S. Franks

Water Science and Technology · with Kavetski · 2006–2010

A researcher in the Science corpus: 6 papers; trusts 9 researchers and is trusted by 47 researchers here, as inferred from the citation graph.

Subfields

• Water Science and Technology — 17 citations into it; #20 of 1,711 by trust here, #137 by citations
• Global and Planetary Change — 16 citations into it; #193 of 10,225 by trust here, #883 by citations
• Environmental Engineering — 13 citations into it
• Artificial Intelligence — 8 citations into it
• Statistics and Probability — 8 citations into it

Whom S. Franks trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Dmitri Kavetski
2. Qingyun Duan
3. Keith Beven
4. George A. Kuczera
5. Soroosh Sorooshian
6. A. Binley
7. Vinod Kumar Gupta

Who trusts S. Franks overall

1. Jasper A. Vrugt
2. Dmitri Kavetski
3. Benjamin Renard
4. M. Clark
5. Keith Beven
6. Mark A. Thyer
7. Hoshin V. Gupta
8. George A. Kuczera
9. G. Schoups
10. H. Dai

Papers from S. Franks's perspective

Ordered by how strongly the researchers S. Franks trusts endorse each paper. Same corpus, a different order for every researcher.

1. The future of distributed models: model calibration and uncertainty prediction.
2. Effective and efficient global optimization for conceptual rainfall‐runoff models
3. Bayesian calibration of computer models
4. Multi-model ensemble hydrologic prediction using Bayesian model averaging
5. An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
6. Dual state-parameter estimation of hydrological models using ensemble Kalman filter
7. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters
8. A manifesto for the equifinality thesis
9. Towards reduced uncertainty in conceptual rainfall‐runoff modelling: dynamic identifiability analysis
10. Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis

Their papers

• Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors (2010) — 825 citations
• Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis (2009) — 394 citations
• Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops (2006) — 441 citations
• Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory (2006) — 644 citations
• Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters (2006) — 378 citations
• Bayesian analysis of input uncertainty in hydrological modeling: 2. Application (2006) — 467 citations