Please wait a minute...
Journal of Arid Land
Journal of Arid Land  2024, Vol. 16 Issue (6): 752-767    DOI: 10.1007/s40333-024-0019-x
Research article     
Assessment of rehabilitation strategies for lakes affected by anthropogenic and climatic changes: A case study of the Urmia Lake, Iran
Seyed Morteza MOUSAVI, Hossein BABAZADEH*(), Mahdi SARAI-TABRIZI, Amir KHOSROJERDI
Department of Water Science and Engineering, Science and Research Branch, Islamic Azad University, Tehran 147789-3855, Iran
Download: HTML     PDF(2426KB)
Export: BibTeX | EndNote (RIS)      

Abstract  

Over the last three decades, more than half of the world's large lakes and wetlands have experienced significant shrinkage, primarily due to climate change and extensive water consumption for agriculture and other human needs. The desiccation of lakes leads to severe environmental, economic, and social repercussions. Urmia Lake, located in northwestern Iran and representing a vital natural ecosystem, has experienced a volume reduction of over 90.0%. Our research evaluated diverse water management strategies within the Urmia Lake basin and prospects of inter-basin water transfers. This study focused on strategies to safeguard the environmental water rights of the Urmia Lake by utilizing the modeling and simulating (MODSIM) model. The model simulated changes in the lake's water volume under various scenarios. These included diverting water from incoming rivers, cutting agricultural water use by 40.0%, releasing dam water in non-agricultural seasons, treated wastewater utilization, and inter-basin transfers. Analytical hierarchy process (AHP) was utilized to analyze the simulation results. Expert opinions with AHP analysis, acted as a multi-criteria decision-making tool to evaluate the simulation and determine the optimal water supply source priority for the Urmia Lake. Our findings underscore the critical importance of reducing agricultural water consumption as the foremost step in preserving the lake. Following this, inter-basin water transfers are suggested, with a detailed consideration of the inherent challenges and limitations faced by the source watersheds. It is imperative to conduct assessments on the impacts of these transfers on the downstream users and the potential environmental risks, advocating for a diplomatic and cooperative approach with adjacent country. This study also aims to forecast the volumes of water that can be transferred under different climatic conditions—drought, normal, and wet years—to inform strategic water management planning for the Urmia Lake. According to our projection, implementing the strategic scenarios outlined could significantly augment the lake's level and volume, potentially by 3.57×109-9.38×109 m3 over the coming 10 a and 3.57×109-10.70×109 m3 in the subsequent 15 a.

Key words： climate change      drought      lake ecological level      agricultural water demand      inter-basin water transfer     
Received: 28 January 2024      Published: 30 June 2024
Corresponding Authors: *Hossein BABAZADEH (E-mail: h_babazadeh@srbiau.ac.ir; h_babazadeh@hotmail.com)
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Seyed Morteza MOUSAVI
Hossein BABAZADEH
Mahdi SARAI-TABRIZI
Amir KHOSROJERDI
Cite this article:

Seyed Morteza MOUSAVI, Hossein BABAZADEH, Mahdi SARAI-TABRIZI, Amir KHOSROJERDI. Assessment of rehabilitation strategies for lakes affected by anthropogenic and climatic changes: A case study of the Urmia Lake, Iran. Journal of Arid Land, 2024, 16(6): 752-767.

URL:

http://jal.xjegi.com/10.1007/s40333-024-0019-x     OR     http://jal.xjegi.com/Y2024/V16/I6/752

Fig. 1 Geographical overview of the Urmia Lake basin and Zab River basin
Fig. 2 Water levels in the Urmia Lake during 2005-2022
Fig. 3 Flowchart illustrating the process of this study
Fig. 4 Schematic diagram of the modeling and simulating (MODSIM) model. IBWT, inter-basin water transfer.
Number Description of options
1 Conservation from currently operating dams+saving from other rivers+release from currently operating dams in non-cultivation months+treated wastewater transfer+annual river input ending in the lake amounting to 10.86×108 m3 in severe drought years.
2 Conservation from currently operating dams+saving from other rivers+release from currently operating dams in non-cultivation months+treated wastewater transfer+water transfer from the Zab River basin+annual river input ending in the lake amounting to 10.86×108 m3 in severe drought years.
