Comparison of SEBAL, METRIC, and ALARM algorithms for estimating actual evapotranspiration of wheat crop

Asadi, Mehdi; Kamran, Khalil Valizadeh

doi:10.1007/s00704-022-04026-3

Cited by 14 publications

(8 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our results regarding image classification indicated the high accuracy of the object-oriented algorithm in capturing LULC changes, in accordance with the findings of Whiteside et al [39]. Based on the results, the maximum and minimum LAS were attributed to farmland and water bodies, respectively, in line with the results reported by Asadi et al [33] and Münch et al [40], who revealed the contribution of residential areas to LAS changes across the different LULCs. This difference might occur due to the type of materials used on ceilings, walls, and facades, which may be constructed with high-reflectivity materials [41].…”

Section: Discussionsupporting

confidence: 92%

“…However, a newly emerged view suggests that trees may not always be as helpful to fighting global warming as the general public thinks, because the dark leaves of trees can increase the temperature by absorbing sunlight, which results in the elimination of the forests' cooling effects [43]. Our findings imply the low contribution of forests to LSA (summer: 0.16 and winter: 0.21), which is in agreement with the findings of Asadi et al [33], who assessed the contribution of different LULCs on LSA using SEBAL and metric methods in Ardabil, and concluded that forests followed by water bodies contributed the least to the LSA. Additionally, our results are in line with those of Yan et al [44], who examined LSA variations between 2002 to 2019 during a period of forest area growth in China, and concluded that the albedo was increased by increased forest greening (increased bright canopy) and decreased dark crevices.…”

Section: Discussionsupporting

confidence: 89%

“…The algorithm works based on the energy balance on the Earth's surface and estimates evapotranspiration using satellite images. In this method, LSA is defined as the ratio of reflected radiation to shortwave radiation, which is calculated as follows [33].…”

Section: Lsa and Lst Calculation Using The Sebal Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo?

et al. 2022

View full text Add to dashboard Cite

Land surface temperature (LST) and land surface albedo (LSA) are the two key regional and global climate-controlling parameters; assessing their behavior would likely result in a better understanding of the appropriate adaptation strategies to mitigate the consequences of climate change. This study was conducted to explore the spatiotemporal variability in LST and LSA across different land use/cover (LULC) classes in northwest Iran. To do so, we first applied an object-oriented algorithm to the 10 m resolution Sentinel-2 images of summer 2019 to generate a LULC map of a 3284 km2 region in northwest Iran. Then, we computed the LST and LSA of each LULC class using the SEBAL algorithm, which was applied to the Landsat-8 images from the summer of 2019 and winter of 2020. The results showed that during the summer season, the maximum and minimum LSA values were associated with barren land (0.33) and water bodies (0.11), respectively; during the winter season, the maximum LSA value was observed for farmland and snow cover, and the minimum value was observed in forest areas (0.21). The maximum and minimum LST values in summer were acquired from rangeland (37 °C) and water bodies (24 °C), respectively; the maximum and minimum values of winter values were detected in forests (4.14 °C) and snow cover (−21.36 °C), respectively. Our results revealed that barren land and residential areas, having the maximum LSA in summer, were able to reduce the heating effects to some extent. Forest areas, due to their low LSA and high LST, particularly in winter, had a greater effect on regional warming compared with other LULC classes. Our study suggests that forests might not always mitigate the effects of global warming as much as we expect.

show abstract

Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 89%

See 1 more Smart Citation

How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo?

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In general, the SEBAL model always presented higher values than those modeled with SAFER. These higher values of SEBAL had already been found in a study conducted by Asadi and Kamran [25] that compared the model with other ETa estimation models. Meanwhile, the ETa values obtained with SAFER corroborate the results already presented by Silva et al [26], Mahmoud and Gan [27], and Santos et al [28], also modeled for sugarcane.…”

Section: Discussionsupporting

confidence: 73%

Evaluation of the SEBAL and SAFER models in the estimation of the actual evapotranspiration and crop coefficients of sugarcane in Colombia

