Spatiotemporal assessment of actual evapotranspiration using satellite remote sensing technique in the Nile Delta, Egypt

Fawzy, Hossam El-Din; Sakr, Adel; El-Enany, Moustafa; Moghazy, Hossam M.

doi:10.1016/j.aej.2020.11.001

Cited by 16 publications

(9 citation statements)

References 29 publications

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“…Due to these limitations, several remote sensing (RS)-based models and algorithms have been developed to quantify the ET a in rice, complementing the agrometeorological data observed on the ground and providing more detailed spatial information. Most of them are based on the surface energy balance, e.g., the Simplified Surface Energy Balance Index (S-SEBI) [18], Surface Energy Balance Algorithm for Land (SEBAL) [19], and Mapping Evapotranspiration at High Spatial Resolution with Internalized Calibration (METRIC) [20]; other models couple biophysical parameters and energy balance, e.g., the Breathing Earth System Simulator (BESS) [21], while others combine carbon and vapor fluxes through the response of the canopy conductance to the photosynthesis rate (PML-V2) [22], or integrate earth observations (i.e., the MODIS surface reflectance, albedo, and daily ground surface climate datasets) and numerical algorithms to calculate the ET a [23].…”

Section: Introductionmentioning

confidence: 99%

A Remote-Sensing-Assisted Estimation of Water Use in Rice Paddy Fields: A Study on Lis Valley, Portugal

2023

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Rice culture is one of the most important crops in the world, being the most consumed cereal grain (755 million tons in 2020). Since rice is usually produced under flooding conditions and water performs several essential functions for the crop, estimating its water needs is essential. Remote sensing techniques have shown effectiveness in estimating and monitoring the water use in crop fields. An estimation from satellite data is a challenge, but could be very useful, in order to spatialize local estimates and operationalize production models. This study intended to derive an approach to estimate the actual crop evapotranspiration (ETa) in rice paddies from a temporal series of satellite images. The experimental data were obtained in the Lis Valley Irrigation District (central coast of Portugal), during the 2019 to 2021 rice growing seasons. The average seasonal ETa (FAO56) resulted 586 ± 23 mm and the water productivity (WP) was 0.47 ± 0.03 kg m−3. Good correlations were found between the crop coefficients (Kc) proposed by FAO and the NDVI evolution in the control rice fields, with R2 ranging between 0.71 and 0.82 for stages II+III (development + middle) and between 0.76 and 0.82 for stage IV (late). The results from the derived RS-assisted method were compared to the ETa values obtained from the surface energy balance model METRIC, showing an average estimation error of ±0.8 mm d−1, with a negligible bias. The findings in this work are promising and show the potential of the RS-assisted method for monitoring ETa and water productivity, capturing the local and seasonal variability in rice growing, and then predicting the rice yield, being a useful and free tool available to farmers.

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Section: Introductionmentioning

confidence: 99%

A Remote-Sensing-Assisted Estimation of Water Use in Rice Paddy Fields: A Study on Lis Valley, Portugal

2023

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“…Access to reliable estimates of ET is important to many applications, including in the fields of climatology, meteorology, and agronomy [2]. For example, as a key indicator of crop growth, ET can be used to calculate the amount of water that is consumed by crops, so it holds vast potential for agricultural irrigation [3][4][5][6]. Climate change can cause changes in temperature and wind speed, which will change the processes of the water cycle and energy balance.…”

Section: Introductionmentioning

confidence: 99%

“…The disadvantage of this method is that new errors will be generated on the LST during the resampling or downscaling process, which will result in issues with the LE estimates; (3) an area-weighting method, which uses high-resolution land cover classification data to decompose the mixed pixels of the large-resolution data, and calculates the roughness length and H based on subpixel landscapes, then weighs the H of each sub-pixel according to the area ratio to obtain the H of the entire mixed pixel. Eventually, LE is corrected through correcting H. This method can improve the accuracy of estimating LE to a certain extent but does not fundamentally solve the heterogeneity of the land surface [43,44]; (4) an evaporative fraction and area fraction (EFAF) method. Li et al first applied the EFAF method to correct the deviation of the LE with a spatial resolution of 300 m and proved its feasibility [45].…”