3 Conservation from currently operating dams+saving from other rivers+release from currently operating dams in non-cultivation months+treated wastewater transfer+annual river input ending in the lake amounting to 14.60×108 m3 in moderate drought years.
4 Conservation from currently operating dams+saving from other rivers+release from currently operating dams in non-cultivation months+treated wastewater transfer+water transfer from the Zab River basin+annual river input ending in the lake amounting to 14.60×108 m3 in moderate drought years.
5 Conservation from currently operating dams+saving from other rivers+release from currently operating dams in non-cultivation months+treated wastewater transfer+annual river input ending in the lake amounting to 18.62×108 m3 in mild drought years.
6 Conservation from currently operating dams+saving from other rivers+release from currently operating dams in non-cultivation months+treated wastewater transfer+water transfer from the Zab River basin+annual river input ending in the lake amounting for 18.62×108 m3 in mild drought years.
7 Savings from stopping irrigated agricultural cultivation in the irrigation network of operating dams (4.52×108 m3 average irrigated cultivation consumption from dams over the last 8 a)+savings from stopping irrigated agriculture supplied by other rivers (8.28×108 m3 according to the third round of survey)+water release from dams in non-cultivation months (3.00×108 m3)+treated wastewater transfer (2.07×108 m3)+water transfer from the Zab River basin (6.00×108 m3)+annual river input ending in the lake (10.86×108 m3 in severe drought years).
8 Savings from stopping irrigated agricultural cultivation in the irrigation network of operating dams (4.52×108 m3 average irrigated cultivation consumption from dams over the last 8 a)+savings from stopping irrigated agriculture supplied by other rivers (8.28×108 m3 according to the third round of survey)+water release from dams in non-cultivation months (3.00×108 m3)+treated wastewater transfer (2.07×108 m3)+water transfer from the Zab River basin (6.00×108 m3)+annual river input ending in the lake (14.60×108 m3 in moderate drought years).
9 Savings from stopping irrigated agricultural cultivation in the irrigation network of operating dams (4.52×108 m3 average irrigated cultivation consumption from dams over the last 8 a)+savings from stopping irrigated agriculture supplied by other rivers (8.28×108 m3 according to the third round of survey)+water release from dams in non-cultivation months (3.00×108 m3)+treated wastewater transfer (2.07×108 m3)+water transfer from the Zab River basin (6.00×108 m3)+annual river input ending in the lake (18.62×108 m3 in mild drought years).
Table 1 Water conservation and management scenarios for the Urmia Lake
Fig. 5 Conceptual model illustrating the impact of reduced consumption and inter-basin water transfer with environmental goals to the Urmia Lake
Fig. 6 Comparative analysis of simulated and observed lake volumes using MODSIM model from 2014-2015 to 2020-2021 water year
Fig. 7 Impact on water levels of the Urmia Lake from implementing Scenarios 7, 8, and 9
Effectiveness on volume of lake water in 15 a period
(×109 m3)		 Equivalent water level of the Urmia Lake (m) Effectiveness on volume of lake water in 10 a period (×109 m3) Equivalent level of the Urmia Lake (m) Scenario number
3.57 1270.92 3.57 1270.92 1
5.00 1271.35 4.77 1271.27 2
4.80 1271.29 4.65 1271.24 3
8.00 1272.21 7.40 1272.03 4
6.75 1271.86 5.97 1271.63 5
10.70 1272.94 9.38 1272.59 6
9.50 1272.60 8.57 1272.40 7
12.85 1273.50 11.00 1273.00 8
16.45 1274.30 13.70 1273.70 9
Table 2 Effectiveness of scenarios in MODSIM model on enhancing volume of the Urmia Lake
Surface flow output from the Zab River basin (×109 m3) Year
17.48 Normal
42.93 Wet
7.69 Drought
