Estimation of actual evapotranspiration in pistachio orchards using SEBAL algorithm in three irrigation system
Subject Areas : Applications in water resources management
1 - Assistant Professor, Iranian Space research center, Tehran, Iran
Keywords: Soil Moisture Sensor, precision agriculture, evapotranspiration, Pistachio, remote sensing,
Abstract :
Background and ObjectiveOver the past 100 years, the country has lost about 90 percent of its per capita renewable water. About 90% of the country's renewable water resources are allocated to the agricultural sector. With the increase in the area of pistachio orchards and the increase in demand for water on the one hand and the limited water resources in the region, on the other hand, the imbalance between supply and demand for water is sharply increasing. In this regard, the most important step to prevent water loss is the uniform distribution of water on the field, optimal at each stage of growth. About 99% of the water absorbed by the plant is used for evapotranspiration. Therefore, studying this phenomenon can play an important role in determining the water needs of plants. It is difficult to measure the actual evapotranspiration outside the laboratory. Many experimental methods have been developed to estimate actual and potential evapotranspiration using meteorological and climatic data. But most of these methods are only able to estimate potential evapotranspiration and do not estimate the actual amount of it. In contrast, remote sensing methods have been developed that are a good solution for estimating the actual evapotranspiration. Satellite imagery with global coverage and repetitive Acquisition has made it possible to monitor evapotranspiration at the field level and during plant growth. Various studies have been conducted to estimate the actual evapotranspiration of agricultural areas using satellite images, which indicate the acceptable accuracy of these methods. However, most of this research is related to agricultural fields and no significant research has been done to estimate evapotranspiration at the orchards. Vegetation at the farms is uniform and homogeneous compared to orchards, so the estimation of vegetation index, which is one of the inputs of the SEBAL model in orchards is more difficult than agricultural fields, which can affect the final accuracy. Therefore, the main purpose of this study is to estimate the amount of evapotranspiration in the pistachio orchard using the SEBAL algorithm and evaluate the accuracy of estimation. Also, this research has beenMaterials and Methods The present research has been carried out in pistachio orchards in Zarandieh city of Markazi province. The gardens had three different irrigation systems including flood irrigation systems, surface, and subsurface drip irrigation systems. Actual evapotranspiration is estimated using water balance and SEBAL algorithm. Meteorological data from Imam Airport Synoptic Station and Landsat8 satellite imagery has been used to estimate evapotranspiration using the SEBAL algorithm. Actual evapotranspiration is estimated at satellite overpass times during the growing season. To select hot and cold pixels in the SEBAL algorithm, the semi-automatic method proposed by Oldmo is used, which minimizes user participation in the selection of hot and cold pixels. To evaluate the accuracy of evapotranspiration estimation, the information of soil moisture sensors in the orchard has been used. 28 sensors measure soil moisture in different parts of the orchard. Using the soil moisture values, the actual evapotranspiration was estimated using the water balance method and used as a reference value.Results and Discussion A comparison of the results of the SEBAL algorithm and water balance method showed that the SEBAl algorithm was able to estimate the actual evapotranspiration in different parts of the orchard with an RMS error of 0.57. In addition, the correlation between the values estimated by the two methods was equal to 0.82, which indicates the appropriate capability of the SEBAL algorithm in estimating evapotranspiration values. The correlation between the actual evapotranspiration estimated from the SEBAL model and the reference evapotranspiration is 0.76. In addition, in the research, changes in the evapotranspiration in different parts of the garden and also gardens with different irrigation systems including flood, surface, and subsurface drips have been investigated. The results show that the orchard with subsurface irrigation had the lowest average of evapotranspiration on different dates. Considering that evapotranspiration is equal to the sum of evaporation from the soil surface and transpiration from the plant, this decrease can be attributed to the decrease in evaporation from the soil surface. In addition, evapotranspiration heterogeneity can be observed in all parts of orchards with the same irrigation system on all dates. For