首页> 外文期刊>Hydrological Processes >Russian nesting dolls effect – Using wavelet analysis to reveal non-stationary and nested stationary signals in water yield from catchments on a northern forested landscape
【24h】

Russian nesting dolls effect – Using wavelet analysis to reveal non-stationary and nested stationary signals in water yield from catchments on a northern forested landscape

机译:俄罗斯嵌套娃娃效应–使用小波分析揭示北部森林景观集水区水产量中的非平稳和嵌套静止信号

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Determining catchment responses to climate signals gives insight into the potential effects of climate change. This study tested the hypothesis that a 28-year time series of water yields from four headwater catchments in the Turkey Lakes Watershed (TLW), Ontario contains signals of non-stationary climate change and naturally occurring stationary climate oscillations and that the effects of these signals are greater in catchments with lower rates of change in water loading and lower water storage capacity (small wetlands). Non-stationary trends explained 0%, 18%, 44%, and 52% of the variance in the water yields of the four catchments. Wavelet analysis using Morlet wavelets identified stationary responses at multiple temporal scales, increasing the amount of variance explained to 56%, 63%, 76%, and 81% when combining stationary and non-stationary models. The catchment with low water loading and low water storage was most sensitive to non-stationary and stationary signals, suggesting that these catchments act as sentinels to detect climatic signals. Wavelet coherence analysis revealed correlations between global climate oscillation indices and water yield. The Atlantic Multidecadal Oscillation (AMO) index was strongly correlated with both temperature and precipitation (R2 = 0.46, P < 0.001 and R2 of 0.34, P < 0.001, respectively). Temperature in the TLW increased by 0.067 °C per year from 1981 to 2008, but approximately 0.037 °C of this increase can be explained by the AMO index. While it is likely that anthropogenic climate change impacts water yields, it is important to account for multiple nested climate oscillations to avoid exaggerating its effects. Copyright © 2012 John Wiley & Sons, Ltd.
机译:确定流域对气候信号的响应,可以洞悉气候变化的潜在影响。这项研究检验了以下假设:安大略省土耳其湖泊流域(TLW)的四个源头集水区的水产量的28年时间序列包含非平稳气候变化和自然发生的平稳性气候振荡的信号,以及这些信号的影响流域的水量变化率较低和蓄水能力较低(小湿地)的流域面积更大。非平稳趋势解释了四个流域水产量变化的0%,18%,44%和52%。使用Morlet小波的小波分析在多个时间尺度上确定了平稳响应,将平稳模型和非平稳模型组合在一起时,所解释的方差量增加到56%,63%,76%和81%。低载水量和低蓄水量的流域对非平稳和静止信号最敏感,这表明这些流域充当了探测气候信号的前哨。小波相干分析揭示了全球气候振荡指数与水产量之间的相关性。大西洋多年代际振荡(AMO)指数与温度和降水都密切相关(R2 = 0.46,P <0.001,R2为0.34,P <0.001)。从1981年到2008年,TLW中的温度每年增加0.067°C,但是这种增加的大约0.037 C可以用AMO指数来解释。尽管人为的气候变化可能会影响水的产量,但重要的是应对多个嵌套的气候波动,以避免夸大其影响。版权所有©2012 John Wiley&Sons,Ltd.

著录项

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号