Table 3 Surface water flow exiting Iran via the Zab River basin without inter-basin water transfer
Inter-basin water transfer from the Zab River basin to the Urmia Lake )×108 m3( Condition
6.00 Scenario of IBWT from the Kanisib+Silveh dams (short term)
5.28 Scenario of IBWT from the Kanisib+Silveh dams (long term)
7.43 Scenario of IBWT from the Kanisib+Silveh+Sardasht dams (long term)
8.34 Scenario of IBWT from the Kanisib+Silveh+Sardasht+Choman dams (long term)
Table 4 Volume of inter-basin water transfer from the Zab River basin to the Urmia Lake
Outflow from the Zab River basin Scenario
Percent (%) Drought year (×108 m3) Percent (%) Wet year
(×108 m3)		 Percent
(%)		 Normal year
)×108 m3)
-78.0 1.69 -14.0 36.93 -34.0 11.48 Scenario of IBWT from the Kanisib+Silveh dams (short term)
-69.0 2.41 -12.0 37.65 -30.0 12.20 Scenario of IBWT from the Kanisib+Silveh dams (long term)
-97.0 0.26 -17.0 35.50 -42.0 10.05 Scenario of IBWT from the Kanisib+Silveh+Sardasht dams (long term)
0.0 -0.65 -19.0 34.59 -48.0 9.14 Scenario of IBWT from Kanisib+Silveh+ Sardasht+Choman dams (long term)
Table 5 Outflow from the Zab River basin under various scenarios
Weighted value (%) Criteria Rank
47.9 Socio-economic impact 1
25.0 Climate 2
15.1 Consumption 3
12.1 Environment 4
Table 6 Prioritization of main criteria based on importance
Rank Weighted value (%) Option Number
3 15.5 Inter-basin water transfer 1
1 51.9 A 40.0% reduction in agricultural water consumption of dams and other surface water 2
4 6.5 Treated wastewater transfer 3
2 26.1 A 40.0% reduction in agricultural water consumption of groundwater 4
Table 7 Ranking of options based on weighted value
Fig. 8 Outcome of model sensitivity analysis
[1]   Abbaspour M, Nazaridoust A. 2007. Determination of environmental water requirements of Lake Urmia, Iran: An ecological approach. International Journal of Environmental Studies, 64(2): 161-169.
[2]   Behboodian M, Kerachian R. 2019. Sustainability assessment of basin-wide water supply and demand scenarios using Intelligent Decision System (IDS) Model. Iran-Water Resources Research, 15(4): 316-329.
[3]   Bui T D, Talebpour Asl D, Ghanavati E, et al. 2020. Effects of inter-basin water transfer on water flow condition of destination basin. Sustainability, 12(1): 338, doi: 10.3390/su12010338.
[4]   Cosgrove W J, Loucks D P. 2015. Water management: Current and future challenges and research directions. Water Resources Research, 51(6): 4823-4839.
[5]   Dehghanipour A H, Zahabiyoun B, Schoups G, et al. 2019. A WEAP-MODFLOW surface water-groundwater model for the irrigated Miyandoab plain, Urmia lake basin, Iran: Multi-objective calibration and quantification of historical drought impacts. Agricultural Water Management, 223: 105704, doi: 10.1016/j.agwat.2019.105704.
[6]   Dehghanipour A H, Schoups G, Zahabiyoun B, et al. 2020. Meeting agricultural and environmental water demand in endorheic irrigated river basins: A simulation-optimization approach applied to the Urmia Lake basin in Iran. Agricultural Water Management, 241: 106353, doi: 10.1016/j.agwat.2020.106353.
[7]   Dong J, Chen X, Li Y, et al. 2023. Inter-basin water transfer effectively compensates for regional unsustainable water use. Water Resources Research, 59(12): e2023WR035129, doi: 10.1029/2023WR035129.
[8]   Ejazi A R, Shariat M, Farshchi P. 2020. Recognition and ranking the causes of the outbreak crises in Uromieh Lake using Delphi technique. Journal of Environmental Sciences and Technology, 22(1): 101-108. (in Persian)
[9]   Faryadi M. 2023. Soil security under salt attack: Protection of the soil against the salinization caused by drying up of Lake Urmia. Soil Security, 13: 100113, doi: 10.1016/j.soisec.2023.100113.
[10]   Hosseini-Moghari S M, Araghinejad S, Tourian M J, et al. 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. Hydrology and Earth System Sciences, 24(4): 1939-1956.
