Publication Details

Category Text Publication
Reference Category Book chapters
DOI 10.1007/978-3-642-39925-1_33
Title (Primary) Assimilation of streamflow observations
Title (Secondary) Handbook of hydrometeorological ensemble forecasting, Vol. 1
Author Noh, S.J.; Weerts, A.; Rakovec, O. ORCID logo ; Lee, H.; Seo, D.-J.
Publisher Duan, Q.; Pappenberger, F.; Thielen, J.; Wood, A.; Cloke, H.; Schaake, J.
Year 2019
Department CHS
Page From 745
Page To 780
Language englisch
Keywords Streamflow; Observation; Data assimilation; Hydrologic modeling; Ensemble; Kalman filtering; Particle filtering; Variational assimilation; Multiscale bias correction; Maximum likelihood ensemble filtering
UFZ wide themes RU5;
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.
Persistent UFZ Identifier
Noh, S.J., Weerts, A., Rakovec, O., Lee, H., Seo, D.-J. (2019):
Assimilation of streamflow observations
In: Duan, Q., Pappenberger, F., Thielen, J., Wood, A., Cloke, H., Schaake, J. (eds.)
Handbook of hydrometeorological ensemble forecasting, Vol. 1
Springer, Berlin, Heidelberg, p. 745 - 780 10.1007/978-3-642-39925-1_33