Volume 26, Issue 1 (Spring 2022)
jwss 2022, 26(1): 147-159 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
ebrahimiyan S, Nohtani M, Sadeghi Mazidi H, Soheili E. Optimal Location of Flood Dispersion Using Quantitative Fundamental Models in Fuzzy Logic (Case Study: Gorbayegan Watershed). jwss 2022; 26 (1) :147-159
URL: http://jstnar.iut.ac.ir/article-1-4129-en.html
URL: http://jstnar.iut.ac.ir/article-1-4129-en.html
University of Zabol , m_nohtani@yahoo.com
Abstract: (2530 Views)
The basis of land management is the geomorphological zoning of the land surface, which is determined based on the same geomorphological characteristics of the zoning. Ground zoning detect land features by basic surface features such as height, slope, and slope direction. In this study, quantitative zoning of the land surface with small coefficients to the surface has been used to identify suitable areas for artificial feeding in the mountainous region of Gohar and Dasht-e Gorbayegan in Fars province. Quantitative zoning of the land surface has been performed by Evans-Shri coefficients due to the accurate determination and separation of types, faces, and surface features of the land has an important role in determining the exact land use. In this research basic models included linear, circular, and divergent models. These basic models with the dimensions of the final windows are ranked second in the MATLAB software to the level the ground is fitted to determine the fit of these models, the parameter of total squared difference has been used. In addition, the suitability of the study area for flood distribution in five different classes was determined using fuzzy logic. The most suitable areas for feeding downstream of the cones had five parameters with a maximum score of 20. The inappropriate class related to the lower plains of alluvial fans have a minimum score of five input classes in fuzzy logic, which is equal to zero.
Type of Study: Research |
Subject:
Ggeneral
Received: 2021/02/6 | Accepted: 2021/06/19 | Published: 2022/05/22
Received: 2021/02/6 | Accepted: 2021/06/19 | Published: 2022/05/22
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
