1,721,091 research outputs found
Phenotypic similarity in sympatric crow species: Evidence of social convergence?
No full textI was supported by project CGL2014-53899-
Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements
No full textand atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff
response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of
moisture conditions is a key factor for accurate predictions.
Different sources of information for the estimation of the soil moisture state are currently available: satellite data,
point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite
sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave
sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The
last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological
applications
In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the
satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from
ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an
evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the
ACHAB and SM-OBS-2 on the whole Italian territory are performed too
Dataset of "Dispersal constrains the biotic connectivity of mountain assemblages"
No full text[Methods for processing the data] In the period 2009-2013, birds censuses were performed in 463 circular plots of 100 m radius, where we recorded all species heard or seen during a 10-min period.
Lichen datasets of species occurrences were compiled from published works in the study area (Aragón et al., 2006; De la Torre Fernández & Fernández Ordóñez, 2000; López de Silanes et al., 1999).
More detailed information about lichen trait-data in Laiolo et al. 2020, NatComm; DOI: 10.1038/s41467-020-14720-3; Bird data compiled from AVONET (Tobias et al., 2023, EcoLett; doi.org/10.1111/ele.13898) and Laiolo et al. 2020, NatComm; DOI: 10.1038/s41467-020-14720-3)We compiled datasets using own data and literature data of surveys of lichens and birds carried out in the Eastern Cantabrian Mountains, NW Spain, and a dataset of functional traits of the species of surveys.Spanish Ministry of Science and Innovation (PID2020-115259GB-I00 and by MCIN/AEI/10.13039/501100011033) and Principado de Asturias (IDI/2021/000075)Peer reviewe
The Smart City Energy infrastructures at the Savona Campus of the University of Genoa
No full textThis paper presents ongoing research activities and technology upgrades carried out by the Power System Research team of the University of Genoa on the Smart City test-bed facilities installed at the Savona Campus. These facilities consist of a Smart Polygeneration Microgrid (SPM) feeding the Campus, of a Smart Energy Building (SEB) connected to the SPM and acting as a “prosumer” and of an Energy Management System (EMS) controlling the Campus generating units and thermal and electrical loads. The SPM, initially set up as a grid-tied system, is now subjected to further improvements in order to be operated in islanded mode. The paper shows that all the aforementioned infrastructures constitute a real example of how to build a sustainable smart city
Planning & Open-Air Demonstrating Smart City Sustainable Districts
No full textThe article is focused on the “demonstration” activities carried out by the University of Genoa at Savona Campus facilities in order to implement the “Living Lab Smart City”. The idea is to transform the Savona Campus in a Living Lab of the City of the Future: smart technologies in Information and Communication Technology (ICT) and energy sectors were installed in order to show a real application of the Smart City concept to population and external stakeholders. Moreover, special attention was given to the environment, personal wellbeing, and social equalities. The sustainable energy Research Infrastructures (RIs) of Savona Campus allowed enhancement of the applied research in degree programs and the collaboration with several companies. In particular, an important partnership with the Italian electric Distribution System Operator (DSO), ENEL S.p.A., started in 2017 to test the capability of these RIs to operate disconnected from the National Grid, relying only on the supply of renewables and storage systems. The “Living Lab Smart City” is an important action to reduce the carbon footprint of the Savona Campus and to increase the awareness of students, teachers and researchers towards Sustainable Development in Higher Education Institutes
Dispersal constrains the biotic connectivity of mountain assemblages
No full textAim: Climate warming is shifting the bioclimatic optima of species towards mountaintops, but the ability of organisms to track these changes also depends on their dispersal skills. Here, we assessed the role of dispersal over niche-driven processes in connecting assemblages along mountain slopes and between mountain massifs. Location: Cantabrian Mountains, Spain. Taxon: Birds (Animalia; Aves) and Lichens (Fungi; Ascomycota, Basidiomycota). Methods: We examined the change with elevation of community-level traits that are dispersal proxies (wing shape in birds and type of dispersing propagule in lichens) and ecological niche proxies (micro-habitat, substrate, and foraging features). We then permutate species composition within sites and massifs to create models of species distribution constrained by dispersal and niche processes. These models were compared with observed species distribution to disclose the relative contribution of dispersal and niche-based processes in the biotic interchange along mountain slopes (vertical connectivity) and between isolated summits (horizontal connectivity). Results: Both bird and lichen communities were formed by species with traits that enhance dispersal at high elevations. These groups also showed similarities in the elevational patterns of niche diversity, which dropped at high elevations. Dispersal was by far the dominant assembly mechanism in both taxa. Pairwise community comparisons among elevation belts showed weak vertical connectivity, with predominant dispersal limitations but also niche barriers between the extremes of the gradient. Among massifs, horizontal connectivity was higher among high mountain assemblages than those from lower elevations. Main Conclusion: Dispersal was found to be the dominant assembly mechanism in mountain systems, even in taxa with high dispersal potential. Highland assemblages had low functional diversity but their species had high mobility. This permits biotic interchange between isolated summits and, potentially, colonization of other summits as climate warms. Our framework combining traits and occurrence-permutation models improve the understanding of community assembly mechanisms along elevation gradients and points to dispersal limitations, especially at low-middle elevations.This work was supported by grants IDI/2021/000075, PID2020-115259GB-I00 and by MCIN/AEI/10.13039/501100011033. We thank Vicente García-Navas and anonymous reviewer for insightful comments. We thank the Picos de Europa National Park for providing permission for vehicle access to some regulated areas (permit number: CO/08/058/2012; CO/08/016/2013; CO/09/033/2011). No permission was required to perform bird transects by walking.Peer reviewe
Evaluation of remotely sensed surface soil moisture and an energy balance model driven by LST data with Italian in situ data
No full textNear-surface soil moisture is a key variable for the description of many hydrological and climatic processes. This variable governs the partitioning of mass and energy fluxes between land surface and the atmosphere, thereby playing an important role for many scientific and operational applications such as flood forecasting, landslide prediction, numerical weather prediction, early drought prediction, climate modelling and water management. Particularly in operational hydrology a correct estimation of soil moisture improves the forecast of the rainfall-runoff response of catchments and consequently improves flood predictions.
