Volume 26, Issue 2 (ُSummer 2022)                   jwss 2022, 26(2): 235-247 | Back to browse issues page


XML Persian Abstract Print


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

tahmasbi T, Abdollahi K, Pajouhesh M. Efficiency of Fuzzy Curve Number on Monthly Runoff Simulation in Beheshtabad Watershed. jwss 2022; 26 (2) :235-247
URL: http://jstnar.iut.ac.ir/article-1-4191-en.html
Shahrekord University , pajouhesh.mehdi@sku.ac.ir
Abstract:   (1854 Views)
The runoff curve number method is widely used to predict runoff and exists in many popular software packs for modeling. The curve number is an empirical parameter important but depends largely on the characteristics of soil hydrologic groups. Therefore, efforts to reduce this effect and extract more accurate soil information are necessary. The present study was conducted to integrate fuzzy logic for extraction runoff curve numbers. A new distribution model called CNS2 has been developed. In the first part of this research, the formulation and programming of the CNS2 model were done using the Python programming language environment, then the model was implemented in the Beheshtabad watershed. This model simulates the amount of runoff production in a watershed in the monthly time step with the fuzzy curve number and takes into account the factor of rainy days, the coefficient of management of the RUSLE-3D equation, and the soils theta coefficient. The results indicated that the model with Nash-Sutcliff 0.6 and the R2 coefficient 0.63 in the calibration set and Nash index 0.53 and R2 coefficient 0.56 in the validation set had appropriate efficiency in runoff simulation. The advantage of the model is that distributive and allows for the identification of areas with higher runoff production.
Full-Text [PDF 851 kb]   (1111 Downloads)    
Type of Study: Research | Subject: Ggeneral
Received: 2021/08/8 | Accepted: 2021/10/12 | Published: 2022/09/1

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.

© 2024 CC BY-NC 4.0 | JWSS - Isfahan University of Technology

Designed & Developed by : Yektaweb