Articles | Volume 9, issue 3
https://doi.org/10.5194/hess-9-209-2005
© Author(s) 2005. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
https://doi.org/10.5194/hess-9-209-2005
© Author(s) 2005. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series
B. A. Amisigo
Center for Development Research, Bonn University, Bonn, Germany
Delft University of Technology, Delft, Netherlands
N. C. van de Giesen
Delft University of Technology, Delft, Netherlands
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- Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters C. Kermorvant et al. 10.3390/ijerph182312803
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26 citations as recorded by crossref.
- Discrimination of water quality monitoring sites in River Vouga using a mixed-effect state space model M. Costa & M. Monteiro 10.1007/s00477-015-1137-y
- Improving the Quality of Satellite Imagery Based on Ground-Truth Data from Rain Gauge Stations A. Militino et al. 10.3390/rs10030398
- Robust Forecasting of River-Flow Based on Convolutional Neural Network C. Huang et al. 10.1109/TSUSC.2020.2983097
- Measuring instantaneous frequency of local field potential oscillations using the Kalman smoother D. Nguyen et al. 10.1016/j.jneumeth.2009.08.012
- Spatio-Temporal Modeling of Data Imputation for Daily Rainfall Series in Homogeneous Zones J. Carvalho et al. 10.1590/0102-778631220150025
- Spatio-temporal dynamic model and parallelized ensemble Kalman filter for precipitation data L. Sánchez et al. 10.1214/15-BJPS297
- Weighted Linear Dynamic System for Feature Representation and Soft Sensor Application in Nonlinear Dynamic Industrial Processes X. Yuan et al. 10.1109/TIE.2017.2733443
- Stochastic Spatio-Temporal Models for Analysing NDVI Distribution of GIMMS NDVI3g Images A. Militino et al. 10.3390/rs9010076
- Modeling Impact of Climate Change on Water Resources and Agriculture Demand in the Volta Basin and other Basin Systems in Ghana B. Amisigo et al. 10.3390/su7066957
- Hydrological modelling in data-scarce catchments: Black Volta basin in West Africa S. Kwakye & A. Bárdossy 10.1007/s42452-020-2454-4
- Current awareness 10.1002/hyp.6193
- Monthly stream flow forecasting via dynamic spatio-temporal models M. Dehghani et al. 10.1007/s00477-014-0967-3
- Modelling the potential spread of Hyalomma marginatum ticks in Europe by migratory birds A. Estrada-Peña et al. 10.1016/j.ijpara.2020.08.004
- A Unified Statistical Approach for Simulation, Modeling, Analysis and Mapping of Environmental Data A. Fassò & M. Cameletti 10.1177/0037549709102150
- Filling Gaps in Measured Discharge Series with Model-Generated Series J. Jónsdóttir et al. 10.1061/(ASCE)1084-0699(2008)13:9(905)
- The EM algorithm in a distributed computing environment for modelling environmental space–time data A. Fassò & M. Cameletti 10.1016/j.envsoft.2009.02.009
- A Kalman filter method for estimation and prediction of space–time data with an autoregressive structure B. Lagos-Álvarez et al. 10.1016/j.jspi.2019.03.005
- Interpolation of daily rainfall using spatiotemporal models and clustering A. Militino et al. 10.1002/joc.4068
- MISSING DISCHARGE DATA FILLING WITH ARTIFICIAL NEURAL NETWORK M. JANHABI 10.26634/jce.9.2.14657
- Evaluation of dynamic regression and artificial neural networks models for real-time hydrological drought forecasting M. Dehghani et al. 10.1007/s12517-017-2990-4
- Diagnosing the potential of hydro-climatic information services to support rice farming in northern Ghana E. Nyadzi et al. 10.1016/j.njas.2018.07.002
- Reconstruction of missing daily streamflow data using dynamic regression models P. Tencaliec et al. 10.1002/2015WR017399
- Gap-filling snow-depth time-series with Kalman Filtering-Smoothing and Expectation Maximization: Proof of concept using spatially dense wireless-sensor-network data F. Avanzi et al. 10.1016/j.coldregions.2020.103066
- Gap-filling of daily streamflow time series using Direct Sampling in various hydroclimatic settings M. Dembélé et al. 10.1016/j.jhydrol.2018.11.076
- Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters C. Kermorvant et al. 10.3390/ijerph182312803
- Space‐time autoregressive estimation and prediction with missing data based on Kalman filtering L. Padilla et al. 10.1002/env.2627
1 citations as recorded by crossref.
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