Beyond Simple Trend Tests: Detecting Significant Changes in Design‐Flood Quantiles

Changes in annual maximum flood (AMF), which are usually detected using simple trend tests (e.g., Mann‐Kendall test (MKT)), are expected to change design‐flood estimates. We propose an alternate framework to detect significant changes in design‐flood between two periods and evaluate it for synthetically generated AMF from the Log‐Pearson Type‐3 (LP3) distribution due to changes in moments associated with flood distribution. Synthetic experiments show MKT does not consider changes in all three moments of the LP3 distribution and incorrectly detects changes in design‐flood. We applied the framework on 31 river basins spread across the United States. Statistically significant changes in design‐flood quantiles were observed even without a significant trend in AMF and basins with statistically significant trend did not necessarily exhibit statistically significant changes in design‐flood. We recommend application of the framework for evaluating changes in design‐flood estimates considering changes in all the moments as opposed to simple trend tests.

[1]  Guo Yu,et al.  Diverse Physical Processes Drive Upper‐Tail Flood Quantiles in the US Mountain West , 2022, Geophysical Research Letters.

[2]  J. Hecht,et al.  Simulation experiments comparing nonstationary design-flood adjustments based on observed annual peak flows in the conterminous United States , 2021, Journal of Hydrology X.

[3]  S. Archfield,et al.  Projecting Flood Frequency Curves Under Near‐Term Climate Change , 2021, Water Resources Research.

[4]  Veber Costa,et al.  Bayesian Approach for Estimating the Distribution of Annual Maximum Floods with a Mixture Model , 2021 .

[5]  G. Villarini,et al.  Global Changes in 20‐Year, 50‐Year, and 100‐Year River Floods , 2021, Geophysical Research Letters.

[6]  Jiali Guo,et al.  Streamflow Variations in Monthly, Seasonal, Annual and Extreme Values Using Mann-Kendall, Spearmen’s Rho and Innovative Trend Analysis , 2020, Water Resources Management.

[7]  S. Arumugam,et al.  Changing Seasonality of Annual Maximum Floods over the Conterminous US , 2020, Journal of Hydrologic Engineering.

[8]  R. Vogel,et al.  HESS Opinions: Beyond the long-term water balance: evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds , 2020, Hydrology and Earth System Sciences.

[9]  K. Ryberg,et al.  Change points in annual peak streamflows: Method comparisons and historical change points in the United States , 2020 .

[10]  P. Ferraro,et al.  Causal Effect of Impervious Cover on Annual Flood Magnitude for the United States , 2020, Geophysical Research Letters.

[11]  R. Vogel,et al.  Updating urban design floods for changes in central tendency and variability using regression , 2020 .

[12]  Sungwook Wi,et al.  Design considerations for riverine floods in a changing climate – A review , 2019, Journal of Hydrology.

[13]  S. Archfield,et al.  Effects of climate, regulation, and urbanization on historical flood trends in the United States , 2019, Journal of Hydrology.

[14]  J. Salas,et al.  Techniques for assessing water infrastructure for nonstationary extreme events: a review , 2018 .

[15]  Richard M. Vogel,et al.  Parsimonious nonstationary flood frequency analysis , 2018 .

[16]  C. Deser,et al.  Precipitation variability increases in a warmer climate , 2017, Scientific Reports.

[17]  Gabriele Villarini,et al.  Recent trends in U.S. flood risk , 2016 .

[18]  C. Spence,et al.  Nonstationary decision model for flood risk decision scaling , 2016 .

[19]  R. Hirsch,et al.  Fragmented patterns of flood change across the United States , 2016, Geophysical research letters.

[20]  G. Villarini,et al.  Mixed populations and annual flood frequency estimates in the western United States: The role of atmospheric rivers , 2015 .

[21]  A. Sankarasubramanian,et al.  Monthly Climate Data for Selected USGS HCDN Sites, 1951-1990, R1 , 2015 .

[22]  Laura Read,et al.  Reliability, return periods, and risk under nonstationarity , 2015 .

[23]  J. Corte-Real,et al.  Rainfall and river flow trends using Mann–Kendall and Sen’s slope estimator statistical tests in the Cobres River basin , 2015, Natural Hazards.

[24]  R. Katz,et al.  Non-stationary extreme value analysis in a changing climate , 2014, Climatic Change.

[25]  Laura E. Condon,et al.  Climate change and non-stationary flood risk for the upper Truckee River basin , 2014 .

[26]  J. Salas,et al.  Revisiting the Concepts of Return Period and Risk for Nonstationary Hydrologic Extreme Events , 2014 .

[27]  Robert M. Hirsch,et al.  Has the magnitude of floods across the USA changed with global CO2 levels? , 2012 .

[28]  A. Sankarasubramanian,et al.  Interannual hydroclimatic variability and its influence on winter nutrient loadings over the Southeast United States , 2011 .

[29]  Richard M. Vogel,et al.  Nonstationarity: Flood Magnification and Recurrence Reduction Factors in the United States 1 , 2011 .

[30]  J. R. Stedinger,et al.  Log-Pearson Type 3 Distribution and Its Application in Flood Frequency Analysis. I: Distribution Characteristics , 2007 .

[31]  Marc Lavielle,et al.  Using penalized contrasts for the change-point problem , 2005, Signal Process..

[32]  Richard M. Vogel,et al.  Trends in floods and low flows in the United States: impact of spatial correlation , 2000 .

[33]  Hans von Storch,et al.  Monte Carlo experiments on the effect of serial correlation on the Mann-Kendall test of trend , 1992 .

[34]  P. Phillips,et al.  Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? , 1992 .

[35]  R. Hirsch,et al.  A Nonparametric Trend Test for Seasonal Data With Serial Dependence , 1984 .

[36]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[37]  A. Pettitt A Non‐Parametric Approach to the Change‐Point Problem , 1979 .

[38]  H. B. Mann Nonparametric Tests Against Trend , 1945 .

[39]  J. Stedinger,et al.  Guidelines for determining flood flow frequency—Bulletin 17C , 2019, Techniques and Methods.

[40]  F. Serinaldi,et al.  Untenable nonstationarity: An assessment of the fi tness for purpose of trend tests in hydrology , 2017 .

[41]  J. K. Vrijling,et al.  TREND AND STATIONARITY ANALYSIS FOR STAREAMFLOW PROCESSES OF RIVERS IN WESTERN EUROPE IN THE 20TH CENTURY , 2005 .