Prediction of ecological status of surface water bodies with supervised machine learning classifiers.

Ensuring a good ecological status of water bodies is one of the key challenges of communities and one of the objectives of the European Water Framework Directive. Although recent works identified the most significant stressors affecting the ecological quality of rivers, the ability to predict the overall ecological status of rivers based on a limited amount of easily accessible geospatial data has not been investigated so far. Most of the analyses focus on detailed local modelling and measurements which cannot be systematically applied at regional scales for the purposes of water resources management. The aim of this work is to understand the capabilities of five supervised machine learning classifiers of predicting the ecological status of rivers based on land use, climate, morphology, and water management parameters extracted over the river catchments corresponding to the ecological monitoring stations. Moreover, the performances of machine learning classifiers are compared to the results of the canonical correlation analysis. The method is applied to 360 catchments in Tuscany (central Italy) with a median size of 33.6 km2 and a Mediterranean climate. The results show (i) a significant correlation of ecological status with summer climate (i.e., maximum temperatures and minimum precipitation), land use and water exploitation, (ii) an 80 % precision of Random Forest algorithm to predict ecological status and (iii) higher capability of all classifiers to predict at least good ecological status. In perspective, such predictive capabilities can support decision making in the land and water resources management and highlight strategies for river eco-hydrological conservation.

Calcite moonmilk of microbial origin in the Etruscan Tomba degli Scudi in Tarquinia, Italy.

A white deposit covering the walls in the Stanza degli Scudi of the Tomba degli Scudi, Tarquinia, Italy, has been investigated. In this chamber, which is still preserved from any kind of intervention such as cleaning and sanitization, ancient Etruscans painted shields to celebrate the military power of the Velcha family. Scanning electron microscopy analysis has revealed the presence of characteristic nanostructures corresponding to a calcite secondary mineral deposit called moonmilk. Analysis of the microbial community identified Proteobacteria, Acidobacteria and Actinobacteria as the most common phyla in strong association with the moonmilk needle fibre calcite and nanofibers of calcium carbonate. Employing classical microbiological analysis, we isolated from moonmilk a Streptomyces strain able to deposit gypsum and calcium carbonate on plates, supporting the hypothesis of an essential contribution of microorganisms to the formation of moonmilk.

Quantification of flood risk mitigation benefits: A building-scale damage assessment through the RASOR platform.

Flood risk mitigation usually requires a significant investment of public resources and cost-effectiveness should be ensured. The assessment of the benefits of hydraulic works requires the quantification of (i) flood risk in absence of measures, (ii) risk in presence of mitigation works, (iii) investments to achieve acceptable residual risk. In this work a building-scale is adopted to estimate direct tangible flood losses to several building classes (e.g. residential, industrial, commercial, etc.) and respective contents, exploiting various sources of public open data in a GIS environment. The impact simulations for assigned flood hazard scenarios are computed through the RASOR platform which allows for an extensive characterization of the properties and their vulnerability through libraries of stage-damage curves. Recovery and replacement costs are estimated based on insurance data, market values and socio-economic proxies. The methodology is applied to the case study of Florence (Italy) where a system of retention basins upstream of the city is under construction to reduce flood risk. Current flood risk in the study area (70 km2) is about 170 Mio euros per year without accounting for people, infrastructures, cultural heritage and vehicles at risk. The monetary investment in the retention basins is paid off in about 5 years. However, the results show that although hydraulic works are cost-effective, a significant residual risk has to be managed and the achievement of the desired level of acceptable risk would require about 1 billion euros of investments.

A role for microbial selection in frescoes' deterioration in Tomba degli Scudi in Tarquinia, Italy.

Mural paintings in the hypogeal environment of the Tomba degli Scudi in Tarquinia, Italy, show a quite dramatic condition: the plaster mortar lost his cohesion and a white layer coating is spread over almost all the wall surfaces. The aim of this research is to verify if the activity of microorganisms could be one of the main causes of deterioration and if the adopted countermeasures (conventional biocide treatments) are sufficient to stop it. A biocide treatment of the whole environment has been carried out before the conservative intervention and the tomb has been closed for one month. When the tomb was opened again, we sampled the microorganisms present on the frescoes and we identified four Bacillus species and one mould survived to the biocide treatment. These organisms are able to produce spores, a highly resistant biological form, which has permitted the survival despite the biocide treatment. We show that these Bacillus strains are able to produce calcium carbonate and could be responsible for the white deposition that was damaging and covering the entire surface of the frescoes. Our results confirm that the sanitation intervention is non always resolutive and could even be deleterious in selecting harmful microbial communities.