Monitoring of crop water consumption changing based on remotely sensed data and techniques in North Sinai, Egypt


  • M. A. El-Shirbeny National Authority for Remote Sensing and Space Sciences (NARSS), Egypt & Department of Agrifood Production and Environmental Sciences (DISPAA), University of Florence, Italy
  • S. Orlandini Climate and Sustainability Foundation (FCS), Italy



Hargreaves (Har), FAO-Penman-Monteith (FPM), Water Deficit Index (WDI), Actual Evapotranspiration (ETa), NOAA/AVHRR, Landsat8


This paper aims to approximate and verify crop water use based on satellite results. Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) were used as the critical parameters derived from NOAA/AVHRR and landsat8 satellite data. Reference evapotranspiration (ETo) was determined using FAO-Penman-Monteith (FPM) agrometeorological data as a standard process. Based on data from remote sensing, the ETo was calculated based on the Hargreaves (Har) process. ETo-FPM has been used to calibrate ETo-Har under the same conditions for five years (2002-2006). Landsat8 data was obtained on 25 June 2013 and 28 June 2014 and used to estimate the crop coefficient (Kc) based on satellite data (Kc-Sat). The LST was used to predict the maximum, minimum, and mean Tair (oC) levels in June 2013 and 2014. ETo was calculated using the expected maximum, minimum, and mean Tair according to the Har method and was used with Kc-Sat to estimate ETc-Har. ETo-FPM is used to measure ETc-FPM with Kc-Sat. LST and NDVI have been used to measure the Water Deficiency Index (WDI). WDI incorporated ETc to measure the actual evapotranspiration of the crop (ETa). ETa-FPM was used for the evaluation of ETa-Har. The relationship between ETa-FPM and ETa-Har was high, where R2 was 0.99 in 2013 and 2014. ETa determined by Hargreaves based on remotely sensed data was overestimated at about 0.8 (mm/day) compared to the FPM process.


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Aboelghar, M., Arafat, S., Abo Yousef, M., El-Shirbeny, M., Naeem, S., Massoud, A., & Saleh, N. (2011). Using SPOT data and leaf area index for rice yield estimation in Egyptian Nile delta. The Egyptian Journal of Remote Sensing and Space Science, 14(2), 81-89.

Aboelghar, M., Arafat, S., Saleh A., Naeem, S., El-Shirbeny, M., & Belal, A. (2010). Retrieving leaf area index from SPOT4 satellite data. The Egyptian Journal of Remote Sensing and Space Science, 13(2), 121-127.

Afify, N. M., El-Shirbeny, M. A., ElWesemy, A. F., & Nabil, M. (2023). Analyzing time series for agricultural extension and its water consumption in arid region: a case study of the Farafra oasis in Egypt’s Western Desert. Euro-Mediterranean Journal for Environmental Integration, 2023.

Alblewi, B., Gharabaghi, B., Alazba, A., & Mahboubi, A. (2015). Evapotranspiration models assessment under hyper-arid environment. Arabian Journal of Geoscience, 8, 9905-9912.

Ali, A. M., Savin, I., Poddubskiy, A., Abouelghar, M., Saleh, N., Abutaleb, K., El-Shirbeny, M., & Dokukin, P. (2021). Integrated method for rice cultivation monitoring using Sentinel-2 data and Leaf Area Index. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 431-441.

Allen, R. G., Jenesen, M. E., Wright, J. M., & Burman, R. D. (1989). Operational estimates of reference evapotranspiration. Agronomy Journal, 81(4), 650-662.

Allen, R. G., Perrier, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration: Guidelines for computing crop water requirements. Irrigation and drainage paper No. 56, FAO, Rome, Italy. Retrieved from

Bois, B., Pieri, P., Van Leeuwen C., Wald, L., Huard, F., Gaudillere, J. P., & Saur, E. (2008). Using remotely sensed solar radiation data for reference evapotranspiration estimation at a daily time step. Agricultural and Forest Meteorology, 148(4), 619-630.

El-Shirbeny, M. A., & Abdellatif, B. (2017). Reference Evapotranspiration Borders Maps of Egypt Based on Kriging Spatial Statistics Method. International Journal of GEOMATE, 13(37), 1-8.

El-Shirbeny, M. A., & Saleh, S. M. (2021). Actual evapotranspiration evaluation based on multi-sensed data. Journal of Aridland Agriculture, 7, 95-102.

