Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-1015-2019
© Author(s) 2019. 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-23-1015-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Identifying rainfall-runoff events in discharge time series: a data-driven method based on information theory
Stephanie Thiesen
CORRESPONDING AUTHOR
Institute of Water Resources and River Basin Management, Karlsruhe
Institute of Technology (KIT), Karlsruhe, Germany
Paul Darscheid
Institute of Water Resources and River Basin Management, Karlsruhe
Institute of Technology (KIT), Karlsruhe, Germany
Uwe Ehret
Institute of Water Resources and River Basin Management, Karlsruhe
Institute of Technology (KIT), Karlsruhe, Germany
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Cited
24 citations as recorded by crossref.
- Quantitative precipitation estimation with weather radar using a data- and information-based approach M. Neuper & U. Ehret
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- River Levee Overtopping: A Bivariate Methodology for Hydrological Characterization of Overtopping Failure M. Isola et al.
- A novel ensemble algorithm based on hydrological event diversity for urban rainfall–runoff model calibration and validation E. Snieder & U. Khan
- Assessing local and spatial uncertainty with nonparametric geostatistics S. Thiesen & U. Ehret
- Dryspells and Minimum Air Temperatures Influence Rice Yields and their Forecast Uncertainties in Rainfed Systems A. Abhishek et al.
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- A statistics-based automated flood event separation S. Fischer et al.
- A pioneering approach to deterministic rainfall forecasting for wet period in the Northern Territory of Australia using machine learning R. Farooq et al.
- Information-theoretic analysis of commercial microwave link and environmental variables in rainfall estimation A. Špačková et al.
- On the Automation of Flood Event Separation From Continuous Time Series H. Oppel & B. Mewes
- Are years-long field studies about window operation efficient? a data-driven approach based on information theory and deep learning M. Bavaresco et al.
- Optimizing parameter learning and calibration in an integrated hydrological model: Impact of observation length and information P. Jiang et al.
- Histogram via entropy reduction (HER): an information-theoretic alternative for geostatistics S. Thiesen et al.
- Ensemble Kalman Inversion for upstream parameter estimation and indirect streamflow correction: A simulation study A. Pensoneault et al.
- A comparison of catchment travel times and storage deduced from deuterium and tritium tracers using StorAge Selection functions N. Rodriguez et al.
- Risk assessment of floor water inrush based on TOPSIS combined weighting model: a case study in a coal mine, China Q. Li et al.
- A hybrid deep learning approach for streamflow prediction utilizing watershed memory and process-based modeling B. Yifru et al.
- An Objective Time‐Series‐Analysis Method for Rainfall‐Runoff Event Identification G. Giani et al.
- Estimation of catchment response time using a new automated event-based approach E. Nagy et al.
- Streamflow forecasting for the Hunza river basin using ANN, RNN, and ANFIS models M. Khan et al.
- Assessment of water inrush risk based comprehensive cloud model: a case study in a lead zinc mine, China Q. Li et al.
- A Mutual Information Theory‐Based Approach for Assessing Uncertainties in Deterministic Multi‐Category Precipitation Forecasts Y. Ning et al.
- Assessment of stream water quality variables, an effective procedure to analyze hysteresis relationships O. Khettab et al.
24 citations as recorded by crossref.
- Quantitative precipitation estimation with weather radar using a data- and information-based approach M. Neuper & U. Ehret
- The testing of a multivariate probabilistic framework for reservoir safety evaluation and flood risks assessment in Slovakia: A study on the Parná and Belá Rivers R. Výleta et al.
- River Levee Overtopping: A Bivariate Methodology for Hydrological Characterization of Overtopping Failure M. Isola et al.
- A novel ensemble algorithm based on hydrological event diversity for urban rainfall–runoff model calibration and validation E. Snieder & U. Khan
- Assessing local and spatial uncertainty with nonparametric geostatistics S. Thiesen & U. Ehret
- Dryspells and Minimum Air Temperatures Influence Rice Yields and their Forecast Uncertainties in Rainfed Systems A. Abhishek et al.
- Spatial distribution characteristics in water yield property of middle Jurassic sandstone aquifers using nonlinear combination method J. Zhu et al.
- A statistics-based automated flood event separation S. Fischer et al.
- A pioneering approach to deterministic rainfall forecasting for wet period in the Northern Territory of Australia using machine learning R. Farooq et al.
- Information-theoretic analysis of commercial microwave link and environmental variables in rainfall estimation A. Špačková et al.
- On the Automation of Flood Event Separation From Continuous Time Series H. Oppel & B. Mewes
- Are years-long field studies about window operation efficient? a data-driven approach based on information theory and deep learning M. Bavaresco et al.
- Optimizing parameter learning and calibration in an integrated hydrological model: Impact of observation length and information P. Jiang et al.
- Histogram via entropy reduction (HER): an information-theoretic alternative for geostatistics S. Thiesen et al.
- Ensemble Kalman Inversion for upstream parameter estimation and indirect streamflow correction: A simulation study A. Pensoneault et al.
- A comparison of catchment travel times and storage deduced from deuterium and tritium tracers using StorAge Selection functions N. Rodriguez et al.
- Risk assessment of floor water inrush based on TOPSIS combined weighting model: a case study in a coal mine, China Q. Li et al.
- A hybrid deep learning approach for streamflow prediction utilizing watershed memory and process-based modeling B. Yifru et al.
- An Objective Time‐Series‐Analysis Method for Rainfall‐Runoff Event Identification G. Giani et al.
- Estimation of catchment response time using a new automated event-based approach E. Nagy et al.
- Streamflow forecasting for the Hunza river basin using ANN, RNN, and ANFIS models M. Khan et al.
- Assessment of water inrush risk based comprehensive cloud model: a case study in a lead zinc mine, China Q. Li et al.
- A Mutual Information Theory‐Based Approach for Assessing Uncertainties in Deterministic Multi‐Category Precipitation Forecasts Y. Ning et al.
- Assessment of stream water quality variables, an effective procedure to analyze hysteresis relationships O. Khettab et al.
Saved (final revised paper)
Latest update: 29 Apr 2026
Short summary
We present a data-driven approach created to explore the full information of data sets, avoiding parametric assumptions. The evaluations are based on Information Theory concepts, introducing an objective measure of information and uncertainty. The approach was applied to automatically identify rainfall-runoff events in discharge time series, however it is generic enough to be adapted to other practical applications.
We present a data-driven approach created to explore the full information of data sets, avoiding...