Abstract
This study evaluated the accuracy of alternative satellite and reanalysis datasets in estimating the Standardized Precipitation Evapotranspiration Index (SPEI). Eight alternate datasets consisting of the gridded precipitation data acquired from IMERG, TRMM, ERA5-Land (ERA5L), and GLDAS and the reference evapotranspiration (ETo) computed by using the ERA5L and GLDAS reanalysis data were exploited. The results revealed that the combination of IMERG precipitation and ERA5L-estimated ETo (IME) outperformed the other alternative data sources in simulating drought severity. The IME also accurately simulated dry months and the length of the most extended dry spells for the majority of the studied regions. This highlights the potential benefits of integrating data sources, which appear to yield better results compared to using single-source datasets. The SPEI estimated by the alternative datasets showed poor agreement with the SPEI calculated based on meteorological records in the hyper-arid/arid areas. However, better results were achieved for the semi-arid and sub-humid/humid conditions. Moreover, the long-term droughts were simulated with higher accuracy relative to short- and mid-term dry epochs. The errors in ETo estimates contribute more significantly to the errors in SPEI for the hyper-arid/arid and semi-arid regions. However, the errors in precipitation products had a greater influence on the errors in SPEI estimates in the sub-humid/humid environments. These findings suggest that improving the quality of reanalysis data used for modeling ETo is likely to considerably enhance the accuracy of SPEI estimates in the semi-arid and arid/hyper-arid environments. Overall, this study provides a reliable guide for drought identification under data limitation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The meteorological records: https://data.irimo.ir/login/login.aspx. ERA5-Land: https://cds.climate.copernicus.eu/. GLDAS 2.1: https://disc.gsfc.nasa.gov/datasets/GLDAS_NOAH025_M_2.1/summary?keywords=gldas. TRMM 3B43: https://disc.gsfc.nasa.gov/datasets/TRMM_3B43_7/summary?keywords=trmm. IMERG Final version: https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGM_06/summary?keywords=imerg.
Code Availability
Not applicable.
References
Abramowitz M, Stegun IA (1964) Handbook of mathematical functions: with formulas, graphs, and mathematical tables. Courier Corporation. pp 1046
Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper No. 56. Food and Agriculture Organization of the United Nations, Rome, Italy. pp 326
Arshad M, Ma X, Yin J, Ullah W, Ali G, Ullah S, Liu M, Shahzaman M, Ullah I (2021) Evaluation of GPM-IMERG and TRMM-3B42 precipitation products over Pakistan. Atmos Res 249. https://doi.org/10.1016/j.atmosres.2020.105341
Bazrafshan J (2017) Effect of air temperature on historical trend of long-term droughts in different climates of Iran. Water Resour Manag 31:4683–4698. https://doi.org/10.1007/s11269-017-1773-8
Caloiero T, Caroletti GN, Coscarelli R (2021) IMERG-based meteorological drought analysis over Italy. Climate 9. https://doi.org/10.3390/cli9040065
Chen N, Li R, Zhang X, Yang C, Wang X, Zeng L, Tang S, Wang W, Li D, Niyogi D (2020) Drought propagation in Northern China Plain: A comparative analysis of GLDAS and MERRA-2 datasets. J Hydrol 588. https://doi.org/10.1016/j.jhydrol.2020.125026
Darand M, Amanollahi J, Zandkarimi S (2017) Evaluation of the performance of TRMM Multi-satellite Precipitation Analysis (TMPA) estimation over Iran. Atmos Res 190:121–127. https://doi.org/10.1016/j.atmosres.2017.02.011
Ebrahimi A, Rahimi D, Joghataei M, Movahedi S (2021) Correlation wavelet analysis for linkage between winter precipitation and three oceanic sources in Iran. Environ Process 8:1027–1045. https://doi.org/10.1007/s40710-021-00524-0
Fu K, Wang K (2022) Quantifying flash droughts over China from 1980 to 2017. J Geophys Res Atmos 127. https://doi.org/10.1029/2022jd037152
Ghozat A, Sharafati A, Hosseini SA (2020) Long-term spatiotemporal evaluation of CHIRPS satellite precipitation product over different climatic regions of Iran. Theor Appl Climatol 143:211–225. https://doi.org/10.1007/s00704-020-03428-5
