Effects of flooding on coastal vegetation and salt marshes

This thesis examines the effects of flooding on coastal and salt marsh vegetation. I conducted a field experiment in Bellocchio Lagoon to test the effects of different inundation periods (Level 1 = 0.468 or 11.23 hours; Level 2 = 0.351 or 8.42 hours; Level 3 = 0.263 or 6.312 hours; Level 4 = 0.155 or 3.72 hours; Level 5 = 0.082 or 1.963 hours; Level 6 = 0.04 or 0.96 hours) on the growth responses and survival of the salt marsh grass Spartina maritima in summer 2011 and 2012. S. maritima grew better at intermediate inundation times (0,351 hours; 0,263 hours, 0,115 hours; 0,082 hours), while growth and survival were reduced at greater inundation periods (0,468 hours). The differences between the 2011 and 2012 experiment were mainly related to differences in the initial number of shoots (1 and 5, respectively in 2011 and 2012). In the 2011 experiment a significant lower number of plants was present in the levels 1 and 6, the rhizomes reached the max pick in level 4, weights was major in level 4, spike length reached the pick in level 3 while leaf length in level 2. In the 2012 experiment the plants in level 6 all died, the rhizomes were more present in level 3, weights was major in level 3, spike length reached the pick in level 3, as well as leaf length. I also conducted a laboratory experiment which was designed to test the effects of 5 different inundation periods (0 control, 8, 24, 48, 96 hours) on the survival of three coastal vegetation species Agrostis stolonifera, Trifolium repens and Hippopae rhamnoides in summer 2012. The same laboratory experiment was repeated in the Netherlands. In Italy, H. rhamnoides showed a great survival in the controls, a variable performance in the other treatments and a clear decrease in treatment 4. Conversely T. repens and A. stolonifera only survive in the control. In the Netherlands experiment there was a greater variability responses for each species, still at the end of the experiment survival was significantly smaller in treatment 4 (96 h of seawater inundation) for all the three species. The results suggest that increased flooding can affect negatively the survival of both saltmarsh and coastal plants, limiting root system extension and leaf growth. Flooding effect could lead to further decline and fragmentation of the saltmarshes and coastal vegetation, thereby reducing recovery (and thus resilience) of these systems once disturbed. These effects could be amplified by interactions with other co-occurring human impacts in these systems, and it is therefore necessary to identify management options that increase the resilience of these systems.

Impact of irrigation in the Po valley (Italy) on meteorological parameters through numerical simulation

Recent studies found that soil-atmosphere coupling features, through soil moisture, have been crucial to simulate well heat waves amplitude, duration and intensity. Moreover, it was found that soil moisture depletion both in Winter and Spring anticipates strong heat waves during the Summer. Irrigation in geophysical studies can be intended as an anthropogenic forcing to the soil-moisture, besides changes in land proprieties. In this study, the irrigation was add to a LAM hydrostatic model (BOLAM) and coupled with the soil. The response of the model to irrigation perturbation is analyzed during a dry Summer season. To identify a dry Summer, with overall positive temperature anomalies, an extensive climatological characterization of 2015 was done. The method included a statistical validation on the reference period distribution used to calculate the anomalies. Drought conditions were observed during Summer 2015 and previous seasons, both on the analyzed region and the Alps. Moreover July was characterized as an extreme event for the referred distribution. The numerical simulation consisted on the summer season of 2015 and two run: a control run (CTR), with the soil coupling and a perturbed run (IPR). The perturbation consists on a mask of land use created from the Cropland FAO dataset, where an irrigation water flux of 3 mm/day was applied from 6 A.M. to 9 A.M. every day. The results show that differences between CTR and IPR has a strong daily cycle. The main modifications are on the air masses proprieties, not on to the dynamics. However, changes in the circulation at the boundaries of the Po Valley are observed, and a diagnostic spatial correlation of variable differences shows that soil moisture perturbation explains well the variation observed in the 2 meters height temperature and in the latent heat fluxes.On the other hand, does not explain the spatial shift up and downslope observed during different periods of the day. Given the results, irrigation process affects the atmospheric proprieties on a larger scale than the irrigation, therefore it is important in daily forecast, particularly during hot and dry periods.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.