Reconstructed Jing River streamflow from western China: A 399-year perspective for hydrological changes in the Loess Plateau

Zhao, Xiaoen; Fang, Keyan; Chen, Feng; Hadad, Martín Ariel; Roig, Fidel A.

doi:10.1016/j.jhydrol.2023.129573

Cited by 20 publications

(7 citation statements)

References 100 publications

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“…The correlation coefficients for the Salween streamflow and southeast TP scPDSI are 0.355 (n = 512, p < 0.001) and 0.182 (n = 516, p < 0.01) after 21 year low-pass filter, respectively. The low-frequency components of the three sequences are highly consistent (figure S5) (Xing et al 2014, Zhao et al 2023.…”

Section: Streamflow Variation and Climate Forcingmentioning

confidence: 75%

Climate change increases the instability of the water supply for hydropower stations on the Tibetan Plateau

Hu,

Chen,

Chen

et al. 2023

Environ. Res. Lett.

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In recent decades, global warming has had a significant impact on the streamflow across the Tibetan Plateau. As the largest tributary in the upper reaches of the Yangtze River, the Yalong river is known for its abundant hydropower resources, and the world’s largest multi-energy complementary base has been built in the Yalong River Basin. However, prudent water resource planning is limited by the lack of long-term, detailed and reliable streamflow records over the Yalong river basin. Here, we develop an October–June streamflow reconstruction for the Yalong River, based on composite tree-ring chronology of Picea likiangensis from seven sampling sites. The reconstruction goes back to 1480 CE, and accounts for 46.5% of the instrumental streamflow variance during 1962–2012. This record indicates that the Interdecadal Pacific Oscillation and the Atlantic Multi-decadal Oscillation were the major contributing factors to streamflow variations. A significant and stable correlation with temperature was found over the past few centuries on the interannual scale. Projections suggest that future climate change may lead to more frequent flood disasters in the Yalong River Basin.

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Section: Streamflow Variation and Climate Forcingmentioning

confidence: 75%

Climate change increases the instability of the water supply for hydropower stations on the Tibetan Plateau

Hu,

Chen,

Chen

et al. 2023

Environ. Res. Lett.

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“…This study focuses on conducting a comparative analysis of the reconstructed precipitation with hydrological reconstruction sequences in North China and the Yellow River Basin (Figure 7). The five sequences selected for comparison encompass precipitation reconstruction in North China from 1686 to 2003 (Li et al, 2006), precipitation anomaly reconstruction in the southern Taihang Mountains from 1510 to 2013 (Zhang et al, 2017), streamflow reconstruction in the middle Yellow River from 1570 to 2012 (Chen et al, 2020), and streamflow reconstruction for the Jing River from 1615 to 2013 (Zhao et al, 2023). Additionally, we incorporate the interdecadal reconstructed precipitation from north Central China (Tan et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Tree‐ring‐based reconstruction of the precipitation variability in the middle Taihang Mountains (1608–2021)

Hou,

Zhao,

Chen

et al. 2024

Intl Journal of Climatology

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Understanding historical droughts in northern China is challenging due to the limited time records of meteorological stations. In this study, we reconstructed the precipitation variability in the middle Taihang Mountains over 414 years by using the tree‐ring width of Pinus tabulaeformis. Based on our climate response analysis, Pinus tabulaeformis growth at the sampling sites was mainly restricted by the total precipitation from August of the previous year to June of the current year (P8‐C6), which was used as the dependent variable for precipitation reconstruction. Spatial analysis demonstrated that the reconstructed precipitation contained obvious spatial representativeness in the Taihang Mountains. We compared the precipitation sequence with other dryness/wetness sequences around the study area, revealing common drought events in most of northern China. Furthermore, the multi‐taper method (MTM) demonstrated a significant period of 2–4 years of the reconstructed precipitation. The precipitation variability in the Taihang Mountains may be influenced by the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Variability (AMV) and has exhibited a negative correlation in recent decades. This study has reconstructed the historical changes in wet and dry conditions to offer a reference for the utilization of modern water resources, especially by linking the decrease in precipitation in the study area with the downfall of the Ming Dynasty.

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“…Ultimately, the reconstructed sequences obtained using the four methods were weighted and averaged with equal weights. Thus, an integrated reconstruction was obtained [60]. The correlation coefficient between the rebuilt and actual temperatures was 0.73 (with a sample size of 56, p < 0.001), and after accounting for degrees of freedom, the variance explained was 52.4% (as depicted in Figure 4a).…”

Section: Minimum Temperature Reconstructionmentioning

confidence: 98%

Anomalous Warm Temperatures Recorded Using Tree Rings in the Headwater of the Jinsha River during the Little Ice Age

Jiang,

Xu,

Tong

et al. 2024

Forests

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As a feature of global warming, climate change has been a severe issue in the 21st century. A more comprehensive reconstruction is necessary in the climate assessment process, considering the heterogeneity of climate change scenarios across various meteorological elements and seasons. To better comprehend the change in minimum temperature in winter in the Jinsha River Basin (China), we built a standard tree-ring chronology from Picea likiangensis var. balfouri and reconstructed the regional mean minimum temperature of the winter half-years from 1606 to 2016. This reconstruction provides a comprehensive overview of the changes in winter temperature over multiple centuries. During the last 411 years, the regional climate has undergone seven warm periods and six cold periods. The reconstructed temperature sensitively captures the climate warming that emerged at the end of the 20th century. Surprisingly, during 1650–1750, the lowest winter temperature within the research area was about 0.44 °C higher than that in the 20th century, which differs significantly from the concept of the “cooler” Little Ice Age during this period. This result is validated by the temperature results reconstructed from other tree-ring data from nearby areas, confirming the credibility of the reconstruction. The Ensemble Empirical Mode Decomposition method (EEMD) was adopted to decompose the reconstructed sequence into oscillations of different frequency domains. The decomposition results indicate that the temperature variations in this region exhibit significant periodic changes with quasi-3a, quasi-7a, 15.5-16.8a, 29.4-32.9a, and quasi-82a cycles. Factors like El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and solar activity, along with Atlantic Multidecadal Oscillation (AMO), may be important driving forces. To reconstruct this climate, this study integrates the results of three machine learning algorithms and traditional linear regression methods. This novel reconstruction method can provide valuable insights for related research endeavors. Furthermore, other global climate change scenarios can be explored through additional proxy reconstructions.

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Reconstructed Jing River streamflow from western China: A 399-year perspective for hydrological changes in the Loess Plateau

Cited by 20 publications

References 100 publications

Climate change increases the instability of the water supply for hydropower stations on the Tibetan Plateau

Climate change increases the instability of the water supply for hydropower stations on the Tibetan Plateau

Tree‐ring‐based reconstruction of the precipitation variability in the middle Taihang Mountains (1608–2021)

Anomalous Warm Temperatures Recorded Using Tree Rings in the Headwater of the Jinsha River during the Little Ice Age

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