1. H. Salimi, E. Asadi, S. Darbandi, Meteorological and hydrological drought monitoring using several drought indices, Appl. Water Sci., 11 (2021) 1–10.
  2. J. Zhao, C. Li, T. Yang, Y. Tang, Y. Yin, X. Luan, S. Sun, Estimation of high spatiotemporal resolution actual evapotranspiration by combining the SWH model with the METRIC model, J. Hydrol., 586 (2020) 124883, doi: 10.1016/j.jhydrol.2020.124883.
  3. Z. Chen, Z. Zhu, H. Jiang, S. Sun, Estimating daily reference evapotranspiration based on limited meteorological data using deep learning and classical machine learning methods, J. Hydrol., 591 (2020) 125286, doi: 10.1016/j.jhydrol.2020.125286.
  4. V. Burchard‐Levine, H. Nieto, D. Riaño, W.P. Kustas, M. Migliavacca, T.S. El‐Madany, J.A. Nelson, A. Andreu, A. Carrara, J. Beringer, A remote sensing‐based threesource energy balance model to improve global estimations of evapotranspiration in semi‐arid tree‐grass ecosystems, Global Change Biol., 28 (2022) 1493–1515.
  5. M. Tasumi, Estimating evapotranspiration using METRIC model and Landsat data for better understandings of regional hydrology in the western Urmia Lake Basin, Agric. Water Manage., 226 (2019) 105805, doi: 10.1016/j.agwat.2019.105805.
  6. H.M. Al-Ghobari, Estimation of reference evapotranspiration for southern region of Saudi Arabia, Agric. For. Meteorol., 19 (2000) 81–86.
  7. M. Elhag, Sensitivity analysis assessment of remotely based vegetation indices to improve water resources management, Environ. Dev. Sustainability, 16 (2014) 1209–1222.
  8. T. Govender, T. Dube, C. Shoko, Remote sensing of land useland cover change and climate variability on hydrological processes in Sub-Saharan Africa: key scientific strides and challenges, Geocarto Int., 38 (2022) 1–25.
  9. M.H. Jahangir, M. Arast, Remote sensing products for predicting actual evapotranspiration and water stress footprints under different land cover, J. Cleaner Prod., 266 (2020) 121818, doi: 10.1016/j.jclepro.2020.121818.
  10. R.G. Allen, M. Tasumi, R. Trezza, Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—model, Hydrol. Processes, 133 (2007) 380–394.
  11. M.C. Anderson, R.G. Allen, A. Morse, W.P. Kustas, Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources, Remote Sens. Environ., 122 (2012) 50–65.
  12. R. Allen, A. Irmak, R. Trezza, J.M. Hendrickx, W. Bastiaanssen, J. Kjaersgaard, Satellite‐based ET estimation in agriculture using SEBAL and METRIC, Hydrol. Processes, 25 (2011) 4011–4027.
  13. H. Nouri, M. Faramarzi, B. Sobhani, S. Sadeghi, Estimation of evapotranspiration based on Surface Energy Balance Algorithm for Land (SEBAL) using Landsat 8 and MODIS images, Appl. Ecol. Environ. Res., 15 (2017) 1971–1982.
  14. R.G. Allen, C. Morton, B. Kamble, A. Kilic, J. Huntington, D. Thau, N. Gorelick, T. Erickson, R. Moore, R. Trezza, EEFlux: A Landsat-Based Evapotranspiration Mapping Tool on the Google Earth Engine, 2015 ASABE/IA Irrigation Symposium: Emerging Technologies for Sustainable Irrigation-A Tribute to the Career of Terry Howell, Sr. Conference Proceedings, 2015, pp. 1–11.
  15. G.B. Senay, M. Friedrichs, R.K. Singh, N.M. Velpuri, Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin, Remote Sens. Environ., 185 (2016) 171–185.
  16. N. Bhattarai, L.J. Quackenbush, J. Im, S.B. Shaw, A new optimized algorithm for automating endmember pixel selection in the SEBAL and METRIC models, Remote Sens. Environ., 196 (2017) 178–192.
  17. J.M. Ramírez-Cuesta, R.G. Allen, D.S. Intrigliolo, A. Kilic, C. Robison, R. Trezza, C. Santos, I.J. Lorite, METRIC-GIS: an advanced energy balance model for computing crop evapotranspiration in a GIS environment, Environ. Modell. Software, 131 (2020) 104770, doi: 10.1016/j.envsoft.2020.104770.
  18. D. Guo, S. Westra, H.R. Maier, An R package for modelling actual, potential and reference evapotranspiration, Environ. Modell. Software, 78 (2016) 216–224.
  19. G.F. Olmedo, S. Ortega Farias, D. Fonseca Luengo, F. Fuentes Peñailillo, Water: tools and functions to estimate actual evapotranspiración using Land Surface Energy Balance Models in R, The R J., 2 (2016) 352–369.
