The impact of flash floods in arid and semi-arid regions is notoriously difficult to measure because storm cells are short-lived, rainfall measurements are not common, and land-surface conditions vary quickly due to urban expansion. This chapter will propose a data-centered, two-model approach for transforming hydrometeorological uncertainties into valid economic-loss estimates. The Wadi Al Jizzi catchment in Sohar, Oman, was used as a representative test site. The two models are (i) the Flood Economic Impact Analysis System (FEIAS), which converts depth-damage curves, locally-calibrated construction costs (537.88 OMR m−2 reinforced-concrete building), and land-cover inventories into economic loss in each of the main sectors, and (ii) the probabilistic HEC-FDA tool, which uses frequency curves based on 30 flood peaks (1987–2007) to calculate Expected Annual Damage (EAD). High-resolution GIS layers (5 m Landsat images, 5 m DEM, shapefiles for roads and utilities), and a one-dimensional/two-dimensional HEC-RAS hydraulic model to provide depth grids for return periods of 10, 20, 50, and 100 years. This integration of the two approaches shows that residential structures and agricultural areas are not only within the damage portfolio, but together these end-uses constitute ~ 81% of total direct losses. In the 100-year scenario, the model estimates water depths of potential losses of 3 m along the significantly vulnerable reaches of the main road (Sultan Qaboos Road), which results in single extreme event residential damages that exceed 2.15 million OMR and cumulative infrastructure damages across single-event scenarios above 2.6 million OMR. The integration of the HEC-FDA stage-damage generated the EAD of 29,121 OMR yr−1 per residential building, which expresses the baseline economic risk that needs to be offset every year to achieve cost-neutral flood mitigation schemes. The sensitivity analysis indicates that over- and under-valuation of land use or flood depth by ± 15%, potentially increases or decreases the EAD by up to 18%, which requires the need for continual data updates as urbanisation progresses upon these flood-prone landscapes. By using deterministic loss estimates together with probabilistic risks, this chapter produces strategic design guidance for stakeholders to generate a trade-off between structural measures (detention basins, diversion channels) and non-structural measures (zoning, early warning technologies, insurance). This framework is transferrable to other data-poor flash flood-prone catchments while also facilitating evidence-based investments towards the development of climate-resilient communities in the drylands.

Flood Damage Cost Assessment and Sensitivity Analysis for Arid Catchments: Impacts of Hydroclimate Variability

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发表日期：

2026年

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Eyad Abushandi

摘要

The impact of flash floods in arid and semi-arid regions is notoriously difficult to measure because storm cells are short-lived, rainfall measurements are not common, and land-surface conditions vary quickly due to urban expansion. This chapter will propose a data-centered, two-model approach for transforming hydrometeorological uncertainties into valid economic-loss estimates. The Wadi Al Jizzi catchment in Sohar, Oman, was used as a representative test site. The two models are (i) the Flood Economic Impact Analysis System (FEIAS), which converts depth-damage curves, locally-calibrated construction costs (537.88 OMR m−2 reinforced-concrete building), and land-cover inventories into economic loss in each of the main sectors, and (ii) the probabilistic HEC-FDA tool, which uses frequency curves based on 30 flood peaks (1987–2007) to calculate Expected Annual Damage (EAD). High-resolution GIS layers (5 m Landsat images, 5 m DEM, shapefiles for roads and utilities), and a one-dimensional/two-dimensional HEC-RAS hydraulic model to provide depth grids for return periods of 10, 20, 50, and 100 years. This integration of the two approaches shows that residential structures and agricultural areas are not only within the damage portfolio, but together these end-uses constitute ~ 81% of total direct losses. In the 100-year scenario, the model estimates water depths of potential losses of 3 m along the significantly vulnerable reaches of the main road (Sultan Qaboos Road), which results in single extreme event residential damages that exceed 2.15 million OMR and cumulative infrastructure damages across single-event scenarios above 2.6 million OMR. The integration of the HEC-FDA stage-damage generated the EAD of 29,121 OMR yr−1 per residential building, which expresses the baseline economic risk that needs to be offset every year to achieve cost-neutral flood mitigation schemes. The sensitivity analysis indicates that over- and under-valuation of land use or flood depth by ± 15%, potentially increases or decreases the EAD by up to 18%, which requires the need for continual data updates as urbanisation progresses upon these flood-prone landscapes. By using deterministic loss estimates together with probabilistic risks, this chapter produces strategic design guidance for stakeholders to generate a trade-off between structural measures (detention basins, diversion channels) and non-structural measures (zoning, early warning technologies, insurance). This framework is transferrable to other data-poor flash flood-prone catchments while also facilitating evidence-based investments towards the development of climate-resilient communities in the drylands.