Performance evaluation of different potential evapotranspiration models and application of optimal models for drought monitoring using the RDI index across different climate regimes of Iran

Document Type : Research/Original/Regular Article

Authors

1 Associate Professor, Department of Geography, Faculty of Literature and Humanities, Urmia University, Urmia, Iran

2 Postdoctoral Researcher, Department of Geography, Faculty of Literature and Humanities, Urmia University, Urmia, Iran

3 B.Sc, Department of Geography, Faculty of Literature and Humanities, Urmia University, Urmia, Iran

Abstract

Introduction

Drought is a climatic anomaly that results from long-term disruptions in components of the water balance (Wang et al., 2021; Portner et al., 2022; Zhang et al., 2023; Kartal, 2024; Tareke, 2025). This phenomenon has both direct and indirect adverse impacts, with water resources being the most significantly affected (Balooei et al., 2024). Water scarcity and its associated challenges are recognized as among the most critical and urgent global crises (Zarei et al., 2019a). Although drought cannot be prevented, understanding its nature and characteristics enhances the potential for partial prediction and, through preparedness and planning, helps reduce—and, where possible, control—its detrimental effects (Rezaei et al., 2024). Therefore, greater attention must be paid to drought and to identifying the key factors influencing it across different regions, particularly in vulnerable countries such as Iran, which face growing water scarcity. The increasing need to understand drought and its consequences has motivated extensive global research aimed at developing various drought indices. Among these, the Reconnaissance Drought Index (RDI), introduced by Tsakiris et al. (2007), is one of the most notable.



Materials and Methods

In this study, daily observational data from nine synoptic stations covering a 30-year period (1991–2020) were obtained from the Iran Meteorological Organization to estimate potential evapotranspiration and the RDI index. These stations were selected so that each represents one of Iran’s major climatic groups. In this research, the performance of six temperature-based models and three radiation-based models for estimating potential evapotranspiration was evaluated. The primary goal of the analysis is to identify which of these simplified approaches provides results most consistent with the FAO Penman–Monteith (FAO-56 PM) model, which is widely recognized as the standard reference method (Allen et al., 1998).



Results and Discussion

Evaluation of Daily Potential Evapotranspiration Models

The results indicated that the performance of evapotranspiration models is strongly influenced by the climatic conditions of each region. For example, the Blaney–Criddle model performed best in certain climates, while the same model showed lower accuracy in others. This finding is consistent with previous studies, including Eghtedarnezhad et al. (2016), which emphasized the role of climatic factors in drought monitoring. Moreover, the variability in model performance across different regions further underscores the need to evaluate and select models that are appropriate for the specific climatic conditions of each area. This observation also aligns with the findings of Lehner et al. (2020) and Beobide-Arsuaga et al. (2021), who stressed the importance of model adaptability to local conditions. Overall, it can be concluded that choosing the appropriate model for estimating evapotranspiration is a crucial step in drought studies and water resource management, and must be carried out with careful consideration of each region’s climatic characteristics.

Evaluation of Monthly Potential Evapotranspiration Models

Overall, the results demonstrate that, similar to the daily scale, temperature-based models do not exhibit uniform behavior across different climates at the monthly scale. A model may perform exceptionally well in one climate while ranking among the weakest in another. These differences highlight the necessity of considering climate type, geographical characteristics, the study period, and careful model selection in climatological research (Latrech et al., 2024).

Assessment of Drought Using the 6- and 12-Month RDI Indices for Optimal Models at Selected Stations

The overall findings of this study indicate that at the 6-month timescale, the frequency of drought and wet periods is higher, whereas at the 12-month timescale, their frequency decreases but their persistence increases. This result is in agreement with the study by Ahrari and Raja (2025), who examined meteorological, agricultural, and hydrological drought indices in the Mahabad plain. Furthermore, based on the results of the present study, the 12-month RDI was identified as a more suitable timescale for monitoring drought and wet periods, which is consistent with the findings of Nouri and Homaee (2020), Torabinejad et al. (2023), and Rezaei et al. (2024).

