Nonstationary flood and its influencing factors analysis in the Hanjiang River Basin, China

被引:8
作者
Jin, Haoyu [1 ,2 ,3 ,4 ]
Willems, Patrick [4 ]
Chen, Xiaohong [1 ,2 ,3 ]
Liu, Moyang [5 ]
机构
[1] Sun Yat Sen Univ, Sch Civil Engn, Guangzhou 510275, Peoples R China
[2] Sun Yat Sen Univ, Guangdong Engn Technol Res Ctr Water Secur Regulat, Guangzhou 510275, Peoples R China
[3] Sun Yat Sen Univ, Guangdong High Educ Inst, Key Lab Water Cycle & Water Secur Southern China, Guangzhou 510275, Peoples R China
[4] Katholieke Univ Leuven, Dept Civil Engn, Hydraul & Geotech Sect, Leuven, Belgium
[5] Australian Natl Univ ANU, Fenner Sch Environm & Soc, Canberra, ACT 0200, Australia
基金
中国国家自然科学基金;
关键词
Catchment runoff; Floods; Nonstationary behavior; GAMLSS; Hanjiang River Basin; China; FREQUENCY-ANALYSIS; CLIMATE; MODELS; SCALE;
D O I
10.1016/j.jhydrol.2023.129994
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Due to the impact of climate change and human activities, flood disasters have occurred frequently in the Hanjiang River Basin (HRB) in recent years, and the stationary behavior of its flood fluctuation has been dis-rupted. In this study, we used Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to analyze the nonstationary changes of annual maximum runoff in the HRB and its influencing factors. It has also been complemented with a stationary model for comparative analysis. We found that the annual maximum runoff has a significant decreasing trend. The top four factors influencing this runoff change are the local changes in pre-cipitation and temperature, and the regional climate oscillations as reflected by the North Atlantic Oscillation index (NAO) and the Pacific North American Index (PNA). The nonstationary model had better simulation effect than the stationary model. The stationary model could not reflect the impact of explanatory variables on annual maximum runoff, while the nonstationary model could well analyze the impact of single and dual explanatory variables. The results of this study provide some new insights in support of flood prevention and control in the HRB.
引用
收藏
页数:19
相关论文
共 45 条
[1]   Investigation of Nonstationary Association of Monsoon Temperature and Precipitation Extremes Through Past and Future over East-Central India (vol 180, pg 1143, 2023) [J].
Biswas, Jit ;
Bhattacharya, Soma .
PURE AND APPLIED GEOPHYSICS, 2023, 180 (06) :2483-2483
[2]   Linear, nonlinear, parametric and nonparametric regression models for nonstationary flood frequency analysis [J].
Chen, Mengzhu ;
Papadikis, Konstantinos ;
Jun, Changhyun ;
Macdonald, Neil .
JOURNAL OF HYDROLOGY, 2023, 616
[3]   An investigation on the non-stationarity of flood frequency across the UK [J].
Chen, Mengzhu ;
Papadikis, Konstantinos ;
Jun, Changhyun .
JOURNAL OF HYDROLOGY, 2021, 597
[4]   Does high risk mean high loss: Evidence from flood disaster in southern China [J].
Chen, Yangyang ;
Li, Jimei ;
Chen, An .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 785
[5]   Pattern of spatio-temporal variability of extreme precipitation and flood-waterlogging process in Hanjiang River basin [J].
Deng, Pengxin ;
Zhang, Mingyue ;
Hu, Qingfang ;
Wang, Leizhi ;
Bing, Jianping .
ATMOSPHERIC RESEARCH, 2022, 276
[6]   Nonstationary flood coincidence risk analysis using time-varying copula functions [J].
Feng, Ying ;
Shi, Peng ;
Qu, Simin ;
Mou, Shiyu ;
Chen, Chen ;
Dong, Fengcheng .
SCIENTIFIC REPORTS, 2020, 10 (01)
[7]   Analysis of the nonstationarity characteristics and future trends of flood extremes in the Dongting Lake Basin [J].
Gao, Yunpeng ;
Xia, Jun ;
Chen, Xingwei ;
Zou, Lei ;
Huang, Jie ;
Yu, Jiarui .
JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 2022, 44
[8]   Nonstationarity in the occurrence rate of floods in the Tarim River basin, China, and related impacts of climate indices [J].
Gu, Xihui ;
Zhang, Qiang ;
Singh, Vijay P. ;
Chen, Xi ;
Liu, Lin .
GLOBAL AND PLANETARY CHANGE, 2016, 142 :1-13
[9]   Study on spatiotemporal distribution characteristics of flood and drought disaster impacts on agriculture in China [J].
Guan, Xinjian ;
Zang, Yawen ;
Meng, Yu ;
Liu, Yuan ;
Lv, Hong ;
Yan, Denghua .
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2021, 64
[10]   An assessment method of annual climatic status in China using extreme climate indices: 2021 as an example [J].
Guo, Zeng-Yuan ;
Chen, Li-Juan ;
Xie, Bing .
ADVANCES IN CLIMATE CHANGE RESEARCH, 2022, 13 (06) :868-874