scholarly journals Streamflow estimation using kriging

1998 ◽  
Vol 34 (6) ◽  
pp. 1599-1608 ◽  
Author(s):  
Wen-Cheng Huang ◽  
Fu-Ti Yang
Keyword(s):  
Streamflow Estimation

scholarly journals SWAT and HBV Models' response to streamflow estimation in the Upper Blue Nile Basin, Ethiopia

2021 ◽  
Author(s):  
Belay B. Bizuneh ◽  
Mamaru A. Moges ◽  
Berhanu G. Sinshaw ◽  
Mulu S. Kerebih
Keyword(s):  
Nile Basin ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Streamflow Estimation ◽  
Upper Blue Nile Basin

Regional Streamflow Estimation by Standard Regional Dependence Function Approach

2005 ◽  
Vol 131 (11) ◽  
pp. 1001-1006 ◽  
Author(s):  
Abdüsselam Altunkaynak ◽  
Mehmet Özger ◽  
Zekai Şen
Keyword(s):  
Function Approach ◽  
Dependence Function ◽  
Streamflow Estimation

scholarly journals Streamflow estimation at partially gaged sites using multiple dependence conditions via vine copulas

2020 ◽  
Author(s):  
Kuk-Hyun Ahn
Keyword(s):  
Missing Values ◽  
The Other ◽  
Dependence Structure ◽  
Proposed Model ◽  
Pee Dee ◽  
Streamflow Estimation ◽  
Vine Copula ◽  
Bivariate Copula ◽  
Pee Dee River ◽  
Vine Copulas

Abstract. Reliable estimates of missing streamflow values are relevant for water resources planning and management. This study proposes a multiple dependence condition model via vine copulas for the purpose of estimating streamflow at partially gaged sites. The proposed model is attractive in modeling the high dimensional joint distribution by building a hierarchy of conditional bivariate copulas when provided a complex streamflow gage network. The usefulness of the proposed model is firstly highlighted using a synthetic streamflow scenario. In this analysis, the bivariate copula model and a variant of the vine copulas are also employed to show the ability of the multiple dependence structure adopted in the proposed model. Furthermore, the evaluations are extended to a case study of 54 gages located within the Yadkin-Pee Dee River Basin, the eastern U. S. Both results inform that the proposed model is better suited for infilling missing values. After that, the performance of the vine copula is compared with six other infilling approaches to confirm its applicability. Results demonstrate that the proposed model produces more reliable streamflow estimates than the other approaches. In particular, when applied to partially gaged sites with sufficient available data, the proposed model clearly outperforms the other models. Even though the model is illustrated by a specific case, it can be extended to other regions with diverse hydro-climatological variables for the objective of infilling.

Physically based coefficient for streamflow estimation in ice-covered channels

2018 ◽  
Vol 563 ◽  
pp. 470-479 ◽  
Author(s):  
Gang Chen ◽  
Shixiang Gu ◽  
Ben Li ◽  
Mi Zhou ◽  
Wenxin Huai
Keyword(s):  
Physically Based ◽  
Streamflow Estimation

scholarly journals Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system

2004 ◽  
Vol 298 (1-4) ◽  
pp. 112-135 ◽  
Author(s):  
Newsha K. Ajami ◽  
Hoshin Gupta ◽  
Thorsten Wagener ◽  
Soroosh Sorooshian
Keyword(s):  
River System ◽  
Hydrologic Model ◽  
Distributed Hydrologic Model ◽  
Streamflow Estimation

Amélioration de méthodes d'estimation des débits journaliers

1993 ◽  
Vol 20 (3) ◽  
pp. 490-499
Author(s):  
Saad Bennis ◽  
Pierre Bruneau
Keyword(s):  
Kalman Filter ◽  
Test Area ◽  
Estimation Methods ◽  
Improve Performance ◽  
Physical Test ◽  
Noise Covariance Matrix ◽  
Filtering Algorithm ◽  
Daily Streamflow ◽  
Streamflow Estimation ◽  
Noise Covariance

The aim of the research described in this paper was to improve results obtained with conventional daily streamflow estimation methods. The technique requires a robust filter such as the Kalman filter. An explanation of the general filtering algorithm is first given, followed by illustration of how the robust-filter technique can be combined with daily streamflow estimation methods to improve performance. In particular, missing data estimates were more precise with the robust filter, and independent residuals with autocorrelation functions close to zero were obtained. The Saint-François River basin was used as a physical test area. Key words: Kalman filter, missing streamflow record, persistence, extrapolation, noise covariance matrix, residual autocorrelation. [Journal translation]

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