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An integrative information aqueduct to close the gaps between satellite observation of water cycle and local sustainable management of water resources

Authors :
Bas Retsios
Nunzio Romano
Giulia Vico
Chris M. Mannaerts
János Mészáros
Eyal Ben Dor
D.T. Rwasoka
Lijie Zhang
Yijian Zeng
Salvatore Manfreda
Félix Francés
Maoya Bassiouni
Silvano Fortunato Dal Sasso
Megan Leigh Blatchford
Paolo Nasta
Zhongbo Su
Nicolas Francos
Ruodan Zhuang
Lianyu Yu
Brigitta Szabó
Faculty of Geo-Information Science and Earth Observation
UT-I-ITC-WCC
Department of Water Resources
Source :
Water, 12(5):1495, 1-36. MDPI, Water, Vol 12, Iss 1495, p 1495 (2020), RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Publication Year :
2020

Abstract

[EN] The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens of kilometer scales. Whilst these data effectively characterize water cycle variability at regional to global scales, they are less suitable for sustainable management of local water resources, which needs detailed information to represent the spatial heterogeneity of soil and vegetation. The following questions are critical to effectively exploit information from remotely sensed and in situ Earth observations (EOs): How to downscale the global water cycle products to the local scale using multiple sources and scales of EO data? How to explore and apply the downscaled information at the management level for a better understanding of soil-water-vegetation-energy processes? How can such fine-scale information be used to improve the management of soil and water resources? An integrative information flow (i.e., iAqueduct theoretical framework) is developed to close the gaps between satellite water cycle products and local information necessary for sustainable management of water resources. The integrated iAqueduct framework aims to address the abovementioned scientific questions by combining medium-resolution (10 m-1 km) Copernicus satellite data with high-resolution (cm) unmanned aerial system (UAS) data, in situ observations, analytical- and physical-based models, as well as big-data analytics with machine learning algorithms. This paper provides a general overview of the iAqueduct theoretical framework and introduces some preliminary results.<br />The authors would like to thank the European Commission and Netherlands Organisation for Scientific Research (NWO) for funding, in the frame of the collaborative international consortium (iAqueduct) financed under the 2018 Joint call of the Water Works 2017 ERA-NET Cofund. This ERA-NET is an integral part of the activities developed by the Water JPI (Project number: ENWWW.2018.5); the EC and the Swedish Research Council for Sustainable Development (FORMAS, under grant 2018-02787); Contributions of B. Szabo was supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences (grant no. BO/00088/18/4).

Details

Language :
English
ISSN :
20734441
Volume :
12
Issue :
5
Database :
OpenAIRE
Journal :
Water
Accession number :
edsair.doi.dedup.....328f63764a53669190adb64163304f4c