Abstract
Climate change strongly influences the available water resources in a watershed due to direct linkage of atmospheric driving forces and changes in watershed hydrological processes. Understanding how these climatic changes affect watershed hydrology is essential for human society and environmental processes. Coupled Model Intercomparison Project phase 6 (CMIP6) dataset of three GCM’s (BCC-CSM2-MR, INM-CM5-0, and MPI-ESM1-2-HR) with resolution of 100 km has been analyzed to examine the projected changes in temperature and precipitation over the Astore catchment during 2020–2070. Bias correction method was used to reduce errors. In this study, statistical significance of trends was performed by using the Man- Kendall test. Sen’s estimator determined the magnitude of the trend on both seasonal and annual scales at Rama Rattu and Astore stations. MPI-ESM1-2-HR showed better results with coefficient of determination (COD) ranging from 0.70–0.74 for precipitation and 0.90–0.92 for maximum and minimum temperature at Astore, Rama, and Rattu followed by INM-CM5-0 and BCC-CSM2-MR. University of British Columbia Watershed model was used to attain the future hydrological series and to analyze the hydrological response of Astore River Basin to climate change. Results revealed that by the end of the 2070s, average annual precipitation is projected to increase up to 26.55% under the SSP1–2.6, 6.91% under SSP2–4.5, and decrease up to 21.62% under the SSP5–8.5. Precipitation also showed considerable variability during summer and winter. The projected temperature showed an increasing trend that may cause melting of glaciers. The projected increase in temperature ranges from - 0.66°C to 0.50°C, 0.9°C to 1.5°C and 1.18°C to 2°C under the scenarios of SSP1–2.6, SSP2–4.5 and SSP5–8.5, respectively. Simulated streamflows presented a slight increase by all scenarios. Maximum streamflow was generated under SSP5–8.5 followed by SSP2–4.5 and SSP1–2.6. The snowmelt and groundwater contributions to streamflow have decreased whereas rainfall and glacier melt components have increased on the other hand. The projected streamflows (2020–2070) compared to the control period (1990–2014) showed a reduction of 3%–11%, 2%–9%, and 1%–7% by SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. The results revealed detailed insights into the performance of three GCMs, which can serve as a blueprint for regional policymaking and be expanded upon to establish adaption measures.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Adnan M, Liu S, Saifullah M, et al (2022) Spatiotemporal variations in runoff and runoff components in response to climate change in a glacierized subbasin of the Upper Indus Basin, Pakistan. Front Earth Sci 10:1–20. https://doi.org/10.3389/feart.2022.970349
Adnan M, Nabi G, Kang S, et al (2017) Snowmelt runoff modelling under projected climate change patterns in the Gilgit river basin of northern Pakistan. Polish J Environ Stud 26(2):525–542. https://doi.org/10.15244/pjoes/66719
Afshan N, Khalid A, Iqbal S, et al (2009) Puccinia subepidermalis sp. nov. and new records of rust fungi from Fairy Meadows, Northern Pakistan. Mycotaxon 110: 173–182. https://doi.org/10.5248/110.173
Akhtar N, Ahmad N, Booij MJ (2008) The impact of climate change on the water resources of Hindukush-Karakorum-Himalaya region under different glacier coverage scenarios. J Hydrol 355(1–4): 148–163. https://doi.org/10.1016/j.jhydrol.2008.03.015
Alhaji UU, Yusuf AS, Edet CO, et al. (2018) Trend analysis of temperature in Gombe State using Mann Kendall trend test. J Sci Res Reports 20(3):1–9. https://doi.org/10.9734/jsrr/2018/42029
Ali AF, Xiao CD, Zhang XP, et al. (2018) Projection of future streamflow of the Hunza River Basin, Karakoram Range (Pakistan) using HBV hydrological model. J Mt Sci 15:2218–2235. https://doi.org/10.1007/s11629-018-4907-4
