Prediction and Analysis of the Probability of Climate Change and Water Scarcity in Yazd

مهندسی عمران فردوسی

Article 2, Volume 38, Issue 1 - Serial Number 49, April 2025, Pages 29-48   

Document Type: Original Article

DOI: 10.22067/jfcei.2024.88585.1306

Authors

mohammadreza Goodarzi^* ; Maryam Sabaghzadeh

Department of Civil Engineering, Water Resources Management Engineering, Yazd University, Yazd, Iran.

Abstract

Yazd, a city historically challenged by a hot and dry climate, has long faced water scarcity issues. Regional managers have consistently sought various methods to secure the necessary water supply. This study examines the situation by defining a water scarcity index based on water supply and demand over the past 12 years and forecasting it for the next 20 years using the LSTM method. According to the results, water consumption is higher in the summer compared to other seasons. Consequently, the impact of climate change on water scarcity was investigated. Future temperature and precipitation were predicted using the HadGEM3-GC31-LL climate model under three scenarios: SSP126 (optimistic), SSP245 (moderate), and SSP585 (pessimistic). Subsequently, 81 different scenarios were developed considering variations in temperature, precipitation, and water scarcity, with the probability of each occurring calculated using conditional probability. The results indicate that despite the increase in annual forecasted precipitation by up to 77% in the optimistic scenario and over 90% in the other two scenarios, the likelihood of severe water scarcity in the future will be higher. Therefore, regional decision-makers must continually seek ways to reduce consumption and enhance water supply.

Keywords

climate change; Water Shortage Index; LSTM; Conditional probability

References

[1]   A. SalehiBaladehi, F. Arabali, and A. Salehi, "The concept and place of water in Iranian culture and Islamic religion and its crystallization in Mazni culture," Architecture, vol. 26, no. 6, pp. 26-35, 2023. (In Persian)

[2]    M. R. Goodarzi, B. Zahabiyoun, A. R. Massah Bavani, and A. R. Kamal, "Performance comparison of three hydrological models SWAT, IHACRES and SIMHYD for the runoff simulation of Gharesou basin," Water and Irrigation Management, vol. 2, no. 1, pp. 25-40, 2012. (In Persian) https://doi.org/10.22059/jwim.2012.25090

[3]    V. Sandeep, A. Khandekar, and M. Kumar, "Water supply, urbanization and climate change," Resilience, Response, and Risk in Water Systems: Shifting Management and Natural Forcings Paradigms, pp. 195-215, 2020. https://doi.org/10.1007/978-981-15-4668-6_11

[4]    M. R. Goodarzi, R. H. Mohtar, R. Piryaei, A. Fatehifar, and M. Niazkar, "Urban WEF Nexus: An Approach for the Use of Internal Resources under Climate Change," Hydrology, vol. 9, no. 10, p. 176, 2022. https://doi.org/10.3390/hydrology9100176

[5]    F. A. Padder and A. Bashir, "SCARCITY OF WATER IN THE TWENTY-FIRST CENTURY: PROBLEMS AND POTENTIAL REMEDIES," Medalion Journal: Medical Research, Nursing, Health and Midwife Participation, vol. 4, no. 1, pp. 1-5, 2023. https://doi.org/10.59733/medalion.v4i1.66

[6]    M. TalebiNia and H. Khosravi, "The Relation between Meteorological Drought and Groundwater Quality in Arid and Semi-arid Climate (Case Study: Isfahan Province)," The Journal of Irrigation and Water Engineering, vol. 11, no. 1, pp. 269-285, 2020. (In Persian) 10.22125/iwe.2020.114970

[7]    M. Goodarzi, M. Sabaghzadeh, and A. Rajabpour niknam, "The Relationship between Land Subsidence and Water Use in Yazd Plain Using Sentinel-1 Images," (in eng), Journal of Applied Research in Geographical Sciences, Research vol. 25, no. 76, pp. 0-0, 2025. http://dx.doi.org/10.61186/jgs.25.76.13

[8]    S. Sadeghi, S. Kazemikia, H. Kheirfam, and Z. Hazbavi, "Experiences and consequences of inter-basin water transfer in the world," Journal of Iran-Water Resources Research (IWRR), 2016. (In Persian)

