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Prediction of Meteorological and Hydrological Drought under Climate Change in the Minab Dam Watershed | ||
| پژوهش های آبخیزداری | ||
| Article 6, Volume 37, Issue 3 - Serial Number 144, September 2024, Pages 76-93 PDF (3.13 M) | ||
| Document Type: Research | ||
| DOI: 10.22092/wmrj.2023.364078.1554 | ||
| Authors | ||
| Fateme Pourhaghverdi1; Ommolbanin Bazrafshan* 2; Hamid Gholami2; Marzieh Shekari3; Hossein Zamani3 | ||
| 1Ph.D., Student, Department of Natural Resources Engineering and Statistics, Faculty of Agricultural and Natural Resources Engineering, University of Hormozgan, Bandar Abbas, Iran | ||
| 2Professor, Department of Natural Resources Engineering, Faculty of Agricultural and Natural Resources Engineering, University of Hormozgan, Bandar Abbas, Iran | ||
| 3Assistant Professor, Department of Mathematics and Statistics, Faculty of Science, University of Hormozgan, Bandar Abbas, Iran | ||
| Abstract | ||
| Introduction and Goal The phenomenon of climate change is the reason for the continued change of the climate pattern in the future in 2016, the Intergovernmental Panel on Climate Change, with the cooperation of various research centers around the world, has started compiling the sixth climate change assessment report CMIP(6). Due to the low spatial resolution of the output of GCM models, it is not appropriate to use them to evaluate the effect of climate change on a local scale. Consequently, it is necessary to scale the output of these models for regional studies using appropriate models or methods. One of the most important effects of climate change is the impact on rainfall and runoff in the watershed, which is effective on meteorological and hydrological droughts. One of the famous rainfall-runoff models that do not require a lot of input data is IHACRES. Researchers have welcomed its use in the last decade. The purpose of this research is to investigate the effects of climate change on meteorological and hydrological drought in the Minab Dam watershed. Materials and Methods In this study, climatic and hydrological data related to the region including daily precipitation, mean daily temperature and mean daily discharge were used to model and simulate the daily discharge of the Minab watershed during the statistical period of 1989 to 2018. From the Canadian model of the sixth report and three climate change scenarios SSP-1-2.5, SSP-3-7.5 and SSP-5-8.5, from the IHACRES model for predicting river flow for the future period from 2019 to 2040 and from the LARS-model WG was used for microscale precipitation and temperature. The Standardized Rainfall/Runoff Index (SPI/SRI) was used to study the drought. To analyze the drought trend and its characteristics, the Mann-Kendall test was utilized in both baseline and future periods. Results and Discussion Using the mentioned data, the runoff was calibrated using the IHACRES model. After the proper performance of the model in the calibration stage, the model was verified and predicted using three scenarios of the sixth report of runoff for a period in the future. Then, SPI, SRI, and drought characteristics (severity, duration, magnitude, and peak) were estimated for the past and future periods, and their changes compared to the future period. The results showed that the trend of precipitation changes in all three scenarios decreased in autumn and winter. Also, by using three scenarios, it was found that the most changes in the observation period were related to November. Also, regarding the flow of the river, its trend is decreasing due to the decrease of precipitation and these changes are mostly related to the autumn and winter seasons (up to 49% decrease), but its changes in the summer season have an increasing trend compared to the base period. In general, the trend of changes in precipitation and discharge in the entire period has an increasing slope. Investigating the effect of climate and meteorological