Category Archives: Publication

Combining geospatial data and numerical models to map and differentiate flooding extents caused by two tropical storms in the Philippines

By Meriam Makinano-Santillan, Jojene R. Santillan

ABSTRACT:

In the year 2014, heavy rains associated with tropical storms Lingling (known as Agaton in the Philippines; January 10-20, 2014) and Jangmi (locally known as Seniang; December 27, 2014 – January 1, 2014) triggered massive flooding and caused fatalities in many localities, particularly in Caraga Region in northeastern Mindanao. Based on ground data, the 10-day Agaton event brought a total rainfall of 922 mm, of which 221 mm where recorded on January 19 alone, a day before it dissipated to the southeast of the Philippines. On the other hand, the 6-day Seniang event brought a total rainfall of 356 mm, of which 259 mm where recorded on December 29 alone. To better understand and differentiate the impacts of heavy rains brought by these tropical storms to the extent of flooding, we reconstructed the two flooding events by combining geospatial data from remote sensing and field surveys with numerical modelling. We focused on the Cabadabaran River Basin (CBR) and the nearby Pandanon River and Caasinan River Watersheds in Agusan del Norte, Caraga Region as our case study area. First, we developed a HEC HMS-based hydrological model of the river basin using a 10-m Synthetic Aperture Radar (SAR) Digital Elevation Model (DEM) for sub-basin delineations, land-cover maps from Landsat 8 OLI images for model parameterization, and rainfall and discharge datasets for model simulation and validation. The purpose of the HEC HMS model was to determine the volume of water coming from the various sub-basins that drains into the floodplains during the storms. The discharge hydrographs were then used as inputs into a 2-dimensional flood model to simulate the movement of flood water along the rivers and in the floodplains and to map the areas that are flooded. The 2D model was developed using a 1-m resolution LiDAR-derived Digital Terrain Model (DTM) and Landsat-derived landcover maps as its major parameters. From the numerical model simulations and output flood maps, we found that the Agaton event produced more discharge and caused wider extent of flooding than the Seniang event. This result is consistent with the fact that rainfall during Agaton was greater in volume than during Seniang. More areas were also in low and medium flood hazard levels (0.1 – 1.5 m depth) during Agaton. However, areas in high hazard levels (>1.5 m depth) appeared to be similar in both events. The results of this study showed the importance of combining geospatial data and techniques with numerical models to reconstruct and understand past flooding events. The flood simulations and maps derived from this study can be useful not only in flood hazard mapping of the project area, but also as visual aids to help people understand the differences of the impacts of different tropical storms in the occurrence of flooding.

KEYWORDS: geospatial data, remote sensing, numerical modeling, flood, tropical storms, Philippines


Publication Details/Metadata:

Paper Title: COMBINING GEOSPATIAL DATA AND NUMERICAL MODELS TO MAP AND DIFFERENTIATE FLOODING EXTENTS CAUSED BY TWO TROPICAL STORMS IN THE PHILIPPINES

Authors: Jojene R. Santillan, Meriam Makinano-Santillan

Publication Date: 2015

Conference Name/Journal/Book Title: 13th Southeast Asian Survey Congress (SEASC 2015): Expanding the Geospatial Future

Publisher: ASEAN Federation of Land Surveying and Geomatics(ASEAN FLAG), Singapore Institute of Surveyors and Valuers (SISV)

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Flood extent validation surveys in the river basins of Caraga region, Mindanao, Philippines and its importance in assessing the accuracy of flood hazard maps

By Arthur Amora, Jojene R. Santillan, Meriam M. Santillan, Ronald Makinano, Jennifer Marqueso, Almer Estorque, George Hussein Mordeno

ABSTRACT:

In this paper, we discuss the methods and results of our field surveys that we conducted to gather information on flood extents that are necessary for assessing the accuracy of flood hazard maps. This activity is a major part of the CSU LiDAR 1 project which we currently undertake for the purpose of generating flood hazard maps of river basins of Caraga Region in Mindanao, Philippines. CSU LiDAR 1 is one of the several projects under the “Phil-LiDAR 1: Hazard Mapping of the Philippines using LiDAR” program funded by the Philippines Council for Industry, Energy and Emerging Technology Research and Development – Department of Science and Technology (PCIEERD-DOST). For the project’s first year of implementation on 2014, it focused on the river basins of Cabadbaran, Mainit-Tubay-Asiga and Tago. The flood hazard maps of these project areas needs to be validated on the actual ground to determine its reliability and accuracy. For 2014, there were two typhoons that struck the Caraga Region in the Philippines, namely: typhoon Lingling (local name Agaton) which hit last January 2014 and typhoon Jangmi (local name Seniang) last December 2014. Necessary information on actual extent of flooding during the two typhoons where collected through conduct of GPS surveys last December 2014 – February 2015. The survey locations were based on random points generated within the flood plains of the three river basins. Information gathered during the surveys includes the estimated flood heights during the two typhoons, the corresponding date and time of occurrence and the geographic coordinates. These datasets were consolidated and statistical analyses were conducted to initially assess the effects of the nearness to the river and the slope from the river banks for the flooding that occurred on every location. Based on the results, it can be generally concluded that those areas that are near to the river are more prone to flooding compared to other areas within the river basin. Nevertheless, a relatively flat slope from the river banks to any point within the floodplain weights more effect on the proneness to flooding of an area. This was verified from the datasets from some far from the river areas but was still flooded due to its relatively flat topography from the river banks. All the data points collected were used to assess the accuracy of flood hazard maps generated by the project for the two typhoon events.

