بررسی تأثیر تغییر اقلیم بر روی دبی قنات‌ها (مطالعه موردی قنات‌های شهرستان بیرجند)

Abbas Novinpour, E., Sadeghi Aghdam, F., & Kaki, M. (2021). The effect of climate change on surface and groundwater resources in Rozeh Tea Plain. New Findings in Applied Geology, 15(29), 15-27. https://doi.org/10.22084/nfag.2020.21337.1414

Adamowski, J., & Chan, H. F. (2011). A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1-4), 28-40. https://doi.org/10.1016/j.jhydrol.2011.06.013

Adhikary, S. K., Rahman, M., & Gupta, A. D. (2012). A stochastic modeling technique for predicting groundwater table fluctuations with time series analysis. International journal of applied science and engineering research, 1(2), 238-249. https://doi.org/10.6088/ijaser.0020101024.

Ahmed, M. (2020). Introduction to Modern Climate Change. Andrew E. Dessler: Cambridge University Press, 2011, 252 pp, ISBN-10: 0521173159. In: Elsevier. https://doi.org/10.1016/j.scitotenv.2020.139397

Amanambu, A. C., Obarein, O. A., Mossa, J., Li, L., Ayeni, S. S., Balogun, O., Oyebamiji, A., & Ochege, F. U. (2020). Groundwater system and climate change: Present status and future considerations. Journal of Hydrology, 589, 1251.63. https://doi.org/10.1016/j.jhydrol.2020.125163

Ansari, S., Massah Bavani, A., & Roozbahani, A. (2016). Effects of climate change on groundwater recharge (Case study: Sefid Dasht plain). Water and Soil, 30(2), 416-431. https://doi.org/10.22067/jsw.v30i2.39574

Chitsazan, M., Rahmani, G., & Neyamadpour, A. (2015). Forecasting groundwater level by artificial neural networks as an alternative approach to groundwater modeling. Journal of the Geological Society of India, 85, 98-106. https://doi.org/10.1007/s12594-015-0197-4

Coulibaly, P., Dibike, Y. B., & Anctil, F. (2005). Downscaling precipitation and temperature with temporal neural networks. Journal of Hydrometeorology, 6(4), 483-496. http://doi.org/10.1175/JHM409.1

Danshgar, H., Bagheri, M., & Mardani, M. (2021). Evaluation of the consequences of climate change and adaptation strategies in Bushkan Plain of Bushehr Province. Journal of Agricultural Economics and Development, 35(1), 63-78. https://doi.org/10.22067/jead.2021.17812.0

Hamzeh, S., Bagherpour, Z., Delghandi, M., & Kardan Moghaddam, H. (2018). Risk assessment of climate change impacts on groundwater level (Case study: Gotvand Aghili aquifer). Journal of Ecohydrology, 5(1), 111-122. https://doi.org/10.22059/ije.2017.235715.645

Hosseinikhah, M., Zeinivand, H., Haghizadeh, A., & Tahmasebipour, N. (2014). Validation of global climate models (GCMS) temperature and rainfall simulation in Kermanshah, Ravansar, and West Islamabad stations. Iranian Journal of Ecohydrology, 1(3), 195-206. https://doi.org/10.22059/ije.2014.54223

Izadi, A., DAVARI, K., ALIZADEH, A., Ghahraman, B., & HAGHAYEGHI, M. S. G. (2007). Water table forecasting using artificial neural networks. https://sid.ir/paper/131658/en

Kamal, A. R., & Masah, A. (2011). The uncertainty assessment of AOGCM & Hydrological models for estimating Gharesu basin temperature, precipitation, and runoff under climate change impact. Iranian Water Researches Journal, 5(2), 39-50.

Karamouz, M., Abolpour, A., & Nazif, S. (2011). Evaluation of the impact of climate change on groundwater resources of Rafsanjan. 4th Iranian conference of water resources management, Tehran, Amirkabir University, May 3rd and 4th.(In Persian), https://civilica.com/doc/116949/

Kurtulus, B., & Razack, M. (2010). Modeling daily discharge responses of a large karstic aquifer using soft computing methods: Artificial neural network and neuro-fuzzy. Journal of Hydrology, 381(1-2), 101-111.. https://doi.org/10.1016/j.jhydrol.2009.11.029

Lemieux, J.-M., Hassaoui, J., Molson, J., Therrien, R., Therrien, P., Chouteau, M., & Ouellet, M. (2015). Simulating the impact of climate change on the groundwater resources of the Magdalen Islands, Québec, Canada. Journal of Hydrology: Regional Studies, 3, 400-423. https://doi.org/10.1016/j.ejrh.2015.02.011.