Section: Introductionmentioning

confidence: 99%

Estimating Evapotranspiration over Heterogeneous Surface with Sentinel-2 and Sentinel-3 Data: A Case Study in Heihe River Basin

et al. 2022

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Evapotranspiration (ET) is an important part of surface–atmosphere interactions, connecting the transfer of matter and energy. Land surface heterogeneity is a natural attribute of the Earth’s surface and is an inevitable problem in calculating ET with coarse resolution remote sensing data, which results in significant error in the ET estimation. This study aims to explore the effect and applicability of the evaporative fraction and area fraction (EFAF) method for correcting 1 km coarse resolution ET. In this study we use the input parameter upscaling (IPUS) algorithm to estimate energy fluxes and the EFAF method to correct ET estimates. Five ground stations in the midstream and downstream regions of the Heihe River Basin (HRB) were used to validate the latent heat flux (LE) calculated by the IPUS algorithm and EFAF method. The evaluation results show that the performance of the EFAF method is superior to that of the IPUS algorithm, with the coefficient of determination (R2) increasing, the root mean square error (RMSE) decreasing, and the mean bias error (MBE) decreasing by 17 W/m2 on average. In general, the EFAF method is suitable for correcting the deviation in LE estimated based on Sentinel data caused by land surface heterogeneity and can be applied to obtain accurate estimates of ET.

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“…Its registered accuracies of 85% on a farm-scale while more than 95% accuracy was recorded on a regional scale (Seneviratne et al 2006). Fawzy et al (2021) used Landsat satellite data with the SEBAL algorithm to study daily evapotranspiration in the Nile Delta, Egypt, and reported that the SEBAL method estimated the transpiration evaporation of the region with acceptable accuracy. The purpose of this study was to compute the actual evapotranspiration (ET) from SEBAL using Landsat 8 images in the the lower bhavani basin, Tamil Nadu.…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal estimation of actual evapotranspiration of lower Bhavani basin, Tamil Nadu using Surface Energy Balance Algorithm for Land Model

Karishma

Kannan

Nagarajan

et al. 2022

JANS

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Estimating evapotranspiration's spatiotemporal variance is critical for regional water resource management and allocation, including irrigation scheduling, drought monitoring, and forecasting. The Surface Energy Balance Algorithm for Land (SEBAL) method can be used to estimate spatio-temporal variations in evapotranspiration (ET) using remote sensing-based variables like Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), surface albedo, transmittance, and surface emissivity. The main aim of the study was to evaluate the actual evapotranspiration for the lower Bhavani basin, Tamil Nadu based on remote sensing methods using Landsat 8 data for the years 2018 to 2020. The actual evapotranspiration was estimated using SEBAL model and its spatial variation was compared over different land covers. The estimated values of daily actual evapotranspiration in the lower Bhavani basin ranged from 0 to 4.72 mm day-1. Thus it is evident that SEBAL model can be used to predict ET with limited ground base hydrological data. The spatially estimated ET values will help in managing the crop water requirement at each stage of crop and irrigation scheduling, which will ensure the efficient use of available water resources.

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Spatiotemporal assessment of actual evapotranspiration using satellite remote sensing technique in the Nile Delta, Egypt

Cited by 16 publications

References 29 publications

A Remote-Sensing-Assisted Estimation of Water Use in Rice Paddy Fields: A Study on Lis Valley, Portugal

A Remote-Sensing-Assisted Estimation of Water Use in Rice Paddy Fields: A Study on Lis Valley, Portugal

Estimating Evapotranspiration over Heterogeneous Surface with Sentinel-2 and Sentinel-3 Data: A Case Study in Heihe River Basin

Spatial and temporal estimation of actual evapotranspiration of lower Bhavani basin, Tamil Nadu using Surface Energy Balance Algorithm for Land Model

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