An algorithm to generate 2D bathymetry of an Alpine river for habitat suitability assessment.

Here we present an original approach to generate 2D high detail riverbed based on a drone photogrammetric survey, and RTK bathymetry measurements for Mera river in the Italian Alps. The aim is to better represent macro-roughness and riverbed structure of the river, also extending it to an ungauged area. Specifically, we apply a step-by-step approach. I) Depth and average slope of the riverbed were calculated from bathymetry data. II) Thus, a trapezoidal channel with constant slope and variable width was defined using the drone images. III) Riffle-pool sequence was assessed as a function of river width and applied to the generated channel. IV) Finally, the semi-random Perlin Noise was added to recreate riverbed irregularities in the natural stream. HEC-RAS 2D hydraulic software was then implemented to assess spatialized water depth and velocity. The proposed methodology could be quite relevant in river hydraulics to decouple roughness coefficient from water submergence, and in Physical Habitat Simulation Model (PHABSIM), where the dependency of the output is not linear with hydraulic parameters (i.e. water depth and velocity). Indeed, we apply PHABSIM for a case study of a stretch of the river and results are compared with a previous environmental study for Mera river.

Soil erosion and sediment transport under climate change for Mera River, in Italian Alps of Valchiavenna.

Erosion is a main form of soil degradation, with severe consequences on slope stability and productivity, and erosion studies are required to predict possible variations of such phenomena, also under climate change scenarios. Here we estimated distributed soil erosion within Valchiavenna valley in the Rhaetian Alps, drained by Mera river, and covering Italy, and Switzerland. We used a Dynamic-RUSLE (D-RUSLE) model, which provides spatially distributed estimates of soil erosion explicitly considering snow dynamic (accumulation/melting) and snow cover, and vegetation seasonality. The model was tuned here during 2010-2019, and validation was pursued using river turbidity data, used to assess riverine sediment transport. The model parameter R-factor for rainfall erosivity was estimated using a hydrological model Poli-Hydro, properly set up in the study area. C-factor for land cover was assessed against land cover maps, with seasonally variable Normalized Difference Vegetation Index from satellite images, to account for variable vegetation stage, and large leaf cover in summer. The K-factor related to erosion susceptibility was evaluated through soil texture and organic content. LS-factor depending on slope was assessed using a DTM. Poli-Hydro and D-RUSLE models were then used to project forward potential soil erosion under climate change scenarios until 2100. Climate series (temperature, precipitation) were generated using 4 shared socio-economic pathways (SSPs) of the Sixth Assessment Report of the IPCC, with 3 global circulation models, properly downscaled locally. We analysed expected soil erosion during 2051-2060, and 2091-2100. We found increase of potential soil erosion, with exception of the EC-Earth model for the SSP2.6. Erosion would especially increase in winter, in response to smaller snow accumulation, and larger liquid rainfall share thereby, and decrease in summer, as due to decreased precipitation. Our results suggest the need for adaptation strategies to counteract increasing soil loss in the future, and may highlight most critical areas of intervention.

Seasonal variations in the optical characteristics of dissolved organic matter in glacial pond water.

Large amounts of dissolved organic matter (DOM) are stored in mountain glaciers. However, few researches have analysed the optical characteristics of DOM in surface waters fed by mountain glaciers and their seasonal variations. In a pond fed by a glacier we observed simultaneous decreases in the dissolved organic carbon, and increases in both absorbance at 254 nm and specific absorption coefficient (SUVA254) during the ice-free season 2015. This behaviour differs from the typical behaviour of lake/pond water in summer, and from the trends observed in a nearby pond not fed by a glacier. The trends of DOM properties, main ions and water stable isotopes at the glacier-fed pond could be attributed to transient modifications of the subglacial hydrological system. Flushing of previously isolated pools of subglacially stored water, containing terrestrial DOM derived from glacially-overridden soil and vegetation, would be driven by intense rainfall events during the melting season. These findings suggest that heavy rainfall events during the melting season have the capability to transiently modify the characteristics of DOM in a glacial pond. These events may be further exacerbated in the future, as summer rainfall events in the Alps are predicted to increase due to global warming.

Coupling multitemporal remote sensing with geomorphology and hydrological modeling for post flood recovery in the Strymonas dammed river basin (Greece).

We present a case study of a long-term integrated monitoring of a flood event which affected part of the Strymonas dammed river basin, a transboundary river with source in Bulgaria, which flows then through Greece to the Aegean Sea. The event, which affected the floodplain downstream the Kerkini dam, started at the beginning of April 2015, due to heavy rain upstream of the monitored area, and lasted for several months, with some water pools still present at the beginning of September, due to the peculiar geomorphological conditions of the watershed. We collected a multi-temporal dataset consisting of a high-resolution, X-band COSMO-SkyMed, and several C-band Sentinel-1 SAR and optical Landsat-8 images of the area. The results allow following the event in time, sketching a multi-temporal map of the post-flood evolution, with relatively high temporal resolution. We then use hydrological modeling to mimic the dynamics of the flooded area against post event weather patterns and thus explain the observed flood extent evolution. We show how integrating remote sensing-derived maps of flooded areas, geomorphological analyses of the landscape and simplified hydrological modeling allows accurate inference about long-term dynamics of flooded areas, very important in the post event in anthropogenic highly modified areas, where recovery time after the flood event is considerable, and long term water persistence may lead to large consequences, carrying economic damages and medical emergencies.