Conclusion

Frequent drought events and the significant damages they cause in various sectors, including agriculture, the environment, socio-economic, and other areas, have made this phenomenon one of the fundamental challenges in different regions of the world. The present study aimed to evaluate the performance of different potential evapotranspiration models and their influence on the RDI drought index across diverse climatic zones, using 30 years (1991–2020) of data from nine synoptic stations representing nine distinct climate types in Iran (BSh, BSk, BWh, BWk, Cfa, Csa, Csb, Dsa, Dsb). The evaluation of nine evapotranspiration models showed that their performance is strongly affected by the climatic characteristics of each region. For example, the Droogers–Allen model performed best in cold semi-arid (BSk), Mediterranean temperate with warm summers (Csb), and cold climates with dry, warm summers (Dsb), whereas the same model exhibited poor performance in hot semi-arid climates (BSh) and several other regions. In the drought analysis section, comparison of the 6- and 12-month RDI indices revealed that although both timescales confirm the occurrence of frequent droughts during most of the study period, the 12-month RDI was identified as the more suitable scale for drought monitoring and analysis in Iran. This is due to its ability to filter out short-term fluctuations and better reflect the persistence of drought periods.

Keywords

Main Subjects

References

منابع:
احراری، سعیده و رجا، امید (1404). بررسی شاخص‌های خشکسالی هواشناسی، کشاورزی و هیدرولوژیکی در دشت مهاباد. مدیریت آب در کشاورزی، 12(1)، 29-48.
اقتدار نژاد، مینا، بذرافشان، ام‌البنین و صادقی لاری، عدنان (1395). ارزیابی تطبیقی شاخص‌های SPI، RDI و SDI در تحلیل مشخصه‌‍‌های خشکسالی هواشناسی و هیدرولوژیکی (مطالعه موردی: دشت بم). دانش آب و خاک، 26(4.2)، 69-81.
امیرزاده، آرش، رئوف، مجید و مصطفی‌زاده، رئوف (1404). ارزیابی الگوی مکانی تغییرات هیدرومدول آبیاری تحت الگوهای کشت متفاوت در شمال‌غرب ایران. مدل‌سازی و مدیریت آب و خاک، 5(1)، 195-212. doi: 10.22098/mmws.2024.15135.1463
بالویی، فاطمه، کابلی‌زاده، مصطفی و محمدی، شاهین (1403). پایش تغییرات زمانی-مکانی خشکسالی هواشناسی و تحلیل روند متغیرهای اقلیمی در استان خوزستان بین سال‌‌های 2000 تا 2020. مخاطرات محیط طبیعی، 13(40)، 73-94. doi: 10.22111/jneh.2024.46574.1987
ترابی‌نژاد، نسترن، زرین، آذر و داداشی رودباری، عباسعلی (1402). بررسی انواع خشکسالی و مشخصه‌های آن در ایران با استفاده از شاخص بارش تبخیر و تعرق استاندارد شده (SPEI). آب و خاک. 37(3)،473-486. doi: 10.22067/jsw.2023.81322.1257
جوان، خدیجه و یحیوی دیزج، آمنه (1403). تحلیل زمانی و مکانی شاخص‌های خشکی UNEP و دومارتن در ایران طی دورۀ 1976ـ2020. مهندسی اکوسیستم بیابان، 12(39)، 89-102. doi: ‎10.22052/deej.2024.253864.1032
رضایی، سارا، معصوم‌پور سماکوش، جعفر و میری، مرتضی (1403). تحلیل ویژگی‌های خشکسالی (شدت، مدت، بزرگی) ایران بر اساس شاخص خشکسالی چند متغیره. فناوری‌های پیشرفته در بهره‌وری آب، 4(1)، 82-98. doi: 10.22126/atwe.2024.10319.1114
رضیئی، طیب (1396). منطقه‌بندی اقلیمی ایران به روش کوپن-گایگر و بررسی جابه‌جایی مناطق اقلیمی کشور در سدۀ بیستم. فیزیک زمین و فضا، 43(2)، 419-439. doi: 10.22059/jesphys.2017.58916
رضیئی، طیب و میری، مرتضی (1401). طبقه‌بندی اقلیمی ایران به روش کوپن – گایگر، انتشارات پژوهشکده حفاظت خاک و آبخیزداری، تهران.