Soil moisture content can be evaluated through several methods such as classical point measurement (TDR, gravimetric, neutron probes, capacitance probe), remote sensing (passive or active microwave sensors) and hydrological models predictions. Ground-based measurements are direct but very localized and limited in coverage; satellite data provide useful but indirect large-scale observations of surface soil moisture and could have problems in some environments (mountain regions, vegetated surfaces, etc..); model predictions provide a more regional perspective but rely on many parameterizations and approximations aimed to a more efficient representation of the physics of the process.
The work considers two different types of satellite-derived data: the HSAF project surface soil moisture (SSM) product, derived from ASCAT scatterometer; and an evaporative fraction index, related to soil moisture content, derived by the ACHAB (Assimilation Code for Heat and moisture Balance) model, an operative energy balance model that assimilates Land Surface Temperatures derived from MSG. These two estimates are compared and validated using in situ soil moisture data available in different Italian regions with the aim of obtaining reliable soil moisture estimates to be used for operational flood forecast. Test has been performed using the HSAF and ACHAB data both as the original estimates and as filtered series applying a linear regression correction and a CDF matching in the way that both CDFs match the CDF of in situ measurements. Further analysis were carried out applying a exponential filter (the so called Soil Water Index) that takes into account the differences between the soil moisture in the uppermost soil layer layer (2-3 cm ) observed by satellite data and the soil moisture in the layer observed by in situ measurements (10-30 cm)
Assimilation of H-SAF Soil Moisture Products for Flash Flood Early Warning Systems. Case Study: Mediterranean Catchments
No full textA reliable estimation of soil moisture conditions is fundamental for rivers’ discharge predictions, especially in small catchments where flash floods occur. In this context, microwave remote sensing can be exploited to estimate soil moisture at large scale. These estimates can be used to enhance the predictions of hydrological models using data assimilation techniques. Flash flood early warning systems can, thus, be improved. This study tested the effect of the assimilation of three different ASCAT-derived soil moisture products, processed and distributed within the EUMETSAT H-SAF framework (SM-OBS-1, SM-OBS-2, SM-DAS-2), into a distributed physically based hydrological model (Continuum). The study areas were three Italian catchments, representative of the typical Mediterranean small basins prone to flash floods. The products were first preprocessed in order to be comparable with the model soil moisture state estimate. Subsequently, they were assimilated using three Nudging-based techniques. Then, observed discharges were compared with the modeled one in order to understand the impact of the assimilation. The analysis was executed for a multiyear period ranging from July 2012 to June 2014 in order to test the assimilation algorithms for operational purposes in real-cases scenarios. Findings showed that the assimilation of H-SAF soil moisture products with simple preprocessing and assimilation techniques can enhance discharge predictions; the improvements significantly affect high flows. Although SM-OBS-2 and SM-DAS-1 are added-value products with respect to SM-OBS-1 (respectively, higher spatial and temporal resolution), they may not necessarily perform better. The impact of the assimilation strongly relies on the permanent catchment characteristics (e.g., topography, hydrography, land cover)
Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle
No full textThe reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in
space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff
response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to
provide good space-time estimates of several hydrological variables and then improve hydrological model
performances especially in environments with scarce ground based data.
The aim of this work is to investigate the impacts on the performances of a distributed hydrological model
(Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST).
In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are
provided by the EUMETSAT’s H-SAF (Satellite Application Facility on Support to Operational Hydrology and
Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM
OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS
2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800
km2), in the northern part of Italy, for the period July 2012-June 2013.
Different assimilation experiments have been performed. The first experiment consists in the assimilation of the
SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived
from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model
predictions of discharge, LST and soil moisture dynamics were tested
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