[11]   Karimian Eghbal M, Hamzehpour N. 2014. Dust control strategies of Urmia Lake using comparative studies of Owens Lake in America. In: The 14th Iran Soil Science Congress-Soil Physics and the Relationship between Water, Soil and Plants. Rafsanjan: Valieasr University of Rafsanjan. (in Persian)
[12]   Khatami S, Berndtsson R. 2013. Urmia lake watershed restoration in Iran:Short- and long-term perspectives. In: The 6th International Perspective on Water Resources & the Environment Conference. Izmir: Environmental & Water Resources Institute, 1-8.
[13]   Koohani M, Behmanesh J, Verdinejad V, et al. 2023. Common water resources conflict analysis due to agriculture land development using game theory and GMCR+ (case study: Nazlouchay Basinin Urmia Lake watershed). Journal of Water and Soil, 37(4): 531-545. (in Persian)
[14]   Masoumi M, Safaee H, Alavi S R, et al. 2016. Optimal cropping pattern with emphasis on reduction in net irrigation requirement via multi objective decision-making models (case study:Miandoab study area). In: The 1st International Conference on Water, Environment and Sustainable Development. Ardabil: University of Mohaghegh Ardabili. (in Persian)
[15]   Micklin P, Aladin N, Plotnikov I. 2014. The Aral Sea:The Devastation and Partial Rehabilitation of a Great Lake. Heidelberg: Springer.
[16]   Mohsenizadeh E, Shourian M. 2018. Optimum water resources allocation planning at basin scale by integrating MODSIM and Cuckoo optimization algorithm. Water Resources Research, 13(4): 1-16. (in Persian)
[17]   Momeni M. 2022. New Topics in Operations Research. (2nd ed.). Tehran: University of Tehran. (in Persian)
[18]   Parsinejad M, Rosenberg D E, Ghale Y A G, et al. 2022. 40-years of Lake Urmia restoration research: Review, synthesis and next steps. Science of the Total Environment, 832: 155055, doi: 10.1016/j.scitotenv.2022.155055.
[19]   Rawshan A, Arez I, Arien H, et al. 2019. Long term historic changes in the flow of lesser Zab River, Iraq. Hydrology, 6: 22, doi: 10.3390/hydrology6010022.
[20]   Sheikha-BagemGhaleh S, Babazadeh H, Rezaie H, et al. 2023. The effect of climate change on surface and groundwater resources using WEAP-MODFLOW models. Applied Water Science, 13: 121, doi: 10.1007/s13201-023-01923-4.
[21]   Sima S, Rosenberg D E, Wurtsbaugh W A, et al. 2021. Managing Lake Urmia, Iran for diverse restoration objectives: Moving beyond a uniform target lake level. Journal of Hydrology: Regional Studies, 35: 100812, doi: 10.1016/j.ejrh.2021.100812.
[22]   Sobirova K M, Qutlimuratova D O, Qurbanbayeva M R. 2023. The Aral Sea: A catastrophic environmental crisis and restoration efforts. International Bulletin of Engineering and Technology, 3(7): 127-129.
[23]   Urmia Lake Rehabilitation Program. 2014. Report on Continuation of the Current Situation of the Lake Urmia. Tehran: Sharif University of Technology. (in Persian)
[24]   Wurtsbaugh W A, Sima S. 2022. Contrasting management and fates of two sister lakes: Great Salt Lake (USA) and Lake Urmia (Iran). Water, 14(19): 3005, doi: 10.3390/w14193005.
[25]   Yasi M. 2017. Management of rivers and dams in supplying and delivering water to Urmia Lake. Strategic Research Journal of Agricultural Sciences and Natural Resources, 2(1): 59-76. (in Persian)
[26]   Yuan R, Wang M, Wang S, et al. 2020. Water transfer imposes hydrochemical impacts on groundwater by altering the interaction of groundwater and surface water. Journal of Hydrology, 583: 124617, doi: 10.1016/j.jhydrol.2020.124617.
[27]   Zhou Y, Guo S, Hong X, et al. 2017. Systematic impact assessment on inter-basin water transfer projects of the Hanjiang River Basin in China. Journal of Hydrology, 553: 584-595.
