Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 538428
Title Assimilation of Streamflow Observations
Author(s) Noh, Seong Jin; Weerts, Albrecht H.; Rakovec, Oldrich; Lee, Haksu; Seo, Dong-Jun
Source In: Handbook of Hydrometeorological Ensemble Forecasting / Duan, Qingyun, Pappenberger, Florian, Thielen, Jutta, Wood, Andy, Cloke, Hannah L., Schaake, John C., Springer Verlag - ISBN 9783642404573 - p. 1 - 36.
DOI https://doi.org/10.1007/978-3-642-40457-3_33-2
Department(s) Hydrology and Quantitative Water Management
WIMEK
Publication type Peer reviewed book chapter
Publication year 2018
Abstract Streamflow is arguably the most important predictor in operational hydrologic forecasting and water resources management. Assimilation of streamflow observations into hydrologic models has received growing attention in recent decades as a cost-effective means to improve prediction accuracy. Whereas the methods used for streamflow data assimilation (DA) originated and were popularized in atmospheric and ocean sciences, the nature of streamflow DA is significantly different from that of atmospheric or oceanic DA. Compared to the atmospheric processes modeled in weather forecasting, the hydrologic processes for surface and groundwater flow operate over a much wider range of time scales. Also, most hydrologic systems are severely under-observed. The purpose of this chapter is to provide a review on streamflow measurements and associated uncertainty and to share the latest advances, experiences gained, and science issues and challenges in streamflow DA. Toward this end, we discuss the following aspects of streamflow observations and assimilation methods: (1) measurement methods and uncertainty of streamflow observations, (2) streamflow assimilation applications, and (3) benefits and challenges streamflow DA with regard to large-scale DA, multi-data assimilation, and dealing with timing errors.
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