رئوف، مجید، امیرزاده، آرش و مصطفی زاده، رئوف (1402). اثر پارامترهای اقلیمی و الگوی کشت روی تبخیر-تعرق و هیدرومدول آبیاری در برخی مناطق شمال‌غرب ایران. آبیاری و زهکشی ایران، 17(5)، 857-868.
صادقیان آق کندی، مرضیه، رضایی، حسین، خلیلی، کیوان و احمدی،
فرشاد. (1403). بررسی عملکرد الگوریتم‌های Kstar و GPR در مدل‌سازی شاخص خشکسالی هواشناسی RDI (مطالعه موردی: شرق حوضه دریاچه ارومیه). مهندسی عمران و محیط‌زیست، 54(114)، 142-151. doi: 10.22034/ceej.2023.55292.2225
صداقت‌ نژاد، مه سیما، مساعدی، ابوالفضل، قهرمان، بیژن و سعادت پور، عالیه (1403). تعیین مناسب‌ترین روش زمین آماری به‌منظور پایش خشکسالی بر مبنای شاخص‌های مختلف خشکسالی و کاربرد آن در دشت نیشابور. فیزیک زمین و فضا، 50(1)، 125-147. doi: 10.22059/jesphys.2023.351663.1007475
فتوت، جلال و اسدی زارچ، محمد امین (1404). مقایسه کارایی شاخص‌های خشکسالی اقلیمی (SPI، RDI وSPEI) در مناطق خشک و نیمه‌خشک با شاخص سنجش از دوری TVDI. مدیریت بیابان، 13(1)، 23-42. doi: 10.22034/jdmal.2025.2041089.1481
قبائی سوق، محمد، زارع ابیانه، حمید، مساعدی، ابوالفضل، و صمدی، سیده زهرا (1394). پایش وضعیت‌های رطوبتی و روند آن‌ها بر مبنای شاخص بارش- تبخیر و تعرق استاندارد شده (SPEI) در نواحی مختلف آب و هوایی ایران. آب و خاک، 30(5)، 1700-1717. doi: 10.22067/jsw.v0i0.47565
یحیوی دیزج، آمنه، اکبری ازیرانی، طیبه، خالدی، شهریار و جوان، خدیجه (1402الف). بررسی فصلی تبخیر تعرق مرجع و تحلیل حساسیت آن به عناصر هواشناسی در ایران. آب و خاک، (4)37، 643-657. doi: 10.22067/jsw.2023.83328.1307
یحیوی دیزج، آمنه، جوان، خدیجه، خالدی، شهریار و اکبری ازیرانی، طیبه (1402ب). ارزیابی تغییر مقدار تبخیر و تعرق مرجع در ایران طی دهه‌های اخیر. مدیریت بیابان، (1)11، 39-58. doi: 10.22034/jdmal.2023.2000984.1413
 References
Adnan, S., Ullah, K., Shuanglin, L., Gao, S., Khan, A. H., & Mahmood, R. (2018). Comparison of various drought indices to monitor drought status in Pakistan. Climate Dynamics, (51), 1885-1899. doi:10.1007/s00382-017-3987-0
Ahrari, S., & Raja, O. (2025). Investigation of meteorological, agricultural, and hydrological drought indicators in Mahabad plain. Water Management in Agriculture, 12(1), 29-48. [In Persian]
Allen RG, Pereira LS, Raes D, Smith M. (1998) Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56. Rome, Italy
Allen RG. (1993) Evaluation of a temperature difference method for computing grass reference evapotranspiration. Report to Water Resources Development and Management Service Land and Water Development Division. FAO. Rome, Italy
Amirzadeh, A., Raoof, M., & Mostafazadeh, R. (2025). Assessing spatial pattern of irrigation hydromodule under different crop patterns in northwestern Iran. Water and Soil Management and Modelling, 5(1), 195-212. doi: 10.22098/mmws.2024.15135.1463 [In Persian]
Ansarifard, S., & Shamsnia, S. A. (2018). Monitoring drought by reconnaissance drought index (RDI) and standardized precipitation index (SPI) using DrinC software. Water Utility J, 20, 29-35.
Baloei, F., Kabolizadeh, M., & Mohammadi, S. (2024). Monitoring temporal-spatial changes of meteorological drought and trend analysis of climatic variables in Khuzestan province from 2000 to 2020. Journal of Natural Environmental Hazards, 13(40), 73-94. doi: 10.22111/jneh.2024.46574.1987 [In Persian]
Bazrafshan, J. (2017). Effect of air temperature on historical trend of long-term droughts in different climates of Iran. Water Resources Management, 31(14), 4683-4698.doi:10.1007/s11269-017-1773-8