[1] LI Chuanhua, ZHANG Liang, WANG Hongjie, PENG Lixiao, YIN Peng, MIAO Peidong. Influence of vapor pressure deficit on vegetation growth in China[J]. Journal of Arid Land, 2024, 16(6): 779-797.
[2] LU Haitian, ZHAO Ruifeng, ZHAO Liu, LIU Jiaxin, LYU Binyang, YANG Xinyue. Impact of climate change and human activities on the spatiotemporal dynamics of surface water area in Gansu Province, China[J]. Journal of Arid Land, 2024, 16(6): 798-815.
[3] CAO Wenyu, BAI Jianjun, YU Leshan. Grassland-type ecosystem stability in China differs under the influence of drought and wet events[J]. Journal of Arid Land, 2024, 16(5): 615-631.
[4] YANG Zhiwei, CHEN Rensheng, LIU Zhangwen, ZHAO Yanni, LIU Yiwen, WU Wentong. Spatiotemporal variability of rain-on-snow events in the arid region of Northwest China[J]. Journal of Arid Land, 2024, 16(4): 483-499.
[5] TANG Xiaoyan, FENG Yongjiu, LEI Zhenkun, CHEN Shurui, WANG Jiafeng, WANG Rong, TANG Panli, WANG Mian, JIN Yanmin, TONG Xiaohua. Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact[J]. Journal of Arid Land, 2024, 16(4): 580-601.
[6] ZHANG Mingyu, CAO Yu, ZHANG Zhengyong, ZHANG Xueying, LIU Lin, CHEN Hongjin, GAO Yu, YU Fengchen, LIU Xinyi. Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang, China[J]. Journal of Arid Land, 2024, 16(3): 373-395.
[7] WANG Baoliang, WANG Hongxiang, JIAO Xuyang, HUANG Lintong, CHEN Hao, GUO Wenxian. Runoff change in the Yellow River Basin of China from 1960 to 2020 and its driving factors[J]. Journal of Arid Land, 2024, 16(2): 168-194.
[8] LIU Xinyu, LI Xuemei, ZHANG Zhengrong, ZHAO Kaixin, LI Lanhai. A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains[J]. Journal of Arid Land, 2024, 16(2): 195-219.
[9] BAI Jizhou, LI Jing, RAN Hui, ZHOU Zixiang, DANG Hui, ZHANG Cheng, YU Yuyang. Influence of varied drought types on soil conservation service within the framework of climate change: insights from the Jinghe River Basin, China[J]. Journal of Arid Land, 2024, 16(2): 220-245.
[10] ZHAO Yaxuan, CAO Bo, SHA Linwei, CHENG Jinquan, ZHAO Xuanru, GUAN Weijin, PAN Baotian. Land use and cover change and influencing factor analysis in the Shiyang River Basin, China[J]. Journal of Arid Land, 2024, 16(2): 246-265.
[11] ZHAO Xuqin, LUO Min, MENG Fanhao, SA Chula, BAO Shanhu, BAO Yuhai. Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change[J]. Journal of Arid Land, 2024, 16(1): 46-70.
[12] Mitiku A WORKU, Gudina L FEYISA, Kassahun T BEKETIE, Emmanuel GARBOLINO. Projecting future precipitation change across the semi-arid Borana lowland, southern Ethiopia[J]. Journal of Arid Land, 2023, 15(9): 1023-1036.
[13] QIN Guoqiang, WU Bin, DONG Xinguang, DU Mingliang, WANG Bo. Evolution of groundwater recharge-discharge balance in the Turpan Basin of China during 1959-2021[J]. Journal of Arid Land, 2023, 15(9): 1037-1051.
[14] MA Jinpeng, PANG Danbo, HE Wenqiang, ZHANG Yaqi, WU Mengyao, LI Xuebin, CHEN Lin. Response of soil respiration to short-term changes in precipitation and nitrogen addition in a desert steppe[J]. Journal of Arid Land, 2023, 15(9): 1084-1106.
[15] ZHANG Hui, Giri R KATTEL, WANG Guojie, CHUAI Xiaowei, ZHANG Yuyang, MIAO Lijuan. Enhanced soil moisture improves vegetation growth in an arid grassland of Inner Mongolia Autonomous Region, China[J]. Journal of Arid Land, 2023, 15(7): 871-885.