RAINFALL-RUNOFF AND RIVER FLOW SIMULATION IN UNGAGED PLACES USING ARTIFICIAL NEURAL NETWORKS AND GIS

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.

MISAGHI F.; DAYYANI SH.; MOHAMMADI K.

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

Journal Paper

Paper Information

Journal: JOURNAL OF AGRICULTURAL KNOWLEDGE Year:2006 | Volume:15 | Issue:4 Page(s): 157-170

Download Full-Text

Persian Verion

View:

789

Download:

Cites:

Information Journal Paper

Title

RAINFALL-RUNOFF AND RIVER FLOW SIMULATION IN UNGAGED PLACES USING ARTIFICIAL NEURAL NETWORKS AND GIS

Author(s)

MISAGHI F. | DAYYANI SH. | MOHAMMADI K. | Issue Writer Certificate

Keywords

ARTIFICIAL NEURAL NETWORKSQ3

GEOGRAPHIC INFORMATION SYSTEMQ2

HYDROLOGYQ2

RAINFALL- RUNOFFQ4

Abstract

River flow estimation has been the interest of hydrologists for long time and several methods have been introduced. Among recent methods, ARTIFICIAL NEURAL NETWORKS (ANN) and GEOGRAPHIC INFORMATION SYSTEM (GIS) have drawn more attention. In this research, GIS was used to calculate the characteristics of watershed, waterways, and flow directions in order to estimate the river flow discharges. Several layers were created in GIS including DEM, flow direction, flow accumulation, flow length and stream grid. In addition, ANN model was used to simulate the nonlinear rainfall runoff phenomena in every subbasin of Gharahsoo river watershed. The outputs of each ANN models in previous section were used as input of ANN model for river flow routing in order to calculate the flow discharge in specific point of the river. In this study, Gharahsoo river was selected to test the proposed methods. The calculated results were compared with observed data and it showed a good agreement.

Cites

No record.

References

No record.

Cite

APA: Copy

MISAGHI, F., DAYYANI, SH., & MOHAMMADI, K.. (2006). RAINFALL-RUNOFF AND RIVER FLOW SIMULATION IN UNGAGED PLACES USING ARTIFICIAL NEURAL NETWORKS AND GIS. JOURNAL OF AGRICULTURAL KNOWLEDGE, 15(4), 157-170. SID. https://sid.ir/paper/28966/en

Vancouver: Copy

MISAGHI F., DAYYANI SH., MOHAMMADI K.. RAINFALL-RUNOFF AND RIVER FLOW SIMULATION IN UNGAGED PLACES USING ARTIFICIAL NEURAL NETWORKS AND GIS. JOURNAL OF AGRICULTURAL KNOWLEDGE[Internet]. 2006;15(4):157-170. Available from: https://sid.ir/paper/28966/en

IEEE: Copy

F. MISAGHI, SH. DAYYANI, and K. MOHAMMADI, “RAINFALL-RUNOFF AND RIVER FLOW SIMULATION IN UNGAGED PLACES USING ARTIFICIAL NEURAL NETWORKS AND GIS,” JOURNAL OF AGRICULTURAL KNOWLEDGE, vol. 15, no. 4, pp. 157–170, 2006, [Online]. Available: https://sid.ir/paper/28966/en

Related Journal Papers