TY - JOUR
T1 - Real-time assimilation of streamflow observations into a hydrological routing model
T2 - Effects of model structures and updating methods
AU - Mazzoleni, Maurizio
AU - Noh, Seong Jin
AU - Lee, Haksu
AU - Liu, Yuqiong
AU - Seo, Dong Jun
AU - Amaranto, Alessandro
AU - Alfonso, Leonardo
AU - Solomatine, Dimitri P.
PY - 2018/2/17
Y1 - 2018/2/17
N2 - This paper comparatively assesses the performance of five data assimilation techniques for three-parameter Muskingum routing with a spatially lumped or distributed model structure. The assimilation techniques used include direct insertion (DI), nudging scheme (NS), Kalman filter (KF), ensemble Kalman filter (EnKF) and asynchronous ensemble Kalman filter (AEnKF), which are applied to river reaches in Texas and Louisiana, USA. For both lumped and distributed routing, results from KF, EnKF and AEnKF are sensitive to the error specification. As expected, DI outperformed the other models in the case of lumped modelling, while in distributed routing, KF approaches, particularly AEnKF and EnKF, performed better than DI or nudging, reflecting the benefit of updating distributed states through error covariance modelling in KF approaches. The results of this work would be useful in setting up data assimilation systems that employ increasingly abundant real-time observations using distributed hydrological routing models.
AB - This paper comparatively assesses the performance of five data assimilation techniques for three-parameter Muskingum routing with a spatially lumped or distributed model structure. The assimilation techniques used include direct insertion (DI), nudging scheme (NS), Kalman filter (KF), ensemble Kalman filter (EnKF) and asynchronous ensemble Kalman filter (AEnKF), which are applied to river reaches in Texas and Louisiana, USA. For both lumped and distributed routing, results from KF, EnKF and AEnKF are sensitive to the error specification. As expected, DI outperformed the other models in the case of lumped modelling, while in distributed routing, KF approaches, particularly AEnKF and EnKF, performed better than DI or nudging, reflecting the benefit of updating distributed states through error covariance modelling in KF approaches. The results of this work would be useful in setting up data assimilation systems that employ increasingly abundant real-time observations using distributed hydrological routing models.
KW - data assimilation
KW - distributed routing
KW - hydrological routing
KW - three-parameter Muskingum model
UR - http://www.scopus.com/inward/record.url?scp=85042117943&partnerID=8YFLogxK
U2 - 10.1080/02626667.2018.1430898
DO - 10.1080/02626667.2018.1430898
M3 - Article
AN - SCOPUS:85042117943
SN - 0262-6667
VL - 63
SP - 386
EP - 407
JO - Hydrological Sciences Journal
JF - Hydrological Sciences Journal
IS - 3
ER -