Almazroui M, Islam MN, Saeed F, et al. (2021) Projected changes in temperature and precipitation over the United States, Central America, and the Caribbean in CMIP6 GCMs. Earth Syst Environ 5:1–24. https://doi.org/10.1007/s41748-021-00199-5
Arfan M, Lund J, Hassan D, et al. (2019) Assessment of spatial and temporal flow variability of the Indus River. Resources 8(2): 103. https://doi.org/10.3390/resources80201031
Atif I, Iqbal J, Su LJ (2019) Modeling hydrological response to climate change in a data-scarce glacierized high mountain Astore basin using a fully distributed TOPKAPI model. Climate 7(11): 127. https://doi.org/10.3390/cli7110127
Ayub S, Akhter G, Ashraf A, Iqbal M (2020) Snow and glacier melt runoff simulation under variable altitudes and climate scenarios in Gilgit River Basin, Karakoram region. Model Earth Syst Environ 6:1607–1618. https://doi.org/10.1007/s40808-020-00777-y
Baig S, Sayama T, Takara K (2021) Hydrological modeling of the astore river basin, pakistan, by integrating snow and glacier melt processes and climate scenarios. J Disaster Res 16(8):1197–1206. https://doi.org/10.20965/jdr.2021.p1197
Beckers J, Smerdon B, Wilson M (2009) Review of hydrologic models for forest management and climate change applications in British Columbia and Alberta. FORREX - Forum for Research and Extension in Natural Resources, Kamloops, Canada. 13(1):35–44.
Berg P, Feldmann H, Panitz HJ (2012) Bias correction of high resolution regional climate model data. J Hydrol 448–449:80–92. https://doi.org/10.1016/j.jhydrol.2012.04.026
Bontemps S, Defourny P, Bogaert E Van, et al. (2011) GLOBCOVER 2009 Products Description and Validation Report. ESA Bull 136:53.
Chiew FHS, Kirono DGC, Kent DM, et al. (2010) Comparison of runoff modelled using rainfall from different downscaling methods for historical and future climates. J Hydrol 387(1–2):10–23. https://doi.org/10.1016/j.jhydrol.2010.03.025
Chisanga C, Phiri E, Chinene V (2017) Statistical bias correction of Fifth Coupled Model Intercomparison Project data from the CGIAR Research Program on climate change, Agriculture and Food Security - Climate Portal for Mount Makulu, Zambia. Br J Appl Sci Technol 21(4):1–16. https://doi.org/10.9734/bjast/2017/33531
Cook BI, Mankin JS, Marvel K, et al. (2020) Twenty-first century drought projections in the CMIP6 forcing scenarios. Earth’s Futur 8(6). https://doi.org/10.1029/2019EF001461
Eyring V, Bony S, Meehl GA, et al. (2016) Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9(5):1937–1958. https://doi.org/10.5194/gmd-9-1937-2016
Fang G, Yang J, Chen Y, et al. (2015) Climate change impact on the hydrology of a typical watershed in the Tianshan Mountains. Adv Meteorol 2015: 1–10. https://doi.org/10.1155/2015/960471
Farhan SB, Zhang Y, Ma Y, et al. (2015) Hydrological regimes under the conjunction of westerly and monsoon climates: a case investigation in the Astore Basin, Northwestern Himalaya. Clim Dyn 44:3015–3032. https://doi.org/10.1007/s00382-014-2409-9
Garee K, Chen X, Bao A, et al. (2017) Hydrological modeling of the upper indus basin: A case study from a high-altitude glacierized catchment Hunza. Water (Switzerland) 9(1):1–20. https://doi.org/10.3390/w9010017
Gocic M, Trajkovic S (2013) Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia. Glob Planet Change 100:172–182. https://doi.org/10.1016/j.gloplacha.2012.10.014
Hassan J, Kayastha RB, Shrestha A, et al. (2017) Predictions of future hydrological conditions and contribution of snow and ice melt in total discharge of Shigar River Basin in Central Karakoram, Pakistan. Sci Cold Arid Reg 9(6):511–524. https://doi.org/10.3724/SP.J.1226.2017.00511
Hayat H, Akbar TA, Tahir AA, et al. (2019) Simulating current and future river-flows in the snowmelt-runoff model and RCP scenarios. Water 11(4): 1–19. https://doi.org/10.3390/w11040761
Ikram F, Afzaal M, Bukhari SAA, Ahmed B (2016) Past and future trends in frequency of heavy rainfall events over Pakistan. Pakistan J Meteorol 12(24):57–78.
