Abstract
The Versilia plain, a well-known and populated tourist area in northwestern Tuscany, is historically subject to floods. The last hydrogeological disaster of 1996 resulted in 13 deaths and in loss worth hundreds of millions of euros. A valid management of the hydraulic and flooding risks of this territory is therefore mandatory. A 7.5 km-long stretch of the Versilia River was simulated in one-dimension using river cross-sections with the FLO-2D Basic model. Simulations of the channel flow and of its maximum flow rate under different input conditions highlight the key role of topography: uncertainties in the topography introduce much larger errors than the uncertainties in roughness. The best digital elevation model (DEM) available for the area, a 1-m light detection and ranging (LiDAR) DEM dating back to 2008–2010, does not reveal all the hydraulic structures (e.g., the 40 cm thick embankment walls), lowering the maximum flow rate to only 150 m3/s, much lower than the expected value of 400 m3/s. In order to improve the already existing input topography, three different possibilities were considered: (1) to add the embankment walls to the LiDAR data with a targeted Differential GPS (DGPS) survey, (2) to acquire the cross section profiles necessary for simulation with a targeted DGPS survey, and (3) to achieve a very high resolution topography using structure from motion techniques (SfM) from images acquired using an unmanned aerial vehicle (UAV). The simulations based on all these options deliver maximum flow rates in agreement with estimated values. Resampling of the 10 cm cell size SfM-DSM allowed us to investigate the influence of topographic resolution on hydraulic channel flow, demonstrating that a change in the resolution from 30 to 50 cm alone introduced a 10% loss in the maximum flow rate. UAV-SfM-derived DEMs are low cost, relatively fast, very accurate, and they allow for the monitoring of the channel morphology variations in real time and to keep the hydraulic models updated, thus providing an excellent tool for managing hydraulic and flooding risks.
Highlights
Heavy rainfall is commonly the most important cause of flooding
Since each cell of the computational domain lying on the left bank of the river (441 cells) needed to be associated with one profile, the missing sections were linearly interpolated from the sections derived from digital elevation model (DEM)
The average spacing between the DEM-derived sections complied with the indications of the FLO-2D reference manual [30], which suggests a spacing between input sections of 5–10 grid elements
Summary
Heavy rainfall is commonly the most important cause of flooding. anthropogenic activities (agriculture, land-use changes, hydraulic modifications and structures, etc.) may contribute to reducing the river capacity to receive the discharge [1,2,3,4]. Dimitriadis et al [11] made a comparative evaluation of 1D and quasi-2D hydraulic models, including FLO-2D, by performing a sensitivity test of the most important hydraulic variables (inflow, channel and floodplain slope and roughness) in simplified channel geometries and in two real-world applications While these authors considered a perfectly known geometry of the model domain in order to avoid the influence of complex topography, we considered a real case channel and we focused on the influence of complex channel geometry by varying the resolution of the input topographic data representing the channel. We compared different acquisition methods such as light detection and ranging (LiDAR), unmanned aerial vehicle (UAV) photo acquisition coupled with structure from motion (SfM) technique and a GPS campaign These methods have different acquisition and post-processing times, resolution, and cost, and produce different simulation results. Following the lead of Arduino et al [8], we updated the 2008 LiDAR data with UAV-SfM data to create an additional accurate channel topography, suitable for numerical hydraulic simulation
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