Welcome on the website of the Young Hydrologic Society – a network for young (aspiring) scientist in the field of hydrology.

This network is an initiative by two MSc. students that think that there is a lot of potential in having a network for early career or aspiring scientist.

The network is currently being set-up and the plan is to have a first meeting during the European Geo-Sciences General Assembly 2013 in Vienna. This meeting in Vienna will be an interactive session where we want to discuss the most important goals of this network and how we need to organize such a network to most effectively achieve these goals.

During the coming months we want to get a team of MSc and PhD students together to further shape the initiative. If you are interested in participating in this process please contact us.

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5 Responses to Home

  1. Maria says:

    that choice of the title for the new Decade shuold be left for a while. However, I would like to offer a personal view concerning what it shuold not include. Yes, uncertainty shuold be a keyword for the new Decade (one of Alberto’s bullets) but I think the word “uncertainty” (or similar) shuold not be in its title. My view is that to include it there, if anyone is still thinking along these lines, would be unwise – because of its negative connotations to the layperson. There shuold be nothing negative in the title. Yes, reducing uncertainty in outputs from our hydrological science, and conveying uncertainty aspects of our science to users, e.g. engineers, politicians, etc, shuold continue (following on from PUB) to be explicit overarching themes for the new Decade but in the interests of being upbeat for presentational purposes let’s not emphasise uncertainty in the title. Elena Toth’s comments that “a fundamental contribution must come from the full exploitation of the available data” through the application of “data-driven” models are sensible. One output from participants of PUB Working Group 1 (top-down modelling) during the Decade now drawing to a close has been research applications of grey box (not black) data-driven rainfall–streamflow (R-S) modelling, e.g. pointing towards how uncertainty in regionalised R-S model parameters might be reduced in practice. IHACRES and data-based mechanistic (DBM) data-driven modelling highlight the distinction, which can become important when temporally coarse data are used for calibrating a discrete-time model for a flashy catchment, between fitting a model to data (curve-fitting – or getting the right answer for the wrong reasons) and fitting a model to a catchment (getting closer to the right answer for the right reasons). For a flashy catchment, even if an IHACRES model parameter is calibrated with good precision using daily data it can be massively inaccurate (and therefore very uncertain). Much recent research has been undertaken without paying enough attention to the fact that, for discrete-time conceptual R-S models, only those calibrated using sufficiently high-frequency data for a given catchment stand a chance of yielding precise and accurate (don’t forget both are required for low uncertainty) model parameters. In the context of discrete-time conceptual R-S modelling this has implications (a) when regionalising the parameters of any such model using national datasets for gauged catchments and (b) whenever such models are used to assist with gaining a better understanding (especially quantitatively) of catchment-scale processes. Relevant textbooks and research literature (until very recently) largely ignore these fundamental points. I think this area of research shuold be further stimulated by the next Decade and, in this sense, would suggest it might be considered together with the points raised by Charles Perrin.Ian LittlewoodVote this comment 0 user(s) like(s) this comment

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