水文統計解析における確率分布モデルの評価

Abstract

The anthors emphasizes the necessity for considering the variability of the estimate ofT-year event in hydrologic frequency analysis and proposes a framework for evaluatingprobability distribution models. The variability (or estimation error) of T-year event is usedas a criterion for model evaluation as well as three goodness-of-fit criteria (SLSC, MLL, and AIC) in the framework. The jackknife and the bootstrap methods play important rolesin estimating the variability. For the annual maxima of k-day precipitation (k=1, 2, 3) inthe Lake Biwa basin, the Gumbel distribution is regarded as the best among five distributionmodels with two parameters; for the daily precipitation at Osaka, the SQRT-exponential-typedistribution of maximum is the best among ten distributions with two or three parameters.The bootstrap method also reveals the relationship between the amount of data and theestimation error of T-year event.