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Response Relationship Between Runoff and Meteorological Drought and Flood Characteristics in Jialing River Basin
LI Wen-hui, ZHANG Yang, CAO Hui, XING Long, REN Yu-feng, ZHAI Shao-jun, MA Yi-ming, LI Wen-da
Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (8) : 53-60.
PDF(7046 KB)
PDF(7046 KB)
Response Relationship Between Runoff and Meteorological Drought and Flood Characteristics in Jialing River Basin
[Objective] Most existing studies on the response relationship between runoff variations and meteorological drought and flood characteristics focus on annual, seasonal, monthly, or weekly scales. This study aims to clarify the quantitative response relationship between meteorological drought and flood characteristics at the daily scale and runoff in the Jialing River Basin, and to effectively evaluate the impact of extreme meteorological drought and flood events on the flow process. [Methods] Based on long-term daily precipitation and flow data from 1989 to 2022, this study employed the SWAP index method and run theory to identify meteorological drought and flood events at the daily scale in the Jialing River Basin. Traditional multiple regression and emerging machine learning models were compared to simulate the internal relationship between meteorological drought and flood characteristics and flow change, revealing the response of runoff variation to drought and flood characteristics. [Results] The results showed that from 1989 to 2022, a total of 68 meteorological drought events occurred in the Jialing River Basin, leading to an average reduction of 48.25% in flow at the Beibei station. Compared to drought duration and intensity, the timing of drought events had a more significant impact on runoff variation and was the primary controlling factor influencing runoff variation. The support vector regression model considering only this factor could more accurately evaluate the change rate of flow caused by drought. During the same period, 40 meteorological flood events occurred in the Jialing River Basin, leading to an average increase of 130.46% in flow at the Beibei station. The accumulated precipitation before the flood peak had the greatest impact on the change rate of flow, and the timing of maximum precipitation before the flood peak had the greatest impact on the timing of flood peak. Multiple regression models were recommended to evaluate the response relationships between flood characteristic factors and the change rate of flow, as well as the timing of flood peak. To evaluate the impact of flood events on peak flow, the random forest model was recommended. The accumulated precipitation before the flood peak was the primary controlling factor influencing peak flow variation. [Conclusion] This study innovatively explores the response relationship between meteorological drought and flood characteristics at the daily scale and runoff variation in the river basin. The findings indicate that emerging machine learning models, such as support vector machines and random forests, can effectively simulate the complex mechanisms through which meteorological drought and flood events affect runoff in the river basin. This has significant implications for the scientific evaluation and prediction of the impact of extreme climate events on runoff characteristics.
meteorological drought and flood / daily scale / multiple regression model / runoff / response relationship / Jialing River Basin
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A new method was proposed to identify drought-flood transition events by combining a drought-flood index (Standard Weighted Average Precipitation, SWAP) with the multi-threshold theory. This method was tested in the Yangtze River Basin using daily precipitation data from 212 stations for the 1961-2017 period. With this method, the meteorological drought and rainstorm flood in the representative station were identified, and representative regional drought-flood transition events and spatiotemporal patterns of drought-flood transition were analyzed. The results show that: SWAP is an effective index to identify the meteorological drought and rainstorm flood. K-means clustering can classify similar drought-flood transition events into one cluster. The drought event plays a dominate role in drought-flood transition events for the middle and lower reaches of the Yangtze River Basin in 2011, and the drought lasts for a much longer duration than the flood during the drought-flood transition event. Drought-flood transition events show an obvious regional pattern for the Yangtze River Basin with low frequency for the upper reaches and high frequency for the middle and lower reaches. In addition, the drought-flood transition frequency presents an increasing trend recently for most parts of the Yangtze River Basin. Overall, the results imply that the proposed method combining meteorological drought index with multi-threshold theory is capable of identifying drought-flood transition events, and can be further used for predicting drought-flood transition events. |
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高密度脂蛋白胆固醇（HDL-C）可以有效促进人体内胆固醇的代谢外排,其水平的高低与患心血管疾病的风险呈负相关关系,是心血管疾病的预防与保护因素。厘清我国中老年人群HDL-C水平的地理分异特征及环境影响因素,对我国心血管疾病防治工作的开展有重要意义。论文基于中国中老年人纵向追踪调查,利用全局空间自相关、冷热点分析等方法阐释中国中老年人群HDL-C水平的空间分异特征及变化趋势,同时对比引入随机森林回归模型及多元线性回归方法探讨HDL-C水平空间分布的环境影响因素及其指示作用。结果表明：中国中老年人群HDL-C水平表现为女性高于男性、农村高于城镇,具有明显的地域差异性,整体呈现出“北低南高,中间过渡”的分布格局,且北方出现了以内蒙古、河北、辽宁为代表的低值聚集区,南方出现了以广东、广西、云南为代表的高值聚集区;SO<sub>2</sub>、NO<sub>2</sub>、降水、气压、PM<sub>10</sub>和PM<sub>2.5</sub>是影响中老年人群HDL-C水平差异分布的主要环境因素,其中高浓度的空气污染物是造成HDL-C值较低的危险因素,充沛的降水和低压环境是防治HDL-C值较低的保护因素。因此,今后关于HDL-C血脂异常防控工作在全国各地应注重其空间分布规律,重点加强对HDL-C低值区的监测,以达到因地制宜、精准防控的目的。
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