A Statistical Hydrological Model for Yangtze River Watershed Based on Stepwise Cluster Analysis

Wang, Feng; Huang, Guohe; Li, Yongping; Xu, Jinliang; Wang, Guoqing; Zhang, Jianyun; Duan, Ruixin; Ren, Jiayan

doi:10.3389/feart.2021.742331

Cited by 6 publications

(7 citation statements)

References 43 publications

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“…YRB is one of the most climate sensitive areas in East Asian, and experiences large year-to-year variability in its summer precipitation during June to July (Li and Lu 2017, Wang et al, 2021a, 2021b. To characterize the persistent heavy precipitation events, the observed daily precipitation of 166 stations (as shown in Figure 1(a)) during 1960 to 2020 are obtained from the National Meteorological Data Center (http:// data.cma.cn).…”

Section: Methodsmentioning

confidence: 99%

Collided with COVID-19 Pandemic, the 2020 Yangtze Flood Is Exceptionally Severe

Wang¹,

Huang²,

Fan³

2022

J ENVIRON INFORM LET

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During June to July, 2020, persistent heavy precipitation in the Yangtze River Basin (YRB) is resulting in extensive flooding, with over 158 fatalities and tremendous economic losses. This year’s disastrous flooding extreme is exceptionally different from those of other years. It contains over 1000-year return period events (for 30-day cumulative precipitation) as observed in Anhui, Guizhou and Sichuan Provinces. The mean precipitation is 308 mm in July 2020, being 54 mm higher than that of July 1998, when serious floods affected the entire Basin causing tremendous socio-economic consequences. Compared with 1998, the short-term (e.g., 1 day) precipitation in YRB did not show significant increases, while the long-term (e.g., 30 days) cumulative precipitation increases significantly. The highest observed 30-day cumulative precipitation is 1221 mm (in Anhui Province) in 2020, while the highest one in 1998 was 1028 mm (in Jiangxi Province). We thus find that this persistent heavy precipitation is the main cause of flooding in 2020. At the same time, TGR may mitigate up 43% of upstream flood, although the main contributors to this year’s YRB flood are in the middle and lower reaches. Affected by COVID-19, the number of people at risk in the threatened area are increased, and their capacities to mitigate the dual impacts of COVID-19 pandemic and flooding are hindered since (a) the flooding-caused mitigations may limit people’s ability to prevent from virus spreading, and (b) the pandemic is retaining a large amount of migrant workers being within YRB and subject to flooding impacts. Overall, our main discovery is that, although the short-term precipitation in YRB did not increase significantly in 2020, the cumulative one increased significantly in 2020.

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Section: Methodsmentioning

confidence: 99%

Collided with COVID-19 Pandemic, the 2020 Yangtze Flood Is Exceptionally Severe

Wang¹,

Huang²,

Fan³

2022

J ENVIRON INFORM LET

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“…The IHAs and the alteration of hydrologic regime at Yichang hydrolog- presents a dynamic relationship with precipitation in timing and magnitude (Wang et al, 2021). The hydrological alteration caused by upstream cascade reservoirs would concentrate more on the magnitude rather than timing of extreme since the outflow is directly As shown in Figure 5a, April monthly flow resembles approximately "two-step ladder" in shape, whose average is respectively 6600, 7050, 10,200, and 8800 m 3 /s in 1949-2002, 2003-2011, 2012-2022, and 2003-2022 Morphologically, the JPDDA method would apply the copula function to tightly link IHAs and the reference variable, rather than discrete product correction like HYT-RVA and RRVA methods in Equations ( 15) and ( 16).…”

Section: Alteration Of Hydrologic Regimementioning

confidence: 99%

A novel Joint Probability Density Difference Approach for assessing the alteration of hydrologic regime

Zhong,

Guo,

Wang

et al. 2024

River Research & Apps

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The construction and operation of upstream reservoirs have significantly altered downstream hydrologic regime. Appropriate and quantifiable assessment method for the alteration of hydrologic regime is considerably vital and emergent for ecological protection and restoration. The Range of Variability Approach (RVA) and modified RVA methods have been widely used in practice to assess the hydrological alteration. However, these methods have failed to concurrently describe the distribution of indicator and morphological features in detail, which might inevitably lead to the misjudgment of alteration. This paper proposes a Joint Probability Density Difference Approach (JPDDA) method to address the major drawbacks of these previous methods with the introduction of Gaussian Kernel Density Estimation (KDE) and copula function. The annual average flow is selected as the reference variable to construct a proper joint probability density function between itself and other hydrological alteration indicators. The JPDDA method could describe the marginal distribution in detail through Gaussian KDE and also link the morphological features with copula function. Along with pervious methods, the hydrological alterations at Yichang hydrological station, Yangtze River are estimated based on the measured flow from 1949 to 2022. It is shown that the hydrologic regime has suffered from a moderate or even heavy alteration under the influence of massive upstream cascade reservoirs, and the JPDDA outperforms the other methods in terms of rationality and stability for practical assessments. Thus, the proposed JPDDA method is strongly advised to handle the hydrological alteration and could provide a reasonable reference for ecological operation.