example, in the orchard with a flood irrigation system, parts of the garden show low evapotranspiration, which can be due to the lack of smoothing of the surface and lack of proper moisture in these areas. Obviously, the same amount of moisture accumulates in other parts of the garden and is inaccessible through deep percolation. This uneven distribution is also observed in the garden with a surface drip irrigation system. For example, the middle part of the garden with surface drip irrigation always shows a higher amount of evapotranspiration, which can indicate the loss of water in this part, due to the miss-operation of the dripper. To evaluate the difference in evapotranspiration in different irrigation systems, the average, minimum, maximum, and standard deviation values of evapotranspiration in orchards related to three different irrigation systems have been calculated. The results showed that in all dates, the ranges and standard deviation of evapotranspiration in the flood irrigation system were higher than in other systems, which indicates the lack of uniform irrigation in the orchard. Also, on all dates, the average amount of evapotranspiration in the orchard with a surface drip irrigation system has been more than flood irrigation system. Vegetation in orchards with drip irrigation systems (surface and subsurface) was denser compared to the flood irrigation systems.Conclusion In this study, the actual evapotranspiration of pistachio orchards has been estimated using satellite imagery and the SEBAL algorithm. The results of the study indicate the appropriate accuracy of the SEBAL algorithm in estimating the actual evapotranspiration of the orchards. Compared with the water balance method, the correlation coefficient was 0.82 and the root means the square error was 0.57. In addition, comparing the moisture situation in different parts of the orchard and in orchards with different irrigation systems has shown that by estimating the actual evapotranspiration using satellite imagery, appropriate information can be obtained on how to distribute moisture in the garden. This information provides valuable information on the optimal management of water resources and increases irrigation efficiency. Other results of this research include the significant difference between surface and subsurface drip irrigation methods. The results show that using subsurface irrigation methods can effectively reduce irrigation water loss due to evaporation from the soil surface. The results show that in areas where there is no access to information from soil moisture sensors or direct measurements of evapotranspiration, the use of the SEBAL algorithm and remote sensing methods can provide appropriate information for optimal water management.
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Akbari M, Seif Z, Zare Abyane H. 2011. Estimation of evapotranspiration by remote sensing technique under different climate condition. Journal of Water and Soil, 25(4): 835-844. https://jsw.um.ac.ir/article/view/42562/article_35105.html. (In Persian).
Alizadeh A, Kamali G. 2007. Water Use of Plant in Iran. Astan Qods Publication, Mashhad, First Edition, 340 p.
Allen GR, Luis SP, Terry AH, Marvin EJ. 2011. Evapotranspiration information reporting: I. Factors governing measurement accuracy. Agricultural Water Management, 98(6): 899-920. doi:https://doi.org/10.1016/j.agwat.2010.12.015.
Babran S, Honarbakhsh N. 2008. Water Crisis in in Iran and the World. Rahbord, 16(48): 193-212. (In Persian).
Bagheri M, Moazzezi F. 2014. Investigation of externalities of groundwater overexploitation on pistachio market of Iran. Journal of Agricultural Economics Research, 5(4): 145-166. (In Persian).
Bastiaanssen W. 2000. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin,Turkey. Journal of Hydrology, 229(1-2): 87-100. doi:https://doi.org/10.1016/S0022-1694(99)00202-4.
Bastiaanssen W, Noordman E, Pelgrum H, Davids G, Thoreson B, Allen R. 2005. SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrigation and Drainage Engineering, 131(1): 85-93. doi:https://doi.org/10.1061/(ASCE)0733-9437(2005)131:1(85).
Chavez J, Gowda P, Evett S, Colaizzi P, Howell T, Marek T. 2007. An application of METRIC for ET mapping in the Texas high plains. Trans ASABE, 1(1): 1-15.
Du J, Song K, Wang Z, Zhang B, Liu D. 2013. Evapotranspiration estimation based on MODIS products and surface energy balance algorithms for land (SEBAL) model in Sanjiang Plain, Northeast China. Chinese Geographical Science, 23(1): 73-91. doi:https://doi.org/10.1007/s11769-013-0587-8.
Ehsani M, Khaledi H. 2003. Water productivity in agriculture. Iranian National Committee on Irrigation And Drainage, Ministry of Energy. (In Persian).
Folhes MT, Rennó CD, Soares JV. 2009. Remote sensing for irrigation water management in the semi-arid Northeast of Brazil. Agricultural Water Management, 96(10): 1398-1408. doi:https://doi.org/10.1016/j.agwat.2009.04.021.
