ABSTRACT:Flooding is considered to be one of the most destructive among many natural disasters such that understanding floods and assessing the risks associated to it are becoming more important nowadays. In the Philippines, Remote Sensing (RS) and Geographic Information System (GIS) are two main technologies used in the nationwide modelling and mapping of flood hazards. Although the currently available high resolution flood hazard maps have become very valuable, their use for flood preparedness and mitigation can be maximized by enhancing the layers of information these maps portrays. In this paper, we present an approach based on RS, GIS and two-dimensional (2D) flood modelling to generate new flood layers (in addition to the usual flood depths and hazard layers) that are also very useful in flood disaster management such as flood arrival times, flood velocities, flood duration, flood recession times, and the percentage within a given flood event period a particular location is inundated. The availability of these new layers of flood information are crucial for better decision making before, during, and after occurrence of a flood disaster. The generation of these new flood characteristic layers is illustrated using the Cabadbaran River Basin in Mindanao, Philippines as case study area. It is envisioned that these detailed maps can be considered as additional inputs in flood disaster risk reduction and management in the Philippines.

ABSTRACT:In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.

ABSTRACT:In this paper, we investigated how survey configuration and the type of interpolation method can affect the accuracy of river flow simulations that utilize LIDAR DTM integrated with interpolated river bed as its main source of topographic information. Aside from determining the accuracy of the individually-generated river bed topographies, we also assessed the overall accuracy of the river flow simulations in terms of maximum flood depth and extent. Four survey configurations consisting of river bed elevation data points arranged as cross-section (XS), zig-zag (ZZ), river banks-centerline (RBCL), and river banks-centerline-zig-zag (RBCLZZ), and two interpolation methods (Inverse Distance-Weighted and Ordinary Kriging) were considered. Major results show that the choice of survey configuration, rather than the interpolation method, has significant effect on the accuracy of interpolated river bed surfaces, and subsequently on the accuracy of river flow simulations. The RMSEs of the interpolated surfaces and the model results vary from one configuration to another, and depends on how each configuration evenly collects river bed elevation data points. The large RMSEs for the RBCL configuration and the low RMSEs for the XS configuration confirm that as the data points become evenly spaced and cover more portions of the river, the resulting interpolated surface and the river flow simulation where it was used also become more accurate. The XS configuration with Ordinary Kriging (OK) as interpolation method provided the best river bed interpolation and river flow simulation results. The RBCL configuration, regardless of the interpolation algorithm used, resulted to least accurate river bed surfaces and simulation results. Based on the accuracy analysis, the use of XS configuration to collect river bed data points and applying the OK method to interpolate the river bed topography are the best methods to use to produce satisfactory river flow simulation outputs. The use of other configurations (and a choice between IDW or OK) except RBCL can also be an alternative in cases when the XS configuration is less practical or expensive to implement.

In mitigating and helping lessen the possible effects and damages of disaster to the communities, the transmission of information or end products derived from remote sensing and other multidisciplinary technologies into the community should be immediate, accessible and comprehensive to aid in better planning and decision-making procedures. In this paper, we share a hazard information dissemination procedure which integrates the use of outputs derived from numerical models, web applications and systems as well as the use of social media and telecommunications to promote the utilization of advanced science and technology outputs that could represent and visualize various flooding scenarios through social media and dynamic communication between stakeholders.