Changing trends and regime shift of streamflow in the Yellow River basin

Zhao, Guangju; Li, Erhui; Mu, Xingmin; Wen, Zhu; Rayburg, Scott; Tian, Peng

doi:10.1007/s00477-015-1058-9

Cited by 49 publications

(29 citation statements)

References 37 publications

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“…9), while an autocorrelation analysis revealed that the hydrological autocorrelation of Yichang and Datong increased after the change points detected above, which also was indicative of potentially decreased resilience in both the middle and lower reaches of the Yangtze River basin. It is generally believed that both climate change and human activities are driving water regime shifts in the Yellow River basin Zhao et al, 2015a).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, we chose to use the annual water discharge from three representative hydrological stations located in the upstream, midstream, and downstream regions of the river basins for the analyses; specifically, these stations were located at Lanzhou (1919-2013), Sanmenxia (1919), and Lijin (1950 within the Yellow River basin, and at Pingshan (1956-2011), Yichang (1950-2011), and Datong (1950-2011 within the Yangtze River basin (Fig. 5) (Zhao et al, 2015a).…”

Section: Case Studymentioning

confidence: 99%

“…As a representative of the capacity of a watershed to absorb and recover from perturbations or disturbances (Folke et al, 2010;Hoque et al, 2012;Randhir, 2014;Wilson and Browning, 2012), watershed resilience and associated transitions in watershed systems has becomes a critical topic in river basin conservation and management (Davidson et al, 2012). In order to understand the vulnerability and resilience of river basins in the face of change, numerous studies have strived to improve knowledge of the linkages between natural variability, drivers of change, ecosystem responses, and feedbacks within a watershed system or its subsystems; these studies have employed both tendency analysis of perturbations and watershed structure (Costa et al, 2003;Zhang et al, 2014a;Zhao et al, 2015a) and process-based model simulations (Coe et al, 2002(Coe et al, , 2011Hu et al, 2015;Levine et al, 2016). For example, Nemec et al (2014) calculated watershed resilience with nine watershed structure properties, i.e.…”

Section: Introductionmentioning

confidence: 99%

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Resilience changes in watershed systems: A new perspective to quantify long-term hydrological shifts under perturbations

Feng

Sun

et al. 2016

Journal of Hydrology

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Keywords:Critical slowing down Resilience indicator Convex model Hydrological regime shift Watershed systems s u m m a r y Natural hydrological regimes are essential to the stability of river basins. While numerous efforts have been put forth to characterize flow regime alterations driven by climate change and human activities, few approaches have been proposed to explore changes in watershed resilience. The present study attempted to introduce a systematic approach that can be used to identify the resilience change of river basins based on annual river discharge through the application of a convex model and the principle of critical slowing down. Specifically, a resilience indicator (p i ) that reflects streamflow autocorrelation at a given time was proposed to represent the temporal variation of the system resilience, and annual water discharge at representative hydrological stations located in upstream, midstream, and downstream regions of a river basin was used to reflect alterations in long-term hydrological processes and the stability of river basins. The application of this method to the Yellow River basin and Yangtze River basin indicated that the system resilience was lower in downstream regions compared to upstream regions. The Yellow River basin has suffered a decrease in resilience in its lower reaches since 1971, which extended to the middle reaches in 1987 and upper reaches in 1990. Similarly, recent observation of the resilience change in the Yangtze River basin indicated that resilience in its lower reaches has likely decreased since 2002, and this low resilience extended to the middle reaches in 2005. Overall, our study presents a new method to predict potential decreases of resilience in complex large scale watershed systems where mechanistic insight is insufficient to build reliable basin-scale hydrological, climate, ecosystem integrated models.

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Section: Discussionmentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Resilience changes in watershed systems: A new perspective to quantify long-term hydrological shifts under perturbations

Feng

Sun

et al. 2016

Journal of Hydrology

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“…BFAST iteratively estimates the time and number of changes, and characterizes change by its magnitude and direction (Verbesselt, Hyndman, Newnham, and Culvenor 2010). BFAST can be used to analyse different types of data dealing with seasonal or non-seasonal time series, such as hydrology and climatology with capability to identify the regime shift (Zhao et al 2015). A more complete description can be found from Verbesselt, Hyndman, Zeileis, and Culvenor (2010).…”

Section: Mann-kendall Trend Analysismentioning

confidence: 99%

Change in nutrient loading pattern due to coupled effect of change in concentration and hydroclimatic forces

Shafiei

McLoughlin

2017

Journal of Freshwater Ecology

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Increase in nutrient loading into large riverine systems is of interest because of long-lasting negative effects on downstream water bodies. We know little of this phenomenon with respect to long-term relationships between water quality metrics and trends in river flow. Here we present a multi-decadal examination of nutrient transport patterns of the South Saskatchewan and Red Deer Rivers, Canada. Using a multimethod approach, we show a slightly increasing trend in annual volume of water reaching a mid-watershed reservoir (Lake Diefenbaker) concomitant with a change in seasonal variability of flow events from the 1970s. Both total nitrogen (TN) and total phosphorus (TP) flux increased during the period of record. TN concentration increased, while TP concentration decreased. On average, the high-flow season transported 95% of annual TP flux, 75% of annual TN flux, and 65% of annual flow. Inter-annually, high-flow season contributions decreased with respect to water volume, but increased with respect to both TN and TP flux. We believe that changes in variability but also timing of hydroclimatic forces are responsible for observed patterns. Higher flows and more precipitation during the high-flow season are most likely responsible for increasing nutrient load regardless of overall decreases in nutrient concentration.

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“…And the relationship between deposition in the LYR and the amount of runoff and SSL from different upper regions has been widely discussed [21][22][23][24][25]. While work investigating the relationship between human activities in upper drainage areas and its effects on the stem channel of the LYR, it may also benefit the management of the LYR except the local drainage area.…”

mentioning

confidence: 99%

Effects of Human Activities in the Wei River Basin on the Lower Yellow River, China

2017

Pol. J. Environ. Stud.

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Changing trends and regime shift of streamflow in the Yellow River basin

Cited by 49 publications

References 37 publications

Resilience changes in watershed systems: A new perspective to quantify long-term hydrological shifts under perturbations

Resilience changes in watershed systems: A new perspective to quantify long-term hydrological shifts under perturbations

Change in nutrient loading pattern due to coupled effect of change in concentration and hydroclimatic forces

Effects of Human Activities in the Wei River Basin on the Lower Yellow River, China

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