20 citations as recorded by crossref.

1. Filling the gap between Earth observation and policy making in the Black Sea catchment with enviroGRIDS A. Lehmann et al. https://doi.org/10.1016/j.envsci.2014.02.005
2. A web platform for landuse, climate, demography, hydrology and beach erosion in the Black Sea catchment A. Lehmann et al. https://doi.org/10.1038/sdata.2017.87
3. Quantifying the Performances of the Semi-Distributed Hydrologic Model in Parallel Computing—A Case Study J. Kim & J. Ryu https://doi.org/10.3390/w11040823
4. SWAT hydrological model as a DaaS cloud service H. Astsatryan et al. https://doi.org/10.1007/s12145-016-0254-6
5. Hydro-climate and biogeochemical processes control watershed organic carbon inflows: Development of an in-stream organic carbon module coupled with a process-based hydrologic model X. Du et al. https://doi.org/10.1016/j.scitotenv.2020.137281
6. Advancing model calibration and uncertainty analysis of SWAT models using cloud computing infrastructure: LCC-SWAT M. Zamani et al. https://doi.org/10.2166/hydro.2020.066
7. Soil and Water Assessment Tool (SWAT Model) for Estimating Groundwater Recharge in Sokoto-Rima River Basin, Northwestern Nigeria E. Akudo et al. https://doi.org/10.66922/jmg.v58n1.022
8. A scalable distributed parallel simulation tool for the SWAT model Q. Lin & D. Zhang https://doi.org/10.1016/j.envsoft.2021.105133
9. GP-SWAT (v1.0): a two-level graph-based parallel simulation tool for the SWAT model D. Zhang et al. https://doi.org/10.5194/gmd-14-5915-2021
10. Scalability and Computational Performance of an Ecohydrological Model Using Machine Learning-Based Prediction N. Cortés-Torres et al. https://doi.org/10.3390/w18040466
11. Reviewing innovative Earth observation solutions for filling science-policy gaps in hydrology A. Lehmann et al. https://doi.org/10.1016/j.jhydrol.2014.05.059
12. Improved Hadoop-based cloud for complex model simulation optimization: Calibration of SWAT as an example J. Ma et al. https://doi.org/10.1016/j.envsoft.2022.105330
13. Parallelization of a hydrological model using the message passing interface Y. Wu et al. https://doi.org/10.1016/j.envsoft.2013.02.002
14. Bringing GEOSS Services into Practice: A Capacity Building Resource on Spatial Data Infrastructures (SDI) G. Giuliani et al. https://doi.org/10.1111/tgis.12209
15. Assessing Climate Change Impacts on Streamflow, Sediment and Nutrient Loadings of the Minija River (Lithuania): A Hillslope Watershed Discretization Application with High-Resolution Spatial Inputs N. Čerkasova et al. https://doi.org/10.3390/w11040676
16. Assessment of blue water-green water interchange under extreme warm and dry events across different ecohydrological regions of western Canada P. Khalili et al. https://doi.org/10.1016/j.jhydrol.2023.130105
17. Comparison of Performance between Genetic Algorithm and SCE-UA for Calibration of SCS-CN Surface Runoff Simulation J. Jeon et al. https://doi.org/10.3390/w6113433
18. Streamflow modeling in a fluctuant climate using SWAT: Yass River catchment in south eastern Australia P. Saha et al. https://doi.org/10.1007/s12665-013-2926-6
19. Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess) S. McDonald et al. https://doi.org/10.1016/j.envsoft.2019.104499
20. A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model K. Abbaspour et al. https://doi.org/10.1016/j.jhydrol.2015.03.027