DOI: 10.1016/j.jhydrol.2019.124365
论文题名: Is there an underestimation of long-term variability of streamflow across the continental United States?
作者: Sang Y.-F. ; Sivakumar B. ; Zhang Y.
刊名: Journal of Hydrology
ISSN: 221694
出版年: 2020
卷: 581 语种: 英语
英文关键词: Discrete wavelet spectrum
; Long-term variability
; Nonstationarity
; Significance
; Streamflow
; Trend
Scopus关键词: Wavelet analysis
; Discrete wavelets
; Long-term variability
; Non-stationarities
; Significance
; Trend
; Stream flow
; climate conditions
; confidence interval
; discrete choice analysis
; hydrometeorology
; long-term change
; streamflow
; trend analysis
; wavelet analysis
; United States
英文摘要: Analysis of the long-term variability of terrestrial streamflow is important for a wide range of studies in hydroclimatology and environment. However, the common practice of detecting only the monotonic trend cannot actually reflect the long-term variability and change in streamflow, thus resulting in an insufficient or biased understanding. This study focuses on the non-monotonic trends of streamflow and its spatial variability across the continental United States (US). Annual streamflow data observed during 1951–2002 at 530 stations across the continental US are studied. The discrete wavelet spectrum (DWS) is used to detect the non-monotonic trend of streamflow and evaluate its statistical significance. The results indicate significant non-monotonic trends in annual streamflow at 172 stations in the northeast Zone and the northern part of the southeast Zone (in the regions east of 100°W). However, considering only the monotonic trends (being significant at only 38 stations) causes a biased understanding of the long-term variability of streamflow in the northeast zone. The results also reveal that the non-monotonic trend of streamflow in the continental US was mainly controlled by the climatic conditions and that the effects of landscape conditions were weak. The average aridity index (AI) of 0.86–1.35 and its DWS-based significance level >0.1 can indicate the significant non-monotonic trend of streamflow at 95% confidence level. The regions that can meet the above two conditions account for 16% of the global terrestrial surfaces. By considering non-monotonic trends, the change ratio of streamflow is found to be double of that of AI, while similar change ratios are obtained from the monotonic trend results, as the reason of significant underestimation. Due to the partly equal roles of low-frequency oscillation and monotonic trend, identification of the non-monotonic trend should be more desirable for the detection and attribution of the long-term variability and change in streamflow. © 2019 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159737
Appears in Collections: 气候变化与战略
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作者单位: Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India
Recommended Citation:
Sang Y.-F.,Sivakumar B.,Zhang Y.. Is there an underestimation of long-term variability of streamflow across the continental United States?[J]. Journal of Hydrology,2020-01-01,581