25 citations as recorded by crossref.

1. 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
2. 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
3. Machine learning applications in flood forecasting and predictions, challenges, and way-out in the perspective of changing environment V. Kumar et al. 10.3934/environsci.2025004
4. A self-organizing map-based approach for groundwater model parameter identification L. Zhao et al. 10.1007/s00477-025-02967-5
5. Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment M. Dal Molin et al. 10.5194/hess-24-1319-2020
6. Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica S. Arciniega-Esparza et al. 10.5194/hess-26-975-2022
7. 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
8. Optimization of a SWAT model by incorporating geological information through calibration strategies A. Sánchez-Gómez et al. 10.1007/s11081-022-09744-1
9. 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
10. Modeling streamflow variability at the regional scale: (1) perceptual model development through signature analysis F. Fenicia & J. McDonnell 10.1016/j.jhydrol.2021.127287
11. 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
12. Flood forecasting methods for a semi‐arid and semi‐humid area in Northern China X. Zhu et al. 10.1111/jfr3.12831
13. Streamflow prediction in ungauged catchments by using the Grunsky method B. Marchezepe et al. 10.1016/j.iswcr.2023.06.004
14. 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
15. 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
16. Evaluation and Comparison of Reanalysis Data for Runoff Simulation in the Data-Scarce Watersheds of Alpine Regions X. Wang et al. 10.3390/rs16050751
17. HESS Opinions: Are soils overrated in hydrology? H. Gao et al. 10.5194/hess-27-2607-2023
18. Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling H. Herath et al. 10.5194/hess-25-4373-2021
19. 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
20. 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
21. Exploring Signature‐Based Model Calibration for Streamflow Prediction in Ungauged Basins M. Dal Molin et al. 10.1029/2022WR031929
22. Hydrometeorological characterization and estimation of landfill leachate generation in the Eastern Amazon/Brazil C. Reyes Flores et al. 10.7717/peerj.14686
23. Modelling and set-point definition for the development of a joint control system of two interconnected wastewater treatment plants and its application in practice J. Schütz et al. 10.2166/wst.2024.386
24. 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
25. 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