Enhancing flood-exposure assessment with high-resolution settlement data: An integrated study from flood hazard to exposure in the Nilwala River Basin, Sri Lanka

Nilwala River Basin, Sri Lanka This study comprehensively assessed flood exposure in a basin by integrating hazard, modelled using the rainfall runoff inundation (RRI) model, with two datasets of different spatial resolutions (30 m and ∼300 m) to identify exposed areas during three historical flood events. Comparisons were made with damage estimates by local authorities. The RRI model simulated river discharge and inundation with reasonable accuracy, especially in the flat downstream sub-catchment of the basin. Although the hazard characteristics of the three flood events differed, their impacts on human settlements were similar. Specifically, damage to households accounted for 64.42 % of all damage in 2003, 60.85 % in 2017 and 100 % in 2018. Densely populated areas in the downstream sub-catchment that were severely affected during all three events were detected using both datasets; however, the relatively coarse-resolution (∼300 m) land-use maps failed to capture small settlements in the upstream sub-catchment that were damaged during the 2003 and 2017 events. These settlements, predominantly located in agricultural and shrubland areas, were identified when using the high-resolution settlement maps (30 m). The use of higher-resolution settlement data therefore significantly enhanced the exposure assessment, complementing the coarser-resolution land-use maps. Our study demonstrates the importance of using high-resolution settlement datasets in exposure assessments to achieve accurate evaluations of flood risks at the river-basin scale. • Comprehensive assessment of flood exposure, starting with flood hazard simulations. • Two datasets of varying spatial resolutions were used to assess flood exposure. • Improved flood exposure assessment with the use of high-resolution settlement data. • Insights for comprehensive flood risk assessment in data-scarce regions are proposed.

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Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2025-11-20
DOI
https://doi.org/10.1016/j.ejrh.2025.102949
Primary Topic
Flood Risk Assessment and Management
Type
article
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article

Enhancing flood-exposure assessment with high-resolution settlement data: An integrated study from flood hazard to exposure in the Nilwala River Basin, Sri Lanka

Jun Magome, Kazuyoshi Souma, Jayapadma Mudalige Miyuru Uthpala Jayapadma, Hiroshi Ishidaira et al.
Journal of Hydrology Regional Studies
Flood Risk Assessment and Management
article

Enhancing flood-exposure assessment with high-resolution settlement data: An integrated study from flood hazard to exposure in the Nilwala River Basin, Sri Lanka

Jun Magome, Kazuyoshi Souma, Jayapadma Mudalige Miyuru Uthpala Jayapadma, Hiroshi Ishidaira, T. N. Wickramaarachchi
article en

Abstract

Nilwala River Basin, Sri Lanka This study comprehensively assessed flood exposure in a basin by integrating hazard, modelled using the rainfall runoff inundation (RRI) model, with two datasets of different spatial resolutions (30 m and ∼300 m) to identify exposed areas during three historical flood events. Comparisons were made with damage estimates by local authorities. The RRI model simulated river discharge and inundation with reasonable accuracy, especially in the flat downstream sub-catchment of the basin. Although the hazard characteristics of the three flood events differed, their impacts on human settlements were similar. Specifically, damage to households accounted for 64.42 % of all damage in 2003, 60.85 % in 2017 and 100 % in 2018. Densely populated areas in the downstream sub-catchment that were severely affected during all three events were detected using both datasets; however, the relatively coarse-resolution (∼300 m) land-use maps failed to capture small settlements in the upstream sub-catchment that were damaged during the 2003 and 2017 events. These settlements, predominantly located in agricultural and shrubland areas, were identified when using the high-resolution settlement maps (30 m). The use of higher-resolution settlement data therefore significantly enhanced the exposure assessment, complementing the coarser-resolution land-use maps. Our study demonstrates the importance of using high-resolution settlement datasets in exposure assessments to achieve accurate evaluations of flood risks at the river-basin scale. • Comprehensive assessment of flood exposure, starting with flood hazard simulations. • Two datasets of varying spatial resolutions were used to assess flood exposure. • Improved flood exposure assessment with the use of high-resolution settlement data. • Insights for comprehensive flood risk assessment in data-scarce regions are proposed.

Journal of Hydrology Regional StudiesVol. 62
University of Ruhuna (LK), Takeda (Japan) (JP), University of Yamanashi (JP)
Openalex Percentile: Top 67%
Flood Risk Assessment and Management
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