Extreme Event-based Rainfall-Runoff Simulation Utilizing GIS Techniques in Irawan Watershed, Palawan, Philippines

Jennifer C. Cacal (1) Engineering Graduate Program, School of Engineering, University of San Carlos, Talamban, Cebu City 6000, Philippines. 2) Department of Civil Engineering College of Engineering, Architecture & Technology, Palawan State University, Tiniguiban, Puer)
Victor Czar A. Austria (Department of Civil Engineering College of Engineering, Architecture & Technology, Palawan State University, Tiniguiban, Puerto Princesa City 5300,)
Evelyn B. Taboada (1) Engineering Graduate Program, School of Engineering, University of San Carlos, Talamban, Cebu City 6000, Philippines. 3) Department of Chemical Engineering, School of Engineering, University of San Carlos, Talamban, Cebu City 6000,)

Civil Engineering Journal
Vol 9, No 1 (2023): January

River flow assessments and ecologically sustainable water management plans are now possible due to the advancement of sophisticated computer models. The US Army Corps of Engineers developed the HEC-HMS model, which can be used for various hydrological simulations. Rainfall-runoff modeling aids in estimating peak flows, which is critical for water resource management planning. On December 18, 2017, a heavy rainfall event in the ungauged Irawan basin in Puerto Princesa City, Palawan, Philippines, was simulated to determine the peak flow and amount of water. The current research aims to construct a rainfall-runoff simulation model. A specific hyetograph is used to make the hydrographs for the basin. This study utilizes ArcGIS and QGIS, which perform the geospatial analysis and provide the HEC-HMS model's hydrologic modeling inputs. The hydrological parameters were determined using soil type, land use, and land cover maps. Incorporating SCS loss, Clark unit hydrograph, and Muskingum flow routing, HEC-HMS was employed in the rainfall-runoff simulation. Rainfall data corresponding to the recorded streamflow was used to calibrate and validate the parameters. Several performance metrics, including Nash-Sutcliffe efficiency (NSE) and Percentage Bias (PBIAS), were utilized to evaluate the overall effectiveness of the system. An effective decision-making and warning system can be implemented using the developed model. Doi: 10.28991/CEJ-2023-09-01-017 Full Text: PDF