Beobide-Arsuaga, G., Bayr, T., Reintges, A., & Latif, M. (2021). Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models. Climate Dynamics, 56(11), 3875-3888. doi:10.1007/s00382-021-05673-4
Blaney, H.F., & Criddle, W.D. (1950). Determining water requirements in irrigated areas from climatologically and irrigation data. Washington Soil Conservation Service (SCS). (Vol. 96).
Droogers P, Allen RG (2002) Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and drainage systems. 16:33–45. doi: 10.1023/A:1015508322413
Eghtedar Nezhad, M., Bazrafshan, O., & Sadeghi Lari, A. (2017). Adaptive Evaluation of SPI, RDI and SDI Indices in Analyzing the Meteorological and Hydrological Drought Characteristics (Case Study: Bam Plain). Water and Soil Science, 26(4.2), 69-81. [In Persian]
Fotovat,J. & Asadi Zarch, M. A. (2025). Comparison of the efficiency of climatic drought indices (SPI, RDI, and SPEI) in arid and semi-arid regions using the remote sensing-based TVDI Index. Desert Management, 13(1), 23-42. doi: 10.22034/jdmal.2025.2041089.1481 [In Persian]
Ghabaei S, M., Zare Abyaneh, H., Mosaedi, A., & Samadi, S. Z. (2016). Assessment of humidity conditions and trends based on standardized precipitation evapotranspiration index (SEPI) over different climatic regions of Iran. Water and Soil, 30(5), 1700-1717. [In Persian]
Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture. 1:96–99.
Irmak S, Irmak A, Allen RG, Jones JW (2003) Solar and net radiation-based equations to estimate reference evapotranspiration in humid climates. Journal of Irrigation and Drainage Engineering .129(5):336–347. doi:10.1061/(ASCE)07339437(2003)129:5(33)
Javan. Kh., & Yahyavi Dizaj, A. (2024). Investigating Temporal and Spatial Variations of UNEP and De Martonne Aridity Indices in Iran from 1976 to 2020. Desert Ecosystem Engineering, 12(39), 89-102. doi: ‎10.22052/deej.2024.253864.1032 [In Persian]
Kartal, V. (2024). Drought Assessment of Yeşilırmak Basin Using Long-term Data. Turkish Journal of Science and Technology, 19(1), 179-192. doi:10.55525/tjst.1392199
Latrech, B., Hermassi, T., Yacoubi, S., Slatni, A., Jarray, F., Pouget, L., & Ben Abdallah, M. A. (2024). Comparative analysis of climate change impacts on climatic variables and reference evapotranspiration in Tunisian Semi-Arid Region. Agriculture, 14(1), 160.10.3390/agriculture14010160
Lehner, F., Deser, C., Maher, N., Marotzke, J., Fischer, E. M., Brunner, L., ... & Hawkins, E. (2020). Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6. Earth System Dynamics, 11(2), 491-508. doi: 10.5194/esd-11-491-2020
Makkink GF (1957) Testing the Penman formula by means of lysimeters. J Inst Water Eng 11:277–288 McEvoy DJ, Huntington JL, Abatzoglou JT, Edwards LM (2012) An evaluation of multiscalar drought indices in Nevada and eastern California. Earth Interact. 16:1–18.
Mianabadi, A., Salari, K., & Pourmohamad, Y. (2022). Drought monitoring using the long-term CHIRPS precipitation over Southeastern Iran, Appl Water Sci, 12, 183. doi:10.1007/s13201-022-01705-4
Nouri, M., & Homaee, M. (2020). Drought trend, frequency and extremity across a wide range of climates over Iran. Meteorological Applications, 27(2), e1899. doi:10.1002/met.1899