Jafari H, Afrasiabi P, Delbari M, Taheri M. 2017. Determination of evapotranspiration and crop coefficient of olive in different growth stages using remote sensing techniques and moisture balance in Tarom Zanjan. Journal of Irrigation and Water Engineering, 7(3): 120-134. http://www.waterjournal.ir/article_74067.html?lang=en. (In Persian).
Karimi A, Farhadi Bansouleh B, Hesadi H. 2012. Estimation of Regional Evapotranspiration Using LANDSAT TM Images and SEBAL Algorithm. Iranian Journal of Irrigation & Drainage, 6(4): 353-364. (In Persian).
Mahmoodi A, Jalali S. 2016. Iranian pistachio export competitiveness in world markets. Journal of Economic Research (Tahghighat- E- Eghtesadi), 51(4): 951-976. doi:https://doi.org/10.22059/JTE.2016.59464. (In Persian).
Miryaghoubzadeh M, Solaimani K, Habib Nejad Roshan M, Shahedi K, Karim, Akhvan S. 2014. Estimation and assessment of actual evapotranspiration using remote sensing data (Case study: Tamar basin, Golestan province, Iran). Irrigation and Water Engineering, 4(3): 89-102. http://www.waterjournal.ir/index.php/component/content/category/article_70896.html?lang=en. (In Persian).
Olmedo GF, Ortega Farias S, Fonseca Luengo D, Fuentes Peñailillo F. 2016. Water: tools and functions to estimate actual evapotranspiración using Land Surface Energy Balance Models in R. The R Journal, 8(2): 352-369. https://journal.r-project.org/archive/2016/RJ-2016-2051/RJ-2016-2051.pdf.
Omidvar J, Noori S, Davari K, Farid Hosseini A. 2013. Estimation of actual evapotranspiration based on satellite images using two algorithms Sebal and Metric. Irrigation and Water Engineering, 3(4): 11-22. http://www.waterjournal.ir/index.php/journal/article_73522.html?lang=en. (In Persian).
Pakrava M, Mehrabi Boshrabadi H, Gilanpour O. 2010. Studying Iranian pistachio export position: Comparative advantage and trading map approach. Journal of Agricultural economics and Development, 19(76): 1-26. (In Persian).
Rawat KS, Bala A, Singh SK, Pal RK. 2017. Quantification of wheat crop evapotranspiration and mapping: A case study from Bhiwani District of Haryana, India. Agricultural Water Management, 187: 200-209. doi:https://doi.org/10.1016/j.agwat.2017.03.015.
Sanaeinejad S, Noori S, Hasheminia S. 2011. Estimation of evapotranspiration using satellite image data in Mashhad area. Journal of Water and Soil (Agricultural Sciences and Technology), 25(3): 540- 547. https://www.sid.ir/en/journal/ViewPaper.aspx?ID=210065. (In Persian).
Santos CACd, Bezerra BG, Silva BBd, Rao TVR. 2010. Assessment of daily actual evapotranspiration with SEBAL and S-SEBI algorithms in cotton crop. Revista Brasileira de Meteorologia, 25(3): 383-392. doi:https://doi.org/10.1590/S0102-77862010000300010.
Tasumi M, Trezza R, Allen RG, Wright JL. 2005. Operational aspects of satellite-based energy balance models for irrigated crops in the semi-arid US. Irrigation and Drainage Systems, 19(3-4): 355-376. doi:https://doi.org/10.1007/s10795-005-8138-9.
Tsouni A, Kontoes C, Koutsoyiannis D, Elias P, Mamassis N. 2008. Estimation of actual evapotranspiration by remote sensing: Application in Thessaly Plain, Greece. Sensors, 8(6): 3586-3600. doi:https://doi.org/10.3390/s8063586.
Wagle P, Bhattarai N, Gowda PH, Kakani VG. 2017. Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum. ISPRS Journal of Photogrammetry and Remote Sensing, 128: 192-203. doi:https://doi.org/10.1016/j.isprsjprs.2017.03.022.
Wagle P, Gowda PH, Northup BK. 2019. Dynamics of evapotranspiration over a non-irrigated alfalfa field in the Southern Great Plains of the United States. Agricultural Water Management, 223: 105727. doi:https://doi.org/10.1016/j.agwat.2019.105727.
