Estimation of Actual Evapotranspiration in Mahidasht using SEBS Algorithm and LANDSAT Images

آب و خاک

Article 2, Volume 30, Issue 3 - Serial Number 47, July 2016, Pages 706-716   

Document Type: Research Article

DOI: 10.22067/jsw.v30i3.41372

Authors

Bahman Farhadi Bansouleh^{* 1}; Alireza Karimi²; Hoamyoun Hesadi³

¹Razi

²Razi University, Kermanshah

³Kermanshah Agriculture and Natural Resources Research Center

Abstract

Introduction: Evapotranspiration (ET) is one of the key parameters in water resource planning and design of irrigation systems. ET could have spatial variations in a plain due to the diversity of plant species and spatial variability of meteorological parameters. Common methods of ET measurement are mostly point based and generalization of their results to the regional level are costly, time consuming and difficult. During the last three decades, several algorithms have been developed to estimate regional ET based on remote sensing techniques. Verstraeten et al. (2008) classified remote sensing-based methods for ET estimation into four categories i) methods based on the surface energy balance, ii) Penman-Monteith equation, iii) water balance and iv) the relationship between surface temperature and vegetation indices. SEBS (Surface Energy Balance System), SEBAL, METRIC and SEBI are examples of the algorithms which is developed based on the surface energy balance approach. SEBS is developed by Su (2002) and has been evaluated by several researchers. However this algorithm has been examined in the several studies in the world,it has been used rarely in Iran. The aim of the current study was to assess the results of SEBS algorithm in Mahidasht, Kermanshah, Iran. The study area is located at the latitude of 34º 5' – 34º 32' N and longitude of 46º 31' - 47º 06' E.
Materials and Methods: A brief description of the SEBS algorithm (in Persian) as well as its procedure to calculate ET based on Landsat images were presented in this paper. All equations of the algorithm were coded in the ERDAS Imagine package software using model maker tools. Actual ET over the study area was estimated using SEBS algorithm during the growth period of grain maize in the year 2010. For this purpose, available LANDSAT TM satellite images during the growing season of maize in 2010 (25 June, 11 July, 27 July and 12 August) were downloaded free of charge from the http://glovis.usgs.gov website (last visited: 26 November 2015).
A Lysimetric study was carried out to obtain reliable amounts of ET to assess the accuracy of calculating actual ET by SEBS algorithm. Because of the absence of the weighing Lysimeters in the study area, Drainable Lysimeter was used. Since the maize was the major crop in the study area, 10 ha maize was planted on 15 May 2010 at the research farm of the Mahidasht agricultural research station. At the same time, maize was cultivated in the Drainable Lysimeter (1m*1.5m*1.5m) which was located almost in the middle of the research farm. Actual ET of maize was calculated with the Lysimeter for each irrigation interval (10 days) based on water balance equation.
The Results of the SEBS algorithm were evaluated on two levels (farm and regional). At the farm level, average of calculating ET at the pixels of research farm was compared with the average of measured ET at the Lysimeter. The absolute and relative differences between the calculated and measured values of ET was used to describe the accuracy of the algorithm. Due to the absence of regional ET measurement, maximum ET estimated by the SEBS algorithm in the plain was compared with the calculated potential crop reference evapotranspiration (ETO). ETO was calculated using the Penman - Monteith formula based on daily weather data obtained from Mahidasht weather station.
Results and Discussion: Results indicated that an average of ET in the study area increased from June to August which coincides with increasing air temperature and vegetation density in the irrigated fields of the study area. The highest and lowest values of actual ET over the study area were determined in the irrigated farms and mountainous area, respectively. The results of Lysimetric study indicated that daily actual ET of maize on 25 June, 11 July, 27 July and 12 August was 4.13, 7.74, 7.45 and 8.05 mm.day-1, respectively. The value of ET estimated by SEBS algorithm was less than actual measured ET by Lysimeter for the all mentioned dates. The maximum absolute difference between estimated ET by SEBS and measured ET with the Lysimeter was occurred on 27 July with the amount 0.34 mm.day-1. Considering the maximum relative difference of 4.56 % between calculated and measured ET, it could be concluded that estimated ET by SEBS algorithm can be acceptable.
Due to the absence of ground-based measurements of evapotranspiration at the regional level, the maximum amount of ET estimated by SEBS algorithm was compared with ETO. The highest and lowest ratio of maximum ET over ETO were calculated as 1.02 and 1.22 which are acceptable values for the crop coefficient (Kc) in the studied period. The maximum difference between estimated ET by SEBS algorithm with ETO was 1.53 mm.day-1 which is equal to 21.86% of ETO in the same date (12 August).
Conclusions: The results of the current study showed that the SEBS algorithm can estimate the actual ET of maize with the acceptable accuracy in the Mahidasht. In the absence of measured ET data at the regional level, it was difficult to have a reasonable judgment on the accuracy of the estimated values of ET by SEBS algorithm at this scale. It is recommended to do the same study on other remote sensing-based approaches of ET estimation.