[9]    A. R. Bagherieh, I. Loloei, and A. Bagherieh, "Numerical Modeling of Tunnels and Lifelines in Liquefiable Grounds Under Seismic Loading," Ferdowsi Civil Engineering, vol. 27, no. 2, pp. 127-144, 2016. https://doi.org/10.22067/civil.v27i2.33094

[10]  M. R. Mansouri Daneshvar, M. Ebrahimi, and H. Nejadsoleymani, "An overview of climate change in Iran: facts and statistics," Environmental Systems Research, vol. 8, no. 1, pp. 1-10, 2019. https://doi.org/10.1186/s40068-019-0135-3

[11]  M. Goodarzi, A. Fatehifar, and F. Avazpoor, "Bivariate Analysis of the Impact of Climate Change on Drought with SPEI Index and Coppola Functions (Case Study: Dugonbadan), Iran-Water Resources Research, vol. 15, no. 4, pp. 352-365, 2019. (In Persian) https://dor.isc.ac/dor/20.1001.1.17352347.1398.15.4.24.7

[12]  O. Bozorg-Haddad, B. Zolghadr-Asli, P. Sarzaeim, M. Aboutalebi, X. Chu, and H. A. Loáiciga, "Evaluation of water shortage crisis in the Middle East and possible remedies," Journal of Water Supply: Research and Technology—AQUA, vol. 69, no. 1, pp. 85-98, 2020. https://doi.org/10.2166/aqua.2019.049

[13]  M. BahmaniBohlooli, M. MousaviHaghighi, and S. Mousavi, "Investigation And Analysis Of Trend of Urban Green Space Water Consumption And Municipal Water Scarcity Using System Dynamics Approach (Case study: Zarghan city)," Iranian Journal of Agricultural Economics and Development Research, vol. 51, no. 3, pp. 551-564, 2020. (In Persian) https://doi.org/10.22059/ijaedr.2020.278023.668732

[14]  Q. V. Dau, K. Kuntiyawichai, and A. J. Adeloye, "Future changes in water availability due to climate change projections for Huong Basin, Vietnam," Environmental Processes, vol. 8, pp. 77-98, 2021. https://doi.org/10.1007/s40710-020-00475-y

[15]  H. Heidari, M. Arabi, T. Warziniack, and S. Sharvelle, "Effects of urban development patterns on municipal water shortage," Frontiers in Water, vol. 3, p. 694817, 2021. https://doi.org/10.3389/frwa.2021.694817

[16]  M. Tabesh, M. MollaRamezani, A. Shorzad, and N. RasiFaghih, "Long-Term Prediction of Domestic Water Demand Using Bayesian Belief Networks," Journal of Civil and Environmental Engineering, vol. 52.2, no. 107, pp. 47-56, 2022. (In Persian) https://doi.org/10.22034/jcee.2021.31917.1763

[17]  Z. GhafariMoghadam and A. SardarShahraki, "Prediction of monthly consumption of drinking water in the Sistan region under climate change impact," Journal of Natural Environmental Hazards (JNEH), vol. 12, no. 37, pp. 75-100, 2023. (In Persian) https://doi.org/10.22111/jneh.2023.42994.1912

[18]  S. Sadati, F. Rostami, and H. Fami, "Sustainable management of water resources in Yazd province: challenges and solutions," Journal of Agricultural Technology, 2010.

[19]  M. Goodarzi, M. Sabaghzadeh, and A. Rajabpour niknam, "The Relationship between Land Subsidence and Water Use in Yazd Plain Using Sentinel-1 Images," Journal of Applied Research in Geographical Sciences, Research vol. 25, no. 76, pp. 0-0, 2025. (In Persian) http://dx.doi.org/10.61186/jgs.25.76.13

[20]  A. Karimi, M. R. Nikoo, R. Karachian, and E. Shirangi, "Assessment of water transport projects impact on long term water supply in Zayandehrud basin by multi-period optimization analysis," Iranian Water Researches Journal, vol. 6, no. 2, pp. 153-163, 2012. (In Persian)

