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引用本文:贺克雕,高伟,段昌群,朱远高,潘瑛,刘嫦娥,张唯,杨桂英.滇池、抚仙湖、阳宗海长期水位变化(1988-2015年)及驱动因子.湖泊科学,2019,31(5):1379-1390. DOI:
HE Kediao,GAO Wei,DUAN Changqun,ZHU Yuangao,PAN Ying,LIU Chang'e,ZHANG Wei,YANG Guiying.Water level variation and its driving factors in Lake Dianchi, Fuxian and Yangzong during 1988-2015. J. Lake Sci.2019,31(5):1379-1390. DOI:
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滇池、抚仙湖、阳宗海长期水位变化(1988-2015年)及驱动因子
贺克雕1,2, 高伟1, 段昌群1, 朱远高2, 潘瑛1, 刘嫦娥1, 张唯1, 杨桂英1,3
1.云南大学生态学与环境学院暨云南省高原山地生态与退化环境修复重点实验室, 昆明 650504;2.云南省水文水资源局, 昆明 650106;3.西南林业大学, 昆明 650224
摘要:
水位变化影响湖泊水质、水量和生态系统功能,是研究湖泊演变的重要内容,但目前针对滇中高原湖群水位变化特征还少见系统报道.本文选择滇池、抚仙湖、阳宗海3个滇中高原湖泊作为研究对象,基于1988-2015年实测水位数据和Mann-Kendall趋势检验法评估了3个湖泊水位变化特征;运用RClimDex模型获得了流域极端降水指标,结合其他指标构建了基于极端气象因子的湖泊水位驱动力指标体系;采用主成分-多元回归模型,解析了极端降水、蒸发等气象因子对滇中高原湖泊水位变化的贡献.结果表明:①滇池、抚仙湖、阳宗海水位年际波动不突出.滇池的年平均水位总体略呈上升趋势,年均上升0.025 m.阳宗海和抚仙湖水位无明显变化.②滇中高原湖泊流域的极端降水指数年际变化趋势不明显.滇池的蒸发量呈明显减小趋势,年均减小21.05 mm.抚仙湖蒸发量呈明显增加趋势,平均每年增加5.52 mm.阳宗海蒸发量的变化不明显.③气象指标可解释滇池水位变化的49.7%,滇池水位变化受气候变化和人类活动的综合影响;阳宗海和抚仙湖水位变化主要受气象条件控制,蒸发量、综合降水指标和连续降水指标对阳宗海水位变化的解释率高达93.3%;综合降水指标和干旱状况指标可以解释抚仙湖水位变化的64.5%.极端降水指标对解释高原湖泊水位变化具有重要作用.
关键词:  滇池  抚仙湖  阳宗海  水位  极端降水  驱动因子
DOI:
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基金项目:国家自然科学基金项目(31670522)和云南省科技项目(2018BC001,2017IB031,2018DG005)联合资助.
Water level variation and its driving factors in Lake Dianchi, Fuxian and Yangzong during 1988-2015
HE Kediao1,2, GAO Wei1, DUAN Changqun1, ZHU Yuangao2, PAN Ying1, LIU Chang'e1, ZHANG Wei1, YANG Guiying1,3
1.School of Ecology and Environmental Sciences & Yunnan Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded Environments, Yunnan University, Kunming 650504, P. R. China;2.Yunnan Hydrology and Water Resources Bureau, Kunming 650106, P. R. China;3.Southwest Forestry University, Kunming 650224, P. R. China
Abstract:
As an emerging research topics of limnology, variations in water level play a key role in regulating water quality, volume and ecosystem function of lakes. However, the characteristics of plateau lake group located in central Yunnan of China have not been well studied. Taking Lake Dianchi, Fuxian and Yangzong as the study cases, the trends of water level were analysed based on Mann-Kendall statistic approach, and an index system related to fluctuations of water level were established with extreme precipitation index generated from RClimDex and other metrological index. Coupling multiple linear regression and principal factor model, a model for water level alteration of plateau lakes was built to distinguish main driving factors and their effects. Results showed that no significant trend was observed in the annual water level fluctuation of these lakes from 1988 to 2015. However, water level had a significant increase trend in Lake Dianchi at a rate of 0.025 m per year, while no trends found in the other two lakes. The extreme climate index in the lake basins had no significantly statistic trend of temporal alteration. Reverse trends of evaporations were observed in Lake Dianchi and Fuxian that have been decreasing by 21.05 mm per year and increasing by 5.52 mm per year, respectively. The trend of evaporation in Lake Yangzong was not pronounced. Variation of water level in Lake Dianchi can be explained by climatic indexes which accounted for 49.7% of total variation, indicating that water level change can be ascribed to the combined effects of anthropogenic activities and climatic conditions. By contrast, water level variations of Lake Fuxian and Yangzong were mainly influenced by climatic conditions. For Lake Yangzong, evaporation, amount of precipitation and days of consecutive precipitation accounted for 93.3% of variation of water level. Index of precipitation and dry spell can explain 64.5% of variation of water level in Lake Fuxian. Extreme precipitation indices play an important role in explaining water level change in plateau lakes.
Key words:  Lake Dianchi  Lake Fuxian  Lake Yangzong  water level  extreme precipitation  driving factors
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