Rivers of North America
Arthur C. Benke, Colbert E. Cushing
AWARDS: 2006 Outstanding Academic Title, by CHOICE The 2005 Award for Excellence in Professional and Scholarly Publishing by the Association of American Publishers (AAP) Best Reference 2005, by the Library Journal Rivers of North America is an important reference for scientists, ecologists, and students studying rivers and their ecosystems. It brings together information from several regional specialists on the major river basins of North America, presented in a large-format, full-color book. The introduction covers general aspects of geology, hydrology, ecology and human impacts on rivers. This is followed by 22 chapters on the major river basins. Each chapter begins with a full-page color photograph and includes several additional photographs within the text. These chapters feature three to five rivers of the basin/region, and cover several other rivers with one-page summaries. Rivers selected for coverage include the largest, the most natural, and the most affected by human impact. This one-of-a-kind resource is professionally illustrated with maps and color photographs of the key river basins. Readers can compare one river system to another in terms of its physiography, hydrology, ecology, biodiversity, and human impacts.
Award History
1 wins · 1 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| PROSE Award for Earth and Environmental Sciences | 2005 | Winner | Official source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
None extracted with sufficient confidence.
03 Suggested argument
No argument inferred with sufficient confidence.
04 Reading orientation
75 / 100 academicAcademic
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 45%.