SIMULATION OF SNOWMELT RUNOFF USING SRM MODEL AND COMPARISON WITH NEURAL NETWORKS ANN AND ANFIS (CASE STUDY: KARDEH DAM BASIN)

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AKBARI M.; RANAEE E.; MIRZAKHAN H.; DARGAHI A.; JARGEH M.R.

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Journal: Journal of Water and Soil Year:2017 | Volume:30 | Issue:6 Page(s): 1794-1807

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Title

SIMULATION OF SNOWMELT RUNOFF USING SRM MODEL AND COMPARISON WITH NEURAL NETWORKS ANN AND ANFIS (CASE STUDY: KARDEH DAM BASIN)

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Keywords

KARDEH DAM BASINQ2

NDSI INDEXQ1

PROCESSING OF SATELLITE IMAGESQ1

SIMULATIONQ1

THE STATISTICAL PARAMETERSQ2

Abstract

Introduction: Snowmelt runoff plays an important role in providing water and agricultural resources, especially in mountainous areas. There are different methods to simulate the process of snowmelt. Inter alia, degree-day model, based on temperature-index is more cited. Snowmelt Runoff Model is a conceptual hydrological model to simulate and predict the daily flow of rivers in the mountainous basins on the basis of comparing the accuracy of AVHRR and TM satellite images to determine snow cover in Karun Basin. Additionally, overestimation of snow-covered area decreased with increasing spatial resolution of satellite data. Studies conducted in the Zayandehrood watershed dam, showed that in the calculation of the snow map cover, changes from MODIS satellite imagery, at the time that the image does not exist, using the digital elevation model and regression analysis can provide to estimate the appropriate data from satellites. In the study of snow cover in eastern Turkey, in the mountainous regions of the Euphrates River, data from five meteorological stations and MODIS images were used with a resolution of 500 m. The results showed that satellite images have a good accuracy in estimating snow cover. In a Watershed in northern Pakistan in the period from 2000 to 2006, SRM model was used to estimate the snow cover using MODIS images. The purpose of this study was to evaluate the snowmelt runoff using remote sensing data and SRM model for flow SIMULATION, based on statistical parameters in the KARDEH DAM BASIN.

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APA: Copy

AKBARI, M., RANAEE, E., MIRZAKHAN, H., DARGAHI, A., & JARGEH, M.R.. (2017). SIMULATION OF SNOWMELT RUNOFF USING SRM MODEL AND COMPARISON WITH NEURAL NETWORKS ANN AND ANFIS (CASE STUDY: KARDEH DAM BASIN). JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), 30(6 ), 1794-1807. SID. https://sid.ir/paper/141813/en

Vancouver: Copy

AKBARI M., RANAEE E., MIRZAKHAN H., DARGAHI A., JARGEH M.R.. SIMULATION OF SNOWMELT RUNOFF USING SRM MODEL AND COMPARISON WITH NEURAL NETWORKS ANN AND ANFIS (CASE STUDY: KARDEH DAM BASIN). JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY)[Internet]. 2017;30(6 ):1794-1807. Available from: https://sid.ir/paper/141813/en

IEEE: Copy

M. AKBARI, E. RANAEE, H. MIRZAKHAN, A. DARGAHI, and M.R. JARGEH, “SIMULATION OF SNOWMELT RUNOFF USING SRM MODEL AND COMPARISON WITH NEURAL NETWORKS ANN AND ANFIS (CASE STUDY: KARDEH DAM BASIN),” JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), vol. 30, no. 6 , pp. 1794–1807, 2017, [Online]. Available: https://sid.ir/paper/141813/en

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