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Author: Ilias Pechlivanidis

HEPEX @ MODSIM 2021

HEPEX @ MODSIM 2021

MODSIM is coming around again this year from 5-9 December and very excitingly you can now attend remotely or in person (!!!). So there are options for everyone! For those who aren’t aware, MODSIM is the biannual conference of the Modelling and Simulation Society of Australia and New Zealand, and attracts >700 delegates from all corners of the globe and all walks of modelling. The HEPEX sessions at MODSIM have a brief but eventful history: they began in 2015 and…

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What is the value of seasonal forecasts for water resources management?

What is the value of seasonal forecasts for water resources management?

Contributed by Andres Peñuela, Christopher Hutton and Francesca Pianosi Improved skill of predictions for the North Atlantic circulation and Northern Europe have motivated an increasing effort to improve seasonal weather forecasting systems. Seasonal weather forecasts are expected to be useful for a range of purposes, including to improve the management of water resource systems. To contribute to the assessment of seasonal forecasts value for water managers, we ran a simulation exercise investigating how they could integrate seasonal forecast products in…

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Hydrological Forecasting at Virtual EGU 2021

Hydrological Forecasting at Virtual EGU 2021

The EGU 2021 Annual General Assembly (vEGU21) will take place from 19–30 April 2021, and due to the challenging Covid-19 situation, this event will be a virtual one. We shall nevertheless grasp all opportunities to get updated on the recent scientific insights and developments and also to virtually socialize with friends and colleagues. To suport the EGU HS Hydrological Forecasting subdivision efforts and make vEGU21 a big success this year too, see below the sessions that are relevant to HEPEXers….

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50 shades of green: lessons about business models for climate services

50 shades of green: lessons about business models for climate services

Contributed by Francesca Larosa (Euro-Mediterranean Center on Climate Change (CMCC), Ca’ Foscari University, and  UCL Energy Institute | UCL Institute for Sustainable Resources) Climate services are essential for adaptation to climate variability and change The transition towards a zero-carbon economy is profoundly reshaping the business-as-usual. If, on one hand, we must cut down our emissions and restructure the way our economies work, on the other hand we need to use the science we have and the tremendous technological progresses we…

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Machine learning for probabilistic hydrological forecasting

Machine learning for probabilistic hydrological forecasting

Contributed by Georgia Papacharalampous and Hristos Tyralis We would firstly like to thank HEPEX for giving us the opportunity to set a background on how machine learning can be used in probabilistic hydrological forecasting.  In this blog post, we start by providing the schematic summary of the discussion given below. Hope you will enjoy the reading! Learning practical problems with data: A machine learning algorithm can be explicitly trained for probabilistic hydrological forecasting Let’s suppose one of our most familiar…

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