Keywords

Kermanshah; Maize; Remote sensing; Satellite image; water balance

References

1- Aghdasi F. 2010. Crop water requirement assessment and annual planning of water allocation. ITC, Enschede, The Netherlands, MSc thesis.

2- Allen R.G., Pereira L.S., Raes D., and Smith M. 1998. Crop evapotranspiration - Guidelines for computing crop water requirements. FAO Irrigation and Drainage paper No. 56, FAO, Rome, Italy.

3- Allen R.G., Tasumi M., Morse A., Trezza R., Wright J.L., Bastiaanssen W., Kramber W., Lorite I., and Robison C.W. 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Applications. Journal of Irrigation and Drainage Engineering. 133(4): 395-406.

4- Bastiaanssen W., Menenti M., Feddes R., and Holtslag A. 1998. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. Journal of hydrology. 212: 198-212.

5- Brutsaert W. 1982. Evaporation into the atmosphere: Theory, history, and applications. Vol. 1. Dordrecht, The Netherlands: D. Reidel publishing company.

6- Brutsaert W. 2005. Hydrology: an introduction. Cambridge University Press.

7- Gao Y., Long D., and Li Z.L. 2008. Estimation of daily actual evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in North China. International Journal of Remote Sensing. 29(11): 3295-3315.

8- Gebreyesus M.G. 2009. Validation of RS approaches to model surface characteristics in hydrology: a case study in Guarena Aquifer, Salamanca, Spain. International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands, MSc thesis.

9- Hailegiorgis W.S. 2006. Remote sensing analysis of summer time evapotranspiration using SEBS algorithm. International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands, MSc thesis, 130 pp.

10- Lin W., van de Velde R., and Su Z. 2006. Satellite based regional scale evapotranspiration in the Hebei Plain, Northeastern China. Proceedings of Dragon. 1: 2004-2007.

11- Morse A., Tasumi M., Allen R.G., and Kramber W.J. 2000. Application of the SEBAL methodology for estimating consumptive use of water and streamflow depletion in the bear river basin of Idaho through Remote Sensing, in Idaho Department of Water Resources–University of Idaho.

12- Santos C.A.C.d., Bezerra B.G., Silva B.B.d., and Rao T.V.R. 2010. Assessment of daily actual evapotranspiration with SEBAL and S-SEBI algorithms in cotton crop. Revista Brasileira de Meteorologia. 25(3): 383-392.

13- Shan X. 2007. Regional evaptranspiration over arid inland Heihe river basin in Northwest China. International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands, Msc thesis.

14- Su H., McCabe M., Wood E., Su Z., and Prueger J. 2005. Modeling evapotranspiration during SMACEX: Comparing two approaches for local-and regional-scale prediction. Journal of hydrometeorology. 6(6): 910-922.

15- Su Z. 2002. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes SEBS-The Surface Energy Balance. Hydrology and Earth System Sciences. 6(1): 85-100.

16- Su Z., Schmugge T., Kustas W.P., and Massman W.J. 2010. An evaluation of two models for estimation of the roughness height for heat transfer between the land surface and the atmosphere. Journal of Applied Meteorology. 40(11): 1933-1951.

17- Temesgen E. 2009. Estimation of evapotranspiration from satellite remote sensing and meteorological data over the Fogera Floodplain–Ethiopia. International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands, MSc. Thesis.

18- Verstraeten W.W., Veroustraete F., and Feyen J. 2008. Assessment of evapotranspiration and soil moisture content across different scales of observation. Sensors. 8(1): 70-117.

19- Yang W., Shabanov N., Huang D., Wang W., Dickinson R., Nemani R., Knyazikhin Y., and Myneni R. 2006. Analysis of leaf area index products from combination of MODIS Terra and Aqua data. Remote sensing of environment. 104(3): 297-312.