Articles | Volume 19, issue 1
https://doi.org/10.5194/hess-19-1-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-1-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A strategy to overcome adverse effects of autoregressive updating of streamflow forecasts
M. Li
CORRESPONDING AUTHOR
CSIRO Digital Productivity Flagship, Floreat, Western Australia, Australia
Q. J. Wang
CSIRO Land and Water Flagship, Highett, Victoria, Australia
J. C. Bennett
CSIRO Land and Water Flagship, Highett, Victoria, Australia
D. E. Robertson
CSIRO Land and Water Flagship, Highett, Victoria, Australia
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- Water flow probabilistic predictions based on a rainfall–runoff simulator: a two-regime model with variable selection M. Courbariaux et al. 10.1007/s13253-017-0278-5
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
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40 citations as recorded by crossref.
- A back-fitting algorithm to improve real-time flood forecasting X. Zhang et al. 10.1016/j.jhydrol.2018.04.051
- Theoretical analysis of non‐Gaussian heterogeneity effects on subsurface flow and transport M. Riva et al. 10.1002/2016WR019353
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- Enhancing the hydrologic system differential response method for flood forecasting correction X. Zhang et al. 10.1016/j.jhydrol.2020.125793
- Advancing Medium-Range Streamflow Forecasting for Large Hydropower Reservoirs in Brazil by Means of Continental-Scale Hydrological Modeling A. Kolling Neto et al. 10.3390/w15091693
- Complex relationship between seasonal streamflow forecast skill and value in reservoir operations S. Turner et al. 10.5194/hess-21-4841-2017
- An error model for long-range ensemble forecasts of ephemeral rivers J. Bennett et al. 10.1016/j.advwatres.2021.103891
- New scaling model for variables and increments with heavy‐tailed distributions M. Riva et al. 10.1002/2015WR016998
- A Bayesian Hierarchical Framework for Postprocessing Daily Streamflow Simulations across a River Network Á. Ossandón et al. 10.1175/JHM-D-21-0167.1
- Water flow probabilistic predictions based on a rainfall–runoff simulator: a two-regime model with variable selection M. Courbariaux et al. 10.1007/s13253-017-0278-5
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting G. Zuo et al. 10.1016/j.jhydrol.2020.124776
- Propagating reliable estimates of hydrological forecast uncertainty to many lead times J. Bennett et al. 10.1016/j.jhydrol.2021.126798
- Study of teleconnection between hydrological variables and climatological variables in a headwater basin of the Maipo River for forecast model application J. Montalva et al. 10.24850/j-tyca-16-4-3
- A long short-term components neural network model with data augmentation for daily runoff forecasting J. Zhang & H. Yan 10.1016/j.jhydrol.2022.128853
- Temporally varied error modelling for improving simulations and quantifying uncertainty L. Liu et al. 10.1016/j.jhydrol.2020.124914
- Reliable hourly streamflow forecasting with emphasis on ephemeral rivers M. Li et al. 10.1016/j.jhydrol.2020.125739
- Stacking ensemble learning models for daily runoff prediction using 1D and 2D CNNs Y. Xie et al. 10.1016/j.eswa.2022.119469
- Assessment of an ensemble seasonal streamflow forecasting system for Australia J. Bennett et al. 10.5194/hess-21-6007-2017
- Quantifying the Risks that Propagate from the Inflow Forecast Uncertainty to the Reservoir Operations with Coupled Flood and Electricity Curtailment Risks Q. Ma et al. 10.3390/w13020173
- Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model J. Bennett et al. 10.1002/2016WR019193
- Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy A. Elshall et al. 10.5194/gmd-12-2009-2019
- Combining two-stage decomposition based machine learning methods for annual runoff forecasting S. Chen et al. 10.1016/j.jhydrol.2021.126945
- Multi-model integrated error correction for streamflow simulation based on Bayesian model averaging and dynamic system response curve J. Wang et al. 10.1016/j.jhydrol.2022.127518
- Application of auto-regressive (AR) analysis to improve short-term prediction of water levels in the Yangtze estuary Y. Chen et al. 10.1016/j.jhydrol.2020.125386
- Forecasting Magnitude and Frequency of Seasonal Streamflow Extremes Using a Bayesian Hierarchical Framework Á. Ossandón et al. 10.1029/2022WR033194
- Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales D. Feng et al. 10.1029/2019WR026793
- Achieving high-quality probabilistic predictions from hydrological models calibrated with a wide range of objective functions J. Hunter et al. 10.1016/j.jhydrol.2021.126578
- Lead-time-dependent calibration of a flood forecasting model P. Astagneau et al. 10.1016/j.jhydrol.2024.132119
- Improved error modelling for streamflow forecasting at hourly time steps by splitting hydrographs into rising and falling limbs M. Li et al. 10.1016/j.jhydrol.2017.10.057
- A Bayesian Hierarchical Model Combination Framework for Real‐Time Daily Ensemble Streamflow Forecasting Across a Rainfed River Basin Á. Ossandón et al. 10.1029/2022EF002958
- A spatial distributed runoff correction approach based on differential response Z. Xiaoqin et al. 10.18307/2021.0624
- Error reduction and representation in stages (ERRIS) in hydrological modelling for ensemble streamflow forecasting M. Li et al. 10.5194/hess-20-3561-2016
- A Data Censoring Approach for Predictive Error Modeling of Flow in Ephemeral Rivers Q. Wang et al. 10.1029/2019WR026128
- Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation R. Sun et al. 10.1016/j.jhydrol.2017.09.041
- Error correction-based forecasting of reservoir water levels: Improving accuracy over multiple lead times X. Zhang et al. 10.1016/j.envsoft.2018.02.017
- Groundwater level prediction using a SOM-aided stepwise cluster inference model J. Han et al. 10.1016/j.jenvman.2016.07.069
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