Arroyo,

Ome Naervaez

2023

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV

View full text Add to dashboard Cite

Estimating actual evapotranspiration (ETa) and crop coefficients (Kc) is crucial for efficient water management in sugarcane crops in Colombia. Because the implementation of water use policies in agriculture has made water management strategies increasingly demanding, the use of surface energy modeling tools such as the Surface Energy Balance Algorithm for Land (SEBAL) and the Simple Algorithm for Evapotranspiration Retrieving (SAFER) has gained importance. These tools not only estimate the amount of water based on evapotranspiration for each satellite-image pixel, but also determine Kc values along with information gathered by weather stations. This study aimed to estimate the ETa and Kc of sugarcane using the SEBAL and SAFER algorithms. Thirteen central pivots located in the sugarcane-growing region of the Cauca river valley were studied for three consecutive crop cycles between 2018 and 2021. Analyses were performed on Landsat 8 satellite images for both modeling algorithms. Reference evapotranspiration (ETo) data from 37 weather stations of the Colombian sugar sector were also interpolated to determine Kc values. SEBAL-based analysis results for ETa showed maximum values of 4.2 mm.day-1 and minimum values of 1.02 mm.day-1, while SAFER yielded maximum values of 3.8 mm.day-1 and minimum values of 1.02mm.day-1. SEBAL-based analysis results for Kc indicated maximum values of 0.9 and minimum values of 0.2, while those of SAFER indicated maximum values of 0.7 and minimum values of 0.1. Although the ETa and Kc values estimated using these models were lower compared with those of FAO 56 and should be calibrated using a direct method, these models showed potential to be applied in water management programs for Colombia’s Cauca river valley.

show abstract

“…It has the several advantages, including minimal ground measurements required, no atmospheric corrections needed, and automatic internal calibration through the Monin-Obukhov scheme (Senkondo et al 2019). Asadi & Kamran, (2022) used Landsat 7 and 8 images to estimate actual wheat crop ET in the Parsabad Moghan Plain, and found that SEBAL had the lowest error and maximum similarity when compared to lysimeter data. Yang et al (2022) found SEBAL-based ET estimates to be nearly accurate with a few overestimations.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of satellite remote sensing-based crop evapotranspiration models over a semi-arid irrigated agricultural farm

Ghosh,

Chakraborty,

Das

et al. 2023

Preprint

View full text Add to dashboard Cite

The measurement of evapotranspiration (ET) is essential in maintaining the energy and water balance in agricultural ecosystems, and it plays a vital role in the hydrological cycle. Precision irrigation water management requires accurate spatiotemporal coverage of crop ET across the farm. Fortunately, with the availability of multi-temporal high-resolution satellite datasets and remote sensing-based surface energy balance (SEB) models, near-real-time estimation of ET is now possible. A recent study evaluated and compared the performance of several SEB models, including the Surface Energy Balance Algorithm for Land (SEBAL), Surface Energy Balance Index (SEBI), Surface Energy Balance System (SEBS), Simplified Surface Energy Balance (SSEB), Simplified-Surface Energy Balance Index (SSEBI), and Two Source Energy Balance (TSEB) models over semi-arid irrigated farms in India. The study used 24 Landsat images captured during the post-monsoon seasons of 2021-22 and 2022-23. The statistical evaluation revealed that SEBAL had the best overall performance (r = 0.91, MBE= -0.48 mm d− 1, MAE = 0.42 mm d− 1 and RMSE = 0.51 mm d− 1), followed by SSEB, TSEB, SSEBI, SEBI, and SEBS, respectively. While SEBAL, SSEB, S-SEBI, and TSEB models performed similarly, SEBI and SEBS consistently underestimated ET over the season. The spatiotemporal map was also used to evaluate the model's performance, and it could accurately differentiate between ET over less water-intensive pulses and water-intensive wheat fields on the farm. Despite discrepancies among the SEB models, SEBAL can still be an operational tool for mapping ET with high accuracy and sufficient variation across pixels, making it an ideal option for incorporating into irrigation scheduling over semi-arid farms.

show abstract

Comparison of SEBAL, METRIC, and ALARM algorithms for estimating actual evapotranspiration of wheat crop

Cited by 14 publications

References 40 publications

How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo?

How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo?

Evaluation of the SEBAL and SAFER models in the estimation of the actual evapotranspiration and crop coefficients of sugarcane in Colombia

Evaluation of satellite remote sensing-based crop evapotranspiration models over a semi-arid irrigated agricultural farm

Contact Info

Product

Resources

About