Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-711-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-711-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Feb 2021
Research article |
| 18 Feb 2021
| 18 Feb 2021
A time-varying parameter estimation approach using split-sample calibration based on dynamic programming
Xiaojing Zhang
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
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- Citizen science data to improve rainfall-runoff model performance in urbanizing Akaki catchment, Awash Basin, Ethiopia G. Mengistie et al. 10.1016/j.ejrh.2024.101822
- Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning X. Lian et al. 10.3390/w16060896
- Impact of surface and underground water uses on streamflow in the upper-middle of the Weihe River basin using a modified WetSpa model M. Wu et al. 10.1016/j.jhydrol.2022.128840
- Strategic bidding for a hydro-wind-photovoltaic hybrid system considering the profit beyond forecast time X. Li et al. 10.1016/j.renene.2022.12.098
- What is the near-natural catchment? An application of hydrological signatures assessment H. Xu et al. 10.1016/j.ecolind.2025.113209
- Uncertainty analysis method for diagnosing multi-point defects in urban drainage systems C. Zhou et al. 10.1016/j.watres.2024.122849
- Estimation of spatiotemporally varying parameters for grid-based distributed hydrologic models X. Zhang et al. 10.1016/j.ejrh.2025.102536
- A hydrologic similarity-based parameters dynamic matching framework: Application to enhance the real-time flood forecasting H. Wu et al. 10.1016/j.scitotenv.2023.167767
- The temporal variations in runoff-generation parameters of the Xinanjiang model due to human activities: A case study in the upper Yangtze River Basin, China X. Zhang et al. 10.1016/j.ejrh.2021.100910
- Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
- Sensor Networks, Data Processing, and Inference: The Hydrology Challenge A. Zanella et al. 10.1109/ACCESS.2023.3318739
- Dynamic calibration of phytoplankton blooms using the modified SWAT model J. Lee et al. 10.1016/j.jclepro.2022.131005
- An analytic operating rule for reservoirs under the Budyko “supply–demand” framework W. Liu et al. 10.1016/j.jhydrol.2022.128788
- Time-varying parameters from the same period in previous years to improve runoff forecasting X. Zhang et al. 10.1016/j.jhydrol.2024.130685
- Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach O. Repina et al. 10.1016/j.coastaleng.2025.104738
- Comparison of data assimilation based approach for daily streamflow simulation under multiple scenarios in Ganjiang River Basin W. Weiguang et al. 10.18307/2023.0323
- A Differentiable Hydrology Approach for Modeling With Time‐Varying Parameters C. Krapu & M. Borsuk 10.1029/2021WR031377
- Deriving adaptive long-term complementary operating rules for a large-scale hydro-photovoltaic hybrid power plant using ensemble Kalman filter H. Li et al. 10.1016/j.apenergy.2021.117482
- Simulating Runoff and Actual Evapotranspiration via Time-Variant Parameter Method: The Effects of Hydrological Model Structures Z. Pan et al. 10.1061/(ASCE)HE.1943-5584.0002220
- Coupled effects of observation and parameter uncertainty on urban groundwater infrastructure decisions M. Mautner et al. 10.5194/hess-26-1319-2022
- Diagnosing structural deficiencies of a hydrological model by time-varying parameters L. Zhou et al. 10.1016/j.jhydrol.2021.127305
21 citations as recorded by crossref.
- Citizen science data to improve rainfall-runoff model performance in urbanizing Akaki catchment, Awash Basin, Ethiopia G. Mengistie et al. 10.1016/j.ejrh.2024.101822
- Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning X. Lian et al. 10.3390/w16060896
- Impact of surface and underground water uses on streamflow in the upper-middle of the Weihe River basin using a modified WetSpa model M. Wu et al. 10.1016/j.jhydrol.2022.128840
- Strategic bidding for a hydro-wind-photovoltaic hybrid system considering the profit beyond forecast time X. Li et al. 10.1016/j.renene.2022.12.098
- What is the near-natural catchment? An application of hydrological signatures assessment H. Xu et al. 10.1016/j.ecolind.2025.113209
- Uncertainty analysis method for diagnosing multi-point defects in urban drainage systems C. Zhou et al. 10.1016/j.watres.2024.122849
- Estimation of spatiotemporally varying parameters for grid-based distributed hydrologic models X. Zhang et al. 10.1016/j.ejrh.2025.102536
- A hydrologic similarity-based parameters dynamic matching framework: Application to enhance the real-time flood forecasting H. Wu et al. 10.1016/j.scitotenv.2023.167767
- The temporal variations in runoff-generation parameters of the Xinanjiang model due to human activities: A case study in the upper Yangtze River Basin, China X. Zhang et al. 10.1016/j.ejrh.2021.100910
- Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
- Sensor Networks, Data Processing, and Inference: The Hydrology Challenge A. Zanella et al. 10.1109/ACCESS.2023.3318739
- Dynamic calibration of phytoplankton blooms using the modified SWAT model J. Lee et al. 10.1016/j.jclepro.2022.131005
- An analytic operating rule for reservoirs under the Budyko “supply–demand” framework W. Liu et al. 10.1016/j.jhydrol.2022.128788
- Time-varying parameters from the same period in previous years to improve runoff forecasting X. Zhang et al. 10.1016/j.jhydrol.2024.130685
- Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach O. Repina et al. 10.1016/j.coastaleng.2025.104738
- Comparison of data assimilation based approach for daily streamflow simulation under multiple scenarios in Ganjiang River Basin W. Weiguang et al. 10.18307/2023.0323
- A Differentiable Hydrology Approach for Modeling With Time‐Varying Parameters C. Krapu & M. Borsuk 10.1029/2021WR031377
- Deriving adaptive long-term complementary operating rules for a large-scale hydro-photovoltaic hybrid power plant using ensemble Kalman filter H. Li et al. 10.1016/j.apenergy.2021.117482
- Simulating Runoff and Actual Evapotranspiration via Time-Variant Parameter Method: The Effects of Hydrological Model Structures Z. Pan et al. 10.1061/(ASCE)HE.1943-5584.0002220
- Coupled effects of observation and parameter uncertainty on urban groundwater infrastructure decisions M. Mautner et al. 10.5194/hess-26-1319-2022
- Diagnosing structural deficiencies of a hydrological model by time-varying parameters L. Zhou et al. 10.1016/j.jhydrol.2021.127305
Latest update: 29 Jun 2025
Short summary
Rainfall–runoff models are useful tools for streamflow simulation. However, efforts are needed to investigate how their parameters vary in response to climate changes and human activities. Thus, this study proposes a new method for estimating time-varying parameters, by considering both simulation accuracy and parameter continuity. The results show the proposed method is effective for identifying temporal variations of parameters and can simultaneously provide good streamflow simulation.
Rainfall–runoff models are useful tools for streamflow simulation. However, efforts are needed...