[21]  H. Mohammadi, K. Hakimi, and E. Ahmadi, "Feasibility of implementing inter-basin water transfer projects in Iran (case study: Beheshtabad-Central Plateau water transfer project)," Human Geography Research (Geographical Research, vol. 51, no. 4, 2020. (In Persian) https://doi.org/10.22059/jhgr.2018.248156.1007603

[22]  t. sharghi, k. Kalantari, A. Asadi, and m. jomehpour, "Simulating the Simultaneously effects of Climate Change and Policy of Water transfer from Agriculture to Industry on Horticultural Products (Case of Yazd Province)," Iranian Journal of Agricultural Economics and Development Research, vol. 47, no. 4, pp. 851-863, 2016.  (In Persian) https://doi.org/10.22059/ijaedr.2016.61332

[23]  m. akaberi, M. Fatemi, and S. Dehghan Khavari, "Projection of Water Supply and Demand in Yazd Province Using the General Regional Equilibrium Pattern," Geographical Researches, Original Research vol. 34, no. 3, pp. 403-412, 2019. http://dx.doi.org/10.29252/geores.34.3.403

[24]  Y. Yu, X. Si, C. Hu, and J. Zhang, "A review of recurrent neural networks: LSTM cells and network architectures," Neural Computation, vol. 31, no. 7, pp. 1235-1270, 2019. https://doi.org/10.1162/neco_a_01199

[25]  A. Graves and A. Graves, "Long short-term memory," Supervised Sequence Labelling with Recurrent Neural Networks,Vol. 385, pp. 37-45, 2012. https://doi.org/10.1007/978-3-642-24797-2_4

[26]  A. Farzad, H. Mashayekhi, and H. Hassanpour, "A comparative performance analysis of different activation functions in LSTM networks for classification," Neural Computing and Applications, vol. 31, pp. 2507-2521, 2019. https://doi.org/10.1007/s00521-017-3210-6

[27]  A. Gensler, J. Henze, B. Sick, and N. Raabe, "Deep Learning for solar power forecasting—An approach using AutoEncoder and LSTM Neural Networks," in 2016 IEEE international conference on Systems, Man, and Cybernetics (SMC), 2016, pp. 002858-002865. https://doi.org/10.1109/SMC.2016.7844673

[28]  Z. Chang, Y. Zhang, and W. Chen, "Electricity price prediction based on hybrid model of adam optimized LSTM neural network and wavelet transform," Energy, vol. 187, p. 115804, 2019. https://doi.org/10.1016/j.energy.2019.07.134

[29]  T. Cooijmans, N. Ballas, C. Laurent, Ç. Gülçehre, and A. Courville, "Recurrent batch normalization," arXiv preprint arXiv:1603.09025, 2016. https://doi.org/10.48550/arXiv.1603.09025

[30]  N. K. Manaswi and N. K. Manaswi, "Understanding and working with Keras," Deep Learning with Applications using Python: Chatbots and Face, Object, and Speech Recognition with TensorFlow and Keras, pp. 31-43, 2018. https://doi.org/10.1007/978-1-4842-3516-4_2

[31]  G. S. Jones et al., "The HadGEM3‐GC3. 1 contribution to the CMIP6 detection and attribution model intercomparison project," Journal of Advances in Modeling Earth Systems, vol. 16, no. 8, p. e2023MS004135, 2024. https://doi.org/10.1029/2023MS004135

[32]  C. J. Williams et al., "Simulation of the mid-Pliocene Warm Period using HadGEM3: experimental design and results from model–model and model–data comparison," Climate of the Past, vol. 17, no. 5, pp. 2139-2163, 2021. https://doi.org/10.5194/cp-17-2139-2021

[33]  M. B. Andrews et al., "Historical simulations with HadGEM3‐GC3. 1 for CMIP6," Journal of Advances in Modeling Earth Systems, vol. 12, no. 6, p. e2019MS001995, 2020. https://doi.org/10.1029/2019MS001995

[34]  M. Dix et al., "CSIRO-ARCCSS ACCESS-CM2 model output prepared for CMIP6 ScenarioMIP ssp126," 2019.

