Hydrological control of dissolved organic carbon dynamics in a forested headwater catchment,Kiryu Experimental Watershed,Japan

To evaluate the influence of hydrological processes on dissolved organic carbon (DOC) dynamics in a forested headwater catchment, DOC concentration was observed along the flow path from rainfall to stream water via throughfall, soil water, groundwater, and spring water for 4 years, and DOC flux through the catchment was calculated. The spatial and temporal variations in DOC concentration and flux were compared with physical hydrological observations and the mean residence time of water. In the upslope soil layer, DOC concentrations were not significantly correlated with water fluxes, suggesting that DOC concentrations were not strictly controlled by water fluxes. In the upslope perennial groundwater, DOC concentration was affected by the change in the amount of microbial degradation of DOC produced by changes in the mean residence time of water. In stream water, the temporal variation in DOC concentration was usually affected by changes in DOC concentration of the inflow component via vertical infiltration from above the perennial groundwater. During dry periods, however, the component from inflow via vertical infiltration was negligible and DOC in the upslope perennial groundwater became the major component of stream water DOC. The temporal variation in stream water DOC concentration during baseflow was affected by rainfall patterns over several preceding months. Therefore, records of rainfall over several preceding months are one of the most important factors for predicting changes in DOC concentration on a catchment scale. Copyright © 2007 John Wiley & Sons, Ltd.     

A weakly non-gaussian model of wave height distribution for random wave train

The wave height distribution with Edgeworth’s form of a cumulative expansion of probability density function (PDF) of surface elevation are investigated. The results show that a non-Gaussian model of wave height distribution reasonably agrees with experimental data. It is discussed that the fourth order moment (kurtosis) of water surface elevation corresponds to the first order nonlinear correction of wave heights and is related with wave grouping.     

Swells of the East China Sea

Over the past few decades, an increasing number of marine activities have been conducted in the East China Sea, including the construction of various marine structures and the passage of large ships. Marine safety issues are paramount and are becoming more important with respect to the likely increase in size of ocean waves in relation to global climate change and associated typhoons. In addition, swells also can be very dangerous because they induce the resonance of floating structures, including ships. This study focuses on an investigation of swells in the East China Sea and uses hindcast data for waves over the past 5 years in a numerical model, WAVEWATCH III (WW3), together with historical climate data. The numerical calculation domain covers the entire North West Pacific. Next, swells are separated and analyzed using simulated wave fields, and both the characteristics and generation mechanisms of swells are investigated.     

Bayesian tsunami fragility modeling considering input data uncertainty

Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data in fragility modeling) is quantified by comparing two tsunami inundation/run-up datasets (one by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government and the other by the Tohoku Tsunami Joint Survey group) and is then propagated through Bayesian statistical methods to assess the effects on the tsunami fragility models. The systematic implementation of the data and methods facilitates the quantitative comparison of tsunami fragility models under different assumptions. Such comparison shows that the binomial logistic method with un-binned data is preferred among the considered models; nevertheless, further investigations related to multinomial logistic regression with un-binned data are required. Finally, the developed tsunami fragility functions are integrated with building damage-loss models to investigate the influences of different tsunami fragility curves on tsunami loss estimation. Numerical results indicate that the uncertainty of input tsunami data is not negligible (coefficient of variation of 0.25) and that neglecting the input data uncertainty leads to overestimation of the model uncertainty.