Preprints
https://doi.org/10.5194/hess-2024-188
https://doi.org/10.5194/hess-2024-188
08 Jul 2024
 | 08 Jul 2024
Status: this preprint is currently under review for the journal HESS.

Flood estimation for ungauged catchments in the Philippines

Trevor B. Hoey, Pamela Louise M. Tolentino, Esmael L. Guardian, John Edward G. Perez, Richard D. Williams, Richard J. Boothroyd, Carlos Primo C. David, and Enrico C. Paringit

Abstract. Flood magnitude and frequency estimation are essential for the design of structural and nature-based flood risk management interventions and water resources planning. However, the global geography of hydrological observations is uneven; in many regions, such as the Philippines, data are spatially and/or temporary sparse, limiting the choice of statistical methods for flood estimation. We evaluate the potential of pooling short historical data series for ungauged catchment flood estimation. Daily mean river discharge data were collected from 842 sites, with data spanning from 1908 to 2018. Of these, 513 candidate sites met criteria to estimate a reliable annual maximum flood. Using the index flood approach, a range of controls were assessed at national and regional scales using land cover and rainfall datasets, and GIS-derived catchment characteristics. Multivariate analysis for predictive equations for 2 to 100 year recurrence interval floods based on catchment area only have R2 ≤ 0.59. Additionally, adding a rainfall variable, the median annual maximum 1-day rainfall, increases R2 to between 0.56 for Q100 and 0.66 for Q2. Very few other variables were significant when added to multiple regression equations. Although the Philippines exhibits regional climate variability, there is limited spatial structure in predictive equation residuals and region-specific predictive equations do not perform significantly better than national equations. Relatively low R2 values are typical of studies from tropical regions. The predictive equations are suitable for use as design equations for the Philippines but uncertainties must be assessed. Our approach demonstrates how combining individually short historical records, after careful screening and exclusion of erroneous data, generates large data sets that can produce consistent results. Extension of continuous flood records is required to reduce uncertainties but national-scale consistency suggests that extrapolation from a small number of carefully selected catchments could provide nationally reliable predictive equations with reduced uncertainties.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Trevor B. Hoey, Pamela Louise M. Tolentino, Esmael L. Guardian, John Edward G. Perez, Richard D. Williams, Richard J. Boothroyd, Carlos Primo C. David, and Enrico C. Paringit

Status: open (until 02 Sep 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Trevor B. Hoey, Pamela Louise M. Tolentino, Esmael L. Guardian, John Edward G. Perez, Richard D. Williams, Richard J. Boothroyd, Carlos Primo C. David, and Enrico C. Paringit

Data sets

Flood estimation for ungauged catchments in the Philippines: Annual Maximum Flow (AMAX) and catchment properties data T. B. Hoey et al. https://doi.org/10.5525/gla.researchdata.1666

Trevor B. Hoey, Pamela Louise M. Tolentino, Esmael L. Guardian, John Edward G. Perez, Richard D. Williams, Richard J. Boothroyd, Carlos Primo C. David, and Enrico C. Paringit

Viewed

Total article views: 157 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
111 35 11 157 15 5 4
  • HTML: 111
  • PDF: 35
  • XML: 11
  • Total: 157
  • Supplement: 15
  • BibTeX: 5
  • EndNote: 4
Views and downloads (calculated since 08 Jul 2024)
Cumulative views and downloads (calculated since 08 Jul 2024)

Viewed (geographical distribution)

Total article views: 150 (including HTML, PDF, and XML) Thereof 150 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Jul 2024
Download
Short summary
Estimating the sizes of flood events is critical for flood-risk management and other activities. We used data from several sources in a statistical analysis of flood size for rivers in the Philippines. Flood size is mainly controlled by the size of the river catchment, along with the volume of rainfall. Other factors, such as land-use, appear to play only minor roles in flood size. The results can be used to estimate flood size for any river in the country alongside other local information.