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Research article2020Peer reviewedOpen access

An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources

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

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 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.

Keywords

unmanned aerial system (UAS); soil moisture; pedotransfer function (PTF); soil spectroscopy; ecohydrological modelling; sustainable water resources management

Published in

Water
2020, Volume: 12, number: 5, article number: 1495

      SLU Authors

      • Sustainable Development Goals

      SDG12 Responsible consumption and production

      UKÄ Subject classification

      Oceanography, Hydrology, Water Resources

      Publication identifier

      DOI: https://doi.org/10.3390/W12051495

      Permanent link to this page (URI)

      https://res.slu.se/id/publ/105930