This study proposes a data assimilation method for a distributed rainfall-runoff prediction system. The system is composed by a rainfall-runoff model and a river routing model. Since it is computationally inefficient for updating all the model variables on the real-time basis, the proposed filtering method takes river discharges, which are simulated by Muskingum-Cunge method, as the state variables. It also sequentially estimates and collects prediction biases induced by the rainfall-runoff model. The application to the Katsura river basin shows that the filtering with bias estimation and correction improves the accuracy of flood predictions.

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In this study, using the inside water inundation model (NILIM), we performed reappear calculation of Typhoon No.11 of 1993 which did serious damage along the Kanda River basin in Tokyo. In the inner water prediction by probability of exceedence rainfall, inundation area was mostly checked with the inundation hazard map released in this position. However, a case of the heavy rain exceeding 100mm/hr, it was found that an inundated area and danger spot increase at many points. Moreover, we cleared that inundation area reduce best when is a case of expanding pipeline by about 1.5 times on the study drainage area, as a result of a reduction measures on the water disaster.

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Three-dimensional unsteady flow with localized areas with large vortices in the intake channel of a small-scale hydroelectric power station has been simulated numerically using a Large-Eddy Simulation (LES) technique. The method computes the motion of the free surface. A Smagorinsky model with wall damping is used as the turbulence model. With the total number of grid points of about six hundred thousand, the complex and unsteady nature of the vortical flow can be reproduced very well by marginally resolving the near-wall flow. Intake vortices of strong intensity with its dynamic characteristics of the free surface indentations associated with air entrainment can be captured and the flow conditions associated with appearance of vortices can be examined based on the results of the present simulation.

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Soil solarization (Solar heating of soil) is being watched as a nonchemical farmland disinfection method. In order to improve this method to an environmentally sound technology, field trials were conducted in the plastic greenhouse of the Wakayama Agricultural Experiment Station. In addition, numerical simulations using the field trial results were also conducted. The target depth to integrate the disinfecting time is 30 cm and the required time to complete soil solarization is 100 hours in the site. The results showed that the diurnal variation of soil surface temperature and the initial soil temperature greatly influence the soil temperature change in the targeted depth and the required time to complete soil solarization. Moreover, the results of the numerical simulations revealed that the proper diurnal variation of soil surface temperature to effectively conduct soil solarization was 33°C to 63°C or more.

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The characteristics of shoreline change, offshore wave energy flux and longshore current velocity were investigated with a 15-year data set. Also, the frequency components lower than 0.001 Hz of them were reconstructed, and the relationships between shoreline change rate, wave energy flux and longshore current velocity were considered. The shoreline change rate has correlations with the wave energy flux and the longshore current velocity. Moreover, the comparisons of the wave energy flux and the longshore current velocity suggested that the shoreline change rate was influenced by both the wave energy flux and the longshore current velocity.

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