Statistical Analysis of Extreme Events in Precipitation, Stream Discharge, and Groundwater Head Fluctuation: Distribution, Memory, and Correlation

Dawley, Shawn1; Zhang, Yong1; Liu, Xiaoting2; Jiang, Peng3; Tick, Geoffrey R.1; Sun, HongGuang3; Zheng, Chunmiao4; Chen, Li5

2019-04

10.3390/w11040707

Water   影响因子和分区

2073-4441

Hydrological extremes in the water cycle can significantly affect surface water engineering design, and represents the high-impact response of surface water and groundwater systems to climate change. Statistical analysis of these extreme events provides a convenient way to interpret the nature of, and interaction between, components of the water cycle. This study applies three probability density functions (PDFs), Gumbel, stable, and stretched Gaussian distributions, to capture the distribution of extremes and the full-time series of storm properties (storm duration, intensity, total precipitation, and inter-storm period), stream discharge, lake stage, and groundwater head values observed in the Lake Tuscaloosa watershed, Alabama, USA. To quantify the potentially non-stationary statistics of hydrological extremes, the time-scale local Hurst exponent (TSLHE) was also calculated for the time series data recording both the surface and subsurface hydrological processes. First, results showed that storm duration was most closely related to groundwater recharge compared to the other storm properties, while intensity also had a close relationship with recharge. These relationships were likely due to the effects of oversaturation and overland flow in extreme total precipitation storms. Second, the surface water and groundwater series were persistent according to the TSLHE values, because they were relatively slow evolving systems, while storm properties were anti-persistent since they were rapidly evolving in time. Third, the stretched Gaussian distribution was the most effective PDF to capture the distribution of surface and subsurface hydrological extremes, since this distribution can capture the broad transition from a Gaussian distribution to a power-law one.

statistical analysis hydrological extremes stretched Gaussian distribution Hurst exponent

SCI ; EI

英语

其他

National Natural Science Foundation of China[41330632] ; National Natural Science Foundation of China[41628202] ; National Natural Science Foundation of China[11572112]

Water Resources

Water Resources

WOS:000473105700077

MDPI

20191906871185

Climate change ; Groundwater ; Lakes ; Probability density function ; Statistical methods ; Storms ; Time series

Atmospheric Properties:443.1 ; Precipitation:443.3 ; Groundwater:444.2 ; Probability Theory:922.1 ; Mathematical Statistics:922.2

Web of Science

1.Univ Alabama, Dept Geol Sci, Tuscaloosa, AL 35487 USA
2.Hohai Univ, Coll Mech & Mat, Nanjing 210098, Jiangsu, Peoples R China
3.Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Jiangsu, Peoples R China
4.Southern Univ Sci & Technol, Guangdong Prov Key Lab Soil & Groundwater Pollut, Sch Environm Sci & Engn, Shenzhen 518055, Guangdong, Peoples R China
5.Desert Res Inst, Div Hydrol Sci, Las Vegas, NV 89119 USA

Dawley, Shawn,Zhang, Yong,Liu, Xiaoting,et al. Statistical Analysis of Extreme Events in Precipitation, Stream Discharge, and Groundwater Head Fluctuation: Distribution, Memory, and Correlation[J]. Water,2019,11(4).

Dawley, Shawn.,Zhang, Yong.,Liu, Xiaoting.,Jiang, Peng.,Tick, Geoffrey R..,...&Chen, Li.(2019).Statistical Analysis of Extreme Events in Precipitation, Stream Discharge, and Groundwater Head Fluctuation: Distribution, Memory, and Correlation.Water,11(4).

Dawley, Shawn,et al."Statistical Analysis of Extreme Events in Precipitation, Stream Discharge, and Groundwater Head Fluctuation: Distribution, Memory, and Correlation".Water 11.4(2019).