Assimilation of Streamflow Observations

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F18%3A76532" target="_blank" >RIV/60460709:41330/18:76532 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-40457-3_33-1" target="_blank" >http://dx.doi.org/10.1007/978-3-642-40457-3_33-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-40457-3_33-1" target="_blank" >10.1007/978-3-642-40457-3_33-1</a>

Result language
angličtina
Original language name
Assimilation of Streamflow Observations
Original language description
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 followin
Czech name
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Czech description
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Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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