| publications-2631 |
Peer reviewed articles |
2017 |
Iulia Dana NEGULA, Alexandru BADEA, Cristian MOISE, Violeta POENARU |
EARTH OBSERVATION SATELLITE DATA IN SUPPORT OF WATER MANAGEMENT FOR AGRICULTURE |
AgroLife Scientific Journal, |
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Simulation & Modeling |
Uncategorized |
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No abstract available |
730109 |
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| publications-2632 |
Peer reviewed articles |
2017 |
Alfonso Calera, Isidro Campos, Anna Osann, Guido D’Urso, Massimo Menenti |
Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users |
Sensors |
10.3390/s17051104 |
Uncategorized |
Precipitation & Ecological Systems |
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The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools. |
730109 |
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| publications-2633 |
Peer reviewed articles |
2019 |
Nicola Ghirardi, Rossano Bolpagni, Mariano Bresciani, Giulia Valerio, Marco Pilotti, Claudia Giardino |
Spatiotemporal Dynamics of Submerged Aquatic Vegetation in a Deep Lake from Sentinel-2 Data |
Water |
10.3390/w11030563 |
Uncategorized |
Precipitation & Ecological Systems |
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We mapped the extent of submerged aquatic vegetation (SAV) of Lake Iseo (Northern Italy, over the 2015–2017 period based on satellite data (Sentinel 2 A-B) and in-situ measurements; the objective was to investigate its spatiotemporal variability. We focused on the southern sector of the lake, the location of the shallowest littorals and the most developed macrophyte communities, mainly dominated by Vallisneria spiralis and Najas marina. The method made use of both in-situ measurements and satellite data (22 Sentinel 2 A-B images) that were atmospherically corrected with 6SV code and processed with the BOMBER (Bio-Optical Model-Based tool for Estimating water quality and bottom properties from Remote sensing images). This modeling system was used to estimate the different substrate coverage (bare sediment, dense stands of macrophytes with high albedo, and sparse stand of macrophytes with low albedo). The presented results substantiate the existence of striking inter- and intra-annual variations in the spatial-cover patterns of SAV. Intense uprooting phenomena were also detected, mainly affecting V. spiralis, a species generally considered a highly plastic pioneer taxon. In this context, remote sensing emerges as a very reliable tool for mapping SAV with satisfactory accuracy by offering new perspectives for expanding our comprehension of lacustrine macrophyte dynamics and overcoming some limitations associated with traditional field surveys. |
730066 |
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| publications-2634 |
Peer reviewed articles |
2019 |
Truls Hveem Hansson, Hans-Peter Grossart, Paul A. del Giorgio, Nicolas F. St-Gelais, Beatrix E. Beisner |
Environmental drivers of mixotrophs in boreal lakes |
Limnology and Oceanography |
10.1002/lno.11144 |
Simulation & Modeling |
Irrigation Systems |
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AbstractMixotrophy is increasingly recognized as an important trophic pathway among phytoplankton, yet its underlying drivers remain largely unknown and unexplored. Here, we present a study utilizing 69 lake samplings in boreal Quebec, Canada, identifying variables driving the success of phytoplankton that have a capacity for mixotrophy and pointing to the underlying mechanisms. We found that the success of mixotrophs (% of total biomass) was positively influenced by both colored dissolved organic matter (cDOM) and dissolved CO2 concentration but limited by the abundance of crustacean zooplankton. The effect of cDOM manifested as a consequence of limited autotrophic phytoplankton biomass in lakes with reduced light penetration. We observed a nonlinear (u‐shaped) relation between CO2 and mixotrophs, with biomass favored at both low and high CO2 concentrations. A reduced fitness of mixotrophs at near‐atmospheric CO2 concentrations is likely owing to the costs of rapidly switching between or maintaining multiple trophic strategies. The abundance of zooplankton had a negative effect on mixotroph biomass but a positive effect on autotrophic phytoplankton. We also found that while the community composition of potentially mixotrophic phytoplankton was to some degree likely influenced by zooplankton biomass, composition was unaffected by the CO2 and cDOM gradients. Overall, this study highlights mixotrophy in boreal lake systems as a strategy of persistence, with the maintenance of a moderate but constant presence across a changing gradient of light and trophic conditions. The results of our study support the hypothesis that phytoplankton with a capacity for mixotrophy provide a superior and stable stoichiometric food source for zooplankton, implicating mixotrophs as a vital component of boreal lake food webs. |
722518 |
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| publications-2635 |
Peer reviewed articles |
2017 |
Leticia Ozawa-Meida, Caroline Wilson, Paul Fleming, Graeme Stuart, Carl Holland |
Institutional, social and individual behavioural effects of energy feedback in public buildings across eleven European cities |
Energy Policy |
10.1016/j.enpol.2017.08.026 |
Cloud Technologies |
Uncategorized |
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No abstract available |
695916 |
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| publications-2636 |
Peer reviewed articles |
2018 |
Lorenzo Compagnucci, Francesca Spigarelli |
Fostering Cross-Sector Collaboration to Promote Innovation in the Water Sector |
Sustainability |
10.3390/su10114154 |
Simulation & Modeling |
Uncategorized |
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Ongoing global climate change, growing population and the intensification of economic activities, increase pressure on water resources, a situation many see as a water governance crisis. Water-related issues are becoming a limiting factor for sustainable economic growth and require a collaborative and interdisciplinary approach, to foster innovative solutions. This paper provides an evidence-based contribution to understanding Triple Helix Model (THM) relations and the path to innovation policy in the water sector. The analysis focuses on the interaction between university–industry–government, with specific reference to the Murcia region in Southeast Spain. This region combines a chronic shortage of water and a leading role for agriculture. Starting from the experience of a researcher, working for the General Water Council of the Murcia Region, this paper is based on both desk research and in-depth personal interviews with representatives of THM actors. In addition, a questionnaire was forwarded to all those companies in charge of providing water services in the Murcia region. The study has found that stakeholders are not fully cooperative in seeking innovation. The main challenges are the renewal of water-related facilities and the improvement of remote control systems, denitrification and desalination technologies and achieving better energy efficiency. To this aim, THM approach is suggested as a source of local innovation policies, identifying a series of tools to foster a collaborative approach. |
734560 |
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| publications-2637 |
Peer reviewed articles |
2017 |
A.E. Ioannou, D. Kofinas, A. Spyropoulou and C. Laspidou |
Data mining for household water consumption analysis using self-organizing maps |
European Water |
10.5281/zenodo.2645124 |
AI & Machine Learning |
Uncategorized |
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No abstract available |
734409 |
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| publications-2638 |
Peer reviewed articles |
2018 |
Alexandra E. Ioannou, Chrysi S. Laspidou |
The Water-Energy Nexus at City Level: The Case Study of Skiathos |
Proceedings |
10.3390/proceedings2110694 |
Hydrological modeling |
Groundwater |
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No abstract available |
734409 |
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| publications-2639 |
Peer reviewed articles |
2018 |
Matej Senožetnik, Zala Herga, Tine Šubic, Luka Bradeško, Klemen Kenda, Kristina Klemen, Petra Pergar, Dunja Mladenić |
IoT Middleware for Water Management |
Proceedings |
10.3390/proceedings2110696 |
Data Management & Analytics |
Groundwater |
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No abstract available |
734409 |
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| publications-2640 |
Peer reviewed articles |
2018 |
Klemen Kenda, Filip Koprivec, Dunja Mladenić |
Optimal Missing Value Estimation Algorithm for Groundwater Levels |
Proceedings |
10.3390/proceedings2110698 |
Data Management & Analytics |
Groundwater |
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No abstract available |
734409 |
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