Tripping over spatial scales: a comment on Guay et al. (2000)

2001 ◽  
Vol 58 (10) ◽  
pp. 2105-2107 ◽  
Author(s):  
John G Williams
Keyword(s):  
Spatial Scale ◽  
Hydrodynamic Model ◽  
Field Data ◽  
Spatial Scales ◽  
Hydrodynamic Modeling ◽  
Velocity Fields ◽  
Two Dimensional ◽  
Biological Models ◽  
Habitat Models

Guay et al. (2000.Can.J.Fish.Aquat.Sci.57:2065–2075) report a test of numerical habitat models (NHMs) that combine two-dimensional hydrodynamic modeling of the depth and velocity fields of a stream reach with simple biological models. The hydrodynamic model was tested with field data from randomly chosen points in the stream, and the overall models were tested with observations of fish in a "verification" section of the stream. This is a proper procedure, but the execution and interpretation of the test seem flawed, largely by a misunderstanding of the spatial scales appropriate. The NHMs used by Guay et al. make predictions for patches or "tiles" at a scale of 1–25 m2; the hydrodynamic component of the NHMs needs to be tested at the same spatial scale.

scholarly journals Comparison of West Balkan adult trout habitat predictions using a Pseudo-2D and a 2D hydrodynamic model

2016 ◽  
Vol 48 (6) ◽  
pp. 1697-1709 ◽  
Author(s):  
Christina Papadaki ◽  
Vasilis Bellos ◽  
Lazaros Ntoanidis ◽  
Elias Dimitriou
Keyword(s):  
Hydrodynamic Model ◽  
River Discharge ◽  
Environmental Flow ◽  
Two Dimensional ◽  
Habitat Models ◽  
One Dimensional ◽  
2D Flow ◽  
A Cell ◽  
The One ◽  
Water Depths

Abstract Hydraulic-habitat models combine the dynamic behavior of river discharge with geomorphological and ecological responses. In this study, they are used for estimating environmental flow requirements. We applied a Pseudo-two-dimensional (2D) model based on the one-dimensional (1D) HEC-RAS model and an in-house 2D (FLOW-R2D) hydrodynamic model to a section of river for several flows in respect of summer conditions of the study reach, and compared the results derived from the models in terms of water depths and velocities as well as habitat predictions in terms of weighted usable area (WUA). In general, 2D models are more promising in habitat studies since they quantify spatial variations and combinations of flow patterns important to stream flora and fauna in a higher detail than the 1D models. Relationships between WUA and discharge for the two models were examined, to compare the similarity as well as the magnitude of predictions over the modelled discharge range. The models predicted differences in the location of maxima and changes in variation of velocity and water depth. Finally, differences in spatial distribution (in terms of suitability indices and WUA) between the Pseudo-2D and the fully 2D modelling results can be considerable on a cell-by-cell basis.

scholarly journals Three dimensional flows beneath a thin layer of 2D turbulence induced by Faraday waves

2020 ◽  
Vol 62 (1) ◽  
Author(s):  
Raffaele Colombi ◽  
Michael Schlüter ◽  
Alexandra von Kameke
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Fluid Motion ◽  
Three Dimensional ◽  
Wave Pattern ◽  
Velocity Fields ◽  
Surface Flow ◽  
Two Dimensional ◽  
Faraday Waves ◽  
2D Turbulence

Abstract Faraday waves occur on a fluid being subject to vertical shaking. Although it is well known that form and shape of the wave pattern depend on driving amplitude and frequency, only recent studies discovered the existence of a horizontal velocity field at the surface, called Faraday flow. This flow exhibits attributes of two-dimensional turbulence and is replicated in this study. Despite the increasing attention towards the inverse energy flux in the Faraday flow and other not strictly two-dimensional (2D) systems, little is known about the velocity fields developing beneath the fluid surface. In this study, planar velocity fields are measured by means of particle image velocimetry with high spatio-temporal resolution on the water surface and at different depths below it. A sudden drop in velocity and turbulent kinetic energy is observed at half a Faraday wavelength below the surface revealing that the surface flow is the main source of turbulent fluid motion. The flow structures below the surface comprise much larger spatial scales than those on the surface leading to very long-tailed temporal and spatial velocity (auto-) correlation functions. The three-dimensionality of the flow is estimated by the compressibility, which increases strongly with depth while the divergence changes its appearance from intermittent and single events to a large scale pattern resembling 2D cut-planes of convection rolls. Our findings demonstrate that the overall fluid flow beneath the surface is highly three-dimensional and that an inverse cascade and aspects of a confined 2D turbulence can coexist with a three-dimensional flow. Graphic abstract

scholarly journals Two-dimensional hydrodynamic modeling of residential areas flooding using a highly detailed computational mesh

2020 ◽  
Vol 163 ◽  
pp. 01010
Author(s):  
Alexey Sazonov ◽  
Inna Krylenko ◽  
Alexey Rumyantcev ◽  
Vitaly Belikov ◽  
Natalia Semenova
Keyword(s):  
21St Century ◽  
Relative Position ◽  
Hydrodynamic Model ◽  
Computational Grid ◽  
Hydrodynamic Modeling ◽  
Two Dimensional ◽  
Residential Areas ◽  
Computational Mesh

Modeling of 2016 year flood, the largest flood of the 21st century for the chosen area, was carried out using two-dimensional hydrodynamic model STREAM_2D on the example of Velikiy Ustyug city, located at the confluence of the Sukhona and Yug Rivers. A highly detailed computational grid created in the AutoMesh-2D editor was used for simulations. Specific feature of the created mesh is consideration of shape and relative position of buildings exposed to flooding.

