What is he best known for?
The fields of study he is best known for:
- Statistics
- Climate change
- Hydrology
Stewart W. Franks spends much of his time researching Bayesian probability, Econometrics, Calibration, Uncertainty analysis and La Niña.
His Econometrics research includes themes of Statistics and Errors-in-variables models.
His work is dedicated to discovering how Calibration, Remote sensing are connected with Range and GLUE and other disciplines.
Stewart W. Franks interconnects Estimation theory and Bayesian inference in the investigation of issues within Uncertainty analysis.
His La Niña research is multidisciplinary, incorporating perspectives in Interdecadal Pacific Oscillation and Southern oscillation.
In Interdecadal Pacific Oscillation, he works on issues like Predictability, which are connected to Streamflow.
His most cited work include:
- IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences (808 citations)
- Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors (474 citations)
- Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops (443 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Climatology, Hydrology, Climate change, Flood myth and Bayesian probability.
His research investigates the connection between Climatology and topics such as Streamflow that intersect with problems in Surface runoff.
His work in the fields of Hydrology, such as Drainage basin, Hydrological modelling, Water quality and Catchment hydrology, intersects with other areas such as Structural basin.
His work on Flood frequency analysis, 100-year flood and Flood forecasting as part of general Flood myth study is frequently connected to Estimation, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Bayesian probability study integrates concerns from other disciplines, such as Calibration, Data mining and Econometrics.
He focuses mostly in the field of Econometrics, narrowing it down to matters related to Uncertainty analysis and, in some cases, Estimation theory.
He most often published in these fields:
- Climatology (31.17%)
- Hydrology (20.78%)
- Climate change (18.18%)
What were the highlights of his more recent work (between 2008-2018)?
- Climatology (31.17%)
- Hydrology (20.78%)
- Climate change (18.18%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Climatology, Hydrology, Climate change, Flood myth and Uncertainty analysis.
His work on Pacific decadal oscillation as part of his general Climatology study is frequently connected to Structural basin, thereby bridging the divide between different branches of science.
His research in the fields of Streamflow, Drainage basin and Surface runoff overlaps with other disciplines such as Transport pathways.
His Flood myth study incorporates themes from El Niño Southern Oscillation and Meteorology.
His biological study spans a wide range of topics, including Econometrics and Bayesian inference.
His study looks at the intersection of Econometrics and topics like Least squares with Calibration and Rain gauge.
Between 2008 and 2018, his most popular works were:
- Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors (474 citations)
- Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis (296 citations)
- Confronting Input Uncertainty in Environmental Modelling (168 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Climate change
- Hydrology
Stewart W. Franks mainly investigates Bayesian probability, Environmental resource management, Climatology, Range and Hydrology.
The Bayesian probability study combines topics in areas such as Calibration, Uncertainty analysis and Econometrics.
His Sensitivity analysis study in the realm of Uncertainty analysis interacts with subjects such as Environmental data.
The various areas that he examines in his Environmental resource management study include Hydrology and Management science.
His Climatology study combines topics in areas such as Global warming, Scale and Evapotranspiration.
His research investigates the connection between Hydrology and topics such as Macrophyte that intersect with issues in Surface runoff.
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