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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.

Flow forecast in the Upper Indus catchment in Pakistan is based on average peak flow travel time between key dams and barrages. There was also no flow forecasting system for the Kabul river sub‐basin where most of the 2010 floods victims were reported. A 5‐km spatially distributed tank model using Integrated Flood Analysis System (IFAS) was developed from the Indus upstream reach until the Taunsa barrage. A preliminary model parameterisation, which relied on global data, was updated with newly surveyed soil hydraulic data. The model calibration was performed with Pakistan Meteorological Department (PMD) rain gauge data. Nash‐Sutcliffe efficiencies ENS were calculated for simulated discharges at key gauges. ENS were very low or negative for past flood simulations. One of the reasons for these low efficiencies was the scarcity of local hydro‐meteorological data, including rainfall. Therefore, corrected JAXA satellite‐based rainfall estimates GSMaP‐NRT were considered input data. GSMaP‐NRT self‐correction method coefficients were calibrated for Upper Indus, but the results only improved slightly. However, upstream discharges as boundary conditions resulted in ENS reaching satisfactory averages over 0.7. Simulated hydrographs were then acceptable in terms of peak timing and/or height. Therefore, the conclusion was to recommend relying on upstream discharges as boundary conditions for operational use of the model.

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A high-speed video camera captures bursting phenomena of a bubble at water surface under various surface tension and kinematic viscosity conditions. Surface tension and viscosity of water are changed by adding ethanol which dissolves into water and changes the surface tension, density and kinematic viscosity of water. A technique is proposed in order to separately evaluate effects of viscosity and surface tension on the water particle generation from bubble eruptions by utilizing the peculiar characteristics of the solution