Articles | Volume 24, issue 3
https://doi.org/10.5194/hess-24-1319-2020
© Author(s) 2020. 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-24-1319-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment
Department Systems Analysis, Integrated Assessment and Modelling,
Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
The Centre of Hydrogeology and Geothermics (CHYN), University of
Neuchâtel, 2000 Neuchâtel, Switzerland
Department of Water Resources and Drinking Water, Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
Mario Schirmer
The Centre of Hydrogeology and Geothermics (CHYN), University of
Neuchâtel, 2000 Neuchâtel, Switzerland
Department of Water Resources and Drinking Water, Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
Massimiliano Zappa
Hydrological Forecast, Swiss Federal Research Institute WSL, 8903
Birmensdorf, Switzerland
Fabrizio Fenicia
Department Systems Analysis, Integrated Assessment and Modelling,
Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
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Cited
21 citations as recorded by crossref.
- Groundwater recharge rate estimation using remotely sensed and ground-based data: A method application in the mesoscale Thur catchment N. Burri et al. 10.1016/j.ejrh.2021.100972
- Streamflow prediction in ungauged catchments by using the Grunsky method B. Marchezepe et al. 10.1016/j.iswcr.2023.06.004
- Why do we have so many different hydrological models? A review based on the case of Switzerland P. Horton et al. 10.1002/wat2.1574
- Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models M. Bacci et al. 10.1016/j.jhydrol.2022.128057
- Spatial and temporal distribution characteristics of typical pollution loads based on SWAT model across Tuojiang River watershed located in Sichuan Province, Southwest of China Y. Wang et al. 10.1007/s10661-023-11481-6
- Evaluation and Comparison of Reanalysis Data for Runoff Simulation in the Data-Scarce Watersheds of Alpine Regions X. Wang et al. 10.3390/rs16050751
- HESS Opinions: Are soils overrated in hydrology? H. Gao et al. 10.5194/hess-27-2607-2023
- Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling H. Herath et al. 10.5194/hess-25-4373-2021
- Preface: Linking landscape organisation and hydrological functioning: from hypotheses and observations to concepts, models and understanding C. Jackisch et al. 10.5194/hess-25-5277-2021
- SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models M. Dal Molin et al. 10.5194/gmd-14-7047-2021
- Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica S. Arciniega-Esparza et al. 10.5194/hess-26-975-2022
- Exploring Signature‐Based Model Calibration for Streamflow Prediction in Ungauged Basins M. Dal Molin et al. 10.1029/2022WR031929
- Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas O. Wani et al. 10.1038/s41598-024-77687-x
- Hydrometeorological characterization and estimation of landfill leachate generation in the Eastern Amazon/Brazil C. Reyes Flores et al. 10.7717/peerj.14686
- Optimization of a SWAT model by incorporating geological information through calibration strategies A. Sánchez-Gómez et al. 10.1007/s11081-022-09744-1
- Subbasin Spatial Scale Effects on Hydrological Model Prediction Uncertainty of Extreme Stream Flows in the Omo Gibe River Basin, Ethiopia B. Gebeyehu et al. 10.3390/rs15030611
- Modeling streamflow variability at the regional scale: (1) perceptual model development through signature analysis F. Fenicia & J. McDonnell 10.1016/j.jhydrol.2021.127287
- Evaluation of the contributions of climate change and overgrazing to runoff in a typical grassland inland river basin Y. Zhou et al. 10.1016/j.ejrh.2024.101725
- Modeling streamflow variability at the regional scale: (2) Development of a bespoke distributed conceptual model F. Fenicia et al. 10.1016/j.jhydrol.2021.127286
- Flood forecasting methods for a semi‐arid and semi‐humid area in Northern China X. Zhu et al. 10.1111/jfr3.12831
- CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland M. Höge et al. 10.5194/essd-15-5755-2023
21 citations as recorded by crossref.
- Groundwater recharge rate estimation using remotely sensed and ground-based data: A method application in the mesoscale Thur catchment N. Burri et al. 10.1016/j.ejrh.2021.100972
- Streamflow prediction in ungauged catchments by using the Grunsky method B. Marchezepe et al. 10.1016/j.iswcr.2023.06.004
- Why do we have so many different hydrological models? A review based on the case of Switzerland P. Horton et al. 10.1002/wat2.1574
- Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models M. Bacci et al. 10.1016/j.jhydrol.2022.128057
- Spatial and temporal distribution characteristics of typical pollution loads based on SWAT model across Tuojiang River watershed located in Sichuan Province, Southwest of China Y. Wang et al. 10.1007/s10661-023-11481-6
- Evaluation and Comparison of Reanalysis Data for Runoff Simulation in the Data-Scarce Watersheds of Alpine Regions X. Wang et al. 10.3390/rs16050751
- HESS Opinions: Are soils overrated in hydrology? H. Gao et al. 10.5194/hess-27-2607-2023
- Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling H. Herath et al. 10.5194/hess-25-4373-2021
- Preface: Linking landscape organisation and hydrological functioning: from hypotheses and observations to concepts, models and understanding C. Jackisch et al. 10.5194/hess-25-5277-2021
- SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models M. Dal Molin et al. 10.5194/gmd-14-7047-2021
- Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica S. Arciniega-Esparza et al. 10.5194/hess-26-975-2022
- Exploring Signature‐Based Model Calibration for Streamflow Prediction in Ungauged Basins M. Dal Molin et al. 10.1029/2022WR031929
- Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas O. Wani et al. 10.1038/s41598-024-77687-x
- Hydrometeorological characterization and estimation of landfill leachate generation in the Eastern Amazon/Brazil C. Reyes Flores et al. 10.7717/peerj.14686
- Optimization of a SWAT model by incorporating geological information through calibration strategies A. Sánchez-Gómez et al. 10.1007/s11081-022-09744-1
- Subbasin Spatial Scale Effects on Hydrological Model Prediction Uncertainty of Extreme Stream Flows in the Omo Gibe River Basin, Ethiopia B. Gebeyehu et al. 10.3390/rs15030611
- Modeling streamflow variability at the regional scale: (1) perceptual model development through signature analysis F. Fenicia & J. McDonnell 10.1016/j.jhydrol.2021.127287
- Evaluation of the contributions of climate change and overgrazing to runoff in a typical grassland inland river basin Y. Zhou et al. 10.1016/j.ejrh.2024.101725
- Modeling streamflow variability at the regional scale: (2) Development of a bespoke distributed conceptual model F. Fenicia et al. 10.1016/j.jhydrol.2021.127286
- Flood forecasting methods for a semi‐arid and semi‐humid area in Northern China X. Zhu et al. 10.1111/jfr3.12831
- CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland M. Höge et al. 10.5194/essd-15-5755-2023
Latest update: 20 Nov 2024