Mahmoodzadeh, D., Ketabchi, H., Ataie-Ashtiani, B., & Simmons, C. T. (2014). Conceptualization of a fresh groundwater lens influenced by climate change: A modeling study of an arid-region island in the Persian Gulf, Iran. Journal of Hydrology, 519, 399-413. https://doi.org/10.1016/j.jhydrol.2014.07.010

Mortezaii, G., Lotfi, J., Khalighi Sigarodi, S., Saravi, M., & Nazari Samini, A. (2020). Analysis and evaluation of hydrological drought indicators in Kurdistan Province. Watershed Engineering and Management, 12(2), 441-453. https://doi.org/10.22092/ijwmse.2019.123305.1566.

Muslimi, K., Imam Gholizadeh, S., & Karami, G. H. (2012). Comparison of ANN and ANFIS artificial intelligence systems in predicting groundwater levels in Bastam Plain, 5th National Conference on Watershed Management and Soil and Water Resources Management,  https://civilica.com/doc/143720

Najafi, s., Sharafati, A., & Kardan moghaddam, H. (2022). Evaluating the effect of climate change on groundwater level changes in the Sari-Neka coastal aquifer. Irrigation and Water Engineering, 13(2), 312-332. https://doi.org/10.22125/iwe.2022.162660

Nazari, H., Dehghani, M., Pirkharrati, H., Asadzadeh, F., & Hajizadeh, F. (2022). Monitoring of groundwater quality parameters using adaptive neural-fuzzy inference system (ANFIS) method(Case study: Ardabil plain). Journal of New Findings in Applied Geology, 16(31), 1-12. https://www.magiran.com/paper/2454855

Regional Water Company, S.K. (2024). Report on the State of Water Resources in South Khorasan Province. https://skhrw.ir/uploaded_files/DCMS/wysiwyg/files/Gozaresh

Sethi, R. R., Kumar, A., Sharma, S., & Verma, H. (2010). Prediction of water table depth in a hard rock basin by using an artificial neural network. International Journal of Water Resources and Environmental Engineering, 2(4), 95-102. https://www.researchgate.net/publication/266472104_Prediction_of_water_table_depth_in_a_hard_rock_basin_by_using_artificial_neural_network

Toure, A., Diekkrüger, B., & Mariko, A. (2016). Impact of climate change on groundwater resources in the Klela basin, southern Mali. Hydrology, 3(2), 17. https://doi.org/10.3390/hydrology3020017

Umamaheswari, G., & Kalamani, D. (2014). Fuzzy logic model for the prediction of groundwater level in Amaravathi River Minor Basin. International Journal of Mathematics Trends and Technology-IJMTT, 11. https://doi.org/10.14445/22315373/IJMTTV11P505

Vahedi, F., Nadiri, A., & AsghariMoghaddam, A. (2015). Evaluation of Artificial Neural Network and Fuzzy Logic Models Efficiency in Groundwater Level Prediction he 1st International Congress on Earth, Space and Clean Energy,  https://civilica.com/doc/456421

Wilby, R. (2004). Guidelines for the use of climate scenarios developed from statistical downscaling methods. Supporting material of the Intergovernmental Panel on Climate Change, available from the DDC of IPCC TGCIA, 27. https://doi.org/10.5281/ZENODO.1438319

Wilby, R. L., Dawson, C. W., & Barrow, E. M. (2002). SDSM—a decision support tool for the assessment of regional climate change impacts. Environmental Modelling & Software, 17(2), 145-157. https://doi.org/10.1016/S1364-8152(01)00060-3

Wilby, R. L., & Harris, I. (2006). A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK. Water resources research, 42(2). https://doi.org/10.1029/2005WR004065

Yang, C.-C., Prasher, S. O., Lacroix, R., Sreekanth, S., Patni, N. K., & Masse, L. (1997). Artificial neural network model for subsurface-drained farmlands. Journal of Irrigation and Drainage Engineering, 123(4), 285-292. https://doi.org/10.1061/(ASCE)07339437(1997)123:4(285).

Zarghami, M., Abdi, A., Babaeian, I., Hassanzadeh, Y., & Kanani, R. (2011). Impacts of climate change on runoffs in East Azerbaijan, Iran. Global and Planetary Change, 78(3-4), 137-146. https://doi.org/10.1016/j.gloplacha.2011.06.003