Abstract
A study of climate change scenarios is presented in this paper by projecting the model of recorded precipitation/temperature data into three future periods by statistical downscaling methods through LARS-WG with data from 7 synoptic stations. The study area largely spans the closed basin of Lake Urmia with overlaps to some of the surrounding basins. The model is at two stages (the downscaling stage comprises the following: (i) it uses large-scale GCM models to provide climate variables (predictors), and (ii) the outcomes are downscaled to the local climatic variables for correlating with the observed time series (e.g. rainfall) for the period of T0, 1961–2001—40 years; the projecting stage comprises the derived precipitation/temperature values at T0 to T1: 2011–2030; T2: 2046–2065; and T3: 2080–2099 periods at synoptic stations using three standard scenarios of A1B, A2, and B1). The outputs are used to map the climate zones, which show the following: (i) climates at T1 are still similar to T0, and if there is any declining trend in precipitation during both periods, they are small to the extent that the shrinkage of Lake Urmia is unlikely to be driven by climate change; (ii) changes are likely at T2 and T3 periods including climatic regimes may turn peakier at the northern and drier at central regions; and (iii) precipitation is likely to decrease in some of the zones at T2 and T3 periods. This underpins the need for more responsive policymaking, and should this not be realised in the near future, the prospect seems bleak in terms of serious damages to Lake Urmia, depleting aquifers and subsequent immigration from the region, but can be averted by responsive planning.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Availability of data and material
Our data are available for anyone on request.
Code availability
We used the standard LARS-WG, which is available online.
Change history
20 February 2023
The presentation of Table 5, Figs. 4, 6 and 7 were enhanced.
References
Abbasian MS, Najafi MR, Abrishamchi A (2021) Increasing risk of meteorological drought in the Lake Urmia basin under climate change: introducing the precipitation-temperature deciles index. J Hydrol 592:125586
Abbaspour KC, Faramarzi M, Seyed Ghasemi S, Yang H (2009) Assessing the impact of climate change on water resources in Iran. Water Resour Res 45:1–16. https://doi.org/10.1029/2008WR007615
Ahmadaali J, Barani GA, Qaderi K, Hessari B (2017) Analysis of the effects of water management strategies and climate change on the environmental and agricultural sustainability of Urmia Lake Basin. Iran J Water 10(2):1–21. https://doi.org/10.3390/w10020160
Alborzi A, Mirchi A, Moftakhari H, Mallakpour I, Alian S, Nazemi A, Hassanzadeh E, Mazdiyasni O, Ashraf S, Madani K, Norouzi H, Zarderakhsh M, Mehran A, Sadegh M, Castelletti A, Agha Kouchak A (2018) Climate-informed environmental inflows to revive a drying lake facing meteorological and anthropogenic droughts. Environ Res Lett 13(8):1–13. https://doi.org/10.1088/1748-9326/aad246
Alizade Govarchin Ghale Y, Baykara M, Unal A (2017) Analysis of decadal land cover changes and salinization in Urmia Lake Basin using remote sensing techniques, Nat. Hazards Earth Syst. Sci. Discuss. [Preprint]. https://doi.org/10.5194/nhess-2017-212
Amiri MJ, Eslamian SS (2010) Investigation of climate change in Iran. J Environ Sci Technol 3:208–216. https://doi.org/10.3923/jest.2010.208.216
Azzizzadeh M, Javan K (2018) Temporal and spatial distribution of extreme precipitation indices over the Lake Urmia Basin. Environ Resour Res 6(1):25–39
CarbonBrief (2018): https://www.carbonbrief.org/mapped-how-every-part-of-the-world-has-warmed-and-could-continue-to-warm
Delju AH, Ceylan A, Piguet E, Rebetez M (2012) Observed climate variability and change in Urmia Lake Basin. Iran. Theor Appl Climatol 111(2):285–296. https://doi.org/10.1007/s00704-012-0651-9
Ghorbani MA, Khatibi R, Karimi V, Zaher Mundher Y, Zounemat Kermani M (2018) Learning from multiple models using artificial intelligence to improve model prediction accuracies: application to river flows. Water Resour Manag 32(4):4201–4215. https://doi.org/10.1007/s11269-018-2038-x
Gollier C, and Treich N (2013) Encyclopedia of energy, natural resource and environmental economics, 2 332–33. https://doi.org/10.1016/B978-0-12-375067-9.00159-5
Hatami Majoumerdi S, Borhani Dariane A (2015) Temperature trend analysis in Urmia Lake basin compared with water level fluctuations of the lake. International Conference on Chemical, Civil and Environmental Engineering (CCEE-2015) June 5–6, 2015 Istanbul (Turkey).
