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James W. Kirchner

Researcher at ETH Zurich

Publications -  265
Citations -  25661

James W. Kirchner is an academic researcher from ETH Zurich. The author has contributed to research in topics: Streamflow & Precipitation. The author has an hindex of 73, co-authored 238 publications receiving 21958 citations. Previous affiliations of James W. Kirchner include Planetary Science Institute & University of California.

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Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays

TL;DR: A novel sequencing approach that combines non-gel-based signature sequencing with in vitro cloning of millions of templates on separate 5 μm diameter microbeads provides an unprecedented depth of analysis permitting application of powerful statistical techniques for discovery of functional relationships among genes.
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Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology

TL;DR: In this article, the authors argue that scientific progress will mostly be achieved through the collision of theory and data, rather than through increasingly elaborate and parameter-rich models that may succeed as mathematical marionettes, dancing to match the calibration data even if their underlying premises are unrealistic.
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Fractal stream chemistry and its implications for contaminant transport in catchments

TL;DR: Detailed time series of chloride, a natural tracer, in both rainfall and runoff from headwater catchments at Plynlimon, Wales indicate that these catchments do not have characteristic flushing times, and their travel times follow an approximate power-law distribution implying that they will retain a long chemical memory of past inputs.
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Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology

TL;DR: This commentary addresses a number of related new avenues for research in watershed science, including the use of comparative analysis, classification, optimality principles, and network theory, all with the intent of defining, understanding, and predicting watershed function and enunciating important watershed functional traits.
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Catchments as simple dynamical systems: catchment characterization, rainfall-runoff modeling, and doing hydrology backward.

TL;DR: In this paper, a first-order nonlinear dynamical system can be inferred directly from measurements of streamflow fluctuations, leading to quantitative estimates of catchment dynamic storage, recession time scales and sensitivity to antecedent moisture, suggesting that it is useful for catchment characterization.