Deterministic chaotic dynamics of Raba River flow (Polish Carpathian Mountains)

Kędra, Mariola

doi:10.1016/j.jhydrol.2013.11.055

Cited by 24 publications

(13 citation statements)

References 71 publications

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“…Not only the regional scale but also the catchment scale was taken into account as an appropriate scale for assessing both LC and climate changes, as well as for modeling their impacts on soil properties and hydrological processes (Routschek, Schmidt, & Kreinenkamp, ). The main advantage of using the catchment as a biogeophysical unit is the analysis carried out at the system level, because the catchment is a dynamical system that integrates the interactions between processes taking place in the catchment through the system's physics (e.g., Kędra, ; Kirchner, ). Analysis at the system level, like at the process level, can in turn facilitate modeling and forecasting of the system's operation and its better management.…”

Section: Introductionmentioning

confidence: 99%

Land cover transitions and changing climate conditions in the Polish Carpathians: Assessment and management implications

Kędra

Szczepanek

2019

Land Degrad Dev

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Widespread, human‐induced land cover (LC) transitions in areas surrounding national parks and nature reserves, accompanied by changing climate conditions, can trigger serious consequences for these natural environments and their ecosystems. The aim of the study was to assess the direction and magnitude of transitions in LC in the Polish Carpathians since 1990 for determining the current status of land degradation neutrality and future degradation risk as well as to analyze concomitant changes in climate conditions to enable sustainable land management. The study area encompasses six national parks with the United Nations Educational, Scientific, and Cultural Organization biosphere reserves, several dozen nature reserves, and landscape parks and is a key source of drinking water in Poland. We studied detailed changes in LC (13 classes). The Wilcoxon signed rank test indicated significant increases in built‐up areas (urban fabric and industrial/transport infrastructure), waters, dense forest cover, and herbaceous vegetation but a decrease in heterogeneous agricultural areas. On the basis of two new methods, we assessed the LC transitions for 20 mountain catchments and for the entire Polish Carpathians. Although we found a slight positive transition in LC for the entire Polish Carpathians, clearly negative transitions occurred in the five analyzed catchments, including those covering two national parks. These LC transitions are accompanied by changing climate conditions with significant increases in air temperature and precipitation. The ongoing intensive urbanization in the studied mountain region, which is accompanied by significant regional warming, implies the need to apply sustainable management practices that will avoid or reduce degradation in the catchments involved.

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Section: Introductionmentioning

confidence: 99%

Land cover transitions and changing climate conditions in the Polish Carpathians: Assessment and management implications

Kędra

Szczepanek

2019

Land Degrad Dev

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“…(2) Similar to the idea of the false neighbor method (FNN) [62], Cao [57] proposed the method of the averaged false nearest neighbors (AFN), AFN defines a quantity:…”

Section: Reconstruction Parameter Of Phase Spacementioning

confidence: 99%

“…Otherwise, E1(m) will not attain a saturated value. Since available samples are limited, random time series may happen that the E1(m) stops changing at some m. Therefore, we defined E2(m), which is used to distinguish whether a set of data is deterministic or random [57,62].…”

Section: Reconstruction Parameter Of Phase Spacementioning

confidence: 99%

Spatiotemporal Variations of Extreme Precipitation and Study on Chaotic Characteristics in the Xijiang River Basin, China

Ding

Liao

Wang

et al. 2019

Water

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Climate change leads to the increase of frequency and intensity for extreme precipitation events, potentially threatening the development of our society. It is of great significance to study the spatiotemporal variation of precipitation for understanding cycle process of water and its response to global warming. This paper selects the Xijiang River basin, which locates on a low latitude and coastland, as the research area. The spatiotemporal distribution and homogeneity of precipitation are analyzed, and the spatial trend is studied using 12 extreme precipitation indices. Finally, chaotic characteristics are evaluated for daily precipitation. The results showed that the precipitation in the basin tended to be unevenly distributed. On wet days, precipitation in the middle and the west was more and more uniform. The proportion of tiny rain was the largest, between 33.5% and 41.3%. The proportion of violent rain was the smallest, between 0.1% and 4.7%. Duan had the highest frequency for violent rain, and the probability of disasters caused by extreme precipitation near the station was the highest. The simple daily intensity index (SDII) showed a significant increase in the middle and the northeast. PRCPTOT (annual total wet-day precipitation) showed a decreasing trend in the northwest. The average rates of variation for R95PTOT (precipitation on very wet days) and R99PTOT (precipitation on extremely wet days) were −0.01 mm/year and 0.06 mm/year, respectively. There might be a risk of drought on the west of the basin in the future. Precipitation in other locations was still relatively abundant. Daily precipitation showed high dimension and high chaotic characteristics. The MED (minimum embedding dimension) was between 11 and 30, and the MLE (largest Lyapunov exponent) was between 0.037 and 0.144.

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“…During the last two decades, research has shown that seemingly complex time series of streamflow could be better understood using nonlinear chaotic models as compared to stochastic techniques. For instance, Kędra (2014) investigated discharge dynamics of the Raba River in southern Poland using several independent methods and concluded that underlying dynamics are not random but deterministic. Similar results were recently obtained by Hassan and Ansari (2010), Xu et al (2010), Sivakumar and Singh (2012), Khatibi et al (2012), and Kalteh and Berndtsson (2007).…”

Section: Introductionmentioning

confidence: 99%

Impact of complexity on daily and multi-step forecasting of streamflow with chaotic, stochastic, and black-box models

Tongal

Berndtsson

2016

Stoch Environ Res Risk Assess

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Despite significant research advances achieved during the last decades, seemingly inconsistent forecasting results related to stochastic, chaotic, and black-box approaches have been reported. Herein, we attempt to address the entropy/complexity resulting from hydrological and climatological conditions. Accordingly, mutual information function, correlation dimension, averaged false nearest neighbor with E1 and E2 quantities, and complexity analysis that uses sample entropy coupled with iterative amplitude adjusted Fourier transform were employed as nonlinear deterministic identification tools. We investigated forecasting of daily streamflow for three climatologically different Swedish rivers, Helge, Ljusnan, and Kalix Rivers using self-exciting threshold autoregressive (SETAR), k-nearest neighbor (k-nn), and artificial neural networks (ANN). The results suggest that the streamflow in these rivers during the 1957-2012 period exhibited dynamics from low to high complexity. Specifically, (1) lower complexity lead to higher predictability at all leadtimes and the models' worst performances were obtained for the most complex streamflow (Ljusnan River), (2) ANN was the best model for 1-day ahead forecasting independent of complexity, (3) SETAR was the best model for 7-day ahead forecasting by means of performance indices, especially for less complexity, (4) the largest error propagation was obtained with the k-nn and ANN and thus these models should be carefully used beyond 2-day forecasting, and (5) higher number input variables except for the dominant variables made insignificant impact on forecasting performances for ANN and k-nn models.

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Deterministic chaotic dynamics of Raba River flow (Polish Carpathian Mountains)

Cited by 24 publications

References 71 publications

Land cover transitions and changing climate conditions in the Polish Carpathians: Assessment and management implications

Land cover transitions and changing climate conditions in the Polish Carpathians: Assessment and management implications

Spatiotemporal Variations of Extreme Precipitation and Study on Chaotic Characteristics in the Xijiang River Basin, China

Impact of complexity on daily and multi-step forecasting of streamflow with chaotic, stochastic, and black-box models

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