Preparation and estimating of evapotranspiration maps based on Landsat 8 satellite data and SEBAL model in Hyrcanian forests (Case study: Pol-Sefid and Kiasar forests)

Document Type : Research Paper

Authors

1 PhD. Student, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran

2 Prof., Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran

3 Assoc., Prof., Department of Irrigation and Reclamation Engineering, University of Tehran, Karaj, I.R. Iran

Abstract

Hyrcanian forests play an important role in absorbing carbon dioxide and reducing the severity of climate change and global warming. The accurate estimation of actual evapotranspiration can help to plan for conservation and management of these forests and their water resources. Direct measurement methods for evapotranspiration have limitations, one of the most important of them is the pointed measurements. Methods for distance measuring have been developed to address these constraints. The purpose of this study was to prepare and estimate actual instantaneous () and daily () evapotranspiration maps from Landsat 8 satellite imagery and SEBAL model in Hyrcanian forests. For this purpose, Landsat 8 satellite images were prepared in two different dates, i.e. 2014/7/26 and 2016/5/28 in 200 thousand hectares of Hyrcanian forests in the cities of Pol-Sefid and Kiasar, and after processing and calculations, latent heat flux was estimated from images and from that basis,  and  maps were prepared. To evaluate these maps,  and land values were calculated using weather data of Pol-Sefid and Kiasar stations and the FAO Penman Monteith method. The estimated  and  means at the Pol-Sefid station were 0.53 and 5.39 and at Kiasar station, 0.48 and 4.98 respectively. The calculated mean of these two parameters, respectively, were 0.60 and 6.16, at the Pol-sefid station and 0.55 and 5.82, at the Kiasar station. The results showed that the percentage of estimated relative differences for  and is 0.068 and 0.809 respectively, and mean percentage of estimated relative differences for  and is 11.99% and 13.56%, respectively, which in total shows the high ability of the used approach for evapotranspiration maps.

Keywords

References

[1]. Marvie Mohadjer, M.R. (2011). Silviculture, University of Tehran Press.
[2]. Lu, D., Chen, Q., Wang, G., Liu, L., Li, G., and Moran, E. (2016). A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems. International Journal of Digital Earth, 9(1): 63-105.
[3]. Atarod, P., Sadghi, M. M., Fathizade, O., Motahry, M., Rahbar, S., Ahmadi, M., and Bairamzade, V. (2015). Temperature- and radiation based methods against theb standard FAO Penman- Monteith for estimating the reference evapotranspiration (ET0) in Gorgan. Forest and Wood Products, 68, 359-369.
[4]. Zhao, L. L., Ronglin, T., Zhengming, W., Yuyun, B., Chenghu, Z., Bohui, T., Guangjian, Y., and Xiaoyu, Z. )2009(. A review of current methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors, 9:3801-3853.
[5]. Alizadeh, A. (2011). Principles Applied Hydrology. Mashhad: University Ferdowsi.
[6]. Dominique, C., Bernard, S., Albert, O. (2005). Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches. Irrigation and Drainage Systems, 19: 223–249.
[7]. Elhag, M., Psilovikos, A., Manakos, I., and Perakis, K. (2011). Application of the SEBS water balance model in estimating daily evapotranspiration and evaporative fraction from remote sensing data over the Nile Delta. Water Resources Management, 25(11): 2731-2742.
[8]. Aronoff, S. (2005). Remote Sensing for GIS Managers.Translated by Darvishsefat. A. A, Pir Bavaghar M. & Rajab Pourrahmati. M. University of Tehran Press.
[9]. Ayad, A. F., Ahmad, H. A., Adrian, O., Anna, J., and Adriana, M. (2016). Estimation of evapotranspiration using sebal algorithm and landsat-8 data-a case study: Tatra Mountains Region. Journal of Geological Resource and Engineering, 6: 257-270.
[10]. Mao, Y., and Wang, K. (2017). Comparison of evapotranspiration estimates based on the surface water balance, modified Penman‐Monteith model, and reanalysis data sets for continental China. Journal of Geophysical Research: Atmospheres, 122(6), 3228-3244.
[11]. Nosrati, K., saravi, M. M., Ahmadi, H., and Agighi, H. (2016). Estimation of evapotranspiration in Taleghan watershed using SEBAL and MODIS model images. Journal Iranian Natural Resources Pasture and Watershed, 68, 385-398.
[12]. Senay, G.B., Friedrichs, M., Singh, R.K., and Velpuri, N.M. (2016(. Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin. Remote Sensing of Environment. 185: 171-185.
[13]. Edward, P. G., Alfredo, R. H., Pamela L. N., and Katherine K. (2007). Integrating remote sensing and ground methods to estimate evapotranspiration. Critical Reviews in Plant Sciences, 26(3): 139-168.
[14]. Yuei, A. L., and Sanjib, K. K. (2014). Evapotranspiration estimation with remote sensing and various surface energy balance algorithms-A review. Energies, 7: 2821-2849.
[15]. Abbasnezhad Alchin, A., Darvishsefat, A.A., and Bazrafshan J. (2018). Comparison of landsat 8 satellite data and SEBAL model for estimating evapotranspiration of Caspian forests with combined Penman Monteith. Iranian Journal of Forest, 3: 389-402.
[16]. Elnmer, A., Khadr, M., Kanae, S., and Tawfik, A. (2019). Mapping daily and seasonally evapotranspiration using remote sensing techniques over the Nile delta. Agricultural Water Management, 213: 682-692.
[17]. Rahimzadegan, M., & Janani, A. (2019). Estimating evapotranspiration of pistachio crop based on SEBAL algorithm using Landsat 8 satellite imagery. Agricultural Water Management: 217: 383-390.
[18]. Numata, I., Khand, K., Kjaersgaard, J., Cochrane, M., and Silva, S. (2017). Evaluation of Landsat-based METRIC modeling to provide high-spatial resolution evapotranspiration estimates for Amazonian forests. Remote Sensing, 9(1): 46-57.
[19]. Valizadeh Kamran, K., and Longbaf, M. (2018). Application of satellite processing images in calculating the water requirement of arable plants (Case Study: The Part of Northern Land of the Khuzestan Province). Journal of Geography and Planning, 22: 287-299.
[20]. Allen, R. G., Tasumi, M., Trezza, R., Waters, R., and Bastiaanssen, W. (2002). SEBAL (Surface Energy Balance Algorithms for Land). Advance Training and User’s Manual- Idaho Implementation, version, 1: 1- 97.
[21]. Allen, R. G., Pereira, L. S., Smith, M., Raes, D., and Wright, J. L. (2005). FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions. Journal of Irrigation and Drainage Engineering, 131(1): 2-13.
[22]. Singh, K. R., and Senay, B. G. (2015). Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States, Water, 8(1): 9-22.
Forest and Wood Products
Volume 73, Issue 3
November 2020
Pages 259-270

Files

Share

How to cite

Statistics