Zand-Parsa S, Shooshtari MM, Majnooni-Heris A. 2016. Measurements of standard Maize evapotranspiration using water balance method and variable root depth in an arid and semi-arid region. Water and Soil Science, 25(1-4): 169-180. (In Persian).
Zhang K, Kimball JS, Running SW. 2016. A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews: Water, 3(6): 834-853. doi:https://doi.org/10.1002/wat2.1168.
Zhang Y, Kong D, Gan R, Chiew FH, McVicar TR, Zhang Q, Yang Y. 2019. Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017. Remote Sensing of Environment, 222: 165-182. doi:https://doi.org/10.1016/j.rse.2018.12.031.
_||_Abdelahi Ezatabadi M, AA J. 2007. Economic investigation of the possibility of using new methods for water supply and demand in agriculture: A case study of pistachio producers in Rafsanjan. Pajouhesh-Va-Sazandegi, 20(2): 113-126. https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=105307. (In Persian).
Akbari M, Seif Z, Zare Abyane H. 2011. Estimation of evapotranspiration by remote sensing technique under different climate condition. Journal of Water and Soil, 25(4): 835-844. https://jsw.um.ac.ir/article/view/42562/article_35105.html. (In Persian).
Alizadeh A, Kamali G. 2007. Water Use of Plant in Iran. Astan Qods Publication, Mashhad, First Edition, 340 p.
Allen GR, Luis SP, Terry AH, Marvin EJ. 2011. Evapotranspiration information reporting: I. Factors governing measurement accuracy. Agricultural Water Management, 98(6): 899-920. doi:https://doi.org/10.1016/j.agwat.2010.12.015.
Babran S, Honarbakhsh N. 2008. Water Crisis in in Iran and the World. Rahbord, 16(48): 193-212. (In Persian).
Bagheri M, Moazzezi F. 2014. Investigation of externalities of groundwater overexploitation on pistachio market of Iran. Journal of Agricultural Economics Research, 5(4): 145-166. (In Persian).
Bastiaanssen W. 2000. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin,Turkey. Journal of Hydrology, 229(1-2): 87-100. doi:https://doi.org/10.1016/S0022-1694(99)00202-4.
Bastiaanssen W, Noordman E, Pelgrum H, Davids G, Thoreson B, Allen R. 2005. SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrigation and Drainage Engineering, 131(1): 85-93. doi:https://doi.org/10.1061/(ASCE)0733-9437(2005)131:1(85).
Chavez J, Gowda P, Evett S, Colaizzi P, Howell T, Marek T. 2007. An application of METRIC for ET mapping in the Texas high plains. Trans ASABE, 1(1): 1-15.
Du J, Song K, Wang Z, Zhang B, Liu D. 2013. Evapotranspiration estimation based on MODIS products and surface energy balance algorithms for land (SEBAL) model in Sanjiang Plain, Northeast China. Chinese Geographical Science, 23(1): 73-91. doi:https://doi.org/10.1007/s11769-013-0587-8.
Ehsani M, Khaledi H. 2003. Water productivity in agriculture. Iranian National Committee on Irrigation And Drainage, Ministry of Energy. (In Persian).
Folhes MT, Rennó CD, Soares JV. 2009. Remote sensing for irrigation water management in the semi-arid Northeast of Brazil. Agricultural Water Management, 96(10): 1398-1408. doi:https://doi.org/10.1016/j.agwat.2009.04.021.
Jafari H, Afrasiabi P, Delbari M, Taheri M. 2017. Determination of evapotranspiration and crop coefficient of olive in different growth stages using remote sensing techniques and moisture balance in Tarom Zanjan. Journal of Irrigation and Water Engineering, 7(3): 120-134. http://www.waterjournal.ir/article_74067.html?lang=en. (In Persian).
Karimi A, Farhadi Bansouleh B, Hesadi H. 2012. Estimation of Regional Evapotranspiration Using LANDSAT TM Images and SEBAL Algorithm. Iranian Journal of Irrigation & Drainage, 6(4): 353-364. (In Persian).