Hargreaves G, Samani Z (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1:96. https://doi.org/10.13031/2013.26773
Huffman GJ, Bolvin DT, Braithwaite D, Hsu K-L, Joyce RJ, Kidd C, Nelkin EJ, Sorooshian S, Stocker EF, Tan J, Wolff DB, Xie P (2020) Integrated multi-satellite retrievals for the global precipitation measurement (GPM) mission (IMERG). In: Levizzani V, Kidd C, Kirschbaum DB, Kummerow CD, Nakamura K, Turk FJ (eds) Satellite Precipitation Measurement, vol 1. Springer International Publishing, Cham, Switzerland, pp 343–353
Keikhosravi-Kiany MS, Masoodian SA, Balling RC, Darand M (2021) Evaluation of tropical rainfall measuring mission, integrated multi-satellite retrievals for GPM, climate hazards centre infrared precipitation with station data, and European centre for medium-range weather forecasts Reanalysis v5 data in estimating precipitation and capturing meteorological droughts over Iran. Int J Climatol 42:2039–2064. https://doi.org/10.1002/joc.7351
Kummerow C, Barnes W, Kozu T, Shiue J, Simpson J (1998) The tropical rainfall measuring mission (TRMM) sensor package. J Atmos Oceanic Tech 15:809–817. https://doi.org/10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2
Ma Q, Li Y, Liu F, Feng H, Biswas A, Zhang Q (2023) SPEI and multi-threshold run theory based drought analysis using multi-source products in China. J Hydrol 616. https://doi.org/10.1016/j.jhydrol.2022.128737
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Proc Conf Appl Climatol. American Meteorological Society Boston, MA, Anaheim, California, 17–22 January. pp 179–183
Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model Evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50:885–900. https://doi.org/10.13031/2013.23153
Mukherjee S, Mishra A, Trenberth KE (2018) Climate change and drought: A perspective on drought indices. Curr Clim Change Rep 4:145–163. https://doi.org/10.1007/s40641-018-0098-x
Muñoz-Sabater J, Dutra E, Agustí-Panareda A, Albergel C, Arduini G, Balsamo G, Boussetta S, Choulga M, Harrigan S, Hersbach H, Martens B, Miralles DG, Piles M, Rodríguez-Fernández NJ, Zsoter E, Buontempo C, Thépaut JN (2021) ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth Syst Sci Data Discuss 2021:1–50. https://doi.org/10.5194/essd-2021-82
Naresh Kumar M, Murthy CS, Sesha Sai MVR, Roy PS (2009) On the use of Standardized Precipitation Index (SPI) for drought intensity assessment. Meteorol Appl 16:381–389. https://doi.org/10.1002/met.136
Ndehedehe CE, Haile GG, Agutu NO, Ferreira VG, Getirana A, Okwuashi O (2020) Hydrological hotspots of climatic influence in Brazil: A two-step regularization approach. Atmos Res 246. https://doi.org/10.1016/j.atmosres.2020.105116
Nouri M, Ebrahimipak NA, Hosseini SN (2022) Estimating reference evapotranspiration for water-limited windy areas under data scarcity. Theor Appl Climatol 150:593–611. https://doi.org/10.1007/s00704-022-04182-6
Nouri M, Homaee M (2020) Drought trend, frequency and extremity across a wide range of climates over Iran. Meteorol Appl 27:e1899. https://doi.org/10.1002/met.1899
Nouri M, Homaee M (2022) Reference crop evapotranspiration for data-sparse regions using reanalysis products. Agric Water Manag 262:107319. https://doi.org/10.1016/j.agwat.2021.107319
Ortiz-Gómez R, Flowers-Cano RS, Medina-García G (2022) Sensitivity of the RDI and SPEI drought indices to different models for estimating evapotranspiration potential in semiarid regions. Water Resour Manag 36:2471–2492. https://doi.org/10.1007/s11269-022-03154-9
Pelosi A, Chirico GB (2021) Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data? Agric Water Manag 258. https://doi.org/10.1016/j.agwat.2021.107169
Pyarali K, Peng J, Disse M, Tuo Y (2022) Development and application of high resolution SPEI drought dataset for Central Asia. Sci Data 9:172. https://doi.org/10.1038/s41597-022-01279-5
Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng C-J, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M, Entin JK, Walker JP, Lohmann D, Toll D (2004) The global land data assimilation system. Bull Am Meteorol Soc 85:381–394. https://doi.org/10.1175/bams-85-3-381
Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture–climate interactions in a changing climate: A review. Earth Sci Rev 99:125–161. https://doi.org/10.1016/j.earscirev.2010.02.004
