Design and evaluation of methodology for nonstationary precipitation frequency analysis in the Northeastern United States

Abstract

Observed data show an increase in the intensity and frequency of heavy precipitation events in various parts of the United States and other geographic regions worldwide, and projected climate data suggest these trends are likely to continue. Consequently, the conventional belief in the stationarity of precipitation time series and the traditional statistical frequency methodologies are now outdated. The nonstationary nature of heavy precipitation data necessitates the development of new approaches for frequency analysis to better represent the present day and projected precipitation frequency. This paper describes a framework to translate future climate scenarios into the nonstationary precipitation frequency estimates needed for hydrologists, developers, water managers, environmental planners, and other professionals. Two main approaches were designed to estimate time-varying precipitation frequency depths for multiple future time horizons up to 2075 based on the climate model runs from 1960 to 2100. One approach involves dividing the time period into sub-periods, treating each sub-period as stationary. This piecewise stationary method is referred to as the quasi-stationary (QS) approach. The second approach, referred to as the nonstationary (NS) approach, expresses precipitation frequency distribution statistics as a function of annual precipitation, time, or other covariates. These approaches were applied to the Northeastern United States for different data sources (LOCA vs. UWPD), types of data (AMS vs. PDS), and scenarios (RCP4.5 vs. RCP8.5). The study findings highlight the distinctive variations between different approaches and assumptions. A sensitivity analysis was conducted to identify critical decision points and assumptions in the modeling process. These results aim to assist researchers and practitioners in making informed choices for future nonstationary precipitation frequency studies. Keywords precipitation frequency, nonstationary precipitation data, climate change

Graphical abstract

References

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