T
Timothy O. Randhir
Researcher at University of Massachusetts Amherst
Publications - 109
Citations - 2167
Timothy O. Randhir is an academic researcher from University of Massachusetts Amherst. The author has contributed to research in topics: Watershed & Watershed management. The author has an hindex of 24, co-authored 92 publications receiving 1587 citations. Previous affiliations of Timothy O. Randhir include Purdue University.
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Research needs for water quality management in the 21st century: A spatial decision support system
TL;DR: The ideas concerning the research needs (information and knowledge) as well as the decision making supports necessary for individuals and communities to make better choices regarding the tradeoffs among potential goods, services and levels of environmental amenities are detailed.
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Watershed land use and aquatic ecosystem response: Ecohydrologic approach to conservation policy
TL;DR: In this paper, a dynamic model that links land use, overland flow, suspended sediment, and an aquatic species is used to evaluate alternate land use policies in a watershed in Massachusetts.
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Trade Liberalization as a Vehicle for Adapting to Global Warming
TL;DR: In this paper, the authors assess the interaction between climate change and agricultural trade policies and find that increased price transmission, as called for under the Uruguay Round Agreement on Agriculture, reduces global welfare in the wake of climate change.
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Riparian restoration for protecting water quality in tropical agricultural watersheds
TL;DR: In this article, the authors used watershed simulation modeling to evaluate impacts of riparian forest restoration on water quality in a tropical agricultural watershed, and observed a spatial and temporal variation in water quality impacts of changes in land use/land cover (LULC) and rainfall patterns.
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Spatial modeling of land cover change and watershed response using Markovian cellular automata and simulation
Eric Marshall,Timothy O. Randhir +1 more
TL;DR: In this article, the authors evaluated potential implications of land cover change on the hydrology of a regional watershed by using Markov Chain analysis and Cellular Automation to assess future land cover based on transitional probabilities and spatial influences.