Hosseini Moghari SM, Araghinejad S, Tourian MJ, Ebrahimi K, Döll P (2020) Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in situ data for calibrating a global hydrological model. Hydrol Earth Syst Sci 24:1939–1956. https://doi.org/10.5194/hess-24-1939-2020
IMPfLUB (2010) Integrated management plan for Lake Urmia Basin, see (accessed on 02 Sept. 2022) https://www.ramsar.org/sites/default/files/documents/library/lakeurmiamanagementplan-i.r.iran2010.pdf. See also: The Drying of Iran's Lake Urmia and its Environmental Consequences (unep.net). Both access in December 2021)
Jalili S, Hamidi S, Morid S, Ghanbar R (2016) Comparative analysis of Lake Urmia and Lake Van water level time series. Arab J Geosci 9(14):644
Khan MS, Coulibaly P, Dibike Y (2006) Uncertainty analysis of statistical downscaling methods. J Hydrol 319(1–4):357–382
Khatibi R, Nadiri AA (2020) Inclusive Multiple Models (IMM) for predicting groundwater levels and treating heterogeneity. Geosci Frontiers 12(2):713–724. Inclusive Multiple Models (IMM) for predicting groundwater levels and treating heterogeneity - ScienceDirect
Khatibi R, Ghorbani MA, Naghshara Sh, Aydin H (2020) A framework for ‘Inclusive Multiple Modelling’ with critical views on modelling practices - applications to modelling water levels of Caspian Sea and Lakes Urmia and Van. J Hydrol 587(1):124923. https://doi.org/10.1016/j.jhydrol.2020.124923
Khatibi R. (2022) “Chapter 1: A basic framework to overarch sustainability, risk and reliability – a critical review,” Risk, Reliability and Sustainability Ed. By Roshni, T., Samui, P., Bui, D., Khatibi, R. and Kim, D., Elsevier Pub.
Peel MC, Finlayson BL, and McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633–1644. https://hess.copernicus.org/articles/11/1633/2007/hess-11-1633-2007.pdf. Accessed 15 Aug 2022
Racsko P, Szeidl L, Semenov M (1991) A serial approach to local stochastic weather models. Ecol Model 57:27–41. https://doi.org/10.1016/0304-3800(91)90053-4
Rahimi J, Ebrahimpour M, Khalili A (2013) Spatial changes of extended De Martonne climatic zones affected by climate change in Iran. Theor Appl Climatol 112:409–418. https://doi.org/10.1007/s00704-012-0741-8
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. Theoret Appl Climatol 141(1):183–199
Razmara P, Massah Bavani AR, Motiee H, Torabi S, Lotfi S (2013) Investigating uncertainty of climate change effect on entering runoff to Urmia Lake Iran. Hydrol Earth Syst Sci 10:2183–2221. https://doi.org/10.5194/hessd-10-2183-2013
Ref 1. https://www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_CONF.151_26_Vol.I_Declaration.pdf. Accessed 14 Aug 2022
Ref 2: see the website http://www.meteotemplate.com/template/plugins/weatherTerminologyHU/index.php. Accessed 14 Aug 2022
Ref 3: see the website https://www.khabaronline.ir/news/541078/27 (Not in English). Accessed 14 Aug 2022
Sadeghfam S, Ehsanitabar A, Khatibi R, Daneshfaraz R (2018) Investigating ‘risk’ of groundwater drought occurrences by using reliability analysis. Ecol Indic 94:170–184. https://doi.org/10.1016/j.ecolind.2018.06.055
Sadeghfam S, Khatibi R, Moradian T, Daneshfaraz R (2021) Statistical downscaling of precipitation using inclusive multiple modelling (IMM) at two levels. J Water Climate Chang 12(7):3373–3387. https://doi.org/10.2166/wcc.2021.106
Sadeghfam S, Mirahmadi R, Khatibi R, Mirabbasi R, Nadiri AA (2022) Investigating meteorological/groundwater droughts by copula to study anthropogenic impacts. Sci Reports 12:8285. https://doi.org/10.1038/s41598-022-11768-7
Sanikhani H, Kisi O, Amirataee B (2018) Impact of climate change on runoff in Lake Urmia basin. Iran Theor Appl Climatol 132:491–502
Semenov MA, Brooks RJ (1999) Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain. Climate Res 11:137–148. https://doi.org/10.3354/cr011137
Semenov MA, Brooks RJ, Barrow EM, Richardson CW (1998) Comparison of the WGEN and LARS-WG stochastic weather generators in diver climates. Clim Res 10:95–107
Semenov MA, Barrow EM (2002) LARS-WG a stochastic weather generator for use in climate impact studies. User’s manual, Version 3.0.
Semenov MA, Stratonovitch P (2010) Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Research 411–14. https://doi.org/10.3354/cr00836
Vaheddoost B, Aksoy H (2021) Interaction of groundwater with Lake Urmia in Iran. Hydrol Process 32(21):3283–3295. https://doi.org/10.1002/hyp.13263
Zamani Nuri A, Farzaneh MR, Fakhri M, Dokoohaki H, Eslamian S, Khordadi MJ (2013) Assessment of future climate classification on Urmia Lake basin under effect of climate change. Int J Hydrol Sci Technol 3(2):128–140. https://doi.org/10.1504/IJHST.2013.057625
Author information
Authors and Affiliations
Contributions
Rasoul Jani: Supervised the research work, produced the initial version, reviewed the finalised paper.
Rahman Khatibi: Critically reviewed the results, rewrote the manuscript, revised its communication.
Sina Sadeghfam: Critically reviewed the modelling results, revised the GIS plots, reviewed the manuscript.
Elnaz Zarrinbal: Carried out the modelling activities for her research work.
Corresponding author
Ethics declarations
Ethics approval
We have conducted no laboratory tests for the paper and have involved no human participants and/or animals.
Consent to participate
The journal has our full consent.
Consent for publication
The journal has our full consent to publish our paper and the data.
Consent for figures
We have produced all the figures ourselves and need no consent.
Conflict of interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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
Jani, R., Khatibi, R., Sadeghfam, S. et al. Climate zoning under climate change scenarios in the basin of Lake Urmia and in vicinity basins. Theor Appl Climatol 152, 181–199 (2023). https://doi.org/10.1007/s00704-023-04380-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-023-04380-w