Flood frequency analysis with consideration of hydrological alterations: Changing properties, causes and implications

Summary Under coupled influences of human activities and climate change, hydrological alterations are unavoidable and should be addressed in the evaluation of flood risk. In this study, the flood risk in the Pearl River basin, one of the economically developed regions in China, is investigated, based on long term annual maximum series (AMS) from 28 hydrological stations. Results indicate the following: (1) significant hydrological alterations have been identified and alterations of precipitation extreme regimes are one of the pivotal factors triggering hydrological alterations of AMS, as abrupt changes of precipitation extremes occur is similar to that of the AMS in time and space. In the East River basin, however, massive human withdrawal of freshwater, a number of water reservoirs and other hydraulic facilities combine to reduce the flood risk. (2) High flood risk can be found in the upper and middle West River basin and the North River basin with an increasing magnitude of 0–40% and 10–30%, respectively. Besides, frequencies of flood events with return periods of longer than 20 years are found to be significantly decreasing. In the East River basin, however, the frequency of floods with a return period of 20 years is increasing, but the flood volume is greatly decreasing. (3) Higher flood risk due to alterations of hydrological extremes will pose a threat to the existing hydraulic facilities. Furthermore, the higher flood risk in the West River and North River basins will potentially threaten the Pearl River Delta, a densely populated region with highly developed socio-economy. The results of this study will thus be of great value in developing measures for resilience to natural hazards in high development economic and coastal regions.

[1]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[2]  Liao Jing.  Comparison and Analysis on the Performance of Hydrological Time Series Change-point Testing Methods , 2007 .

[3]  Vijay P. Singh,et al.  Analysis of the periods of maximum consecutive wet days in China , 2011 .

[4]  P. Bates,et al.  Flood frequency analysis for nonstationary annual peak records in an urban drainage basin , 2009 .

[5]  R. Stouffer,et al.  Stationarity Is Dead: Whither Water Management? , 2008, Science.

[6]  P. Sen.  Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[7]  I. Mares,et al.  Extreme value analysis in the Danube lower basin discharge time series in the twentieth century , 2009 .

[8]  J. Hosking.  L‐Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics , 1990 .

[9]  Chong-yu Xu,et al.  Abrupt behaviors of the streamflow of the Pearl River basin and implications for hydrological alterations across the Pearl River Delta, China , 2009 .

[10]  Shaofeng Yan,et al.  Evaluating the non-stationary relationship between precipitation and streamflow in nine major basins of China during the past 50 years , 2011 .

[11]  Ian Brodie,et al.  Rational Monte Carlo method for flood frequency analysis in urban catchments , 2013 .

[12]  F. Massey.  The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .

[13]  J. R. Wallis,et al.  Robustness of the rescaled range R/S in the measurement of noncyclic long run statistical dependence , 1969 .

[14]  Franklin B. Schwing,et al.  Coherency detection of multiscale abrupt changes in historic Nile flood levels , 2002 .

[15]  H. Levene.  Robust tests for equality of variances , 1961 .

[16]  P. Bridge,et al.  Increasing physicians' awareness of the impact of statistics on research outcomes: comparative power of the t-test and and Wilcoxon Rank-Sum test in small samples applied research. , 1999, Journal of clinical epidemiology.

[17]  Donald H. Burn,et al.  Non-stationary pooled flood frequency analysis , 2003 .

[18]  V. Singh,et al.  Spatial–temporal changes of precipitation structure across the Pearl River basin, China , 2012 .

[19]  Chong-yu Xu,et al.  Trends and abrupt changes of precipitation maxima in the Pearl River basin, China , 2009 .

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

[21]  C. A. McGilchrist,et al.  Note on a Distribution-free CUSUM Technique , 1975 .

[22]  Jianfeng Li,et al.  Copula-Based Analysis of Hydrological Extremes and Implications of Hydrological Behaviors in the Pearl River Basin, China , 2011 .

[23]  V. Singh,et al.  Non-stationary approach to at-site flood frequency modelling I. Maximum likelihood estimation , 2001 .

[24]  C. Peng,et al.  Effects of future climate change, CO2 enrichment, and vegetation structure variation on hydrological processes in China , 2012 .

[25]  S. Becker,et al.  Precipitation, temperature and runoff analysis from 1950 to 2002 in the Yangtze basin, China / Analyse des précipitations, températures et débits de 1950 à 2002 dans le bassin du Yangtze, en Chine , 2005 .

[26]  Qiang Zhang,et al.  Changing properties of hydrological extremes in south China: natural variations or human influences? , 2010 .

[27]  Morton B. Brown,et al.  Robust Tests for the Equality of Variances , 1974 .

[28]  M. Kendall,et al.  Rank Correlation Methods , 1949 .

[29]  Xinjun Tu,et al.  Spatio-temporal patterns of hydrological processes and their responses to human activities in the Poyang Lake basin, China , 2011 .

[30]  Chong-yu Xu,et al.  Changes of atmospheric water vapor budget in the Pearl River basin and possible implications for hydrological cycle , 2010 .

[31]  F. Gasse,et al.  Hydrological response of a catchment to climate and land use changes in Tropical Africa: case study South Central Ethiopia , 2003 .

[32]  G. N. Wijesekara,et al.  Assessing the impact of future land-use changes on hydrological processes in the Elbow River watershed in southern Alberta, Canada , 2012 .