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William H. Farmer

Researcher at United States Geological Survey

Publications -  43
Citations -  1482

William H. Farmer is an academic researcher from United States Geological Survey. The author has contributed to research in topics: Streamflow & Hydrological modelling. The author has an hindex of 16, co-authored 38 publications receiving 1017 citations. Previous affiliations of William H. Farmer include Tufts University & Massachusetts Institute of Technology.

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Twenty-three unsolved problems in hydrology (UPH)–a community perspective

Günter Blöschl, +212 more
TL;DR: In this article, a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts is described. But despite the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work.
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Climate Change, Agriculture and Food Security in Tanzania: CLIMATE CHANGE AND FOOD SECURITY IN TANZANIA

TL;DR: In this article, the impact of climate change on food security in Tanzania is estimated using a highly disaggregated, recursive dynamic economy-wide model of Tanzania, and the authors find that, relative to a no-climate change baseline and considering domestic agricultural production as the channel of impact, food security appears likely to deteriorate as a consequence of climate changes.
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Quantifying the Likelihood of Regional Climate Change: A Hybridized Approach

TL;DR: In this article, the authors present a technique that extends the latitudinal projections of the 2D atmospheric model of the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate model projections archived from exercises carried out for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC).
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On the deterministic and stochastic use of hydrologic models

TL;DR: In this paper, a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored.