Volume 10, Issue 1 (spring 2006)                   JCPP 2006, 10(1): 91-105 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

S. Rastgoo, B. Ghahraman, H. Sanei Nejad, K. Davary, S. R. Khodashenas. Estimation of Erosion and Sedimentation of Tang-e-Kenesht Basin with Empirical Models of MPSIAC and EPM Using GIS. JCPP 2006; 10 (1) :91-105
URL: http://jcpp.iut.ac.ir/article-1-525-en.html
Abstract:   (24223 Views)
This research is aimed to predict erosion and sedimentation of Tang-e-Kenesht basin in Kermanshah province using MPSIAC and EPM models in GIS software. This basin has about 14348 hectare area. This region has various vegetation, geology and soil texture and land use types. The basin has divided into 9 sub-basins and its maximum and minimum elevations are 3300 and 1400 m, respectively. Needed data were collected in part through published reports, while the remainings were derived by field survey. Necessary maps in MPSIAC and EPM models were prepared in Autocad-2000 medium and were transported to Arc-Info, after some revisions to them. After constructing topologies for all polygons, we entered all layers weights in Arc-View software. Combinations of all layers were managed thereafter. Nine layers for MPSIAC model and three layers for EPM model were combined to result the final layer of erosion and sedimentation. Basin erosion was calculated as 1002.7 and 1739.2 m3/Km2 by MPSIAC and EPM models, respectively. The result for basin sediment was 521.7 and 307.8 m3/Km2, respectively. Thereafter, medium and high erosion classes were found for the two models under study, respectively. Due to not fully compatible tables for EPM model and its subjective nature, one can conclude that MPSIAC model may have better performance.
Full-Text [PDF 1521 kb]   (1808 Downloads)    
Type of Study: Research | Subject: General

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.