CALAMAR. Measuring and forecasting rainfall using radar hydrometeorology

Leonardo da Vinci. "It is necessary for us … to commence with experience and from this to proceed to investigate the reason." Hygrometer. In the late 15th century Leonardo da Vinci gave a first accurate explanation of the hydrologic cycle, including even evaporation and precipitation. With his hygrometer he determined atmospherical humidity by measuring the imbalance caused by the absorption of moisture by the cotton wool, on one scale, which, when dry, is equal to the weight on the other side. It was one of his many observations methods for hydrologic phenomena with which he put his natural scientific obsession into practice.

Measurement - forecast-based decision-making - analysis CALAMAR is a software system that provides real-time measurement and short-term forecasting of rainfall on each square kilometre of a given area covered by radar hydrometeorology. CALAMAR is a genuine decision-making tool; combined with probabilistic (risk indicator) or deterministic (rainfall flow) models, it enables forecasting of rainstorms which is sufficiently accurate to allow time to act in-field. In off-line mode, CALAMAR enables a rainfall event to be reconstructed: with the aid of deterministic hydrological and hydraulic modelling: this enables the causes of any difficulties to be identified and corrected, providing better environmental protection. CALAMAR is geared to stakeholders who have to deal with situations which are significantly affected by rainfall in both built-up and rural areas: Flood Forecasting Agencies Local government officials with responsibility for flood risk management Managers of sanitation and/or natural waterways: - Real-time management of network infrastructures - Permanent diagnostic reporting for urban sanitation networks - Assistance in planning network maintenance operations Engineers responsible for drafting or finalising the hydraulic model for a sanitation network and/or a watershed‘s rainfall-flow model Hydrologists wishing to improve a measurement network.