Immerzeel WW, van Beek LPH, Konz M, et al. (2012) Hydrological response to climate change in a glacierized catchment in the Himalayas. Clim Change 110:721–736. https://doi.org/10.1007/s10584-011-0143-4
IPCC (2021) Summary for Policymakers. In: Lee H, Calvin K, Dasgupta D, et al (eds.), Synthesis Report of the IPCC Sixth Assessment Report (AR6): The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. https://doi.org/10.3410/f.740620545.793587812
Iqbal M, Wen J, Masood M, et al. (2022) Impacts of climate and land-use changes on hydrological processes of the source region of Yellow River, China. Sustainability 14 (22). https://doi.org/10.3390/su142214908
Iqbal M, Wen J, Wang X, et al. (2018) Assessment of air temperature trends in the source region of Yellow River and its sub-basins, China. Asia-Pacific J Atmos Sci 54:111–123. https://doi.org/10.1007/s13143-017-0064-x
Kendall MG (1975) Rank correlation methods, Griffin Press, London, UK, 4th edition.
Khan AJ, Koch M (2021) Generation of a long-term daily gridded precipitation dataset for the Upper Indus Basin (UIB) through temporal Reconstruction, Correction & Informed Regionalization-“ReCIR”. Int Soil Water Conserv Res 9(3): 445–460. https://doi.org/10.1016/j.iswcr.2021.01.005
Khan SA, Ashiq M, Gabriel HF (2014) Assessment of flows in a glaciated region-Shigar River Basin, Pakistan. Tech Journal, Univ Eng Technol Taxila 19(1):38–50.
Kim YH, Min SK, Zhang X, et al. (2020) Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Weather Clim Extrem 29. https://doi.org/10.1016/j.wace.2020.100269
Kreienkamp F, Lorenz P, Geiger T (2020) Statistically downscaled CMIP6 projections show stronger warming for Germany. Atmosphere (Basel) 11(11): 1–19. https://doi.org/10.3390/atmos11111245
Latif Y, Yaoming M, Yaseen M (2018) Spatial analysis of precipitation time series over the Upper Indus Basin. Theor Appl Climatol 131:761–775. https://doi.org/10.1007/s00704-016-2007-3
Loukas A, Vasiliades L (2014) Streamflow simulation methods for ungauged and poorly gauged watersheds. Nat Hazards Earth Syst Sci 14:1641–1661. https://doi.org/10.5194/nhess-14-1641-2014
Mann HB (1945) Nonparametric test against trend. Econometrica 13(3): 245–259. https://doi.org/10.2307/1907187
Marotzke J, Jakob C, Bony S, et al. (2017) Climate research must sharpen its view. Nature Clim Change 7:89–91. https://doi.org/10.1038/nclimate3206
Masood M, Shakir AS, Azhar AH, et al. (2020) Assessment of real time, multi-satellite precipitation products under diverse climatic and topographic conditions. Asia-Pacific J Atmos Sci 56:577–591. https://doi.org/10.1007/s13143-019-00166-1
Meinshausen M, Nicholls ZRJ, Lewis J, et al. (2020) The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500. Geosci Model Dev 13(8):3571–3605. https://doi.org/10.5194/gmd-13-3571-2020
Mishra V, Bhatia U, Tiwari AD (2020) Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6. Sci Data 7:1–13. https://doi.org/10.1038/s41597-020-00681-1
Moriasi DN, Arnold JG, Van Liew MW, et al. (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Am Soc Agric Biol Eng 50(3): 885–900. https://doi.org/10.13031/2013.23153
Moss R, Babiker M, Brinkman S, et al. (2008) Towards new scenarios for analysis of emissions, climate change, impacts, and response strategies: IPCC Expert Meeting report: 19–21 September, 2007, Noordwijkerhout, the Netherlands. Intergovernmental Panel on Climate Change https://doi.org/10.1017/cb09780511546013.004
Naeem UA, Hashmi HN, Shamim MA, et al. (2012) Flow variation in Astore River under assumed glaciated extents due to climate change. Pak J Engg & Appl Sci 11:73–81.
