National-scale geodatabase of catchment characteristics in the Philippines for river management applications

Abstract

Quantitative descriptions of stream network and river catchment characteristics provide valuable context for enabling geomorphologically-informed sustainable river management. For countries where high-quality topographic data are available, there are opportunities to enable open access availability of baseline products from systematic assessment of morphometric and topographic characteristics. In this study, we present a national-scale assessment of fundamental topographic characteristics of Philippine river systems. We applied a consistent workflow using TopoToolbox V2 to delineate stream networks and river catchments using a nationwide digital elevation model (DEM) acquired in 2013 and generated through airborne Interferometric Synthetic Aperture Radar (IfSAR). We assessed morphometric and topographic characteristics for 128 medium- to large-sized catchments (catchment area > 250 km2) and organised the results in a national-scale geodatabase. The dataset realises the potential of topographic data as part of river management applications, by enabling variations in hydromorphology to be characterised and contextualised. The dataset is used to reveal the diversity of stream networks and river catchments in the Philippines. Catchments have a continuum of shapes (Gravelius compactness coefficient ranges from 1.05 to 3.29) with drainage densities that range from 0.65 to 1.23 km/km2. Average catchment slope ranges from 3.1 to 28.1° and average stream slope varies by more than an order of magnitude from 0.004 to 0.107 m/m. Inter-catchment analyses show the distinctive topographic signatures of adjacent river catchments; examples from NW Luzon highlight topographic similarity between catchments whereas examples from Panay Island shown marked topographic differences. These contrasts underline the importance of using place-based analyses for sustainable river management applications. By designing an interactive ArcGIS web-application to display the national-scale geodatabase, we improve data accessibility and enable users to freely access, explore and download the data (https://glasgow-uni.maps.arcgis.com/apps/webappviewer/index.html?id=a88b9ca0919f4400881eab4a26370cee). The national-scale geodatabase provides a baseline understanding of fundamental topographic characteristics in support of varied geomorphological, hydrological and geohazard susceptibility applications.

Observations and computational multi‐phase modelling in tropical river settings show complex channel changes downstream from rainfall‐triggered landslides

“…We imposed a minimum value (0.001 m/m) to avoid spuriously small values of channel slope. For context, the mean channel slope calculated from 128 medium‐ to large‐sized catchments in the Philippines was 0.032 m/m (Boothroyd et al, 2023) and locally for the Antamok River segment the average channel slope is 0.07 m/m. Because stream network points were densely spaced (5 m spacing), topographically derived attributes vary over short distances (Ferencevic & Ashmore, 2012).…”

“…Major anthropogenic modifications to the river network include dams and several mine tailings storage facilities (TSFs). River centreline dataset is from Boothroyd et al (2023). [Color figure can be viewed at wileyonlinelibrary.com] and the mean slope value is 30 degrees, although the steepest slopes reach up to 76 degrees.…”

“…We used TopoToolbox V2 to delineate catchments from a nationwide DEM (Grafil & Castro, 2014) using standard flow-routing algorithms (Schwanghart & Scherler, 2014) with the D8 algorithm used to derive flow direction and a drainage area threshold of 1 km 2 to extract the stream network (Boothroyd et al, 2023). The position of the stream network was validated against the Google Earth imagery and showed good visual agreement.…”

Selecting the accurate hydrological method for estimating peak discharge in the Lesti River Catchment Area, Malang Regency, East Java Province, Indonesia

“…However, synthetic peak hydrograph analysis was not available when the rainfall data was required to compile the hydrograph of the units of size Calculated peak discharge using synthetic unit hydrograph methods commonly used in Indonesia include the Snyder-SCS, Snyder-Alexeyev, Nakayasu SUH, GAMA-1, DPMA-IOH, and HSS-αβγ methods (Ansori et al, 2023;Natakusumah et al, 2011). The other way to estimate peak discharge was Rational, Melchior, Weduwen, and Hasper, known as lumped methods (Ansori et (Boothroyd et al, 2023;Metselaar, 2023;Salvadore et al, 2015). This research analyzed and identified an appropriate catchment in East Java Province, Indonesia, to accom-plish this aim.…”

“…Where: tp is time lag (hr), Qp is peak discharge (m 3 sec -1 ), Tb is base time (hr), Q pR is unit discharge per unit area (m 3 sec -1 km -2 ); tr is effective rain duration (hr), C t and C p are coefficients that depend on the units and characteristics of the catchment(Boothroyd et al 2023). The coefficients Ct and Cp values need to be determined empirically because they vary between regions.…”