Preprints
https://doi.org/10.5194/egusphere-2024-1956
https://doi.org/10.5194/egusphere-2024-1956
30 Jul 2024
 | 30 Jul 2024

Beyond Total Impervious Area: A New Lumped Descriptor of Basin-Wide Hydrologic Connectivity for Characterizing Urban Watersheds

Francesco Dell'Aira and Claudio I. Meier

Abstract. Urbanization impacts on hydrologic response are typically indexed as a function of the fraction of total impervious area (TIA), i.e., the proportion of impervious areas in a basin. This implicitly assumes that changes in flood characteristics are somehow proportional to the extents of land-development, without considering that such impacts may vary widely depending on the location of the developed areas with respect to each other, the less-developed land patches, the stream network, and the basin outlet. In other words, TIA is blind to the spatial arrangement of the different types of land patches within a basin, and to the nuanced ways in which runoff volumes are differentially generated over them and then subsequently retained or detained, as they are routed towards the stream network and then the outlet. To overcome such limitations, we propose a new lumped index that measures the impacts of urbanization on basin response in terms of the emerging hydrologic connectivity, the distributed, directional basin property driven by topographically induced runoff pathways and locally affected by the different land-use/land-cover types present in a watershed. This alternative, hydrologic-connectivity-based index of urbanization (HCIU) displays sensitivity to the spatial arrangement of both fully developed as well as less developed or undeveloped patches, each with different degrees of imperviousness, roughness, and other characteristics affecting their abilities to either generate or else retain/detain runoff, reflecting their distinct localized effects on hydrologic connectivity. The proposed HCIU can be readily obtained in a GIS environment from easily available raster geospatial data. We found that HCIU improves the predictive power of regional equations for peak flow in three large case-study homogeneous regions, when used in place of the traditional TIA.

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.
Francesco Dell'Aira and Claudio I. Meier

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1956', Anonymous Referee #1, 10 Oct 2024
    • AC1: 'Reply on RC1', Francesco Dell'Aira, 20 Oct 2024
    • AC3: 'Additional reply to RC1', Francesco Dell'Aira, 25 Oct 2024
      • RC3: 'Reply on AC3', Anonymous Referee #1, 25 Oct 2024
        • AC4: 'Reply on RC3', Francesco Dell'Aira, 25 Oct 2024
  • RC2: 'Comment on egusphere-2024-1956', Anonymous Referee #2, 11 Oct 2024
    • AC2: 'Reply on RC2', Francesco Dell'Aira, 20 Oct 2024
Francesco Dell'Aira and Claudio I. Meier

Model code and software

HCIU urbanization metric Francesco Dell'Aira https://github.com/dllaira/HCIU-urbanization-metric

Francesco Dell'Aira and Claudio I. Meier

Viewed

Total article views: 324 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
192 88 44 324 6 8
  • HTML: 192
  • PDF: 88
  • XML: 44
  • Total: 324
  • BibTeX: 6
  • EndNote: 8
Views and downloads (calculated since 30 Jul 2024)
Cumulative views and downloads (calculated since 30 Jul 2024)

Viewed (geographical distribution)

Total article views: 358 (including HTML, PDF, and XML) Thereof 358 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 Nov 2024
Download
Short summary
Scientists and engineers need better indices to frame the hydrologic effects of land development. Existing approaches are not able to reflect the interactions due to the spatial arrangement of distinct land patches, which affect how much runoff is generated and how fast it can travel downstream, impacting flood response. Our novel, GIS-based modeling framework explicitly considers these aspects and is applicable to a wide range of problems, including peak-flow predictions in ungauged basins.