M. Vis
Water Science and Technology · 2012–2018
A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Water Science and Technology — 7 citations into it; #659 of 1,711 by trust here, #1,442 by citations
- Environmental Engineering — 5 citations into it; #4,048 of 5,479 by trust here, #5,257 by citations
- Global and Planetary Change — 5 citations into it; #6,936 of 10,225 by trust here, #9,714 by citations
Whom M. Vis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts M. Vis overall
Papers from M. Vis's perspective
Ordered by how strongly the researchers M. Vis trusts endorse each paper. Same corpus, a different order for every researcher.
- Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives
- Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods
- Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling
- A process‐based diagnostic approach to model evaluation: Application to the NWS distributed hydrologic model
- Individual Comparisons by Ranking Methods
- One decade of multi-objective calibration approaches in hydrological modelling: a review
- Which objective function to calibrate rainfall–runoff models for low-flow index simulations?
- Teaching hydrological modeling with a user-friendly catchment-runoff-model software package
- Smart low flow signature metrics for an improved overall performance evaluation of hydrological models
- The future of distributed models: model calibration and uncertainty prediction.
Their papers
- Evaluating model performance: towards a non-parametric variant of the Kling-Gupta efficiency (2018) — 206 citations
- Teaching hydrological modeling with a user-friendly catchment-runoff-model software package (2012) — 550 citations