi‐criteria analysis and the maximum entropy model. J Flood Risk Management. 2020; e12607. https://doi.org/10.1111/jfr3.12607 (Open access)
Abstract
The assessments of flood‐prone areas and flood risk due to pluvial flooding for Davao Oriental on Mindanao Island in the Philippines were carried out by the analytic hierarchy process (AHP) and maximum entropy (Maxent) models using multiple criteria such as slope, elevation, soil type, rainfall, drainage density, distance to the main channel, and population density. Flood records from 70 survey points were obtained and used to verify the model results. The criteria weights of the top three important factors in the AHP are rainfall (42%), slope (23%), and elevation (15%), whereas those in the Maxent model are elevation (36%), rainfall (23%), and soil (19%). The verification results show that the accuracies of the AHP and Maxent model are 81 and 95.6%, respectively, indicating that both approaches are reliable in flood hazard and risk assessments. Approximately 22% of the total area and approximately 30% of the total population of Davao Oriental are classified as high risk of pluvial flooding in the current situation by the AHP method. This study shows a broad‐scale high‐level data‐driven screening method that can be used to help identify potential hot spots for pluvial flooding for which more detailed numerical modelling studies should be undertaken.
- I. Guiamel and H.S. Lee*, 2020. Watershed Modelling of the Mindanao River Basin in the Philippines Using the SWAT for Water Resource Management. Civil Eng. Journal, 6(4), 626-648. (Open access)
Abstract
This study aims to simulate the watershed of the Mindanao River Basin (MRB) to enhance water resource management for potential hydropower applications to meet the power demand in Mindanao with an average growth of 3.8% annually. The soil and water assessment tool (SWAT) model was used with inputs for geospatial datasets and weather records at four meteorological stations from DOST-PAGASA. To overcome the lack of precipitation data in the MRB, the precipitation records were investigated by comparing the records with the global gridded precipitation datasets from the NCDC-CPC and the GPCC. Then, the SWAT simulated discharges with the three precipitation data were calibrated with river discharge records at three stations in the Nituan, Libungan and Pulangi rivers. Due to limited records for the river discharges, the model results were, then, validated using the proxy basin principle along the same rivers in the Nituan, Libungan, and Pulangi areas. The R2 values from the validation are 0.61, 0.50 and 0.33, respectively, with the DOST-PAGASA precipitation; 0.64, 0.46 and 0.40, respectively, with the NCDC-CPC precipitation; and 0.57, 0.48 and 0.21, respectively, with the GPCC precipitation. The relatively low model performances in Libungan and Pulangi rivers are mainly due to the lack of datasets on the dam and water withdrawal in the MRB. Therefore, this study also addresses the issue of data quality for precipitation and data scarcity for river discharge, dam, and water withdrawal for water resource management in the MRB and show how to overcome the data quality and scarcity.
The works of Jonathan and Ismail are now published as above. Congratulations!
