Coastal vulnerability assessment based on video wave run-up observations at a mesotidal, steep-sloped beach

Coastal imagery obtained from a coastal video monitoring station installed at Faro Beach, S. Portugal, was combined with topographic data from 40 surveys to generate a total of 456 timestack images. The timestack images were processed in an open-access, freely available graphical user interface (GUI) software, developed to extract and process time series of the cross-shore position of the swash extrema. The generated dataset of 2% wave run-up exceedence values R 2 was used to form empirical formulas, using as input typical hydrodynamic and coastal morphological parameters, generating a best-fit case RMS error of 0.39 m. The R 2 prediction capacity was improved when the shore-normal wind speed component and/or the tidal elevation η tide were included in the parameterizations, further reducing the RMS errors to 0.364 m. Introducing the tidal level appeared to allow a more accurate representation of the increased wave energy dissipation during low tides, while the negative trend between R 2 and the shore-normal wind speed component is probably related to the wind effect on wave breaking. The ratio of the infragravity-to-incident frequency energy contributions to the total swash spectra was in general lower than the ones reported in the literature E infra/E inci > 0.8, since low-frequency contributions at the steep, reflective Faro Beach become more significant mainly during storm conditions. An additional parameterization for the total run-up elevation was derived considering only 222 measurements for which η total,2 exceeded 2 m above MSL and the best-fit case resulted in RMS error of 0.41 m. The equation was applied to predict overwash along Faro Beach for four extreme storm scenarios and the predicted overwash beach sections, corresponded to a percentage of the total length ranging from 36% to 75%.info:eu-repo/semantics/publishedVersio

A Simple System Dynamics Model for the Global Production Rate of Sand, Gravel, Crushed Rock and Stone, Market Prices and Long-Term Supply Embedded into the WORLD6 Model

A model for global supply of sand, gravel and cut stone for construction based on a system dynamics model was developed for inclusion in the WORLD6 model. The Sand-Gravel-Stone model simulates production and market supply, demand and price for natural sand and gravel, sand and gravel from crushed rock and cut stone. The model uses market mechanisms where the demand is depending on population size, maintenance and price. For the period 2000–2050, the WORLD6 model outputs correlate with the GINFORS model outputs (r 2 = 0.98), but they may take different pathways after 2050. The resources of sand and gravel are estimated at 12 trillion ton each, another 125 trillion tons of rock is suitable for crushing to sand and gravel and at least 42 trillion ton of quality stone is available for production of cut stone. The simulation, under assumed business-as-usual conditions, shows that cut stone production will reach a maximum level by about 2020–2030 and stabilize after that. The cause for this is that demand exceeds extraction as well as slow exhaustion of the known reserves of high-quality stone. Sand and gravel show plateau behaviour and reach their maximum production rate in 2060–2070. The reason for the slight peak towards a plateau behaviour is partly driven by an expected population decline and increasing prices for sand and gravel, limiting demand. Assuming business-as-usual conditions rates remain at that level for centuries