El-Shirbeny, M. A., Abdellatif, B., Ali A. M., & Saleh N. H. (2016). Evaluation of Hargreaves based on remote sensing method to estimate potential crop evapotranspiration. International Journal of GEOMATE, 11(23), 2143-2149.

El-Shirbeny, M. A., Aboelghar, M. A., Arafat, S. M., & El-Gindy, A.-G. M. (2011, October 7). Mutual influence between climate and vegetation cover through satellite data in Egypt. Proceeding of the SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII.

El-Shirbeny, M. A., Aboelghar, M. A., Arafat, S. M., & El-Gindy, A.-G. M. (2014a). Assessment of the mutual impact between climate and vegetation cover using NOAA-AVHRR and Landsat data in Egypt. Arabian Journal of Geoscience, 7(4), 1287-1296.

El-Shirbeny, M. A., Ali, A. M., & Saleh, N. H. (2014b). Crop Water Requirements in Egypt Using Remote Sensing Techniques. Journal of Agricultural Chemistry and Environment, 3(2B), 57-65.

El-Shirbeny, M. A., Ali, A. M., Badra, M. A., & Bauomy, E. M. (2014c). Assessment of Wheat Crop Coefficient Using Remote Sensing Techniques. World Research Journal of Agricultural Sciences, 1(2), 12-16.

El-Shirbeny, M. A., Ali, A. M., Khdery, G. A., Saleh, N. H., Afify, N. M., Badr, M. A., & Bauomy, E. M. (2021a). Monitoring agricultural water in the desert environment of New Valley Governorate for sustainable agricultural development: a case study of Kharga. Euro-Mediterranean Journal for Environmental Integration, 6(2), 1-15.

El-Shirbeny, M. A., Ali, A. M., Savin, I., Poddubskiy, A., & Dokukin, P. (2021b). Agricultural Water Monitoring for Water Management Under Pivot Irrigation System Using Spatial Techniques. Earth Systems and Environment, 5(2), 341-351.

El-Shirbeny, M. A., Alsersy, M. A. M., Saleh, N. H., & Abu-Taleb, K. A. (2015). Changes in irrigation water consumption in the Nile Delta of Egypt assessed by remote sensing. Arabian Journal of Geoscience, 8, 10509-10519.

El-Shirbeny, M. A., Biradar, C., Amer, K., & Paul, S. (2022). Evapotranspiration and Vegetation Cover Classifications Maps Based on Cloud Computing at the Arab Countries Scale. Earth Systems and Environment, 6, 837-849.

El-Shirbeny, M. A., Mohamed, E. S., & Negm, A. (2019). Estimation of Crops Water Consumptions Using Remote Sensing with Case Studies from Egypt. In A. m. Negm (Ed.), Conventional Water Resources and Agriculture in Egypt (Vol. 74, pp. 161-186) Cham, Switzerland: Springer.

El-Shirbeny, M. A., Saleh, N. H., & Ali, A. M. (2014d). Estimation of Potential Crop Evapotranspiration Using Remote Sensing Techniques. Proceedings of the 10th International Conference of AARSE (pp. 460-468).

Erdem, Y., Sehirali, S., Erdem, T., & Kenar, D. (2006). Determination of Crop Water Stress Index for Irrigation Scheduling of Bean (Phaseolus vulgaris L.). Turkish Journal of Agriculture and Forestry, 30(3), 195-202.

Er-Raki, S., Chehbouni, A., Guemouria, N., Duchemin, B., Ezzahar, J., & Hadria, R. (2007). Combining FAO-56 model and groundbased remote sensing to estimate water consumption of wheat crops in semi-arid regions. Agricultural Water Management, 87(1), 41-54.

Gamal, R., El-Shirbeny, M., Abou-Hadid, A., Swelam, A., El-Gindy, A.-G., Arafa, Y., & Nangia, V. (2022). Identification and Quantification of Actual Evapotranspiration Using Integrated Satellite Data for Sustainable Water Management in Dry Areas. Agronomy, 12(9), 2143.

Garcia, M., Fernández, N., Villagarcía, L., Domingo, F., Puigdefábregas, J., & Sandholt, I. (2014). Accuracy of the Temperature–Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions. Remote Sensing of Environment, 149, 100-117.

