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

Zhongbo Su*, Yijian Zeng, Nunzio Romano, Salvatore Manfreda, Félix Francés, Eyal Ben Dor, Brigitta Szabó, Giulia Vico, Paolo Nasta, Ruodan Zhuang, Nicolas Francos, János Mészáros, Silvano Fortunato Dal Sasso, Maoya Bassiouni, Lijie Zhang, Donald Tendayi Rwasoka, Bas Retsios, Lianyu Yu, Megan Leigh Blatchford, Chris Mannaerts

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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 eectively 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 eectively 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.

Original languageEnglish
Article number1495
JournalWater (Switzerland)
Volume12
Issue number5
DOIs
StatePublished - 1 May 2020

Funding

FundersFunder number
Swedish Research Council for Sustainable Development
European Commission
European Cooperation in Science and TechnologyCA16219
Svenska Forskningsrådet Formas2018-02787
Nederlandse Organisatie voor Wetenschappelijk OnderzoekENWWW.2018.5
Magyar Tudományos AkadémiaBO/00088/18/4
Universidad Autónoma de Sinaloa

    Keywords

    • Ecohydrological modelling
    • Pedotransfer function (PTF)
    • Soil moisture
    • Soil spectroscopy
    • Sustainable water resources management
    • Unmanned aerial system (UAS)

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