Peer-Review Assignment #1: A Summary of Silva & Taborda's "Integration of beach hydrodynamic and morphodynamic modelling in a GIS environment"
This article showcases a geoprocessing tool called “Beach Morphodynamic Modelling” (or “BeachMM”), created and developed by Silva and Taborda, using the Python scripting language within an ArcGIS 10.0 environment. The authors discuss the merits, flexibility, and extended software integration capabilities of ArcGIS and Python, in greatly simplifying a complex hydro-morphodynamic modelling process at a study site on the west coast beach stretch of Nazaré, Portugal in Europe. The BeachMM tool is freely available for download at http://disepla.fc.ul.pt/Micore/Micore.html. Before continuing, I would like to briefly define what these two, intimidating, five-syllables-long words mean:
- Hydrodynamics – “a branch of physics that deals with the motion of fluids and the forces acting on solid bodies immersed in fluids and in motion relative to them” (Merriam-Webster). Simply put, how does water act when it’s in motion? Are there any attributing objects affecting the pressure of water in motion? Is the direction in which the water is moving important, relative to other factors, etc.?
- Morphodynamics – “refers to the study of the interaction and adjustment of the seafloor topography and fluid hydrodynamic processes, seafloor morphologies and sequences of change dynamics involving the motion of sediment” (Wikipedia). Simply put, morphodynamics focuses on the transportation of sediments through water in motion, as well as the effects and physical (geological) formations in coastal areas because of it.
The authors of this article do not define these terms, as I did above, most likely because the audiences reading it probably already know them. For me, however, this article forced me to do my own little research on these terms to better understand and appreciate the value of this study. The word “dynamic” seems like an understatement when imagining all the variables involved in these sciences. But the main thing to remember here is that hydrodynamics and morphodynamics are a result and effect of each other.
Continuing, in their article, Silva and Taborda explain that since the beginning of the 20th century, the increase of human interaction in coastal areas has brought to light the importance of updating coastal management policies and procedures in the event of coastal hazards. In case you were wondering, coastal hazards refer to “physical phenomena that expose a coastal area to risk of property damage, loss of life and environmental degradation” (Wikipedia). The article explains that predictive models simulating physical processes and supplying quantitative data are indicative of effectively updating and appropriately creating coastal management policies and procedures for dealing with potential coastal hazards. The authors go into detail by writing about the two most powerful coastal, hydro-morphodynamic models available now: SWAN and XBeach. The authors define SWAN as a model that estimates different wave parameters, and takes into account “several physical processes and represents its effects on spatial wave propagation, refraction, shoaling, generation, dissipation and non-linear wave-wave interactions” in coastal areas; while XBeach is a “numerical model for nearshore processes intended as a tool to compute the natural coastal response during time-varying storm and hurricane conditions”. The authors go in-depth as to how these models operate and generate outputs based on input parameters, configurations, data formats, and more. Unfortunately, an error free data compilation of both models’ outputs is impossible before additional, complex, meticulous, and cumbersome compatible adjustments are made. This is where BeachMM comes into play.
BeachMM basically integrates both SWAN and XBeach modelling capabilities into one tool in ArcGIS. The extensive functionality of GIS programming with Python in ArcGIS allows for easier interoperability and exchange of information between SWAN and XBeach. Specifically, the BeachMM tool implements the following four main tasks:
Continuing, in their article, Silva and Taborda explain that since the beginning of the 20th century, the increase of human interaction in coastal areas has brought to light the importance of updating coastal management policies and procedures in the event of coastal hazards. In case you were wondering, coastal hazards refer to “physical phenomena that expose a coastal area to risk of property damage, loss of life and environmental degradation” (Wikipedia). The article explains that predictive models simulating physical processes and supplying quantitative data are indicative of effectively updating and appropriately creating coastal management policies and procedures for dealing with potential coastal hazards. The authors go into detail by writing about the two most powerful coastal, hydro-morphodynamic models available now: SWAN and XBeach. The authors define SWAN as a model that estimates different wave parameters, and takes into account “several physical processes and represents its effects on spatial wave propagation, refraction, shoaling, generation, dissipation and non-linear wave-wave interactions” in coastal areas; while XBeach is a “numerical model for nearshore processes intended as a tool to compute the natural coastal response during time-varying storm and hurricane conditions”. The authors go in-depth as to how these models operate and generate outputs based on input parameters, configurations, data formats, and more. Unfortunately, an error free data compilation of both models’ outputs is impossible before additional, complex, meticulous, and cumbersome compatible adjustments are made. This is where BeachMM comes into play.
BeachMM basically integrates both SWAN and XBeach modelling capabilities into one tool in ArcGIS. The extensive functionality of GIS programming with Python in ArcGIS allows for easier interoperability and exchange of information between SWAN and XBeach. Specifically, the BeachMM tool implements the following four main tasks:
- Conversion between different bathymetric raster formats;
- Automatic creation of model input parameter files according to user input and bathymetric grid properties;
- Save model output in ArcGIS compatible formats; and
- Call the external models to run within the ArcGIS
In short, BeachMM is a productive, time-saving tool that removes margin of error, automates the compilation of data formats, and visually displays results with minimal, manual user interaction. It’s safe to say that the integration of programming in GIS can be a game-changer when time is of essence.
Silva, A. M. A. N., & Taborda, R. P. M. (2013). Integration of beach hydrodynamic and morphodynamic modelling in a GIS environment. The Journal of Coastal Conservation – Springer Science+Business Media B.V., 201-210. Retrieved June 14, 2017, from https://hostsited2l.uwf.edu/content/enforced/998343-50402GIS5103201705/SupplementalReadings/PotentialsForPeerReview/Silva_et_al_2013.pdf?_&d2lSessionVal=DC5sP9N0JWX3zJRP9TZxsHauH&ou=998343.
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