  20. L.B. Ferreira, F.F. da Cunha, Multi-step ahead forecasting of daily reference evapotranspiration using deep learning, Comput. Electron. Agric., 178 (2020) 105728, doi: 10.1016/j. compag.2020.105728.
  21. M. He, J.S. Kimball, Y. Yi, S.W. Running, K. Guan, A. Moreno, X. Wu, M. Maneta, Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework, Remote Sens. Environ., 230 (2019) 111201, doi: 10.1016/j.rse.2019.05.020.
  22. Z. Su, The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes, Hydrol. Earth Syst. Sci., 6 (2002) 85–100.
  23. R.K. Singh, A. Irmak, S. Irmak, D.L. Martin, Application of SEBAL model for mapping evapotranspiration and estimating surface energy fluxes in south-central Nebraska, J. Irrig. Drain. Eng., 134 (2008) 273–285.
  24. W. Bastiaanssen, B. Thoreson, B. Clark, G. Davids, Discussion of “Application of SEBAL model for mapping evapotranspiration and estimating surface energy fluxes in south-central Nebraska” by Ramesh K. Singh, Ayse Irmak, Suat Irmak, and Derrel L. Martin, J. Irrig. Drain. Eng., 136 (2010) 282–283.
  25. F. Mohammed, A. Elfeki, M. Elhag, A. Chaabani, A comparative study of the estimation methods for NRCS curve number of natural arid basins and the impact on flash flood predications, Arabian J. Geosci., 14 (2021) 1–23.
  26. A. Irmak, R.G. Allen, J. Kjaersgaard, J. Huntington, B. Kamble, R. Trezza, I. Ratcliffe, Operational remote sensing of ET and challenges, Remote Sens. Environ., (2012) 467–492.
  27. M. Elhag, Inconsistencies of SEBS model output based on the model inputs: global sensitivity contemplations, J. Indian Soc. Remote Sens., 44 (2016) 435–442.
  28. S. Hussain, A.M. Elfeki, A. Chaabani, E.A. Yibrie, M. Elhag, Spatio-temporal evaluation of remote sensing rainfall data of TRMM satellite over the Kingdom of Saudi Arabia, Theor. Appl. Climatol., 150 (2022) 363–377.
  29. W. Senkondo, S.E. Munishi, M. Tumbo, J. Nobert, S.W. Lyon, Comparing remotely-sensed surface energy balance evapotranspiration estimates in heterogeneous and datalimited regions: a case study of Tanzania’s Kilombero Valley, Remote Sens., 11 (2019) 1289, doi: 10.3390/rs11111289.
  30. S. Ortega, Evaluation of the METRIC Model for Mapping Energy Balance Components and Actual Evapotranspiration for a Super-Intensive Drip-Irrigated Olive Orchard, Dissertations & Theses in Natural Resources, 2019, p. 296.
  31. B. Jarbou, A. Alqarawy, A. Chabaani, A. Elfeki, M. Elhag, Spatiotemporal analysis of the annual rainfall in the Kingdom of Saudi Arabia: predictions to 2030 with different confidence levels, Theor. Appl. Climatol., 146 (2021) 1479–1499.
  32. S. Islam, R.A. Khan, M. Ahmad, M. Al Qahtani, Computation of potential evapo-transpiration under different climatic condition, Kingdom of Saudi Arabia, Int. J. Eng. Assoc., 4 (2015) 107–111.
  33. A.M. Youssef, S.A. Sefry, B. Pradhan, E.A. Alfadail, Analysis on causes of flash flood in Jeddah city (Kingdom of Saudi Arabia) of 2009 and 2011 using multi-sensor remote sensing data and GIS, Geomatics Nat. Hazards Risk, 7 (2016) 1018–1042.
  34. F.M. Al Zawad, A. Aksakal, Impacts of Climate Change on Water Resources in Saudi Arabia, The 3rd International Conference on Water Resources and Arid Environments (2008) and the 1st Arab Water Forum, 2010, pp. 511–523.
  35. M. Elhag, J. Bahrawi, S. Boteva, Input/output inconsistencies of daily evapotranspiration conducted empirically using remote sensing data in arid environments, Open Geosci., 13 (2021) 321–334.
  36. J. Steiner, T. Howell, A. Schneider, Lysimetric evaluation of daily potential evapotranspiration models for grain sorghum, Agron. J., 83 (1991) 240–247.
  37. R.K. Singh, S. Islam, R.A. Khan, M. Danish, Analysis of potential evapotranspiration of different cities of Kingdom of Saudi Arabia, J. Artif. Intell. Res., 5 (2015) 48–51.
  38. M. Elhag, A. Psilovikos, I. Manakos, K. Perakis, Application of the SEBS water balance model in estimating daily evapotranspiration and evaporative fraction from remote sensing data over the Nile Delta, Water Resour. Manage., 25 (2011) 2731–2742.
  39. S. Hussain, J. Bahrawi, M. Awais, M. Elhag, Understanding the role of the radiometric indices in temporal evapotranspiration estimation in arid environments, Desal. Water Treat., 256 (2022) 221–234.
