The Philippines is one of the most vulnerable countries in Southeast Asia to climate change impacts [23] and consistently ranks as one of the most globally affected countries by extreme weather [24, 25]. Climate change is impacting the magnitude and frequency of extreme flood-generating storms [26, 27] and a high proportion of the population are exposed to hazards arising from fluvial flooding and erosion [28]. Challenges associated with water resource management (e.g., water security [29]) and hydrometeorological hazards (e.g., floods [30] and rainfall-triggered landslides [31]) have necessitated the acquisition of high-quality topographic datasets, primarily for resource mapping and predictive hazard modelling purposes. A nationwide topographic dataset with 5 m spatial resolution and 1 m root-mean-square error vertical accuracy was acquired in 2013 using airborne Interferometric Synthetic Aperture Radar (IfSAR) from the National Mapping and Resource Information Authority (NAMRIA) [32]. Higher resolution topographic data with a 1 m spatial resolution were acquired between 2012 and 2016 for major floodplains using airborne Light Detection and Ranging (LIDAR) from the Disaster Risk and Exposure Assessment for Mitigation (DREAM) and Phil-LiDAR 1 programs ( ) [33].
High-quality topographic data have been used to realise a step-change in hydrometeorological hazard information in the Philippines; underpinning nationwide landslide susceptibility assessments and detailed flood hazard reports for more than 300 river catchments [34]. Detailed maps for landslide, flood and storm surge hazards are used by Local Government Units (LGUs) for disaster preparedness planning and communicated to wider audiences through a web-based disaster Geographic Information System (Web-GIS) from the Nationwide Operational Assessment of Hazards (NOAH) program ( ). The high-quality topographic data have also been used for resource mapping applications as part of the Phil-LiDAR 2 Program [33, 35]. Alongside additional remote sensing products (e.g., satellite imagery), the topographic data have been used to map stream networks, river catchments, irrigation networks and inland wetlands through the Development of the Philippine Hydrologic Dataset for Watersheds from LiDAR Surveys (PHD project) [36, 37]. The hydrological dataset contains information on 770 principal river basins (catchment area > 40 km2) but attribute information is limited to a small number of simple descriptors (e.g., catchment area and length of stream network lines).
Despite the availability of high-quality topographic data with a nationwide coverage, a systematic national-scale assessment of fundamental topographic characteristics of stream networks and river catchments has yet to be undertaken. Achieving such an analysis has the potential to provide a baseline dataset for geomorphologically-informed sustainable river management that is similarly significant to the transformation of flood risk management by airborne LiDAR. For water resource planning, the Philippines is divided into 12 water resources regions and 18 major river basins; designated by the National Water Resources Council [38]. Although existing river basin management plans contain information on catchment topography (e.g., qualitative and quantitative descriptions of terrain), the plans are only available for some of the larger river basins (catchment area > 3000 km2). For smaller catchments, inconsistent methods have been applied to derive topographic information for a variety of research purposes (e.g., geochemical mapping of the Santo Tomas River [39], fluvial morphology assessments in the Bislak catchment [40], streamflow predictions in the Abuan catchment [41], land use change impacts on hydrology in the Calumpang catchment [42]). Inter-catchment comparisons have previously been undertaken for small numbers of catchments (e.g., catchments with similar hydrological regimes [43]) or across a limited geographical extent (e.g., individual islands [44]). To date, it has not been possible to contextualise the topographic characteristics of stream network and river catchments at the national-scale, because: (1) fundamental topographic characteristics of small- to medium-sized catchments (catchment area In this study, we systematically assess fundamental topographic characteristics of stream networks and river catchments in the Philippines. Using high-quality topographic data, we apply a consistent workflow to calculate topographic characteristics for 128 medium- to large-sized river catchments (catchment area > 250 km2). We provide a national-scale assessment of selected topographic characteristics before making detailed inter-catchment comparisons to illustrate similarities and differences between adjacent catchments. Our findings reveal the topographic diversity of stream networks and river catchments; individual catchments have distinctive topographic signatures and we observe substantial variation between catchments. This finding underpins the need to use the dataset for geomorphologically-informed sustainable river management applications, some of which we highlight. To improve data accessibility, we host our national-scale geodatabase in an interactive ArcGIS web-application that enables users to freely view, explore and download the data.
In this section we summarise the workflow used to calculate fundamental topographic characteristics and display the results in an interactive ArcGIS web-application. The workflow is summarised in Fig 1, indicating the main processing steps and resultant products.
We used a nationwide IfSAR DEM acquired in 2013 for our analysis; it has a 5 m spatial resolution and covers approximately 300,000 km2 of the Philippine landmass [34]. Although higher resolution LIDAR data is available for the floodplains of more than 300 river catchments, the spatial coverage of the LIDAR data is incomplete (i.e., topographic data are not available for all parts of every catchment). Furthermore, by using the IfSAR DEM we maintained a consistent vertical accuracy at the national-scale (1 m root-mean-square error [34]). Due to computational constraints associated with processing the topographic data, we bilinearly resampled the 5 m IfSAR DEM to a 10 m spatial resolution before completing the analyses.
We used TopoToolbox V2 to delineate stream networks and river catchments using standard flow-routing algorithms [18] with the D8 algorithm used to derive flow direction. Having calculated flow accumulation and extracted individual drainage basins, we used an upstream area threshold value (1 km2) to delineate alluvial channels to be included within the stream network [45]. The upstream area threshold value marked the transition from debris flow-dominated channels to alluvial channels. The position of the DEM-derived stream networks were in good visual agreement with the position of channels in Google Earth imagery and within close proximity to the stream networks mapped through the PHD program [36, 37]. DEMs typically contain artefacts and errors that propagate into topographic analyses [46], meaning that derived attributes such as stream slope vary over short distances [47]. We ensured downstream decreasing elevations and provided a hydrologically correct DEM by applying constrained regularized smoothing to the stream network to minimise DEM artefacts and errors (smoothing factor, K = 2; quantile, τ = 0.5; [48]). Several attributes were extracted at all points along the stream network, including the elevation, drainage area, stream slope, stream order and distance from outlet. Because stream network points were densely spaced (0.01 km spacing; equal to DEM resolution), we aggregated points over river segment lengths of 0.05, 0.1, 0.2 and 1 km to generalize any local fluctuations in attribute values (Table 1). The segments split the stream network into homogeneous reaches of a set length; these were evenly distributed between confluences, confluences and outlets, and confluences and channel heads. The approach ensured that a consistent delineation method was applied to all stream networks and river catchments.
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