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

Matteo Giuliani,Roman Fedorov,Andrea Castelletti,Piero Fraternali

doi:10.5194/hess-20-5049-2016

Matteo Giuliani, Roman Fedorov + Show 2 more

Open Access

https://doi.org/10.5194/hess-20-5049-2016

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Abstract

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.

Highlights

Snow accumulation and melting are fundamental components of the hydrological cycle in many watersheds across the world (e.g., Mote et al, 2005; Holko et al, 2011)
A first qualitative analysis of the virtual snow index σ defined in Eq (4) can be performed by comparatively analyzing the trajectory of this virtual snow indexes (VSIs) with respect to the snow height observations in the closest ground station (i.e., Oga San Colombano, located around 15 km from the webcam) or with respect to some physical variables closely related to the snow dynamics
The images, crawled from multiple web data sources, are automatically processed to derive time series of virtual snow indexes representing a proxy of the snowcovered area

Summary

Introduction

Snow accumulation and melting are fundamental components of the hydrological cycle in many watersheds across the world (e.g., Mote et al, 2005; Holko et al, 2011). Snow processes are generally monitored through both ground monitoring networks (e.g., Brown and Braaten, 1998; López-Moreno and Nogués-Bravo, 2006) and remote sensing (for a review, see König et al, 2001; Dietz et al, 2012, and references therein). Both sources have serious limitations in alpine contexts, mainly related to the high spatial (e.g., Newald and Lehning, 2011) and temporal variability of snow-related processes (Blöschl, 1999; Egli, 2008; Gleason et al, 2016).

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