KEYWORDS: flood extent validation, Caraga Region, Mindanao, Philippines


Publication Details/Metadata:

Paper Title: FLOOD EXTENT VALIDATION SURVEYS IN THE RIVER BASINS OF CARAGA REGION, MINDANAO, PHILIPPINES AND ITS IMPORTANCE IN ASSESSING THE ACCURACY OF FLOOD HAZARD MAPS

Authors: Arthur Amora, Jojene R. Santillan, Meriam M. Santillan, Ronald Makinano, Jennifer Marqueso, Almer Estorque, George Hussein Mordeno

Publication Date: 2015

Conference Name/Journal/Book Title: 13th Southeast Asian Survey Congress (SEASC 2015): Expanding the Geospatial Future

Publisher: ASEAN Federation of Land Surveying and Geomatics (ASEAN FLAG), Singapore Institute of Surveyors and Valuers (SISV)

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The development of a hydrological model for water level forecasting in the Philippines’ deepest lake.

By Arthur M. Amora, Jojene R. Santillan, Meriam M. Santillan

ABSTRACT:

Lake Mainit is considered to be the Philippine’s deepest lake with a maximum depth reaching about 223 m. It is geographically located between the Provinces of Surigao del Norte and Agusan del Norte, in the Island of Mindanao. With a surface area of 149.86 km2, it ranks fourth to Laguna Lake as one of the Philippine’s largest lakes. The lake receives inflows from several major and minor tributaries located in the municipalities of Mainit and Alegria (Surigao del Norte) and Kitcharao and Jabonga (Agusan del Norte). During heavy rainfall events, inflows from these tributaries increase the lake’s water level and causes flooding of barangays located near the shore. This scenario is exemplified recently during the January 2014 Typhoon Agaton. In this paper, we present the development of a hydrologic model of Lake Mainit in order to gain a better understanding of how the various tributaries contribute to the lake’s water level during rainfall events. With the development of this model, the water level in the lake can be simulated or forecasted given the amount of rainfall measured by existing rainfall stations located in the lake’s vicinity.

KEYWORDS: Lake Mainit, reservoir, water level, forecasting, HEC HMS


Publication Details/Metadata:

Paper Title: THE DEVELOPMENT OF A HYDROLOGIC MODEL FOR WATER LEVEL FORECASTING INT THE PHILIPPINES’ DEEPEST LAKE

Authors: Arthur M. Amora, Jojene R. Santillan, Meriam M. Santillan

Publication Date: 2015

Conference Name/Journal/Book Title: 3rd Philippine Geomatics Symposium 2014 (PhilGEOS 2014)

Publisher: Training Center for Applied Geodesy and Photogrammetry, University of the Philippines, Diliman, Quezon City

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Detection and Correction of ASTER GDEM v2 Data Anomalies Through DEM Differencing

By Jojene R. Santillan, Meriam M. Santillan

ABSTRACT:

The ASTER GDEM Version 2 (v2) which was released in 2011 is considered to be the highest resolution and readily available global digital elevation model. Having a spatial resolution of 30-m, the ASTER GDEM v2 contains significant improvements of Version 1 in terms of spatial coverage, refined horizontal resolution, water masking, and inclusion of new ASTER data to supplement the voids and artifacts. Despite of these improvements, data anomalies such as abrupt rise (“bumps”) and fall (“pits”) in elevation values in the ASTER GDEM v2 still remains. In this paper, we present a simplified and semi-automatic approach of detecting and correcting data anomalies in the ASTER GDEM v2 of Tago River Basin in Surigao del Sur, Mindanao, Philippines. The anomaly detection procedure consisted of calibrating the elevation values in the ASTER GDEM v2 against a resampled SRTM DEM version 4.1, creating a difference image between the calibrated ASTER GDEM and SRTM DEM, applying a low pass filter to the difference image, employing the K-means clustering algorithm to classify the difference image pixels into various classes, and then labeling them as bumps, pits or neither (i.e., not anomaly) using a known set of pixels pre-selected prior to K-means classification. The accuracy of the detection was at 99.47% based on an independent set of randomly selected validation pixels. The detected anomalies were then masked out from ASTER GDEM v2, and the elevation values of these pixels were replaced by elevation values extracted from the resampled SRTM DEM. The corrected DEM was used for hydrological applications such as computations of flow direction and flow accumulation grids, sub-basin delineations and stream network definition. These DEM derivatives are important inputs in hydrological model development for the river basin.

KEYWORDS: ASTER GDEM v2, SRTM DEM, anomaly detection, DEM correction


Publication Details/Metadata:

Paper Title: DETECTION AND CORRECTION OF ASTER GDEM V2 DATA ANOMALIES THROUGH DEM DIFFERENCING
Authors: Jojene R. Santillan, Meriam M. Santillan
Publication Date: 2014
Conference Name/Journal/Book Title: 35th Asian Conference on Remote Sensing 2014 (ACRS 2014)
Volume: 2
Pages: 1261-1266
Publisher: Asian Association on Remote Sensing
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