BLM-OR/WA, Watershed Assessment Model Development
Sector: Education • Location: United States of America
Source: Grants.gov
The Aquatic and Riparian Monitoring Program (AREMP) assesses the effectiveness of cumulative land management action on watershed condition across multiple jurisdictions within the range of the Northern Spotted Owl. Watersheds are evaluated using upslope and riparian information derived from Geographic Information System (GIS) and remotes sensing data, as well as inchannel attributes measured as pa
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | archived |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
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Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | The Aquatic and Riparian Monitoring Program (AREMP) assesses the effectiveness of cumulative land management action on watershed condition across multiple jurisdictions within the range of the Northern Spotted Owl. Watersheds are evaluated using upslope and riparian information derived from Geographic Information System (GIS) and remotes sensing data, as well as inchannel attributes measured as part of a field sampling program. The AREMP uses both a decision support model framework, as well as statistical methodologies, developed, refined, and implemented in cooperation with CESU Portland State University to estimate several parameters used to assess watershed condition. Approaches and methodologies are reevaluated between 5 year reporting intervals to improve our ability to track condition and trend of watersheds at multiple spatial scales. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
