In this study, a flood damage assessment method was proposed for the assessment of flood risk in data-poor river basins by using a physical-based numerical model, satellite-based information and socio-economic factors. The Pampanga river basin of the Philippines was selected for the case study. For the flood damage assessment, hazard characteristics, such as flood depth and duration, were computed using the rainfall runoff inundation model. Agriculture and households, which are major exposures in flood-prone areas, were taken into account for the flood damage assessment. The potential damage to agriculture was estimated by using the damage functions of agriculture and flood characteristics. The damage functions of agriculture for each growing stage were defined as the function of flood depth and duration. Field investigations and questionnaire surveys were conducted at the selected barangays (villages) in the Pampanga river basin to develop a methodology for household damage estimation. The damage estimation approach for damage to household buildings including assets, was developed based on the flood and household characteristics. The potential damage to house building and assets was estimated. The estimated damage of agriculture and households was compared with the reported values.

The objective of this study was to estimate rice crop damage over the entire Cambodia during a large flood event from July to November 2011. An integrated approach was applied to detect and monitor flood areas with flood depth and duration for near real-time rice crop damage estimation in 2011 by using MODIS time-series imagery. The combined data consists of developed MLSWI, EVI from MODIS, new FID from DEM, land use, and simplified empirical damage curves. These data are expected to play an important role in emergency response efforts and rapid risk assessment for high-risk flood areas in the Cambodian floodplain. A rice crop damage map will be generated, showing areas with different damage levels based on flood duration and floodwater depth, including 25% (8 days, below 1.5 m), 50% (8 days, over 1.5 m; 16 days, below 1.5 m), and 100% (16 days, over 1.5 m). The resulting map was validated and shows about 80% consistency with the government census based on field-scale investigation and survey. Index Terms-Cambodian floodplain, damage curves, large flood, MODIS, rice crop damage.

Experience shows that debris flows containing large woody debris (driftwood) can be more damaging than debris flows without driftwood. In this study, the deposition process of debris flows carrying driftwood was investigated using numerical simulations and flume experiments. Debris-flow trapping due to driftwood jamming in a slit-check dam was also investigated. A numerical model was developed with an interacting combination of Eulerian expression of the debris flow and Lagrangian expression of the driftwood, in which the fluctuating coordinates and rotation of the driftwood were treated stochastically. The calculated shapes and thicknesses of a debris-flow fan and the positions and orientations of the deposited driftwood on a debris-flow fan were consistent with experimental flume results. The jamming of driftwood in a slit-check dam was evaluated based on geometry and probability. The simulated results of outflow discharge and the proportion of driftwood passed through the slit-check dam also agreed with the experimental results.

Flood features were analyzed and risk knowledge was examined in studies in selected river basins of Southeast Asia. Rainfall runoff features were analyzed in Indonesia’s Solo river basin and in the Philippines’ Pampanga and Cagayan river basins using ground-observed and satellite-based (GSMaP) rainfall data. Flood damage was assessed for risk management by considering physical damage to agricultural and household in the Cambodian flood plain of the Lower Mekong Basin and in the Philippines’s Pampanga river basin. A comparison of simulated and observed runoff hydrographs showed that the accuracy of GSMaP rainfall in the Solo and Cagayan river basins in studied flood events was lower than in the Pampanga river basin case. In the Pampanga and Cagayan river basins, the density of rainfall station networks was below the WMO recommendation, and GSMaP rainfall data would be more effective in getting supplementary information for existing flood-forecasting systems for these river basins. Physical damage to households including residential assets and agricultural damage were estimated quantitatively based on flood features. The estimated value of agricultural and house damage was fairly consistent with reported values. Reliable flood damage data are important for developing flood damage functions and for confirming such estimation. Uncertainties associated with input data, model parameters, and damage information strongly influence the damage estimated. These uncertainties must be considered carefully in flood risk assessment models.

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Torrential and long-lasting rainfall often causes long-duration floods in flat and lowland areas in data-scarce Nyaungdon Area of Myanmar, imposing large threats to local people and their livelihoods. As historical hydrological observations and surveys on the impact of floods are very limited, flood hazard assessment and mapping are still lacked in this region, making it hard to design and implement effective flood protection measures. This study mainly focuses on evaluating the predicative capability of a 2D coupled hydrology-inundation model, namely the Rainfall-Runoff-Inundation (RRI) model, using ground observations and satellite remote sensing, and applying the RRI model to produce a flood hazard map for hazard assessment in Nyaungdon Area. Topography, land cover, and precipitation are used to drive the RRI model to simulate the spatial extent of flooding. Satellite images from Moderate Resolution Imaging Spectroradiometer (MODIS) and the Phased Array type L-band Synthetic Aperture Radar-2 onboard Advanced Land Observing Satellite-2 (ALOS-2 ALOS-2/PALSAR-2) are used to validate the modeled potential inundation areas. Model validation through comparisons with the streamflow observations and satellite inundation images shows that the RRI model can realistically capture the flow processes (R2 ≥ 0.87; NSE ≥ 0.60) and associated inundated areas (success index ≥ 0.66) of the historical extreme events. The resultant flood hazard map clearly highlights the areas with high levels of risks and provides a valuable tool for the design and implementation of future flood control and mitigation measures.

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