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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 12
Hydrol. Earth Syst. Sci., 20, 5049–5062, 2016
https://doi.org/10.5194/hess-20-5049-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 5049–5062, 2016
https://doi.org/10.5194/hess-20-5049-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Dec 2016

Research article | 21 Dec 2016

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

Matteo Giuliani1, Andrea Castelletti1,2, Roman Fedorov1, and Piero Fraternali1 Matteo Giuliani et al.
  • 1Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza L. da Vinci, 32, 20133 Milano, Italy
  • 2Institute of Environmental Engineering, ETH, Wolfgang-Pauli-Str. 15, 8093 Zurich, Switzerland

Abstract. Snow is a key component of the hydrologic cycle in many regions of the world. Despite recent advances in environmental monitoring that are making a wide range of data available, continuous snow monitoring systems that can collect data at high spatial and temporal resolution are not well established yet, especially in inaccessible high-latitude or mountainous regions. The unprecedented availability of user-generated data on the web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images, either produced by users or generated by touristic webcams. A fully automated process fetches mountain images from multiple sources, identifies the peaks present therein, and estimates virtual snow indexes representing a proxy of the snow-covered area. Our procedure has the potential for complementing traditional snow-related information, minimizing costs and efforts for obtaining the virtual snow indexes and, at the same time, maximizing the portability of the procedure to several locations where such public images are available. The operational value of the obtained virtual snow indexes is assessed for a real-world water-management problem, the regulation of Lake Como, where we use these indexes for informing the daily operations of the lake. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

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The unprecedented availability of user-generated data on the Web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images. The value of the obtained virtual snow indexes is assessed for a real-world water management problem.
The unprecedented availability of user-generated data on the Web is opening new opportunities...
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