The city of Bangalore, India, faces challenges to provide enough water for the current and future water demand for drinking and irrigation purposes. The wet and dry periods are becoming more extreme, which together with the rise of population results in the need for a better insight of the future water availability in the four main reservoirs around Bangalore.
A Quantile Regression approach (ML) provides us with the uncertainty bands of the future water availability forecast. The machine learning technique used is trained for monthly, weekly and daily forecasts for the reservoirs inflow, based on incoming radiation and precipitation forecasts.
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ir. N. van der Vliet Consultant Water and climate Thema's Water and climate 0320294283 n.vandervliet@hkv.nl Linkedin profiel bekijken -
ir. T.J.T. van der Heijden Consultant Water and energy Thema's Water and climate t.vanderheijden@hkv.nl Linkedin profiel bekijken -
ir. D.F. Honingh Consultant Water and climate Thema's Water and climate d.honingh@hkv.nl Linkedin profiel bekijken -
ir. J.G. Stenfert adviseur AI, water en klimaat Thema's Data science, Waterveiligheid j.stenfert@hkv.nl Linkedin profiel bekijken
Knowledge entrepreneurs in flood risk and water resources management
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The Netherlands
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