Compounding effects of human activities and climatic changes on the river water temperature evolution mechanism for ecological effects

IF 1.7 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES
Ning He, Wenxian Guo, Xuyang Jiao, Hongxiang Wang
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Abstract

Understanding the drivers and ecological effects of river water temperature (Tw) change remains a complex and challenging task in the field of ecohydrology. We developed the extreme‐point symmetric mode decomposition to quantitatively identify the trend, period and mutation of water temperature (Tw). The sparrow search algorithm‐long short‐term memory model was constructed to reconstruct the historical Tw to quantitatively identify the effects of human activities (HA) and climate change (CC) at different time scales. The random forest method was used to analyse the contribution rates of different meteorological factors and to clarify the main factors. Our results demonstrate that the Tw had a cooling trend in the 1980s, and the other decades have a warming trend, and the annual Tw distribution shows an obvious ‘unimodal’ distribution. The interannual Tw has a short period of 2–3a, 6–12a and a long period of 10–15a. At the interannual scale, as the distance from estuaries decreases, the influence of HA gradually diminishes, and only the great Tw is governed by CC. Contributions from HA and CC to Tw vary at the seasonal and monthly scales due to geographical differences. In Cuntan, the contribution of HA to Tw is greater than that of climatic factors. The contribution rates of climatic and HA in the three regions of Yichang, Hankou and Datong also exhibit their respective characteristics and fluctuation patterns. The maximum temperature is the most important factor affecting the change of Tw. Abnormal Tw changes result in delayed spawning and characteristic reproduction Tw attainment dates for the Four Major Chinese Carps and Acipenser sinensis.
人类活动和气候变化对河流水温演变生态效应机制的复合影响
在生态水文学领域,了解河流水温(Tw)变化的驱动因素和生态效应仍然是一项复杂而具有挑战性的任务。我们开发了极值点对称模式分解方法来定量识别水温(Tw)的变化趋势、周期和突变。构建了麻雀搜索算法-长短期记忆模型来重建历史水温(Tw),以定量识别不同时间尺度上人类活动(HA)和气候变化(CC)的影响。采用随机森林方法分析了不同气象因子的贡献率,并明确了主要因子。结果表明,Tw 在 20 世纪 80 年代呈降温趋势,其他年代呈升温趋势,Tw 的年分布呈明显的 "单峰 "分布。年际 Tw 分布有一个 2-3a、6-12a 的短周期和一个 10-15a 的长周期。在年际尺度上,随着与河口距离的减小,HA 的影响逐渐减弱,只有大 Tw 受 CC 的影响。由于地理差异,HA 和 CC 对 Tw 的贡献在季节和月度尺度上有所不同。在寸滩,HA 对 Tw 的贡献大于气候因素。宜昌、汉口和大同三个地区的气候和 HA 的贡献率也表现出各自的特点和波动规律。最高气温是影响 Tw 变化的最重要因素。Tw的异常变化导致中国四大名鲤和中华鲟的产卵延迟和繁殖Tw达到日期的特征。
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来源期刊
River Research and Applications
River Research and Applications 环境科学-环境科学
CiteScore
4.60
自引率
9.10%
发文量
158
审稿时长
6 months
期刊介绍: River Research and Applications , previously published as Regulated Rivers: Research and Management (1987-2001), is an international journal dedicated to the promotion of basic and applied scientific research on rivers. The journal publishes original scientific and technical papers on biological, ecological, geomorphological, hydrological, engineering and geographical aspects related to rivers in both the developed and developing world. Papers showing how basic studies and new science can be of use in applied problems associated with river management, regulation and restoration are encouraged as is interdisciplinary research concerned directly or indirectly with river management problems.
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