scholarly journals Quantifying Climate Change and Ecological Responses within the Yangtze River Basin, China

2018 ◽  
Vol 10 (9) ◽  
pp. 3026 ◽  
Author(s):  
Feiyan Chen ◽  
Aiwen Lin ◽  
Hongji Zhu ◽  
Jiqiang Niu
Keyword(s):  
Yangtze River ◽  
Vegetation Index ◽  
Yangtze River Basin ◽  
Meteorological Data ◽  
Ecological Indicators ◽  
The Yangtze River ◽  
Temperature And Precipitation ◽  
Annual Total ◽  
The Yangtze River Basin ◽  
Moderate Positive Correlation

The interactions between climate change and vegetation have a significant impact on the dynamics of the global carbon cycle. Based on the observed meteorological data from 1961 to 2013 and the temperature and precipitation data simulated by various climate models (simulations phase 5 of the Climate Model Intercomparison Project dataset), this paper analyzes the temperature and precipitation changes of the Yangtze River Basin (YRB) and finds that they are a similar trend, that is, the temperature presents a significant upward trend (R2 = 0.49, p < 0.01), and the variation trend of precipitation is not significant (R2 = 0.01). Specifically, based on observed meteorological data, the annual mean temperature increased significantly and the area of increasing temperature accounted for 99.94% of the total region (p < 0.05); however, there was no significant change in annual precipitation. Ecological indicators (normalized difference vegetation index (NDVI); enhanced vegetation index (EVI); leaf area index (LAI); gross primary production (GPP); and net primary production (NPP)) of the YRB showed an increasing trend, and annual NDVI, annual EVI, LAI, annual total GPP and annual total NPP increased at respective rates of 0.002 yr−1, 0.001 yr−1, 0.07 m2m−2decade−1, 9 TgCyr−1yr−1, and 6 TgCyr−1yr−1, respectively. Correlation analysis between temperature/precipitation and NDVI/EVI/LAI/GPP/NPP was used to determine the relationships between climatic parameters and ecological indicators. Specifically, the temperature is significantly positively correlated with annual NDVI (R2 = 0.37, p < 0.05), with annual mean LAI (R2 = 0.35, p < 0.05) and with annual GPP (R2 = 0.37, p < 0.05). In addition, there is a moderate positive correlation between mean EVI and mean growing season air temperature (R2 = 0.24); annual mean air temperature is a moderate positive correlation with annual NPP (R2 = 0.28). Our findings confirm that temperature is more closely related to ecological factors than precipitation over the YRB in these decades.

scholarly journals The Use of SPEI and TVDI to Assess Temporal-Spatial Variations in Drought Conditions in the Middle and Lower Reaches of the Yangtze River Basin, China

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Shaodan Chen ◽  
Liping Zhang ◽  
Xin Liu ◽  
Mengyao Guo ◽  
Dunxian She
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Meteorological Data ◽  
Negative Relationship ◽  
The Yangtze River ◽  
Drought Conditions ◽  
The Yangtze River Basin ◽  
Effects Of Drought ◽  
Remote Sensing Methods

Droughts represent the most complex and damaging type of natural disaster, and they have taken place with increased frequency in China in recent years. Values of the standardized precipitation evapotranspiration index (SPEI) calculated using station-based meteorological data collected from 1961 to 2013 in the middle and lower reaches of the Yangtze River Basin (MLRYRB) are used to monitor droughts. In addition, the SPEI is determined for different timescales (1, 3, 6, and 12 months) to characterize dry or wet conditions in this study area. Moreover, remote sensing methods can cover large areas, and multispectral and temporal observations are provided by satellite sensors. The temperature vegetation dryness index (TVDI) is selected to permit assessment of drought conditions. In addition, the correlation between the SPEI and TVDI values is calculated. The results show that the SPEI values over different timescales reflect complex variations in drought conditions and have been well applied in the MLRYRB. Droughts occurred on an annual basis in 1963, 1966, 1971, 1978, 1979, 1986, 2001, 2011, and 2013, particularly 2011. In addition, the regional average drought frequency in the study area during 1961–2013 is 30%, as determined using the SPEI. An analysis of the correlation between the monthly values of the TVDI and the SPEI-3 shows that a negative relationship exists between the SPEI-3 and the TVDI. That is, smaller TVDI values are associated with greater SPEI-3 values and reduced drought conditions, whereas larger TVDI values are associated with smaller SPEI-3 values and enhanced drought conditions. Therefore, this study of the relationship between the SPEI and the TVDI can provide a basis for government to mitigate the effects of drought.

