Preprints
https://doi.org/10.5194/egusphere-2024-2340
https://doi.org/10.5194/egusphere-2024-2340
19 Aug 2024
 | 19 Aug 2024

Modelling Flood Losses to Microbusinesses in Ho Chi Minh City, Vietnam

Anna Buch, Dominik Paprotny, Kasra Rafiezadeh Shahi, Heidi Kreibich, and Nivedita Sairam

Abstract. Microbusinesses are important sources of livelihood for low- and middle-income households. In Ho Chi Minh City (HCMC), Vietnam, many microbusinesses are set up in the ground floor of residential houses susceptible to urban floods. Increasing flood risk in HCMC threatens the financial resources of microbusinesses by damaging business contents and causing business interruption. Since flood loss estimations are rarely conducted at object-level resolution and are often focused on households or large companies, the losses suffered by microbusinesses are often overlooked. This study aims to derive the drivers of flood losses in microbusinesses by applying a Conditional Random Forest to survey data (content losses: n=317; business interruption losses: n=361) collected from microbusinesses in HCMC. The variability of content losses and business interruption were adequately explained by the revenues of the businesses from monthly sales, age of the building where the business is established and water depth in the building during the flood event. Based on the identified drivers, probabilistic loss models (non-parametric Bayesian Networks) were developed using a combination of data-driven and expert-based model formulation. The models estimated the flood losses for HCMC’s microbusinesses with a mean absolute error of 3.8 % for content losses and 18.7 % for business interruption losses. The Bayesian Network model for business interruption performed with a similar predictive performance when it was regionally transferred and applied to comparable survey data from another Vietnamese city, Can Tho. The flood loss models introduced in this study make it possible to derive flood risk metrics specific to microbusinesses to support adaptation decision making and risk transfer mechanisms.

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.
Anna Buch, Dominik Paprotny, Kasra Rafiezadeh Shahi, Heidi Kreibich, and Nivedita Sairam

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-2024-2340', Anonymous Referee #1, 25 Oct 2024
    • CC1: 'Reply on RC1', Anna Buch, 28 Oct 2024
  • RC2: 'Comment on egusphere-2024-2340', Anonymous Referee #2, 16 Dec 2024
Anna Buch, Dominik Paprotny, Kasra Rafiezadeh Shahi, Heidi Kreibich, and Nivedita Sairam

Model code and software

Flood Loss Models for Microbusinesses, Vietnam Anna Buch https://github.com/A-Buch/flood-loss-models-4-HCMC/tree/microbusiness-paper

Anna Buch, Dominik Paprotny, Kasra Rafiezadeh Shahi, Heidi Kreibich, and Nivedita Sairam

Viewed

Total article views: 260 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
185 59 16 260 21 6 6
  • HTML: 185
  • PDF: 59
  • XML: 16
  • Total: 260
  • Supplement: 21
  • BibTeX: 6
  • EndNote: 6
Views and downloads (calculated since 19 Aug 2024)
Cumulative views and downloads (calculated since 19 Aug 2024)

Viewed (geographical distribution)

Total article views: 298 (including HTML, PDF, and XML) Thereof 298 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Dec 2024
Download
Short summary
Many households in Vietnam depend on revenues from microbusinesses (shop-houses). However, losses caused by regular flooding to the microbusinesses are not modelled. Business turnover, building age and water depth are found to be the main drivers of flood losses to microbusinesses. We built and validated probabilistic models (Non-parametric Bayesian Networks) that estimate flood losses to microbusinesses. The results help in flood risk management and adaption decision making for microbusinesses.