Sheffield J, Wood EF, Pan M, Beck H, Coccia G, Serrat-Capdevila A, Verbist K (2018) Satellite remote sensing for water resources management: Potential for supporting sustainable development in data-poor regions. Water Resour Res 54:9724–9758. https://doi.org/10.1029/2017wr022437
Singh VP, Guo H, Yu FX (1993) Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome. Stoch Hydrol Hydraul 7:163–177. https://doi.org/10.1007/bf01585596
Su Q, Singh VP (2023) Calibration‐free priestley‐taylor method for reference evapotranspiration estimation. Water Resour Res 59. https://doi.org/10.1029/2022wr033198
Taghizadeh E, Ahmadi-Givi F, Brocca L, Sharifi E (2021) Evaluation of satellite/reanalysis precipitation products over Iran. Int J Remote Sens 42:3474–3497. https://doi.org/10.1080/01431161.2021.1875508
Ullah I, Ma X, Yin J, Asfaw TG, Azam K, Syed S, Liu M, Arshad M, Shahzaman M (2021) Evaluating the meteorological drought characteristics over Pakistan using in situ observations and reanalysis products. Int J Climatol 41:4437–4459. https://doi.org/10.1002/joc.7063
UNEP (1997) World atlas of desertification. Arnold, Hodder Headline, PLC, UK, London, pp 182
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. J Clim 23:1696–1718. https://doi.org/10.1175/2009jcli2909.1
Vicente-Serrano SM, Domínguez-Castro F, Reig F, Tomas-Burguera M, Peña-Angulo D, Latorre B, Beguería S, Rabanaque I, Noguera I, Lorenzo-Lacruz J, El Kenawy A (2022) A global drought monitoring system and dataset based on ERA5 reanalysis: A focus on crop-growing regions. Geosci Data J 00:1–14. https://doi.org/10.1002/gdj3.178
Vicente-Serrano SM, Van der Schrier G, Beguería S, Azorin-Molina C, Lopez-Moreno J-I (2015) Contribution of precipitation and reference evapotranspiration to drought indices under different climates. J Hydrol 526:42–54. https://doi.org/10.1016/j.jhydrol.2014.11.025
Wable PS, Jha MK, Shekhar A (2018) Comparison of drought indices in a Semi-Arid River Basin of India. Water Resour Manag 33:75–102. https://doi.org/10.1007/s11269-018-2089-z
Wang J, Zhang Q, Zhang L, Wang Y, Yue P, Hu Y, Ye P (2022) The global pattern and development trends & directions on the drought monitoring research from 1983 to 2020 by using bibliometric analysis. Bull Am Meteorol Soc. https://doi.org/10.1175/bams-d-21-0324.1
Wei L, Jiang S, Ren L, Wang M, Zhang L, Liu Y, Yuan F, Yang X (2021) Evaluation of seventeen satellite-, reanalysis-, and gauge-based precipitation products for drought monitoring across mainland China. Atmos Res 263. https://doi.org/10.1016/j.atmosres.2021.105813
Xu R, Tian F, Yang L, Hu H, Lu H, Hou A (2017) Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau based on a high-density rain gauge network. J Geophys Res Atmos 122:910–924. https://doi.org/10.1002/2016jd025418
Yang H, Zhang J, Langston C (2009) Synchronization of radar observations with multi-scale storm tracking. Adv Atmos Sci 26:78–86. https://doi.org/10.1007/s00376-009-0078-0
Yao N, Li Y, Qg D, Li L, Peng L, Feng H (2019) Influence of the accuracy of reference crop evapotranspiration on drought monitoring using standardized precipitation evapotranspiration index in mainland China. Land Degrad Dev 31:266–282. https://doi.org/10.1002/ldr.3447
Yu L, Leng G, Python A (2022) A comprehensive validation for GPM IMERG precipitation products to detect extremes and drought over mainland China. Weather Clim Extrem 36. https://doi.org/10.1016/j.wace.2022.100458
Funding
This research received financial support through grants provided by SWRI (the Iran Soil and Water Research Institute) under Project No. 108402. The author would like to sincerely thank the three anonymous reviewers for their invaluable comments and feedback.
Author information
Authors and Affiliations
Contributions
Not applicable.
Corresponding author
Ethics declarations
Ethics Approval
Not applicable.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Competing Interests
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Nouri, M. Drought Assessment Using Gridded Data Sources in Data-Poor Areas with Different Aridity Conditions. Water Resour Manage 37, 4327–4343 (2023). https://doi.org/10.1007/s11269-023-03555-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-023-03555-4