Bivariate Frequency Analysis of Hydrological Drought Using a Nonstationary Standardized Streamflow Index in the Yangtze River

2019 ◽  
Vol 24 (2) ◽  
pp. 05018031 ◽  
Author(s):  
Ling Kang ◽  
Shangwen Jiang
2020 ◽  
Vol 56 (8) ◽  
Author(s):  
Bin Xiong ◽  
Lihua Xiong ◽  
Shenglian Guo ◽  
Chong‐Yu Xu ◽  
Jun Xia ◽  
...  

2019 ◽  
Vol 79 ◽  
pp. 03022
Author(s):  
Shangwen Jiang ◽  
Ling Kang

Under changing environment, the streamflow series in the Yangtze River have undergone great changes and it has raised widespread concerns. In this study, the annual maximum flow (AMF) series at the Yichang station were used for flood frequency analysis, in which a time varying model was constructed to account for non-stationarity. The generalized extreme value (GEV) distribution was adopted to fit the AMF series, and the Generalized Additive Models for Location, Scale and Shape (GAMLSS) framework was applied for parameter estimation. The non-stationary return period and risk of failure were calculated and compared for flood risk assessment between stationary and non-stationary models. The results demonstrated that the flow regime at the Yichang station has changed over time and a decreasing trend was detected in the AMF series. The design flood peak given a return period decreased in the non-stationary model, and the risk of failure is also smaller given a design life, which indicated a safer flood condition in the future compared with the stationary model. The conclusions in this study may contribute to long-term decision making in the Yangtze River basin under non-stationary conditions.


2021 ◽  
Author(s):  
Yuxiu He ◽  
Qiang Wang ◽  
Youpeng Xu ◽  
Ziyi Li ◽  
Jia Yuan ◽  
...  

Abstract A compound perspective on hydrological extreme events is of paramount significance as it may lead to damages with larger losses. In this study, an integrated framework, based on downscaled climate variables and hydrological model, i.e. the Soil and Water Assessment Tool, was applied to generate extreme precipitation (Rx1day) and extreme streamflow (Sx1day) series under historical and future climate conditions. Then the potential impacts of climate change for univariate and bivariate joint frequency of extreme precipitation and flood in Xitiaoxi River Basin (XRB), a representative watershed of the Yangtze River Delta, is detected. The compound risk of extreme precipitation and flood under different levels of joint return period for historical and projected periods are estimated by copula‐based two-dimensional approaches. Major findings can be summarized: (1) The Rx1day and Sx1day under future scenarios increased by -0.4 ~ 11.7% and 0.7 ~ 20.4%, respectively, compared to historical period based on univariate frequency analysis, indicating the increasing magnitude of the flood in the future. (2) Climate change with different emission scenarios all have a driving effect on the rising coactivity of extreme precipitation and flood under compound flooding frequency analysis. In addition, the enhancement of climate change to extreme events is more apparent for extremes with higher return period and under the periods of 2080s. (3) Moreover, the flood frequency designs are deduced by bivariate joint distribution are safer than that by univariate distribution. This study may provide actionable insights to formulate the planning scheme of flood control and disaster reduction under the changing environment.


2020 ◽  
Vol 11 (S1) ◽  
pp. 164-188 ◽  
Author(s):  
Senna Bouabdelli ◽  
Mohamed Meddi ◽  
Ayoub Zeroual ◽  
Ramdane Alkama

Abstract This study aims to estimate hydrological drought risk using probabilistic analysis of bivariate drought characteristics to assess both past and future drought severity and duration in three basins located in the widest karst massif of northern Algeria. The procedures entail: (1) identification of extent of meteorological drought that could trigger corresponding hydrological drought through their characteristics; (2) assessment of future risk of extreme drought according to two emission scenarios of the representative concentration pathway (RCP 4.5 and 8.5); and (3) estimation of drought return periods using bivariate frequency analysis and investigation of their future change rates under climate change. Hydrological droughts were computed by using the bias-corrected future climate projections from nine global climate models downscaled using the Rossby Centre Regional Climate model (RCA4), and GR2M hydrological model. The analysis revealed a connection between meteorological and hydrological drought occurrences and the response time depended on the memory effect of the considered basin. We also found strong consensus between past drought event return periods, determined by bivariate frequency analysis, and those determined by climate models under RCP8.5 scenario. Finally, in regards to drought return periods (10, 50 and 100 years), the risk of extreme drought recurrence in the future has been projected to be larger than the reference period.


2018 ◽  
Vol 637-638 ◽  
pp. 1432-1442 ◽  
Author(s):  
Dan Zhang ◽  
Qi Zhang ◽  
Jiaming Qiu ◽  
Peng Bai ◽  
Kang Liang ◽  
...  

2004 ◽  
Vol 88 (8) ◽  
pp. 59-64
Author(s):  
Changyu Shao ◽  
Qinger Deng

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