Lessons from calibrating a global flood forecasting system

Lessons from calibrating a global flood forecasting system

Contributed by Feyera Hirpa, University of Oxford. Hydrological models are key tools for predicting flood disasters several days ahead of their occurrence. However, their usability as a decision support tool depends on their skill in reproducing the observed streamflow. The forecast skill is subject to a cascade of uncertainties originating from errors in the models’ structure, parametrization, initial conditions and meteorological forcing. The Global Flood Awareness System (GloFAS) is an operational flood forecasting system that produces ensemble streamflow forecasts with…

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Nice hydrographs for everyone, from everyone: Introducing eWaterCycle II

Nice hydrographs for everyone, from everyone: Introducing eWaterCycle II

Contributed by Rolf Hut, TU Delft. “Nice hydrographs! Can you now compare your model to ‘that other hydrology groups model’?” The PhD student suppresses the urge to roll her eyes. Her supervisor is asking her to go back into code-hell. That other model is written in Fortran and she works in Python. It took her two months to get the Python model used in her group running in the first place. Realizing she needed to install an obtuse library on…

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How writing an article can come out of the blue (KGE on log-transformed flows: a bad idea?)

How writing an article can come out of the blue (KGE on log-transformed flows: a bad idea?)

Contributed by Léonard Santos (Irstea, France). It is common to read articles in which the Kling and Gupta Efficiency (KGE, Gupta et al., 2009) or its modified version (KGE’, Kling et al., 2012) are used as a metric to evaluate the quality of streamflow simulations. They are often seen as a solution to substitute the Nash and Sutcliffe Efficiency (NSE, Nash and Sutcliffe, 1970). However, are these two criterion totally comparable? Can the KGE be used exactly in the same…

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Fictitious Forcings have Macondo in Trouble: A Hackathon Story

Fictitious Forcings have Macondo in Trouble: A Hackathon Story

Contributed by Georgy Ayzel.  Meteorological ensemble forecasts form the core of every system for hydrological ensemble prediction. There are multiple data sources where our meteorological ensembles could come from: historical observations, numerical weather prediction and climate models, or stochastic weather generators. Different sources serve different ways we want to communicate and deliver the information of possible runoff responses to various meteorological conditions. However, there is a source that is typically ignored in the modern landscape of ensemble runoff prediction –…

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Summer 2018 in Europe: did the EFAS seasonal outlook predict low river flows?

Summer 2018 in Europe: did the EFAS seasonal outlook predict low river flows?

— this post is jointly published on the blogs of HEPEX and the European Drought Centre — Contributed by Louise Arnal (ECMWF and University of Reading), Shaun Harrigan (ECMWF) & David Lavers (ECMWF). Summer 2018 in Europe was remarkable from a hydroclimate perspective, with large regions experiencing persistent dry conditions, very little to no rainfall for extended periods, a series of heatwaves with record-breaking temperatures and numerous wildfires (in the UK, Sweden, Greece, Spain, Portugal, Latvia and Germany, among others)….

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