ESTIMATION OF EVENT FLOOD PEAK DISCHARGE AND RUNOFF VOLUME USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (A CASE STUDY: KASILIAN WATERSHED)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

JANIZADEH SAEED; VAFAKHAH MEHDI

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF WATERSHED MANAGEMENT RESEARCH Year:2017 | Volume:8 | Issue:15 Page(s): 250-258

Download Full-Text

Persian Verion

View:

722

Download:

Cites:

Information Journal Paper

Title

ESTIMATION OF EVENT FLOOD PEAK DISCHARGE AND RUNOFF VOLUME USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (A CASE STUDY: KASILIAN WATERSHED)

Author(s)

JANIZADEH SAEED | VAFAKHAH MEHDI | Issue Writer Certificate

Keywords

ANNQ1

ANFISQ1

EXCESS RAINFALLQ1

FACTOR ANALYSISQ2

KASILIAN WATERSHEDQ2

SENSITIVITY ANALYSISQ1

Abstract

Prediction of flood peak discharge and runoff volume is one of the major challenges in the management of watersheds. The present study was carried out to estimate event flood peak discharge and runoff volume using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in KASILIAN WATERSHED, Iran. For this purpose, 15 rainfall characteristics were considered for 60 storms from 1975 to 2009. Statistical indices of mean square error (RMSE), coefficient of efficiency (CE) and the coefficient of determination (R2) were used to assess models performance. The results showed that flood peak discharge variable, ANFIS with RMSE=1.28m3s-1, CE=%82 and R2=0.86 has better performance than ANN with RMSE=1.22m3s-1, CE=%82 and R2=0.95 and for runoff volume variable, ANFIS with RMSE=2369.54 m3, CE=%99 and R2=0.99 has better performance than ANN with RMSE=10282.82m3, CE=%98 and R2=0.98. Also, the results of the SENSITIVITY ANALYSIS indicated that the most sensitive factor is EXCESS RAINFALL for runoff flood peak discharge and runoff volume estimation.

Cites

No record.

References

No record.

Cite

APA: Copy

JANIZADEH, SAEED, & VAFAKHAH, MEHDI. (2017). ESTIMATION OF EVENT FLOOD PEAK DISCHARGE AND RUNOFF VOLUME USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (A CASE STUDY: KASILIAN WATERSHED). JOURNAL OF WATERSHED MANAGEMENT RESEARCH, 8(15), 250-258. SID. https://sid.ir/paper/230369/en

Vancouver: Copy

JANIZADEH SAEED, VAFAKHAH MEHDI. ESTIMATION OF EVENT FLOOD PEAK DISCHARGE AND RUNOFF VOLUME USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (A CASE STUDY: KASILIAN WATERSHED). JOURNAL OF WATERSHED MANAGEMENT RESEARCH[Internet]. 2017;8(15):250-258. Available from: https://sid.ir/paper/230369/en

IEEE: Copy

SAEED JANIZADEH, and MEHDI VAFAKHAH, “ESTIMATION OF EVENT FLOOD PEAK DISCHARGE AND RUNOFF VOLUME USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (A CASE STUDY: KASILIAN WATERSHED),” JOURNAL OF WATERSHED MANAGEMENT RESEARCH, vol. 8, no. 15, pp. 250–258, 2017, [Online]. Available: https://sid.ir/paper/230369/en

Related Journal Papers