scholarly journals Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World

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.

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.


2008 ◽  
Vol 17 ◽  
pp. 23-29 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades ◽  
J. Tzabiras

Abstract. This paper evaluates climate change effects on drought severity in the region of Thessaly, Greece. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for the division of Thessaly region to twelve hydrological homogeneous areas based on their geomorphology. Mean monthly precipitation values from 50 precipitation stations of Thessaly for the hydrological period October 1960–September 1990 were used for the estimation of mean areal precipitation. These precipitation timeseries have been used for the estimation of Standardized Precipitation Index (SPI) for multiple time scales (1-, 3-, 6-, 9-, and 12-months) for each sub-basin or area. The outputs of Global Circulation Model CGCM2 were applied for two socioeconomic scenarios, namely, SRES A2 and SRES B2 for the assessment of climate change impact on droughts. The GCM outputs were downscaled to the region of Thessaly using a statistical methodology to estimate precipitation time series for two future periods 2020–2050 and 2070–2100. A method has been proposed for the estimation of annual cumulative drought severity-time scale-frequency curves. These curves integrate the drought severity and frequency for various types of drought. The SPI timeseries and annual weighted cumulative drought severity were estimated and compared with the respective timeseries and values of the historical period 1960–1990. The results showed that the annual drought severity is increased for all hydrological areas and SPI time scales, with the socioeconomic scenario SRES A2 being the most extreme.


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

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

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