Mahmoodi A, Jalali S. 2016. Iranian pistachio export competitiveness in world markets. Journal of Economic Research (Tahghighat- E- Eghtesadi), 51(4): 951-976. doi:https://doi.org/10.22059/JTE.2016.59464. (In Persian).
Miryaghoubzadeh M, Solaimani K, Habib Nejad Roshan M, Shahedi K, Karim, Akhvan S. 2014. Estimation and assessment of actual evapotranspiration using remote sensing data (Case study: Tamar basin, Golestan province, Iran). Irrigation and Water Engineering, 4(3): 89-102. http://www.waterjournal.ir/index.php/component/content/category/article_70896.html?lang=en. (In Persian).
Olmedo GF, Ortega Farias S, Fonseca Luengo D, Fuentes Peñailillo F. 2016. Water: tools and functions to estimate actual evapotranspiración using Land Surface Energy Balance Models in R. The R Journal, 8(2): 352-369. https://journal.r-project.org/archive/2016/RJ-2016-2051/RJ-2016-2051.pdf.
Omidvar J, Noori S, Davari K, Farid Hosseini A. 2013. Estimation of actual evapotranspiration based on satellite images using two algorithms Sebal and Metric. Irrigation and Water Engineering, 3(4): 11-22. http://www.waterjournal.ir/index.php/journal/article_73522.html?lang=en. (In Persian).
Pakrava M, Mehrabi Boshrabadi H, Gilanpour O. 2010. Studying Iranian pistachio export position: Comparative advantage and trading map approach. Journal of Agricultural economics and Development, 19(76): 1-26. (In Persian).
Rawat KS, Bala A, Singh SK, Pal RK. 2017. Quantification of wheat crop evapotranspiration and mapping: A case study from Bhiwani District of Haryana, India. Agricultural Water Management, 187: 200-209. doi:https://doi.org/10.1016/j.agwat.2017.03.015.
Sanaeinejad S, Noori S, Hasheminia S. 2011. Estimation of evapotranspiration using satellite image data in Mashhad area. Journal of Water and Soil (Agricultural Sciences and Technology), 25(3): 540- 547. https://www.sid.ir/en/journal/ViewPaper.aspx?ID=210065. (In Persian).
Santos CACd, Bezerra BG, Silva BBd, Rao TVR. 2010. Assessment of daily actual evapotranspiration with SEBAL and S-SEBI algorithms in cotton crop. Revista Brasileira de Meteorologia, 25(3): 383-392. doi:https://doi.org/10.1590/S0102-77862010000300010.
Tasumi M, Trezza R, Allen RG, Wright JL. 2005. Operational aspects of satellite-based energy balance models for irrigated crops in the semi-arid US. Irrigation and Drainage Systems, 19(3-4): 355-376. doi:https://doi.org/10.1007/s10795-005-8138-9.
Tsouni A, Kontoes C, Koutsoyiannis D, Elias P, Mamassis N. 2008. Estimation of actual evapotranspiration by remote sensing: Application in Thessaly Plain, Greece. Sensors, 8(6): 3586-3600. doi:https://doi.org/10.3390/s8063586.
Wagle P, Bhattarai N, Gowda PH, Kakani VG. 2017. Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum. ISPRS Journal of Photogrammetry and Remote Sensing, 128: 192-203. doi:https://doi.org/10.1016/j.isprsjprs.2017.03.022.
Wagle P, Gowda PH, Northup BK. 2019. Dynamics of evapotranspiration over a non-irrigated alfalfa field in the Southern Great Plains of the United States. Agricultural Water Management, 223: 105727. doi:https://doi.org/10.1016/j.agwat.2019.105727.
Zand-Parsa S, Shooshtari MM, Majnooni-Heris A. 2016. Measurements of standard Maize evapotranspiration using water balance method and variable root depth in an arid and semi-arid region. Water and Soil Science, 25(1-4): 169-180. (In Persian).
Zhang K, Kimball JS, Running SW. 2016. A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews: Water, 3(6): 834-853. doi:https://doi.org/10.1002/wat2.1168.
Zhang Y, Kong D, Gan R, Chiew FH, McVicar TR, Zhang Q, Yang Y. 2019. Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017. Remote Sensing of Environment, 222: 165-182. doi:https://doi.org/10.1016/j.rse.2018.12.031.