Climate change and anthropogenic pressures are expected to reduce global freshwater availability and to exacerbate water crises in the near futures. To manage water crisis, the most common path of the past century has been a “hard-path”, based on centralized structural actions, strongly affecting the environment. This work aims at developing novel adaptive water management control strategies, in a multi-stakeholders context, based on soft-path measures. We focus on the direct, data-driven use of exogenous information to improve the systems anticipation capability. Specifically, the value of snow data in informing water resource systems operation is explored using a model free approach. The underline idea is that information on the snow water equivalent (SWE) in the basin may be relevant to manage the reservoir releases. To this aim SWE estimates are retrieved from SAR COSMO-SkyMed X-band images. The approach is demonstrated on snow-rain fed river basin in the Italian Alps: the Lake Como watershed. Preliminary results show the relevance of snow information to the reservoir management as well as the potential for remote sensed products in data-driven optimization.

Informing water management by direct use of SAR retrieved snow information in snow-rainfall dominated watersheds

DENARO, SIMONA;CASTELLETTI, ANDREA FRANCESCO;TEBALDINI, STEFANO;
2015

Abstract

Climate change and anthropogenic pressures are expected to reduce global freshwater availability and to exacerbate water crises in the near futures. To manage water crisis, the most common path of the past century has been a “hard-path”, based on centralized structural actions, strongly affecting the environment. This work aims at developing novel adaptive water management control strategies, in a multi-stakeholders context, based on soft-path measures. We focus on the direct, data-driven use of exogenous information to improve the systems anticipation capability. Specifically, the value of snow data in informing water resource systems operation is explored using a model free approach. The underline idea is that information on the snow water equivalent (SWE) in the basin may be relevant to manage the reservoir releases. To this aim SWE estimates are retrieved from SAR COSMO-SkyMed X-band images. The approach is demonstrated on snow-rain fed river basin in the Italian Alps: the Lake Como watershed. Preliminary results show the relevance of snow information to the reservoir management as well as the potential for remote sensed products in data-driven optimization.
International Geoscience and Remote Sensing Symposium (IGARSS)
9781479979295
9781479979295
data-driven; SAR; snow; SWE; water management; Earth and Planetary Sciences (all); Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/984297
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