Naeem UA, Habib-ur-Rehman, Hashmi HN, et al. (2015) Ranking sensitive calibrating parameters of UBC Watershed Model. KSCE J Civ Eng 19:1538–1547. https://doi.org/10.1007/s12205-015-0515-9
O’Neill BC, Kriegler E, Riahi K, et al. (2014) A new scenario framework for climate change research: The concept of shared socioeconomic pathways. Clim Change 122:387–400. https://doi.org/10.1007/s10584-013-0905-2
Pokhrel I, Kalra A, Rahaman MM, et al. (2020) Forecasting of future flooding and risk assessment under CMIP6 climate projection in Neuse River, North Carolina. Forecasting 2(3):323–345. https://doi.org/10.3390/forecast2030018
Quick MC, Pipes A (1977) U.B.C. watershed model. Hydrol Sci Bull 22:153–161. https://doi.org/10.1080/02626667709491701
Quick MC, Pipes A (1976) A Combined snowmelt and rainfall runoff model. Can J Civ Eng 3(3):449–460. https://doi.org/10.1139/l76-045
Quick MC (1995) University of British Columbia Watershed Model Manual Version 4.0., Department of Civil Engineering, The University of British Columbia Vancouver Campus, B.C., Canada.
Salma S, Rehman S, Shah MA (2012) Rainfall trends in different climate zones of Pakistan. Pakistan J Meteorol 9(17):37–47.
Salmi T, Määttä A, Anttila P, et al. (2002) Detecting trends of annual values of atmospheric pollutants by the Mann-Kendall test and Sen’s slope estimates: The Excel template application MAKESENS. Publications on Air Quality No. 31, Report code FMI-AQ-31, Finnish Meteorological Institute, 35 pp.
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63(324):1379–1389. https://doi.org/10.1080/01621459.1968.10480934
Shadmani M, Marofi S, Roknian M (2012) Trend analysis in reference evapotranspiration using Mann-Kendall and Spearman’s Rho tests in arid regions of Iran. Water Resour Manag 26:211–224. https://doi.org/10.1007/s11269-011-9913-z
Shafeeque M, Luo Y (2021) A multi-perspective approach for selecting CMIP6 scenarios to project climate change impacts on glacio-hydrology with a case study in Upper Indus river basin. J Hydrol 599: 126466. https://doi.org/10.1016/j.jhydrol.2021.126466
Shakir AS, Habib-ur-Rehman, Ehsan S (2010) Climate change impact on river flows in Chitral Watershed. Pakistan J Eng Appl Sci 7:12–23.