  40. H. Nouri, S. Beecham, F. Kazemi, A. Hassanli, S. Anderson, Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces, Hydrol. Earth Syst. Sci. Discuss., 10 (2013) 3897–3925.
  41. S. Chowdhury, M. Al-Zahrani, Implications of climate change on water resources in Saudi Arabia, Arabian J. Sci. Eng., 38 (2013) 1959–1971.
  42. L.B. Ferreira, F.F. da Cunha, R.A. de Oliveira, E.I. Fernandes Filho, Estimation of reference evapotranspiration in Brazil with limited meteorological data using ANN and SVM–a new approach, J. Hydrol., 572 (2019) 556–570.
  43. U. Avdan, G. Jovanovska, Algorithm for automated mapping of land surface temperature using Landsat 8 satellite data, J. Sens., 2016 (2016) 1–8.
  44. B. Kumari, M. Tayyab, J. Mallick, M.F. Khan, A. Rahman, Satellite-driven land surface temperature (LST) using Landsat 5, 7 (TM/ETM+ SLC) and Landsat 8 (OLI/TIRS) data and its association with built-up and green cover over urban Delhi, India, Remote Sens., 1 (2018) 63–78.
  45. G. Roerink, Z. Su, M. Menenti, S-SEBI: a simple remote sensing algorithm to estimate the surface energy balance, Phys. Chem. Earth Part B, 25 (2000) 147–157.
  46. J.G. Liu, P.J. Mason, Image Processing and GIS for Remote Sensing: Techniques and Applications, John Wiley & Sons, 2016.
  47. H. Oguz, LST calculator: a program for retrieving land surface temperature from Landsat TM/ETM+ imagery, Environ. Eng. Manage. J., 12 (2013) 549–555.
  48. A. Rajeshwari, N. Mani, Estimation of land surface temperature of Dindigul district using Landsat 8 data, Int. J. Eng. Res. Technol., 3 (2014) 122–126.
  49. N.P. Siddique, A. Ghaffar, Spatial and temporal relationship between NDVI and land surface temperature of Faisalabad city from 2000–2015, Eur. Online J. Nat. Soc., 8 (2019) 55–64.
  50. C.L. de Almeida, T.R.A. de Carvalho, J.C. de Araújo, Leaf area index of Caatinga biome and its relationship with hydrological and spectral variables, Agric. For. Meteorol., 279 (2019) 107705, doi: 10.1016/j.agrformet.2019.107705.
  51. J. Wang, T.W. Sammis, A.A. Andales, L.J. Simmons, V.P. Gutschick, D.R. Miller, Crop coefficients of open-canopy pecan orchards, Agric. Water Manage., 88 (2007) 253–262.
  52. H. Nouri, M. Faramarzi, B. Sobhani, S. Sadeghi, Estimation of evapotranspiration based on surface energy balance algorithm for land (SEBAL) using Landsat 8 and MODIS images, Appl. Ecol. Environ. Res., 15 (2017) 1971–1982.
  53. E. Nuaman, M. Elhag, J. Bahrawi, L. Zhang, H.F. Gabriel, K. Ur Rahman, Soil erosion modelling and accumulation using RUSLE and remote sensing techniques: case study Wadi Baysh, Kingdom of Saudi Arabia, Sustainability, 15 (2023) 3218–3232.
  54. M. Taheri, M. Gholizadeh, M. Nasseri, B. Zahraie, H. Poorsepahy- Samian, V. Espanmanesh, Performance evaluation of various evapotranspiration modeling scenarios based on METRIC method and climatic indexes, Environ. Monit. Assess., 193 (2021) 1–18.
  55. C.M. Frey, E. Parlow, R. Vogt, M. Harhash, M.M. Abdel Wahab, Flux measurements in Cairo. Part 1: in situ measurements and their applicability for comparison with satellite data, Int. J. Climatol., 31 (2011) 218–231.
  56. M. Elhag, J.A. Bahrawi, Realization of daily evapotranspiration in arid ecosystems based on remote sensing techniques, Geosci. Instrum. Methods Data Syst., 6 (2017) 141–147.
  57. M. Elhag, I. Gitas, A. Othman, J. Bahrawi, A. Psilovikos, N. Al-Amri, Time series analysis of remotely sensed water quality parameters in arid environments, Saudi Arabia, Environ. Dev. Sustainability, 23 (2021) 1392–1410.
  58. A.Y. Aldhebiani, M. Elhag, A.K. Hegazy, H.K. Galal, N.S. Mufareh, Consideration of NDVI thematic changes in density analysis and floristic composition of Wadi Yalamlam, Saudi Arabia, Geosci. Instrum. Methods Data Syst., 7 (2018) 297–306.
  59. A. Psilovikos, M. Elhag, Forecasting of remotely sensed daily evapotranspiration data over Nile Delta region, Egypt, Water Resour. Manage., 27 (2013) 4115–4130.