drought in the study area showed that the hydrological and meteorological drought values have been increasing in the past, but in the future, in most scenarios, the drought trend is decreasing, which generally lacks a statistically significant trend. It is also clearly visible in the characteristics of drought. Conclusion and Suggestions Considering the regional changes of drought caused by global climate changes, considering different combinations of scenarios can be useful for early warning of drought as well as water resources management planning. In general, the conditions of drought management and forecasting in many parts of Iran, especially in arid and semi-arid regions, are currently far from the ideal situation. Therefore, it is necessary to be prepared to deal with it. Therefore, in severe droughts, the use of climate change models to predict future conditions can be very useful in evaluating the ability to provide water and the need for auxiliary water sources. | ||
| Keywords | ||
| Downscaled; Minab watershed; Precipitation-runoff model; Sixth climate report; Standardized precipitation/runoff index | ||
| References | ||
|
Aalami M, Agha Babaei b, Ahmadi M, Farzin S. 1393. Optimal allocation of water resource systems using dynamic system. Journal of Water Resources Engineering, 23(7):23-39. (In persian). https://civilica.com/doc/50565/. Abbaszadeh M, Bazrafshan O, Mahdavi R, Sardooi ER, Jamshidi S. 2023. Modeling future hydrological characteristics based on land Use/land cover and climate changes using the SWAT model. Water Resources Management, pp. 1-18. https://doi.org/10.1007/s11269-023-03545-6. Achite M, Bazrafshan O, Katipoğlu OM, Azhdari Z. 2023. Evaluation of hydro-meteorological drought indices for characterizing historical droughts in the Mediterranean climate of Algeria. Natural Hazards, pp. 1-27. Aghabeigi N, Ismali Auri A, Mostafazadeh R, and Golshan M. 2018. Climate changes on runoff with the IHACRES hydrological model in the watersheds of Ardabil province. Scientific Research Journal of Irrigation and Water Engineering in Iran. 10 (38): 163-176. (In Persian). https://doi.org/10.22125/IWE.2019.100750. Ayers J, Dodman D. 2010. Climate change adaptation and development I: The state of the debate. Progress in Development Studies 10(2): 161-168. https://doi.org/10.1177/146499340901000205. Azari M, Moradi H. R, Saghafian B, Faramarzi M. 2016. Climate change impacts on stream flow. https://doi.org/10.1080/02626667.2014.967695. Bahrami S, Bazrafshan O, esmaelpour Y. 2022. Efficiency of drought meteorological indices in hydrological and hydrogeological drought warning (Case study: The watershed of Esteghlal Dam -Minab). Extension and Development of Watershed Management, 10(36): 27-36. https://doi.org/20.1001.1.26454777.1401.10.36.4.8. Bazrafshan O, Zamani H, Mozaffari E, Azhdari, Shekari M. 2023. Trivariate risk analysis of meteorological drought in Iran under climate change scenarios. Meteorology and Atmospheric Physics, 135(6): 52-69. https://doi.org/10.1007/s00703-023-00988-9. Carcano EC, Bartolini P, Muselli M, Piroddi L. 2008. Jordan Recurrent Neural Network Versus IHACRES in modeling daily stream flows. Hydrology, 362(3): 291-307. https://doi.org/10.1016/j.jhydrol.2008.08.026. Cooper VA, Neguyen VTV, Nichol JA. 2007. Calibration of conceptual rainfall-runoff models using global optimization methods with hydrologic process-based parameter constraints. Journal of Hydrology. 334(3-4): 455-466. https://doi.org/10.1016/j.jhydrol.2006.10.036. Croke BFW, Jakeman AJ. 2008. Use of the IHACRES rainfall-runoff model in arid and semiarid regions. In: Weather HS. Sorooshian S. Sharma KD. (Eds.), Hydrological Modeling in Arid and Semi-arid Areas. Cambridge University Press, Cambridge. pp.41-48. Croke BFW, Jakeman AJ. 2005. Use of the IHACRES rainfall-runoff model in arid and semiarid regions, in: Hydrological Modelling in Arid and Semi-Arid Areas, edited by: Wheater, H., Sorooshian, S. and Sharma, K. D., Cambridge University Press, Cambridge, pp. 41–48. Jakeman A, J,Hornberger GM. 1993. How much complexity is warranted in a rainfall runoff model? Water Resources Research. 