Precipitation extremes in the Yangtze River Basin, China: regional frequency and spatial–temporal patterns

2013 ◽  
Vol 116 (3-4) ◽  
pp. 447-461 ◽  
Author(s):  
Yongqin David Chen ◽  
Qiang Zhang ◽  
Mingzhong Xiao ◽  
Vijay P. Singh ◽  
Yee Leung ◽  
...  
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Temporal Patterns ◽  
Precipitation Extremes ◽  
The Yangtze River ◽  
The Yangtze River Basin ◽  
Regional Frequency

Weakening Influence of Spring Soil Moisture over the Indo-China Peninsula on the Following Summer Mei-Yu Front and Precipitation Extremes over the Yangtze River Basin

2020 ◽  
Vol 33 (23) ◽  
pp. 10055-10072
Author(s):  
Chujie Gao ◽  
Gen Li ◽  
Bei Xu
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Summer Monsoon ◽  
Yangtze River ◽  
Large Scale ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
Precipitation Extremes ◽  
The Yangtze River ◽  
The Yangtze River Basin

AbstractThe seasonal prediction of precipitation extremes over the Yangtze River basin (YRB) has always been a great challenge. This study investigated the effects of spring soil moisture over the Indo-China Peninsula (ICP) on the following summer mei-yu front and YRB precipitation extremes during 1961–2010. The results indicated that the frequency of summer YRB precipitation extremes was closely associated with the mei-yu front intensity, which exhibited a strong negative correlation with the preceding spring ICP soil moisture. However, the lingering climate influence of the ICP soil moisture was unstable, with an obvious weakening since the early 1990s. Due to its strong memory, an abnormally lower spring soil moisture over the ICP would increase local temperature until the summer by inducing less evapotranspiration. Before the early 1990s, the geopotential height elevation associated with the ICP heating affected the western Pacific subtropical high (WPSH), strengthening the southwesterly summer monsoon. Consequently, the mei-yu front was intensified as more warm, wet air was transported to the YRB, and local precipitation extremes also occurred more frequently associated with abnormal ascending motion mainly maintained by the warm temperature advection. In the early 1990s, the Asian summer monsoon underwent an abrupt shift, with the changing climatological states of the large-scale circulations. Therefore, the similar ICP heating induced by the anomalous soil moisture had different effects on the monsoonal circulation, resulting in weakened responses of the mei-yu front and YRB precipitation extremes since the early 1990s.

scholarly journals Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 731
Author(s):  
Zhuoqing Hao ◽  
Jixia Huang ◽  
Yantao Zhou ◽  
Guofei Fang
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Spatiotemporal Pattern ◽  
Pinewood Nematode ◽  
The Yangtze River ◽  
Pine Wilt ◽  
The Yangtze River Basin

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.

scholarly journals Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Basin ◽  
The Yangtze River ◽  
Ecosystem Monitoring ◽  
Catastrophic Flood ◽  
Basin Scale ◽  
The Yangtze River Basin

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.

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