Omar, L. C., Mariano, N. C., Alberto, G., Ernestina, P. G., Jorge, M. M., & Enrique, T. D. (2022). Sensitivity of four indices of meteorological drought for rainfed maize yield prediction in the state of Sinaloa, Mexico. Agriculture, 12(4), 525. 10.3390/agriculture12040525
Ortiz-Gómez, R., Flowers-Cano, R. S., & Medina-García, G. (2022). Sensitivity of the RDI and SPEI drought indices to different models for estimating evapotranspiration potential in semiarid regions. Water Resources Management, 36(7), 2471-2492.
Pörtner, H.O., Roberts, D.C., Poloczanska, E.S., Mintenbeck, K., Tignor, M., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V. and Okem, A. (2022). Summary for policymakers.
Priestley CHB, Taylor RJ (1972) On the assessment of surface heat fux and evaporation using large scale parameters. Mon Weather Rev 100:81–92.
Rahimi, J., Laux, P., & Khalili, A. (2020). Assessment of climate change over Iran: CMIP5 results and their presentation in terms of Köppen–Geiger climate zones. Theoretical and Applied Climatology, 141, 183-199.
Raoof, M., Amirzadeh, A. & Mostafazadeh, R. (2024). Effect of climatic parameters and cultivation pattern on Evapotranspiratin and Irrigation Hydromodul in some areas of northwest Iran. Journal of Irrigation and Drainage, 17(5), 857-868 [In Persian]
Raziei, T. (2017). Köppen-Geiger climate classification of Iran and investigation of its changes during 20th century. Journal of the Earth and Space Physics, 43(2), 419-439. doi: 10.22059/jesphys.2017.58916 [In Persian]
Raziei, T. and Miri, M. (2022). Köppen-Geiger climate classification of Iran. Soil Conservation and Watershed Management Research Institute, Tehran [In Persian].
Rezaei, S., Masoompour Samakosh, J., & Miri, M. (2024). Analysis of drought characteristics (severity, duration, magnitude) in Iran based on multivariate standardized drought index. Advanced Technologies in Water Efficiency, 4(1), 82-98. doi: 10.22126/atwe.2024.10319.1114 [In Persian]
Sadeghian Agkandy, M. , Rezaie, H., Khalili, K. & Ahmadie, F. (2024). Investigating the Performance of Kstar and GPR Algorithms in Modeling RDI Meteorological Drought Index (Case Study: East of Urmia Lake Basin). Journal of Civil and Environmental Engineering, 54(114), 142-151. doi: 10.22034/ceej.2023.55292.2225 [In Persian]
Sedaghat Nejad, M., Mosaedi, A. , Ghahraman, B. & Saadatpour, A. (2024). Determining the optimal geostatistical method for drought monitoring based on different drought indices and its application in Neishabour Plain. Journal of the Earth and Space Physics, 50(1), 125-147. doi: 10.22059/jesphys.2023.351663.1007475 [In Persian]
Simsek, O., Yildiz-Bozkurt, S., & Gumus, V. (2024). Analysis of meteorological drought with different methods in the Black Sea region, Turkey. Acta Geophysica, 72(3), 1927-1943.
Sobhani, B., Safarianzengir, V., & Kianian, M. K. (2019). Drought monitoring in the Lake Urmia basin in Iran. Arab J Geosci 12: 448.
Surendran, U., Anagha, B., Raja, P., Kumar, V., Rajan, K., & Jayakumar, M. (2019). Analysis of drought from humid, semi-arid and arid regions of India using DrinC model with different drought indices. Water Resources Management, 33(4), 1521-1540.
