Human impact overwhelms long-term climate control of fire in the Yangtze River Basin since 3.0 ka BP

Under the background of global warming, the trends and variabilities of different grades of precipitation have significant effects on the management of regional ecosystems and water resources. Based on a daily precipitation dataset collected from 148 meteorological stations in the Yangtze River Basin from 1960 to 2017, precipitation events were divided into four grades (small, moderate, large, and heavy precipitation events) according to the precipitation intensity to analyze the temporal and spatial change trends of different grades of precipitation amounts and frequencies, and the influence of different grades of precipitation on total precipitation was also discussed in this study. The results revealed that small precipitation amounts over the Yangtze River Basin decreased significantly, with a rate of −1.22%/10a, while heavy precipitation amounts showed a significant increasing trend (4.27%/10a) during the study period. The precipitation frequency of small and total events decreased significantly, with rates of −3.86%/10a and −2.97%/10a, respectively. Regionally, from the upper reaches to the lower reaches of the Yangtze River Basin, the contribution rate of small precipitation amounts and frequencies to the total precipitation gradually decreased, while heavy precipitation amounts and frequencies increased. The different grades of precipitation in region II showed a decreasing trend due to its unique geographical features. Furthermore, a Pearson correlation analysis was used to analyze the response of precipitation to long-term air temperature, demonstrating that small and moderate precipitation amounts and frequencies were mainly negatively correlated with long-term air temperature and that heavy precipitation amounts showed a stronger positive correlation with long-term air temperature (13.35%/K). Based on this, the rate of change in heavy precipitation in the Yangtze River Basin may be higher under the background of climate warming, which will lead to greater risks of extreme floods in the future. Evaluating and predicting the trends of different grades can provide a theoretical reference for agricultural production, flood control, and drought mitigation.

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Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Forests ◽

10.3390/f12060731 ◽

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.

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Impacts of land use change on thermodynamic and dynamic changes of precipitation for the Yangtze River Basin, China

International Journal of Climatology ◽

10.1002/joc.7037 ◽

2021 ◽

Author(s):

Qian Lin ◽

Jie Chen ◽

Wei Li ◽

Kailin Huang ◽

Xuezhi Tan ◽

...

Keyword(s):

Land Use ◽

Land Use Change ◽

River Basin ◽

Yangtze River ◽

Yangtze River Basin ◽

The Yangtze River ◽

Dynamic Changes ◽

The Yangtze River Basin

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

Remote Sensing ◽

10.3390/rs13153023 ◽

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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