Multi-objective calibration of conceptual hydrological model by AMALGAM algorithm

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.

Farahmand Rad M.; BARANI GH.A.; POURREZA BILONDI M.; GHAZANFARI MOGHADAM M.S.

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

Journal Paper

Paper Information

Journal: Journal of Water and Soil Conservation Year:2018 | Volume:25 | Issue:3 Page(s): 161-175

Download Full-Text

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

Persian Verion

View:

439

Download:

Cites:

Information Journal Paper

Title

Multi-objective calibration of conceptual hydrological model by AMALGAM algorithm

Author(s)

Farahmand Rad M. | BARANI GH.A. | POURREZA BILONDI M. | GHAZANFARI MOGHADAM M.S. | Issue Writer Certificate

Keywords

A multi-algorithm genetically adaptive multi-objectiveQ1

AMALGAMQ1

Hydrological model calibrationQ1

MILCQ1

Abstract

Background and Objectives: One of the ways to predict and estimate the amount of runoff from rainfall is the use of hydrological models. Calibration process is a critical step which should be carried out carefully to optimize the model parameters. Multi-objective optimization algorithms as one of the most important and practical topics in various fields of study could be employed to achieve a reasonable calibration. The purpose of these algorithms is to determine the values of model parameters to find the best possible solution and achieve different goals. Materials and Methods: In this study, Multi-objective optimization algorithm (AMALGAM) used to calibrate conceptual daily hydrologic model (MILC). MILC model employs the Soil Conservation Service-Curve Number method for abstraction (SCS-CN) for estimation of losses, the geomorphological Instantaneous Unit Hydrograph (GIUH) for routing of rainfall excess of catchment. This paper applies a four-objective calibration strategy focusing on peak flows (NSE), low flows (TRMSE), water balance (ROCE) and flashiness (SFDCE) to parameter estimation of MILC model. After calibration process, a trade-off point extracted from Paretofront was selected to include the appropriate values of all four objectives simultaneously. This point is applied to verify the validation period. Results: The obtained values during the validation period (0. 71 ≤ NSE ≤ 0. 78) indicate that the MILC model has good performance to simulate the amount of peak flows but according to ROCE and SFDCE values it has weak performances to simulate the balance water and median flow respectively. Conclusion: The values obtained for the TRMSE target function during the periodic verification period were 1. 22 to 1. 22 (TRMSE = 0 in optimal mode), which indicates that the simulations are suitable for low flows. Multi-objective optimization algorithm for the automatic calibration process of rainfall-runoff model, due to the use of multiple objective functions that target each part of the hydro graph of the basin, challenges the model in simulating all current flows in the basin. This issue shows the importance of using multi-objective algorithms to calibrate hydrologic models. Also, the intelligent selection of multi-objective functions in the calibration process of the model plays a key role in understanding the model more fully by using multi-objective algorithms instead of single-objective for the calibration process.

Cites

No record.

References

No record.

Cite

APA: Copy

Farahmand Rad, M., BARANI, GH.A., POURREZA BILONDI, M., & GHAZANFARI MOGHADAM, M.S.. (2018). Multi-objective calibration of conceptual hydrological model by AMALGAM algorithm. JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), 25(3 ), 161-175. SID. https://sid.ir/paper/156114/en

Vancouver: Copy

Farahmand Rad M., BARANI GH.A., POURREZA BILONDI M., GHAZANFARI MOGHADAM M.S.. Multi-objective calibration of conceptual hydrological model by AMALGAM algorithm. JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES)[Internet]. 2018;25(3 ):161-175. Available from: https://sid.ir/paper/156114/en

IEEE: Copy

M. Farahmand Rad, GH.A. BARANI, M. POURREZA BILONDI, and M.S. GHAZANFARI MOGHADAM, “Multi-objective calibration of conceptual hydrological model by AMALGAM algorithm,” JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), vol. 25, no. 3 , pp. 161–175, 2018, [Online]. Available: https://sid.ir/paper/156114/en

Related Journal Papers