Tareke, K. A. (2025). Long-term hydrological drought monitoring and trend analysis in Blue Nile River basin. Heliyon, 11(1). doi: 10.1016/j.heliyon.2024.e41161
Thomas, T., Jaiswal, R. K., Galkate, R. V., & Nayak, T. R. (2016). Reconnaissance drought index-based evaluation of meteorological drought characteristics in Bundelkhand. Procedia Technology, (24), 23-30.
Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical Review, 38(1), 55-94.
Torabi Haghighi, A., Abou Zaki, N., Rossi, P. M., Noori, R., Hekmatzadeh, A. A., Saremi, H., & Kløve, B. (2020). Unsustainability syndrome—from meteorological to agricultural drought in arid and semi-arid regions. Water, 12(3), 838. doi:10.3390/w12030838
Torabinezhad, N. , Zarrin, A. & Dadashi-Roudbari, A. (2023). Analysis of Different Types of Droughts and Their Characteristics in Iran Using the Standardized Precipitation Evapotranspiration Index (SPEI). Water and Soil, 37(3), 473-486. doi: 10.22067/jsw.2023.81322.1257 [In Persian]
Tsakiris, G., Pangalou, D., & Vangelis, H. (2007). Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resources Management, 21, 821-833. doi:10.1007/s11269-006-9105-4
Vaghefi, S. A., Keykhai, M., Jahanbakhshi, F., Sheikholeslami, J., Ahmadi, A., Yang, H., & Abbaspour, K. C. (2019). The future of extreme climate in Iran. Scientific Reports, 9(1), 1464. doi:10.1038/s41598-018-38071-8[In Persian]
Wang, M., Jiang, S., Ren, L., Xu, C. Y., Menzel, L., Yuan, F., ... & Yang, X. (2021). Separating the effects of climate change and human activities on drought propagation via a natural and human-impacted catchment comparison method. Journal of Hydrology, 603, 126913.
Yahyavi Dizaj, A., Akbari Azirani, T. , Khaledi, S. & Javan, K. (2023a). Seasonal Analysis of Reference Evapotranspiration and Its Sensitivity to Meteorological Elements in IRAN. Water and Soil, 37(4), 643-657. doi: 10.22067/jsw.2023.83328.1307 [In Persian]
Yahyavi Dizaj, A., Javan, K., Khaledi, S., & Akbari Azirani, T. (2023b). Evaluation of Changes in Reference Evapotranspiration in Iran Over the Last Decades. Desert Management, 11(1), 39-58. doi:10.22034/jdmal.2023.2000984.1413 [In Persian]
Yuce, M. I., & Esit, M. (2021). Drought monitoring in Ceyhan basin, Turkey. Journal of Applied Water Engineering and Research, 9(4), 293-314. doi:10.1080/23249676.2021.1932616
Zarei, A. R. (2019). Analysis of changes trend in spatial and temporal pattern of drought over south of Iran using standardized precipitation index (SPI). SN Applied Sciences, 1(5), 465. doi:10.1007/s42452-019-0498-0
Zarei, A. R., & Moghimi, M. M. (2019). Environmental assessment of semi-humid and humid regions based on modeling and forecasting of changes in monthly temperature International Journal of Environmental Science and Technology, 16, 1457-1470.
Zhang, R., Bento, V. A., Qi, J., Xu, F., Wu, J., Qiu, J., ... & Wang, Q. (2023). The first high spatial resolution multi-scale daily SPI and SPEI raster dataset for drought monitoring and evaluating over China from 1979 to 2018. Big Earth Data, 7(3), 860-8
 
 
Water and Soil Management and Modelling
Volume 6, Issue 3
August 2026
Pages 35-55

Files

History

  • Receive Date: 02 December 2025
  • Revise Date: 22 December 2025
  • Accept Date: 07 January 2026

Share

How to cite

Statistics