What is he best known for?
The fields of study he is best known for:
- Statistics
- Hydrology
- Artificial intelligence
Jim Freer mostly deals with Hydrology, GLUE, Surface runoff, Uncertainty analysis and Equifinality.
His Hydrology study frequently draws parallels with other fields, such as Soil water.
Jim Freer interconnects Variable, Econometrics, Statistics, Bayes' theorem and Algorithm in the investigation of issues within GLUE.
His biological study spans a wide range of topics, including Rating curve, Water table and Subsurface flow.
His work on Sensitivity analysis is typically connected to Workflow as part of general Uncertainty analysis study, connecting several disciplines of science.
His study in Equifinality is interdisciplinary in nature, drawing from both Calibration, Estimation theory, Errors-in-variables models and Process.
His most cited work include:
- Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology (1505 citations)
- Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach (645 citations)
- A decade of Predictions in Ungauged Basins (PUB)—a review (519 citations)
What are the main themes of his work throughout his whole career to date?
Jim Freer mainly focuses on Hydrology, Drainage basin, Climatology, Flood myth and Hydrology.
His research on Hydrology frequently connects to adjacent areas such as Storm.
His studies link Nutrient with Storm.
His work carried out in the field of Climatology brings together such families of science as Climate change, Climate model and Precipitation.
His Flood myth research includes themes of Probabilistic logic and Meteorology.
His research on Watershed often connects related areas such as Streamflow.
He most often published in these fields:
- Hydrology (34.55%)
- Drainage basin (13.94%)
- Climatology (11.21%)
What were the highlights of his more recent work (between 2017-2021)?
- Hydrology (34.55%)
- Drainage basin (13.94%)
- Streamflow (6.97%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Hydrology, Drainage basin, Streamflow, Climatology and Volcano.
Flood myth and Groundwater are among the areas of Hydrology where he concentrates his study.
He usually deals with Drainage basin and limits it to topics linked to Process and Aquifer, Percentile, Karst and Sample.
His Streamflow study incorporates themes from Climate classification, Catchment hydrology and Robustness.
His work deals with themes such as Scale, Bias correction and Model selection, which intersect with Climatology.
His studies in Volcano integrate themes in fields like Plume and Geomorphology.
Between 2017 and 2021, his most popular works were:
- Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores (98 citations)
- A Comparison of Methods for Streamflow Uncertainty Estimation (39 citations)
- A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data (39 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Hydrology
- Artificial intelligence
Jim Freer spends much of his time researching Hydrology, Streamflow, Precipitation, Hydrology and Drainage basin.
His Hydrology research integrates issues from Sample and Process.
His research integrates issues of Parameter space, Catchment hydrology and Radiometer in his study of Streamflow.
The study incorporates disciplines such as Flood loss, Flood hazard, Structural basin and Global climate in addition to Precipitation.
The Hydrology study combines topics in areas such as Observational methods in psychology, Environmental resource management and Forcing.
The concepts of his Drainage basin study are interwoven with issues in Percentile, Particulates, Pollution, Dissolved organic carbon and Nutrient.
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