29(8): 2637-2649. https://doi.org/10.1029/93WR00877. Kendall M. 1975. Rank correlation methods. Charles Griffin, London. [Citation Time(s):1] Lloyd EH. 1970. Return periods in the presence of persistence. Journal of Hydrology, 10(3): 291-298. https://doi.org/10.1016/0022-1694(70)90256-8. Mann HB. 1945. Nonparametric tests against trend. Econometrical: Journal of the Econometric Society, pp. 245-259. https://doi.org/10.2307/1907187. McKee T, Doesken N, Kleist J. 1993. The relationship of drought frequency and duration to time scales. Proc Eighth Conference Appl Climatol, American Meteorological Society, Boston. pp. 179-184. Monahan WB, Theobald DM. 2018. Climate change adaptation benefits of potential conservation partnerships. PloS one 13(2): 1-23. https://doi.org/10.1371/journal.pone.0191468. Mozaffari E, Moradi N, Bazrafshan O. 2021. Spatio-temporal variability of characteristics of meteorological drought in Iran under climate change scenarios. Desert Management, 8(16):153-163. https://doi.org/10.22034/JDMAL.2021.243146. Mirdashtovan M, Malekian A, Mohseni Saravi, M. 2018. Stream flow simulation using statistical downscaling of climatic data: Urmia Lake Basin. Iranian journal of Ecohydrology, 5(2): 419-431. https://doi.org/ 10.22059/ije.2017.232662.586. Patil SD, Stieglitz M. 2015. Comparing spatial and temporal transferability of hydrological model parameters. Journal of Hydrology 525(2): 409-417. https://doi.org/10.1016/j.jhydrol.2015.04.003. Rahimi B, Hafezparastmovedat M.2020. Investigation of the IHACRES model in the prediction of runoff caused by climate models, the fifth report (Case study: Jamishan Dam). The First National Conference of Applied Reserches on Water and Power Industry Razi University, Kermanshah, pp. 30-31 December 2020. (In Persian). https://civilica.com/doc/1202087/. Rahnama S, Shahidi A,Yaqubzadeh M. 2021. Forecasting climate change based on temperature and creation based on the 6th report of the IPCC (Case study: Bandar Abbas International Station and the 2th National Conference on Modeling and Technologies). New in Water Management, Birjand, https://civilica.com/doc/1736910. Rasco P, Szeidl L, Semenov MA. 1991. A serial approach to local stochastic models. Journal of Ecological Modeling 57, 27-41. https://doi.org/10.1016/0304-3800(91)90053-4. https://doi:10.3354/cr010095. Sabzi Parvar AA, Shadmani M. 2013. Analysis of reference evaporation and transpiration using Mann-Kendall and Spearman tests in dry areas of Iran, Water and Soil Journal, 25(4): 824-823. (In Persian). https://doi.org/ 10.22067/JSW.V0I0.10242. Shukla S, Wood AW. 2008. Use of a standardized runoff index for characterizing hydrologic drought. Geophysical Research Letters, 35(2): 23-41. https://doi.org/10.1029/2007GL032487. Shukla S, Wood AW. 2008. Use of a standardized runoff index for characterizing hydrologic drought. Geophys. Res. Lett. 35, L02405. https://doi.org/10.1029/2007GL032487. Tebaldi C, Debeire KV. Eyring E, Fischer J, Fyfe P, Friedlingstein R, Knutti J, Lowe B, O'Neill B Sanderson , D. van Vuuren. 2021. Climate model projections from the scenario model intercomparison project (ScenarioMIP) of CMIP6. Earth System Dynamics, 12(1): 253-293. https://doi.org/10.5194/esd-12-253-2021. Zareie M, Qanbarpur M, Habibnejad Roshan M, Shahedi K. 2009. Simulation of river flow using IHACRES: A case study in Kasilian Basin, Journal of Iranian Engineering Sciences and Watershed Management Vol. 8, pp 10-20 (In Persian). http://jwmsei.ir/article-1-115-fa.html Zarin A, Dadashi Rudbari A. 2021. Prediction of consecutive dry and wet periods in Iran based on Hamdi output of 6CMIP bias corrected models. Earth and Space Physics, 47(3): 5-16 (In Persian). https://doi.org/ 10.22059/jesphys.2021.319270.1007295. | ||
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