降雨和湖泊海拔与厄尔湖和托洛瓦泻湖系统破裂事件相关的时间序列模型,加利福尼亚北部沿海

IF 1 4区 生物学 Q3 FISHERIES
R. M. Sullivan
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引用次数: 0

摘要

我评估了厄尔湖、托洛瓦湖及其沿加利福尼亚州北部海岸的组合泻湖系统的历史降雨量、水位和决口事件的时空变化趋势。我研究了时间序列分析在2008年至2021年区域范围内对降雨和湖泊高程进行建模和预测的有效性。我采用了半参数广义加性模型回归来研究泻湖的人为破坏和环境参数同时发生之间的历史关系,以更好地了解每个破坏事件周围的条件。对降雨量和湖面高程的中心趋势的评估显示,它们的平均值、正偏曲线和轻风廓线波动很大。增强Dickey-Fuller检验发现,季节性降雨是稳定的,但湖面高程只有在第一个季节性差异之后才达到稳定。每个时间序列的分解和MannKendall和Sen的斜率估计发现,季节性湖面高程有显著下降趋势,但降雨量没有下降趋势。季节性自回归综合移动平均(SARIMA)时间序列分析和稳定性和可靠性诊断测试发现,降雨量(SARIMA[1,0][2,1,1]12)和地表湖高程(SARIMA[1,1,2][1,,0]12)的最佳拟合模型用于预测每个参数的未来值。对每个决口事件获得的变量进行多元回归,结果表明,由降雨量、高度和波高组合解释的方差比例(55.0%)和零偏差比例(72.1%)是“最佳”模型,在所有其他评估模型中,广义交叉验证统计量最低。所有模型都一致认为,在用于模拟地表湖泊高程的每一组预测属性中,降雨量是最重要的因素。表面海拔的下降趋势,加上历史区域和湿地植物群落范围的变化,可能是由于每年泻湖的系统性破坏。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time series modeling of rainfall and lake elevation in relation to breaching events at the Lake Earl and Tolowa lagoon system, coastal northern California
I evaluated trends in spatial and temporal variability in historical levels of rainfall, water elevation, and breach events for lakes Earl, Tolowa, and their combined lagoon system along the coast of northern California. I examined the efficacy of time series analyses to model and forecast rainfall and lake elevation at a regional scale from 2008 to 2021. I employed semi-parametric Generalized Additive Model regression to investigate the historical relationship between anthropogenic breaching of the lagoon and simultaneous occurrences of environmental parameters to better understand conditions surrounding each breach event. Evaluation of the central tendency of rainfall and surface lake elevation showed high fluctuations in their mean, positive skewed, and leptokurtic curves. Augmented Dickey-Fuller tests found that seasonal rainfall was stationary, but surface lake elevation attained stationarity only after the first seasonal difference. Decomposition of each time series and MannKendall and Sen’s slope estimators, found a significant decreasing trend in seasonal surface lake elevation but no trend was found in rainfall. Seasonal Autoregressive Integrated Moving Average (SARIMA) time series analysis and diagnostic tests of stability and reliability found best fit models for rainfall (SARIMA[1,0,0] [2,1,1]12) and surface lake elevation (SARIMA [1,1,2] [1,0,0]12) used to forecast future values for each parameter. Multiple regression of variables obtained at each breach event showed that the proportion of variance (55.0%) and null deviance (72.1%) explained by the combination of rainfall, hightide, and wave height was the “best” model with the lowest Generalized Cross-Validation statistic of all other models evaluated. All models agreed that rainfall was the most significant factor within each set of predictor attributes used to model surface lake elevation. A declining trend in surface elevation in combination with variation in the historical area and extent of wetland plant communities may be attributable to systematic breaching of the lagoon annually.
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