Hiler, E. A., & Clark, R. N. (1971). Stress day index to characterize effects of water stress on crop yields. Transactions of American Society of Agricultural and Biological Engineers, 14(4), 757-761.

Hu, G., Jia, L., & Menenti, M. (2015). Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011. Remote Sensing of Environment, 156, 510-526.

Jackson, R. D., Idso, S. B., Reginato, R. J., & Pinter, J. R. (1981). Canopy temperature as a crop water stress indicator. Water Resources Research, 17(4), 1133-1138.

Kamble, B., Kilic, A., & Hubbard, K. (2013). Estimating Crop Coefficients Using Remote Sensing-Based Vegetation Index. Remote Sensing, 5(4), 1588-1602.

Luo, Y., Chang, X., Peng, S., Khan, S., Wang, W., Zheng, Q., & Cai, X. (2014). Short-term forecasting of daily reference evapotranspiration using the Hargreaves–Samani model and temperature forecasts. Agricultural Water Management, 136, 42-51.

Magliulo, V., d’Andria, R., & Rana, G., (2003). Use of the modified atmometer to estimate reference evapotranspiration in Mediterranean environments. Agricultural Water Management, 63(1), 1-14.

Merlin, O., Chirouze, J., Olioso, A., Jarlan, L., Chehbouni, G., & Boulet, G. (2014). An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S). Agricultural and Forest Meteorology, 184, 188-203.

Mohamed, E. S., Belal, A. A., Abd-Elmabod, S. K., El-Shirbeny, M. A., Gad A., & Zahran, M. B. (2021). Smart farming for improving agricultural management. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 971-981.

Moran, M. S., Clarke, T. R., Inoue, Y., & Vidal, A. (1994). Estimating crop water deficit using the relation between surface air temperature and spectral vegetation index. Remote Sensing of Environment, 49(3), 246-263.

Norman, J. M., Divakarla, M., & Goel, N. S. (1995). Algorithms for extracting information from remote thermal-IR observations of the Earth’s surface. Remote Sensing of Environment, 51(1), 157-168.

Rana, G., & Katerji, N. (2000). Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: a review. European Journal of Agronomy, 13(2-3), 125-153.

Rwasoka, D. T., Gumindoga, W., & Gwenzi, J. (2011). Estimation of actual evapotranspiration using the Surface Energy Balance System (SEBS) algorithm in the Upper Manyame catchment in Zimbabwe. Physics and Chemistry of the Earth, 36(14-15), 736-746.

Silva, V. de P. R. da, Borges, C. J. R., Farias, C. H. A., Singh, V. P., Albuquerque, W. G., & Silva, B. B. da. (2012). Water requirements and single and dual crop coefficients of sugarcane grown in a tropical region, Brazil. Agricultural Sciences, 3(2), 274-286.

Sobrino, J. A., Caselles, V., & Coll, C. (1993). Theoretical split-window algorithms for determining the actual surface temperature. Il Nuovo Cimento C, 16, 219-236.

Tadesse, T., Senay, G. B., Berhan, G., Regassa, T., & Beyen, S. (2015). Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia. International Journal of Applied Earth Observation and Geoinformation, 40, 39-54.

Tolba, R. A., El-Shirbeny, M. A., Abou-Shleel, S. M., & El-Mohandes, M. A. (2020). Rice acreage delineation in the Nile Delta based on thermal signature. Earth Systems and Environment, 4, 287-296.

Valor, E., & Caselles, V. (1996). Mapping land surface emissivity from NDVI: Application to European, African and South American Areas. Remote Sensing of Environment, 57(3), 167-184.

Yin, Y., Wu, S., Zheng, D., & Yang, O. (2008). Radiation calibration of FAO56-Penman–Monteith model to estimate reference crop evapotranspiration in China. Agricultural Water Management, 95(1), 77-84.

Zhao, S., Yang, Y., Zhang, F., Sui, X., Yao, Y., Zhao, N., Zhao, Q., & Li, C. (2015). Rapid evaluation of reference evapotranspiration in Northern China. Arabian Journal of Geosciences, 8, 647-657.



How to Cite

El-Shirbeny, M. A., & Orlandini, S. (2023). Monitoring of crop water consumption changing based on remotely sensed data and techniques in North Sinai, Egypt. Journal of Aridland Agriculture, 9, 1–8.