Forecasting Rainfall Induced Landslide using High Resolution DEM and Simple Water Budget Model

Monday, 15 December 2014
Paul Kenneth Dimayuga Luzon and Alfredo Mahar Francisco Amante Lagmay, National Institute of Geological Sciences, University of the Philippines, Quezon City, Philippines
Philippines is hit by an average of 20 typhoons per year bringing large amount of rainfall. Monsoon carrying rain coming from the southwest of the country also contributes to the annual total rainfall that causes different hazards. Such is shallow landslide mainly triggered by high saturation of soil due to continuous downpour which could take up from hours to days. Recent event like this happened in Zambales province September of 2013 where torrential rain occurred for 24 hours amounting to half a month of rain. Rainfall intensity measured by the nearest weather station averaged to 21 mm/hr from 10 pm of 22 until 10 am the following day. The monsoon rains was intensified by the presence of Typhoon Usagi positioned north and heading northwest of the country. A number of landslides due to this happened in 3 different municipalities; Subic, San Marcelino and Castillejos. The disaster have taken 30 lives from the province. Monitoring these areas for the entire country is but a big challenge in all aspect of disaster preparedness and management. The approach of this paper is utilizing the available forecast of rainfall amount to monitor highly hazardous area during the rainy seasons and forecasting possible landslide that could happen. A simple water budget model following the equation Perct=Pt-R/Ot-∆STt-AET(where as the terms are Percolation, Runoff, Change in Storage, and Actual Evapotraspiration) was implemented in quantifying all the water budget component. Computations are in Python scripted grid system utilizing the widely used GIS forms for easy transfer of data and faster calculation. Results of successive runs will let percolation and change in water storage as indicators of possible landslide.. This approach needs three primary sets of data; weather data, topographic data, and soil parameters. This research uses 5 m resolution DEM (IfSAR) to define the topography. Soil parameters are from fieldworks conducted. Weather data are from the Philippine Atmospheric, Geophysical and Astronomical Services Administration. The model is calibrated from stream gauges downsteam corresponding to the calculated runoff. Reliability of the results are as good as the data and is limited by the availability of such, though continuous enhancement of the method is expected as implementation progresses.