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Nonstationary flood and its influencing factors analysis in the Hanjiang River Basin, China.
- Source :
-
Journal of Hydrology . 2023 Part A, Vol. 625, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- • We used the GAMLSS model to compare the effects of different explanatory variables on the annual maximum runoff. • We compared the simulation differences between the stationary model and the nonstationary model. • We analyzed the effects of single and double explanatory variables on the annual maximum runoff. 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 disrupted. 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 precipitation 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *WATERSHEDS
*NORTH Atlantic oscillation
*FACTOR analysis
*FLOOD control
*RUNOFF
Subjects
Details
- Language :
- English
- ISSN :
- 00221694
- Volume :
- 625
- Database :
- Academic Search Index
- Journal :
- Journal of Hydrology
- Publication Type :
- Academic Journal
- Accession number :
- 172307761
- Full Text :
- https://doi.org/10.1016/j.jhydrol.2023.129994