Abstract
River flow reconstruction under the background of long-term climate change is of great significance for understanding the regional response to future drought and flood disasters, and the sustainable development of water resources. Investigating the basic characteristics and changing trends of the streamflow of the Ganjiang River is scientifically important to mitigate drought and flood disasters in the future. This study reconstructed drought and flood grade series of five regional stations of the Ganjiang River based on spatially explicit and well-dated local chronicle materials and used a linear regression model of modern drought/flood grades and precipitation to reconstruct historical precipitation for the past 515 years. The relationships between the modern precipitation of five regional stations and streamflow of Waizhou Station, which is the last hydrological station of the Ganjiang River were analyzed through principal component regression. The adjusted R2 is 0.909, with a low relative bias of −1.82%. The variation of streamflow from AD 1500 to AD 2014 was reconstructed using the proposed model. Result shows that high flows occur in nine periods and low flows occur in 11 periods. Extremely low stream flow in 515 years appears during the middle and late 17th century. Cumulative anomaly and Mann-Kendall mutation test results reveal that a transition point from predominantly low to high flows occur in AD 1720. Redfit power spectrum analysis result shows that the variation periods of streamflow are 2–5, 7–8 years, and approximately 32 years, where the most significant period is 2–3 years. Continuous wavelet transform indicates that the corresponding relation occurs between streamflow and El Niño/Southern Oscillation for eight years. Streamflow is affected by temperature and East Asian monsoon that is controlled by solar activities. The flood may be related to strong solar activity, monsoon failure, and vice versa. Hydrological frequency curve analysis shows that the streamflow of the Ganjiang River once in a hundred years may reach up to 1031 × 108 m3 for flood or 485 × 108 m3 for drought and the standard of once in a millennium runoff may reach up to 1188 × 108 m3 for flood or 450 × 108 m3 for drought. These results may provide basic hydrological data for the sustainable development of society and serve as a reference for mitigating the impact of drought and flood disasters in the future.
Highlights
Extreme climate hydrological events have increasingly occurred [1] under the context of global warming for the past 100 years [2,3]
The Fifth Assessment Report of the Intergovernmental Panel on Climate Change consistently indicates that the extent, intensity, and frequency of extreme climate hydrological events have significantly changed [4,5]
In 1998, a large-scale flood disaster occurred in Eastern China [8], causing a huge impact on the Ganjiang River basin and economic losses amounting to approximately 15 billion yuan [9]
Summary
Extreme climate hydrological events have increasingly occurred [1] under the context of global warming for the past 100 years [2,3]. In 1998, a large-scale flood disaster occurred in Eastern China [8], causing a huge impact on the Ganjiang River basin and economic losses amounting to approximately 15 billion yuan [9]. A long-time scale variation series of streamflow should be reconstructed, and its variation characteristics should be analyzed by utilizing other climatic proxies In this way, the new streamflow series can provide basic data for basin water resource management and hydraulic project construction. Drought and flood historical files, which refer to the exact years and the places in the county scale of disasters, have been frequently used by scholars to reconstruct past climate conditions because of their accuracy [29]. Zhang et al [30] reconstructed variations of climatic dry/wet alternations of Eastern China for the past 1000 years by using drought and flood historical files derived from local chronicles. Long and intense precipitation; deep water on the ground; serious damage to crops, animals, and dams caused by floods; floods did not occur in many years
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