Determining Physical Characteristics of Watersheds in Artvin Province Using SRTM and Topographic Map Data
It is a fact that applying Geographical Information Systems (GIS) and associated software and/or modules on studies regarding use and protection of water resources have been increased in recent years. With such programs, some physical characteristics of watersheds including borders, land use, draina...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Artvin Coruh University
2016-09-01
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| Series: | Doğal Afetler ve Çevre Dergisi |
| Subjects: | |
| Online Access: | http://dacd.artvin.edu.tr/tr/download/article-file/224688 |
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| Summary: | It is a fact that applying Geographical Information Systems (GIS) and associated software and/or modules on studies regarding use and protection of water resources have been increased in recent years. With such programs, some physical characteristics of watersheds including borders, land use, drainage system, slope and elevation can be determined in a quick, detailed and reliable way. In this research, the aim was to use ArcHydro module -integrated with ArcGIS 10.3.1 one of the programs of GIS- to assess some features (borders, drainage, size, steepness, etc.) of river basins located within Artvin province. In order to create Digital Elevation Model (DEM), data from both “Shuttle Radar Topography Mission (SRTM)” and “topographical map” was used; thus, providing comparison of the results gathered from these two base maps. In general, it was stated that both SRTM and topographic map data resulted in very close findings in determining watershed characteristics. For example, while the number of large watersheds (10-100 km2) counted as 315 and 312 by SRTM and topographic maps, respectively, the number of very large watersheds (> 100 km2) was 30 according to both base maps. Moreover, in grouping of slope classification, as 89.29% of the province was found to be within the very-steep slope class based on the topographic maps, a very similar result of 87.13% was revealed using SRTM data. |
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| ISSN: | 2528-9640 2528-9640 |