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Journal of Rehabilitation in Civil Engineering
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Volume Volume 6 (2018)
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Sardar Shahraki, A., Farokhzadeh, S., Sharifi, M. (2018). Determining the Effective Distance of Wind Shelter Index by Defining Innovative Index Named Virtual Wind Shelter in a Non-Snowy Watershed. Journal of Rehabilitation in Civil Engineering, 6(2), 98-110. doi: 10.22075/jrce.2017.11994.1205
Ali Sardar Shahraki; Siamak Farokhzadeh; Mohammad Reza Sharifi. "Determining the Effective Distance of Wind Shelter Index by Defining Innovative Index Named Virtual Wind Shelter in a Non-Snowy Watershed". Journal of Rehabilitation in Civil Engineering, 6, 2, 2018, 98-110. doi: 10.22075/jrce.2017.11994.1205
Sardar Shahraki, A., Farokhzadeh, S., Sharifi, M. (2018). 'Determining the Effective Distance of Wind Shelter Index by Defining Innovative Index Named Virtual Wind Shelter in a Non-Snowy Watershed', Journal of Rehabilitation in Civil Engineering, 6(2), pp. 98-110. doi: 10.22075/jrce.2017.11994.1205
Sardar Shahraki, A., Farokhzadeh, S., Sharifi, M. Determining the Effective Distance of Wind Shelter Index by Defining Innovative Index Named Virtual Wind Shelter in a Non-Snowy Watershed. Journal of Rehabilitation in Civil Engineering, 2018; 6(2): 98-110. doi: 10.22075/jrce.2017.11994.1205

Determining the Effective Distance of Wind Shelter Index by Defining Innovative Index Named Virtual Wind Shelter in a Non-Snowy Watershed

Article 7, Volume 6, Issue 2 - Issue Serial Number 12, Summer and Autumn 2018, Page 98-110  XML
Document Type: Regular Paper
DOI: 10.22075/jrce.2017.11994.1205
Authors
Ali Sardar Shahraki 1; Siamak Farokhzadeh2; Mohammad Reza Sharifi3
1University of Sistan and Baluchestan
2PhD Student of Water Resources Management, University of Sistan and Blouchestan, Iran
3Assistant Professor, Civil Engineering Group of Shahid Chamran University, Iran
Receive Date: 24 July 2017,  Revise Date: 17 August 2017,  Accept Date: 05 September 2017 
Abstract
The wind’s effectiveness was compared in different points of a watershed using a quantity called The Wind Shelter Index.The wind’s effectiveness was compared in different points of a watershed using a quantity called The Wind Shelter Index. It is necessary to choose a distance called the effective distance in the process of this index determination. The criterion already used for this purpose was only usable in snowy places. According to the wind shelter index usability in some phenomena that are not in snowy areas, the use of this index will be applied. This study uses observational data of snow surveys from 258 points in Samsami Basin to introduce a new index called “Virtual Wind Shelter” that can be used to choose the effective distance of the area applicable in snowy and non-snowy places. The results showed that the index introduced in this study has the capability of replacement with the correlation of wind shelter index with snow depth criterion.
Keywords
Wind Shelter Index; The Effective Distance; Virtual Wind Shelter; Non-Snowy Watershed
Main Subjects
Rehabilitation and Maintenance in Civil Engineering
References
[1] Daneshkar Arasteh P., Tajrishi M., Mirlotfi M., (2007). “Study of wind blow speed on Sistan's Nime well's reservoir's surface evaporation using the Daltonian method.” Sharif research Journal, No. 37, pp. 49-56.

[2] Sharifi M. (2007). “Study of spatial distribution Snow water equivalent using the combining methods.” Ph.D., dissertation, Shahid Chamran university of Ahvaz.

[3] Sharifi M., Akhond Ali A., Porhemat J., Mohamadi J., (2007). “Evaluation of two methods of linear correlation equation and the ordinary kriging in order to estimate the spatial distribution of snow depth in Samsami watershed basin.” Iran-Watershed Management Science and engineering research Journal. No.1, Vol.1.

[4] Abtew W., Iricanin N. (2008). “Hurricane Effects on South Florida Water Management System: A Case Study of Hurricane Wilma of October 2005.” Journal of Spatial Hydrology, Vol.8, No.1 Spring 2008.

[5] Chapman L. (2000). “Assessing topographic exposure.” Meteorol. Appl. 7, pp. 335–340

[6] Dozier J., Bruno J., Downey P. (1981). “A faster solution to the horizon problem.” Comput. Geosci., Vol. 7, pp. 145-151.

[7] Elder K. (1995). “Snow distribution in alpine watersheds.” Ph.D.dissertation, University of California, Santa Barbara, CA; 309 pp.

[8] Erickson T.A., Williams M.W., Winstral A. (2005). “Persistence of topographic controls on the spatial distribution of snow in rugged mountain, Colorado, United States.” Water Resources Research 41, pp. 1-17.

[9] Fohn P.M.B. (1980). “Snow transport over mountain crests.” Journal of Glaciology, Vol. 29, No. 94, pp. 469-480.

[10] Gray D.M., Male D.H. (1981). “Handbook of snow.”  Pergamon: New York.

[11] Litaor M.I., Williams M., Seastedt T.R, (2008). “Topographic controls on snow distribution, soil moisture, and species diversity of herbaceous alpine vegetation, Niwot Ridge, Colorado” Journal of Geophysical Research, VOL. 113, G02008, doi: 10.1029/2007JG000419,

[12] Marofi S., Tabari H., Zare Abyaneh H. (2011) “Predicting Spatial Distribution of Snow Water Equivalent Using Multivariate Non-linear Regression and Computational Intelligence Methods.” Water Resources Management, Online publication date: 12-Jan-2011.

[13] Molotch N.P., Colee M.T., Bales R.C., Dozier J. (2005). “Estimating the spatial distribution of snow water equivalent in an alpine basin using binary regression tree models: the impact of digital elevation data independent variable selection.” Hydrological Processes, 19, pp. 1459-1479.

[14] Molotch N.P., Roger C., Bales R.C. (2006). “SNOTEL re presentativeness in the RioGrande headwaters on the basis of physiographics and re motely sensed snow cover persistence.” Hydrological Processes 20 , pp. 723–739.

[15] Schmidt R.A. (1982). “Properties of blowing snow.” Rev. Geophys. Space Phys., 20, pp. 39–44.

[16] Wang Z., Bowles D. (2007). “Overtopping breaches for a long dam estimated using a three-dimensional model.” 26th Annual United States Society on Dams Conference, San Antonio, Texas, USA, 1-5th May 2006, 2006b.

[17] Winstral A., Elder K., Davis R.E. (2002). “Spatial Snow Modeling of Wind-Redistributed Snow Using Terrain Based Parameters.” Journal of Hydrometeorology, Vol. 3, pp. 524-538.

[18] Winstral A., Marks D. (2002). “Simulation wind fields and snow redistribution using terrain-based parameters to model snow accumulation and melt over a semi-arid mountain catchment.” Hydrological Processes, Vol. 16, pp. 3585-3603.

[19] Winstral A., Marks D., Gurney R. (2009). “An efficient method for distributing wind speeds over heterogeneous terrain.” Hydrological Processes: 23, 2526–2535.

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