[35]  K. Haleem, A. U. Khan, J. Khan, A. A. Ghanim, and A. M. Al-Areeq, "Evaluating future streamflow patterns under SSP245 scenarios: insights from CMIP6," Sustainability, vol. 15, no. 22, p. 16117, 2023. https://doi.org/10.3390/su152216117

[36]  N. M. Reddy and S. Saravanan, "Extreme precipitation indices over India using CMIP6: A special emphasis on the SSP585 scenario," Environmental Science and Pollution Research, vol. 30, no. 16, pp. 47119-47143, 2023. https://doi.org/10.1007/s11356-023-25649-7

[37]  J. Schmidli, C. Frei, and P. L. Vidale, "Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods," International Journal of Climatology: A Journal of the Royal Meteorological Society, vol. 26, no. 5, pp. 679-689, 2006.

[38]  A. Hájek, "Conditional probability," in Philosophy of statistics: Elsevier, 2011, pp. 99-135. https://doi.org/10.1016/B978-0-444-51862-0.50003-4

[39]  A. C. Horne et al., "Informing environmental water management decisions: Using conditional probability networks to address the information needs of planning and implementation cycles," Environmental Management, vol. 61, pp. 347-357, 2018. https://doi.org/10.1007/s00267-017-0874-8

[40]  Z. Hao, F. Hao, V. P. Singh, A. Y. Sun, and Y. Xia, "Probabilistic prediction of hydrologic drought using a conditional probability approach based on the meta-Gaussian model," Journal of Hydrology, vol. 542, pp. 772-780, 2016. https://doi.org/10.1016/j.jhydrol.2016.09.048

[41]  A. O. Anele, E. Todini, Y. Hamam, and A. M. Abu-Mahfouz, "Predictive uncertainty estimation in water demand forecasting using the model conditional processor," Water, vol. 10, no. 4, p. 475, 2018. https://doi.org/10.3390/w10040475

[42]  S. Yue, "A statistical measure of severity of El Niño events," Stochastic Environmental Research and Risk Assessment, vol. 15, pp. 153-172, 2001. https://doi.org/10.1007/PL00009789

[43]  R. Rodrigues Mendes Ribeiro, J. Natal, C. Polpo de Campos, and C. Dias Maciel, "Conditional probability table limit-based quantization for Bayesian networks: model quality, data fidelity and structure score," Applied Intelligence, pp. 1-21, 2024. https://doi.org/10.1007/s10489-023-05153-8

[44]  f. yosefvand, s. shabanlou, and a. rajabi, "Prediction of Sediment Transport in Sewer Using a Combination of Adaptive-Neuro Fuzzy Inference Systems and Genetic Algorithm," Ferdowsi Civil Engineering, vol. 32, no. 4, pp. 31-44, 2019. (In Persian) https://doi.org/10.22067/civil.v32i4.72720

[45]  B. Balouchi, M. R. Nikoo, M. Shafai Bajestan, and M. Dehghani, "Application of SVR and GRNN Models in Estimating Maximum Scour Depth at River Confluences under Live-Bed Condition," Ferdowsi Civil Engineering, vol. 29, no. 1, pp. 79-92, 2017. (In Persian) https://doi.org/10.22067/civil.v29i1.43654

[46]  M. R. Goodarzi, M. Sabaghzadeh, and M. Niazkar, "Evaluation of Snowmelt Impacts on Flood Flows Based on Remote Sensing Using SRM Model," Water, vol. 15, no. 9, p. 1650, 2023. https://doi.org/10.3390/w15091650

[47]  H. Fattahi, F. Malekmahmoudi, and H. Ghaedi, "Predicting the most important geomechanical parameter of rock mass using the harmony search and teaching learning based optimization algorithms," Ferdowsi Civil Engineering, vol. 35, no. 3, pp. 1-18, 2022. (In Persian) 10.22067/jfcei.2022.72095.1056

[48]  M. H. Yaqoubi, B. Keshtegar, and H. A. Rahdar, "Model-Based Analysis for Ultimate Axial Load of Circular CFST Columns Using Artificial Neural Network," Ferdowsi Civil Engineering, vol. 32, no. 3, pp. 33-48, 2019. (In Persian) https://doi.org/10.22067/civil.v32i3.73399