scholarly journals MuSCA: a multi-scale model to explore carbon allocation in plants

2018 ◽  
Author(s):  
F. Reyes ◽  
B. Pallas ◽  
C. Pradal ◽  
F. Vaggi ◽  
D. Zanotelli ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Field Data ◽  
Carbon Allocation ◽  
Spatial Scales ◽  
Computation Time ◽  
Fruit Growth ◽  
Scale Model ◽  
Growth Unit ◽  
Multi Scale ◽  
The Impact

ABSTRACTBackground and aimsCarbon allocation in plants is usually represented at a specific spatial scale, peculiar to each model. This makes the results obtained by different models, and the impact of their scale of representation, difficult to compare. In this work we developed a Multi Scale Carbon Allocation model (MuSCA) that can be applied at different, user-defined, topological scales of a plant, and used to assess the impact of each spatial scale on simulated results and computation time.MethodsModel multi-scale consistency and behavior were tested by applications on three realistic apple tree structures. Carbon allocation was computed at five spatial scales, spanning from the metamer (the finest scale, used as a reference) up to 1st order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data.Key ResultsThe model showed physiological coherence in representing competition for carbon assimilates. Results from intermediate values of the friction parameter best fitted the field data. For these, fruit growth simulated at the metamer scale (considered as a reference) differed from about 1% at growth unit scale up to 35% at first order branch scale. Generally, the coarser the spatial scale the more fruit growth diverged from the reference and the lower the obtained within-tree fruit growth variability. Coherence in the carbon allocated across scales was also differently impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time up to four orders of magnitude.ConclusionsMuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation, suggesting that this factor should be carefully evaluated when using different carbon allocation models or comparing their results. Trades-off between computation time and prediction accuracy can be evaluated by changing topological scales.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

Experimental and Numerical Hydrodynamic Modeling of an Underwater Manipulator

2001 ◽  
Author(s):  
A. Khanicheh ◽  
A. Tehranian ◽  
A. Meghdari ◽  
M. S. Sadeghipour
Keyword(s):  
Drag Coefficient ◽  
Dynamic Modeling ◽  
Hydrodynamic Model ◽  
Degrees Of Freedom ◽  
Added Mass ◽  
Hydrodynamic Modeling ◽  
Degree Of Freedom ◽  
Experimental Results ◽  
Underwater Manipulator ◽  
Three Degrees Of Freedom

Abstract This paper presents the kinematics and dynamic modeling of a three-link (3-DOF) underwater manipulator where the effects of hydrodynamic forces are investigated. In our investigation, drag and added mass coefficients are not considered as constants. In contrast, the drag coefficient is a variable with respect to all relative parameters. Experiments were conducted to validate the hydrodynamic model for a one degree-of-freedom manipulator up to a three degrees-of-freedom manipulator. Finally, the numerical and experimental results are compared and thoroughly discussed.

scholarly journals Characteristics of Climate Change and Extreme Weather from 1951 to 2011 in China

2018 ◽  
Vol 15 (11) ◽  
pp. 2540 ◽  
Author(s):  
Chunli Zhao ◽  
Jianguo Chen ◽  
Peng Du ◽  
Hongyong Yuan
Keyword(s):  
Climate Change ◽  
Spatial Scale ◽  
Spatial Scales ◽  
Seasonal Fluctuation ◽  
Extreme Weather ◽  
Temperature And Precipitation ◽  
Weather Variation ◽  
Variation Characteristics ◽  
Established Fact ◽  
Temporal And Spatial

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.

Scale-dependent relationships between benthic habitat characteristics and abundances of blacklip abalone, Haliotis rubra (Leach)

2010 ◽  
Vol 61 (11) ◽  
pp. 1227 ◽  
Author(s):  
Elisabeth M. A. Strain ◽  
Craig R. Johnson
Keyword(s):  
Spatial Scale ◽  
Red Algae ◽  
Positive Relationship ◽  
Spatial Scales ◽  
Habitat Characteristics ◽  
Benthic Habitat ◽  
Sessile Invertebrates ◽  
Haliotis Rubra ◽  
The Relationship ◽  
Biotic Characteristics

Habitat characteristics can influence marine herbivore densities at a range of spatial scales. We examined the relationship between benthic habitat characteristics and adult blacklip abalone (Haliotis rubra) densities across local scales (0.0625–16 m2), at 2 depths, 4 sites and 2 locations, in Tasmania, Australia. Biotic characteristics that were highly correlated with abalone densities included cover of non-calcareous encrusting red algae (NERA), non-geniculate coralline algae (NCA), a matrix of filamentous algae and sediment, sessile invertebrates, and foliose red algae. The precision of relationships varied with spatial scale. At smaller scales (0.0625–0.25 m2), there was a positive relationship between NERA and ERA, and negative relationships between sediment matrix, sessile invertebrates and abalone densities. At the largest scale (16 m2), there was a positive relationship between NERA and abalone densities. Thus, for some biotic characteristics, the relationship between NERA and abalone densities may be scalable. There was very little variability between depths and sites; however, the optimal spatial scale differed between locations. Our results suggest a dynamic interplay between the behavioural responses of H. rubra to microhabitat and/or to abalone maintaining NERA free of algae, sediment, and sessile invertebrates. This approach could be used to describe the relationship between habitat characteristics and species densities at the optimal spatial scales.

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