|ABSTRACT||Mediterranean beaches are characterized by lack of sand, microtidal regime, and a very intensive social and economic use; therefore they are very vulnerable to climate change driven impacts like sea level rise and increase of storm intensity. So there is an urgent need of instruments to measure vulnerability; assess existing management practices, and inform a more efficient daily management practice.
We propose a LIDAR-based instrument to identify dysfunctional beach stretches, its vulnerability to climatic change, and inform evidence-based management systems in order to adapt Mediterranean beaches to climatic change.
Currently, the most widely-used information sources are numerical models that simulate the hydrodynamic and morphodynamic processes that govern sediment availability and predict the impacts produced by storms. Regarding beach management, these models have three main flaws. (1) Some relevant factors are undetectable to numerical models; the most relevant being aeolian sand transport and its interactions with human activity. (2) There are wide information gaps along the Mediterranean coast, because of the need of long-term data (preferably more than 20 years) provided by expensive sensors, like directional wave buoys. Lastly, (3) as numerical models are optimized to explain what happens in the course of extreme events, it is difficult to inform daily beach management, urban planning, and give clues to adapt to climatic change.
The vertical accuracy of LIDAR data can be re-calibrated by comparing elevation values obtained by other sources, so reducing mean error and giving RMS values as low as 8 cm. The differentiation of the LIDAR data in a set of equal length cells (usually 100 m) leads to the transformation of the beach in a sequence of points containing three-dimensional information. To assess the efficiency of this instrument, we studied two different beach cells (with different sand grain diameters and morphodynamic beach states) at Catalonia, NE Spain.
Some of the most relevant outcomes were the following:
• The scatterplots of beach width and volume and also when comparing beach volume and average slope, showed characteristic patterns that change with sand grain diameter.
• The analysis of outliers led to rapid identification of dysfunctional hot-spots and its causal processes.
• Volume of emerged sand and average beach slope provide reliable spatial-explicit information of vulnerability.
• Analysis and comparison between different LIDAR flights, and its correlates with well-known formulations for wave run-up and horizontal maximum wave reach for different return periods, can lead to reliable short-term scenarios.
As a final conclusion, LIDAR data constitute a cheaper, faster and with increasing accuracy source of information that can help to fill the information gap along the Mediterranean coast, and provide much of the needed information to adapt to climate change.|