Shifteh Some’e B, Ezani A, Tabari H (2012) Spatiotemporal trends and change point of precipitation in Iran. Atmos Res 113:1–12. https://doi.org/10.1016/j.atmosres.2012.04.016
Shrestha M, Acharya SC, Shrestha PK (2017) Bias correction of climate models for hydrological modelling - are simple methods still useful? Meteorol Appl 24(3):531–539. https://doi.org/10.1002/met.1655
Sleziak P, Výleta R, Hlavčová K, et al. (2021) A hydrological modeling approach for assessing the impacts of climate change on runoff regimes in Slovakia. Water (Switzerland) 13(23):1–21. https://doi.org/10.3390/w13233358
Syed Z, Ahmad S, Dahri ZH, et al. (2022) Hydroclimatology of the Chitral River in the Indus Basin under changing climate. Atmosphere 13(2): 1–20. https://doi.org/10.3390/atmos13020295
Tahir AA, Adamowski JF, Chevallier P, et al. (2016) Comparative assessment of spatiotemporal snow cover changes and hydrological behavior of the Gilgit, Astore and Hunza River basins (Hindukush-Karakoram-Himalaya region, Pakistan). Meteorol Atmos Phys 128:793–811. https://doi.org/10.1007/s00703-016-0440-6
Tahir AA, Chevallier P, Arnaud Y, et al. (2011) Snow cover dynamics and hydrological regime of the Hunza River basin, Karakoram Range, Northern Pakistan. Hydrol Earth Syst Sci 15(7):2275–2290. https://doi.org/10.5194/hess-15-2275-2011
Usta DFB, Teymouri M, Chatterjee U (2022a) Assessment of temperature changes over Iran during the twenty-first century using CMIP6 models under SSP1–26, SSP2–4.5, and SSP5–8.5 scenarios. Arab J Geosci 15:416. https://doi.org/10.1007/s12517-022-09709-9
Usta DFB, Teymouri M, Chatterjee U, et al. (2022b) Projections of atmospheric changes over Iran in 2014–2050 using the CMIP6-HighResMIP experiment. Arab J Geosci 15:1–18. https://doi.org/10.1007/s12517-022-10639-9
Usta DFB, Teymouri M, Chatterjee U, et al. (2022c) Temperature projections over Iran during the twenty-first century using CMIP5 models. Model Earth Syst Environ 8:749–760. https://doi.org/10.1007/s40808-021-01115-6
Wang S, Ding Y, Iqbal M (2017) Defining runoff indices and analyzing their relationships with associated precipitation and temperature indices for Upper River basins in the Northwest Arid region of China. Water (Switzerland) 9(8). https://doi.org/10.3390/w9080618
Waseem M, Ajmal M, Ahmad I, et al. (2021) Projected drought pattern under climate change scenario using multivariate analysis. Arab J Geosci 14(544):1–13. https://doi.org/10.1007/s12517-021-06860-7
Zhang Y, You Q, Chen C, et al. (2016) Impacts of climate change on streamflows under RCP scenarios: A case study in Xin River Basin, China. Atmos Res 178–179:521–534. https://doi.org/10.1016/j.atmosres.2016.04.018
Zhang L, Karnauskas KB, Donnelly JP, et al. (2017) Response of the North Pacific tropical cyclone climatology to global warming: Application of dynamical downscaling to CMIP5 models. J Clim 30(4):1233–1243. https://doi.org/10.1175/JCLI-D-16-0496.1
Acknowledgement
The authors are grateful to the Centre of Excellence in Water Resource Engineering, UET, Lahore and College of Engineering, IT and Environment, Charles Darwin University, Australia for support in conducting this study. The authors are also thankful to Pakistan Meteorological Department (PMD) and Water and Power Development Authority (WAPDA), Pakistan to provide the observed meteorological and hydrological data used in the study.
Funding
Funding note: Open Access funding enabled and organized by CAUL and its Member Institutions
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Zeshan Ali, Mudassar Iqbal and Ihsan Ullah Khan. The first draft of the manuscript was written by Zeshan Ali and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Data Availability: The spatial data used in this study including elevation, land use and glaciers data is freely available and can be accessed from the websites given in data section of the manuscript. The climatic parameters and streamflow data is the property of Pakistan Meteorological Department (PMD) and Water and Power Development Authority (WAPDA), Pakistan, respectively and can be requested to these departments via official channels.
Conflict of Interest: The authors declare no conflicts of interest.
Rights and permissions
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Ali, Z., Iqbal, M., Khan, I.U. et al. Hydrological response under CMIP6 climate projection in Astore River Basin, Pakistan. J. Mt. Sci. 20, 2263–2281 (2023). https://doi.org/10.1007/s11629-022-7872-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11629-022-7872-x