scholarly journals Spatial Downscaling of Tropical Rainfall Measuring Mission (TRMM) Annual and Monthly Precipitation Data over the Middle and Lower Reaches of the Yangtze River Basin, China

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 568 ◽  
Author(s):  
Shaodan Chen ◽  
Liping Zhang ◽  
Dunxian She ◽  
Jie Chen
Keyword(s):  
Spatial Resolution ◽  
Yangtze River ◽  
Vegetation Index ◽  
Yangtze River Basin ◽  
Tropical Rainfall Measuring Mission ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
The Yangtze River ◽  
The Yangtze River Basin ◽  
Monthly Precipitation Data

Precipitation plays an important role in the global water cycle, in addition to material and energy exchange processes. Therefore, obtaining precipitation data with a high spatial resolution is of great significance. We used a geographically weighted regression (GWR)-based downscaling model to downscale Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data over the middle and lower reaches of the Yangtze River Basin (MLRYRB) from a resolution of 0.25° to 1 km on an annual scale, and the downscaled results were calibrated using the geographical differential analysis (GDA) method. At present, either the normalized difference vegetation index (NDVI) or a digital elevation model (DEM) is selected as the environmental variable in the downscaling models. However, studies have shown that the relationship between the NDVI and precipitation gradually weakens when precipitation exceeds a certain threshold. In contrast, the enhanced vegetation index (EVI) overcomes the saturation shortcomings of the NDVI. Therefore, this study investigated the performances of EVI-derived and NDVI-derived downscaling models in downscaling TRMM precipitation data. The results showed that the NDVI performed better than the EVI in the annual downscaling model, possibly because this study used the annual average NDVI, which may have neutralized detrimental saturation effects. Moreover, the accuracy of the downscaling model could be effectively improved after correcting for residuals and calibrating the model with the GDA method. Subsequently, the downscaled rainfall was closer to the actual weather station rainfall observations. Furthermore, the downscaled results were decomposed into fractions to obtain monthly precipitation data, showing that the proposed method by utilizing the GDA method could improve not only the spatial resolution of remote sensing precipitation data, but also the accuracy of data.

scholarly journals Link between East Asian summer monsoon and sedimentation in river-mouth sandbars since the early Holocene preserved in the Yangtze River subaqueous delta front

2020 ◽  
Vol 95 ◽  
pp. 84-96
Author(s):  
Gang Xu ◽  
Jian Liu ◽  
Marcello Gugliotta ◽  
Yoshiki Saito ◽  
Lilei Chen ◽  
...  
Keyword(s):  
Yangtze River ◽  
Late Holocene ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
River Mouth ◽  
Early Holocene ◽  
The Yangtze River ◽  
Delta Front ◽  
The Yangtze River Basin ◽  
Asian Summer

AbstractThis paper presents geochemical and grain-size records since the early Holocene in core ECS0702 with a fine chronology frame obtained from the Yangtze River subaqueous delta front. Since ~9500 cal yr BP, the proxy records of chemical weathering from the Yangtze River basin generally exhibit a Holocene optimum in the early Holocene, a weak East Asian summer monsoon (EASM) period during the middle Holocene, and a relatively strong EASM period in the late Holocene. The ~8.2 and ~4.4 cal ka BP cooling events are recorded in core ECS0702. The flooding events reconstructed by the grain-size parameters since the early Holocene suggest that the floods mainly occurred during strong EASM periods and the Yangtze River mouth sandbar caused by the floods mainly formed in the early and late Holocene. The Yangtze River-mouth sandbars since the early Holocene shifted from north to south, affected by tidal currents and the Coriolis force, and more importantly, controlled by the EASM. Our results are of great significance for enriching both the record of Holocene climate change in the Yangtze River basin and knowledge about the formation and evolution progress of the deltas located in monsoon regions.

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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