scholarly journals Assessing the impact of open-ocean and back-barrier shoreline change on Dauphin Island, Alabama, at multiple time scales over the last 75 years

2018 ◽  
Author(s):  
Christopher G. Smith ◽  
Joseph W. Long ◽  
Rachel E. Henderson ◽  
Paul R. Nelson
2021 ◽  
Author(s):  
Jing Zhao

<p>The elevated atmospheric carbon dioxide concentration (CO<sub>2</sub>), as a key variable linking human activities and climate change, seriously affects the watershed hydrological processes. However, whether and how atmospheric CO<sub>2</sub> influences the watershed water-energy balance dynamics at multiple time scales have not been revealed. Based on long-term hydrometeorological data, the variation of non-stationary parameter n series in the Choudhury's equation in the mainstream of the Wei River Basin (WRB), the Jing River Basin (JRB) and Beiluo River Basin (BLRB), three typical Loess Plateau regions in China, was examined. Subsequently, the Empirical Mode Decomposition method was applied to explore the impact of CO<sub>2</sub> on watershed water-energy balance dynamics at multiple time scales. Results indicate that (1) in the context of warming and drying condition, annual n series in the WRB displays a significantly increasing trend, while that in the JRB and BLRB presents non-significantly decreasing trends; (2) the non-stationary n series was divided into 3-, 7-, 18-, exceeding 18-year time scale oscillations and a trend residual. In the WRB and BLRB, the overall variation of n was dominated by the residual, whereas in the JRB it was dominated by the 7-year time scale oscillation; (3) the relationship between CO<sub>2 </sub>concentration and n series was significant in the WRB except for 3-year time scale. In the JRB, CO<sub>2 </sub>concentration and n series were significantly correlated on the 7- and exceeding 7-year time scales, while in the BLRB, such a significant relationship existed only on the 18- and exceeding 18-year time scales. (4) CO<sub>2</sub>-driven temperature rise and vegetation greening elevated the aridity index and evaporation ratio, thus impacting watershed water-energy balance dynamics. This study provided a deeper explanation for the possible impact of CO<sub>2</sub> concentration on the watershed hydrological processes.</p>


Author(s):  
Adam Propst ◽  
Adam Parker ◽  
Zachary Capps ◽  
Kara Peters ◽  
Mohammed A. Zikry

Low-velocity impact events occurring over the span of a few milliseconds cause changes in composite structures through relaxation and delamination propagation which manifest themselves over the span of several seconds. Changes in embedded fiber Bragg grating sensor response allow the damage in the composite structure to be measured in lieu of simply analyzing the impact event itself. By observing the damage progression and subsequent failure of the sample, the sensor signal response can thus be used to predict the lifetime of the structure. In this paper, we expand previous sensor interrogation and damage identification methodologies by using scanning instrumentation capable of operating over multiple time scales. 2D woven composite specimens are subjected to multiple low velocity impacts while the fiber Bragg grating (FBG) sensor response is monitored in time scales of one millisecond to tens of seconds. A high frequency scanning spectrometer is used to determine the peak Bragg wavelength while scanning the FBG sensor at approximately 1 kHz during and immediately after the impact. Also, a high fidelity slow-scan laser source measures the quasi-static sensor response several seconds to minutes following the impact events. Features of the two measurement sets are used to identify the structural integrity of the laminate specimen after each impact event.


2018 ◽  
Author(s):  
Yan Liang ◽  
◽  
Daniele J. Cherniak ◽  
Chenguang Sun

2019 ◽  
Vol 11 (4) ◽  
pp. 1163 ◽  
Author(s):  
Melissa Bedinger ◽  
Lindsay Beevers ◽  
Lila Collet ◽  
Annie Visser

Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.


2021 ◽  
Vol 40 (9) ◽  
pp. 2139-2154
Author(s):  
Caroline E. Weibull ◽  
Paul C. Lambert ◽  
Sandra Eloranta ◽  
Therese M. L. Andersson ◽  
Paul W. Dickman ◽  
...  

Author(s):  
Jia-Rong Yeh ◽  
Chung-Kang Peng ◽  
Norden E. Huang

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal’s complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease.


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