Abstract
Nonstationarity in hydrological variables has been identified throughout Japan in recent years. As a result, the reliability of designs derived from using method based on the assumption of stationary might deteriorate. Non-stationary hydrological frequency analysis is among the measures to counter this possibility. Using this method, time variations in the probable hydrological quantity can be estimated using a non-stationary extreme value distribution model with time as an explanatory variable. In this study, we build a new method for constructing the confidence interval regarding the non-stationary extreme value distribution by applying a theory of probability limit method test. Furthermore, by introducing a confidence interval based on probability limit method test into the non-stationary hydrological frequency analysis, uncertainty in design rainfall because of lack of observation information was quantified, and it is shown that assessment pertaining to both the occurrence risk of extremely heavy rainfall and changes in the trend of extreme rainfall accompanied with climate change is possible.
Highlights
Introduction of Confidence Interval Based onProbability Limit Method Test into Non-StationaryHydrological Frequency AnalysisKeita Shimizu 1, *, Tadashi Yamada 2 and Tomohito J
As shown in the previous chapter, applying an analytical method for non-stationary hydrological frequency, the probability distribution of the extreme hydrological quantity can be estimated with time as an explanatory variable
In recent years, increasing unsteadiness in the rainfall associated with climate change has become apparent; this is expected to continue in the future
Summary
Introduction of Confidence Interval Based onProbability Limit Method Test into Non-StationaryHydrological Frequency AnalysisKeita Shimizu 1, *, Tadashi Yamada 2 and Tomohito J. By introducing a confidence interval based on probability limit method test into the non-stationary hydrological frequency analysis, uncertainty in design rainfall because of lack of observation information was quantified, and it is shown that assessment pertaining to both the occurrence risk of extremely heavy rainfall and changes in the trend of extreme rainfall accompanied with climate change is possible. In recent years, increasingly non-stationary hydrological quantity has been identified, ascribed to the effects of climate change associated with global warming [2,3,4,5] In this context, this unsteadiness implies either that the time series of hydrological quantity has both a trend and cycle, or that the probability distribution followed by hydrological quantity changes temporally. A report highlighting such predictions was published by the National
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