Interactions of the Yangtze river flow and hydrologic processes of the Poyang Lake, China

Hu, Qi; Feng, Song; Guo, Hua; Chen, Guiya; Jiang, Tong

doi:10.1016/j.jhydrol.2007.09.005

Cited by 259 publications

(158 citation statements)

References 7 publications

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“…Table 2 shows details of the applied GCM/RCMs. and Kumar 2013; Hu et al 2007;Santos and da Silva 2015). The indices chosen for this study are listed in Table 3.…”

Section: Observed Hydrological and Climate Datamentioning

confidence: 99%

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

2017

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The aim of the study is to investigate trends in selected hydroclimatic indices using novel and conventional tools, for future climate projections in the twentyfirst century. Selected quasi-natural Norwegian and Polish catchments are used as a case study. The projected flows are provided by GR4J rainfall-runoff conceptual model, coupled with an ensemble of climate model projections from EURO-CORDEX initiative. The trends are analysed using conventional Mann-Kendall and modified MannKendall statistical approaches, a time-frequency approach based on discrete wavelet transform (DWT) and the dynamic harmonic regression (DHR) method. Of all methods applied the DHR gives the most conservative trend estimates. Trends depend on the specific hydroclimatic character and flow regime of the catchment. The results confirmed that in catchments with a rainfall-driven flood regime, an increase in the amount of precipitation is followed by increased flows, with strong seasonal changes, whereas, in catchments with a snow-driven flood regime, despite an increase of mean annual flow, decrease in annual maximum flow is observed. Generally, positive trend is the most dominant in all catchments studied and the methods were consistent in detection of trend except in seasonal trend test.

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“…Table 2 shows details of the applied GCM/RCMs. and Kumar 2013; Hu et al 2007;Santos and da Silva 2015). The indices chosen for this study are listed in Table 3.…”

Section: Observed Hydrological and Climate Datamentioning

confidence: 99%

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

2017

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“…High return periods, however, were mainly observed in the south side of the middle Yangtze River basin. The region that contributed greatly to the development of flooding in the Yangtze River (Hu et al 2007). The spatial distribution of the high return periods of AM10 is also consistent with the exceptional high water levels in the middle Yangtze River (Zong and Chen 2000).…”

Section: The 1998 Extreme Precipitation From Probabilistic Perspectivementioning

confidence: 99%

Modeling Annual Extreme Precipitation in China Using the Generalized Extreme Value Distribution

Feng

Nadarajah

2007

Journal of the Meteorological Society of Japan

Self Cite

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Extreme precipitation events are the major causes of severe floods in China. In this study, four time series of daily, 2-day, 5-day, and 10-day annual maximum precipitation from 1951 to 2000 at 651 weather stations in China were analyzed. The generalized extreme value (GEV) distribution was used, to model the annual extreme precipitation events at each station. The GEV distribution was also modified to explore the linear temporal trends in the extreme events. The results showed that more than 12% of the stations have significant ( p-value < 0:10) linear trends. Decreasing trends are mainly observed in northern China, and increasing trends are observed in the Yangtze River basin and northwestern China. The return periods of extreme precipitation have changed for stations with significant temporal trends. The 50-year event observed in parts of the Yangtze River basin, and northwestern China during 1951-60, has become a more frequent 25-year event in the 1990s. The spatial distribution of the return levels of the 651 stations are closely related to the climatic mean precipitation, and are influenced by the East Asian summer monsoon system (return levels are measures of extremity-for example, a 10 year return level is the value that can be expected to be exceeded on average once in every 10 years). The return period of extreme precipitation, that caused the 1998 severe floods in the Yangtze River basin, was also evaluated from a probabilistic perspective.

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“…Water levels and the lake area undergo remarkable seasonal variations [33]. During the wet season, the floodplains are submerged and form a lake with a sensibly horizontal water surface.…”

Section: Study Areamentioning

confidence: 99%

Characteristics and Factors Influencing the Hysteresis of Water Area–Stage Curves for Poyang Lake

Huang

Peng

Liu

et al. 2017

Water

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Flood dynamics of large lake floodplain systems are typically complex. This paper analyses the characteristics and factors that influence the hysteresis of water area-stage curves for Poyang Lake, the largest freshwater lake in China characterized by complex geomorphology and upstream-downstream exchange conditions. For this purpose, a two-dimensional hydrodynamic model (EFDC) based on seven scenarios is established. The results indicate that the area-stage curve presents significant hysteretic characteristics due to different water surface gradients that emerge during the water-rising and water-falling periods. Counter-clockwise, clockwise, and splayed hysteresis directions observed at the northern, southern, and central hydrometric stations, respectively, are found in Poyang Lake for the first time. Upstream catchment inflows and Hukou stage reflecting the downstream condition are the main factors that influence hysteresis. The temporal fluctuation of catchment inflows and Hukou stage has a remarkably positive impact on hysteresis, namely, an increase in fluctuation brings about a larger hysteresis. The effects of magnitude change in the two factors on hysteresis are opposing. Catchment inflows are positively related, while the decline of the Hukou stage will produce a more pronounced hysteresis. The outcomes of this study will benefit the water management of Poyang Lake and other similar large lakes.

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Interactions of the Yangtze river flow and hydrologic processes of the Poyang Lake, China

Cited by 259 publications

References 7 publications

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

Modeling Annual Extreme Precipitation in China Using the Generalized Extreme Value Distribution

Characteristics and Factors Influencing the Hysteresis of Water Area–Stage Curves for Poyang Lake

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