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“…The framework of the developed approach is presented in Figure 1. SCA was introduced by Huang (1992) and has been widely used in pieces of environmental research, such as climate change, air pollution, process control, and hydrology prediction (Huang et al, 2006;Wang X. Q. et al, 2013;Li et al, 2015;Wang and Huang, 2015;Fan et al, 2016;Zhuang et al, 2016;Sun et al, 2019;Zhai et al, 2019;Duan et al, 2020;Ren et al, 2021b;Wang et al, 2021). These studies have indicated the SCA has satisfactory performance in projecting environmental processes with complex non-linear and dynamic relationships.…”

Section: Stepwise-clustered Simulation Approach For Projecting Future Heat Wavesmentioning

confidence: 99%

“…However, the underlying complex relationships (including non-linear and discrete relationships) between dependent and independent variables can be revealed by the generated cluster tree without assuming the functional relationship compared to these downscaling methods (Wang X. Q. et al, 2013;Zhuang et al, 2016;Duan et al, 2020). Handling the complicated relationship among multiple dependent and independent variables at the same time is another significant advantage of SCA (Fan et al, 2015;Wang et al, 2021). In addition, heat wave, as one of the extreme climate events, the projection of which is also challenging due to the inherently complex relationship between predictors (i.e., large-scale coarse atmospheric variables) and predictands (i.e., local surface variables).…”

Section: Stepwise-clustered Simulation Approach For Projecting Future Heat Wavesmentioning

confidence: 99%

A Stepwise-Clustered Simulation Approach for Projecting Future Heat Wave Over Guangdong Province

Ren

Huang

et al. 2021

Front. Ecol. Evol.

Self Cite

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A heat wave is an important meteorological extreme event related to global warming, but little is known about the characteristics of future heat waves in Guangdong. Therefore, a stepwise-clustered simulation approach driven by multiple global climate models (i.e., GCMs) is developed for projecting future heat waves over Guangdong under two representative concentration pathways (RCPs). The temporal-spatial variations of four indicators (i.e., intensity, total intensity, frequency, and the longest duration) of projected heat waves, as well as the potential changes in daily maximum temperature (i.e., Tmax) for future (i.e., 2006–2095) and historical (i.e., 1976–2005) periods, were analyzed over Guangdong. The results indicated that Guangdong would endure a notable increasing annual trend in the projected Tmax (i.e., 0.016–0.03°C per year under RCP4.5 and 0.027–0.057°C per year under RCP8.5). Evaluations of the multiple GCMs and their ensemble suggested that the developed approach performed well, and the model ensemble was superior to any single GCM in capturing the features of heat waves. The spatial patterns and interannual trends displayed that Guangdong would undergo serious heat waves in the future. The variations of intensity, total intensity, frequency, and the longest duration of heat wave are likely to exceed 5.4°C per event, 24°C, 25 days, and 4 days in the 2080s under RCP8.5, respectively. Higher variation of those would concentrate in eastern and southwestern Guangdong. It also presented that severe heat waves with stronger intensity, higher frequency, and longer duration would have significant increasing tendencies over all Guangdong, which are expected to increase at a rate of 0.14, 0.83, and 0.21% per year under RCP8.5, respectively. Over 60% of Guangdong would suffer the moderate variation of heat waves to the end of this century under RCP8.5. The findings can provide decision makers with useful information to help mitigate the potential impacts of heat waves on pivotal regions as well as ecosystems that are sensitive to extreme temperature.

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A Statistical Hydrological Model for Yangtze River Watershed Based on Stepwise Cluster Analysis

Cited by 6 publications

References 43 publications

Collided with COVID-19 Pandemic, the 2020 Yangtze Flood Is Exceptionally Severe

Collided with COVID-19 Pandemic, the 2020 Yangtze Flood Is Exceptionally Severe

A novel Joint Probability Density Difference Approach for assessing the alteration of hydrologic regime

A Stepwise-Clustered Simulation Approach for Projecting Future Heat Wave Over Guangdong Province

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