Selecting model scenarios of real hydrodynamic forcings on mesotidal and macrotidal estuaries influenced by river discharges using K-means clustering

Bárcena, Javier F.; Camus, Paula; Garcı́a, Andrés; Álvarez, César

doi:10.1016/j.envsoft.2015.02.007

Cited by 24 publications

(12 citation statements)

References 47 publications

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“…As a result, a preliminary study embraces all possible plume patterns is necessary, and a first step is to target the general behavior of the estuarine-plume system. Bárcena et al, (2015) explained that two approaches may be conducted for that: simulating several scenarios using constant conditions of hydrodynamic forcings or simulating few scenarios using the most frequent or extreme real hydrodynamic forcings during short-medium term periods (month to year).…”

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

“…Also, without any prior information on the cluster structure (sphericity of clusters, possible overlap) the fuzzy c-mean provides better results than its crisp counterpart (Selim & Kamel, 1992). As a result, hydrologic and climatologic combinations can be identified by fuzzy-cmean (Kim et al, 2011;Zhang et al, 2011;Bárcena et al, 2015).…”

Section: Fuzzy C-mean Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

A fuzzy classification of the hydrodynamic forcings of the Rhone River plume: An application in case of accidental release of radionuclides

Delaval

Duffa²,

Pairaud³

et al. 2021

Environmental Modelling & Software

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Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

Section: Fuzzy C-mean Algorithmmentioning

confidence: 99%

A fuzzy classification of the hydrodynamic forcings of the Rhone River plume: An application in case of accidental release of radionuclides

Delaval

Duffa²,

Pairaud³

et al. 2021

Environmental Modelling & Software

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“…A comparison between the original tide series and the synthetic time series reconstructed with the clusters derived from these classifications was performed using the efficiency coefficient (CE). CE was selected because it is the best objective function for reflecting the overall adjustment of a clustering output (Bárcena et al., 2015). CE is a normalized statistic developed by Nash and Sutcliffe (1970) that determines the relative magnitude of the residual variance ( noise ) and therefore reflects the accuracy with which the centroids estimate the original data (Equation ):

C E = \frac{true \sum_{1}^{n} {false(O_{i} - C_{i} false)}^{2}}{true \sum_{1}^{n} {false(O_{i} - Ō false)}^{2}},

where O i is the i‐data ( γ 1 , g 2 , or TR) of the original series, C i is the i‐data ( γ 1 , g 2 , or TR) of the representative centroid and n is the number of nodes where the tide is evaluated.…”

Section: Statistical and Cluster Analysis Of Global Tide Asymmetrymentioning

confidence: 99%

A Global Classification of Astronomical Tide Asymmetry and Periodicity Using Statistical and Cluster Analysis

2020

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Tidal asymmetry plays a key role in the behavior of estuaries. Positive and negative asymmetries are associated with flood‐ and ebb‐dominated estuaries, respectively. Asymmetry arises from both the interaction among the main tidal constituents and the harmonics generated when tide propagates in shallow waters. Most previous research focuses on the deformation of the tide within estuaries; however, ocean tide may show asymmetry at the estuary entrance, which implies that the boundary condition is already deformed. This fact has important implications for tide propagation, estuarine transport processes, and flow exchanges between estuaries and open oceans. In this study, the global astronomical tide is classified according to its asymmetry and periodicity. The objective is to provide a guiding framework of representative astronomical tide types (ATtypes) on a worldwide scale to be used as a reference for further research on the transport of substances in estuaries. The applied methodology is based on the use of the TPXO9‐atlas global barotropic tidal solution and detailed statistical analysis. Probability density functions of the tidal elevation time derivative and the tidal form factor were extracted from TPXO9‐atlas with a spatial resolution ranging from 1/6° to 1/30°. The K‐means algorithm was applied to these parameters, and 25 representative ATtypes were identified. The classification was validated with 757 worldwide tide gauge records. The results show that 11.3% of coastal areas show negative asymmetries, 11.3% positive asymmetries, while symmetric tides dominate 77.4% of coastal areas. In these areas, estuaries can show asymmetries exclusively dependent on overtides and compound tides generated during inland propagation without being externally conditioned.

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“…In the first step, the k-means algorithm was used to partition the changed land use cells during T1 to T2 into five clusters. The k-means clustering technique is capable of dividing multidimensional data into a number of clusters by defining prototypes and calculating the distance to each prototype (Bárcena et al 2015). It is commonly used to automatically partition a data set into k groups by selecting k initial cluster centers and then iteratively refining them as follows:…”

Section: Partitioning the Research Area By K-means And Knn-cluster Almentioning

confidence: 99%

A partitioned and asynchronous cellular automata model for urban growth simulation

Zeng

2015

International Journal of Geographical Information Science

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Cellular automata (CA) models are used to analyze and simulate the global phenomenon of urban growth. However, these models are characterized by ignoring spatially heterogeneous transition rules and asynchronous evolving rates, which make it difficult to improve urban growth simulations. In this paper, a partitioned and asynchronous cellular automata (PACA) model was developed by implementing the spatial heterogeneity of both transition rules and evolving rates in urban growth simulations. After dividing the study area into several subregions by k-means and knn-cluster algorithms, a C5.0 decision tree algorithm was employed to identify the transition rules in each subregion. The evolving rates for cells in each regularly divided grid were calculated by the rate of changed cells. The proposed PACA model was implemented to simulate urban growth in Wuhan, a large city in central China. The results showed that PACA performed better than traditional CA models in both a cell-to-cell accuracy assessment and a shape dimension accuracy assessment. Figure of merit of PACA is 0.368 in this research, which is significantly higher than that of partitioned CA (0.327) and traditional CA (0.247). As for the shape dimension accuracy, PACA has a fractal dimension of 1.542, which is the closest to that of the actual land use (1.535). However, fractal dimension of traditional CA (1.548) is closer to that of the actual land use than that of partitioned CA (1.285). It indicates that partitioned transition rules play an important role in the cell-to-cell accuracy of CA models, whereas the combination of partitioned transition rules and asynchronous evolving rates results in improved cell-to-cell accuracy and shape dimension accuracy. Thus, implementing partitioned transition rules and asynchronous evolving rates yields better CA model performance in urban growth simulations due to its accordance with actual urban growth processes. ARTICLE HISTORY

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Selecting model scenarios of real hydrodynamic forcings on mesotidal and macrotidal estuaries influenced by river discharges using K-means clustering

Cited by 24 publications

References 47 publications

A fuzzy classification of the hydrodynamic forcings of the Rhone River plume: An application in case of accidental release of radionuclides

A fuzzy classification of the hydrodynamic forcings of the Rhone River plume: An application in case of accidental release of radionuclides

A Global Classification of Astronomical Tide Asymmetry and Periodicity Using Statistical and Cluster Analysis

A partitioned and asynchronous cellular automata model for urban growth simulation

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