• pISSN 2305-7068
  • eISSN 2097-7476
  • Indexed by ESCI CABI CAS
  • DOAJ EBSCO ProQuest Scopus GeoRef AJ CNKI
Advanced Search
Volume 14 Issue 2
Jun.  2026
Turn off MathJax
Article Contents
Shah NA, Shafique M, Iqbal B, et al. 2026. Hazard driven debris flow simulation and risk evaluation in the Karakorum Mountain ranges, Northern Pakistan. Journal of Groundwater Science and Engineering, 14(2): 252-270 doi:  10.26599/JGSE.2026.9280082
Citation: Shah NA, Shafique M, Iqbal B, et al. 2026. Hazard driven debris flow simulation and risk evaluation in the Karakorum Mountain ranges, Northern Pakistan. Journal of Groundwater Science and Engineering, 14(2): 252-270 doi:  10.26599/JGSE.2026.9280082

Hazard driven debris flow simulation and risk evaluation in the Karakorum Mountain ranges, Northern Pakistan

doi: 10.26599/JGSE.2026.9280082
More Information
  • Corresponding author: geologist.nisar07@gmail.com
  • Received Date: 2024-11-20
  • Accepted Date: 2026-01-13
  • Available Online: 2026-04-30
  • Publish Date: 2026-06-30
  • Northern Pakistan is highly susceptible to debris flows due to its complex geomorphic structure, steep topography, climate change, glaciation, monsoonal rainfall, active seismicity, deforestation, and human activities. Despite this, high-resolution, quantitative assessments of debris flow hazards are limited, constraining effective disaster risk management. This study aims to model a representative debris flow event in the Ghizer District to predict potential deposition areas and support emergency preparedness and sustainable land-use planning in this hazard-prone region. High-resolution Unmanned Aerial Vehicle (UAV)-derived topographic data were integrated with the Rapid Mass Movement Simulation (RAMMS-DF) model to simulate debris flow runout for three release scenarios, representing distinct and combined initiation zones. Satellite images and field validation were used to delineate release and erosion zones, while vulnerability and risk were assessed by mapping exposed elements including 210 buildings and a population of 1,500 and applying spatial multi-criteria analysis within a Geographic Information System (GIS) framework. The numerical simulation for the most critical event, Scenario 3 (representing simultaneous dual-source initiation), yielded the highest magnitude results with a total flow volume of 193,717 m3, a peak flow height of 12.96 m, and a maximum impact pressure of 992.28 kPa. Vulnerability mapping identified infrastructure and agricultural land as the most exposed. Risk assessment showed that the combined scenario posed the greatest threat to local assets and communities. The study demonstrates that debris flow dynamics in high-mountain environments are non-linearly sensitive to initial release volumes and the interaction between multiple flow sources. Topographic controls such as channel confinement and slope variations are the primary drivers of flow intensity and energy dissipation. This research establishes a replicable, data-driven framework for quantitative risk assessment in data-limited mountainous regions. The resulting high-resolution hazard and risk maps provide a scientific basis for defining land-use restrictions, prioritizing slope stabilization, and guiding the placement of emergency infrastructure to support disaster-resilient development in northern Pakistan.
  • 加载中
  • Abraham MT, Satyam N, Reddy SKP, et al. 2021. Runout modeling and calibration of friction parameters of Kurichermala debris flow, India. Landslides, 18: 737−754. DOI:  10.1007/s10346-020-01540-1.
    Ahmad N, Shafique M, Hussain ML, et al. 2025. Integrated debris flow hazard and risk assessment using UAV data and RAMMS, a case study in northern Pakistan. Natural Hazards, 121(2): 1463−1487. DOI:  10.1007/s11069-024-06862-0.
    Ahmad T, Jan MQ, Drüppel K. 2025. Geology of the central Kohistan Arc, Northern Swat, Kalam (NW, Pakistan), results of a new 1: 50, 000 scale geological mapping. Journal of Maps, 21(1): 2572765. DOI:  10.1080/17445647.2025.2572765.
    Ahmed M, Titti G, Trevisani S, et al. 2025. Is higher resolution always better? A comparison of open-access DEMs for optimized slope unit delineation and regional landslide prediction. Natural Hazards and Earth System Sciences, 25(7): 2519−2539. DOI:  10.5194/nhess-25-2519-2025.
    Alcántara-Ayala I, Sassa K. 2023. Landslide risk management: From hazard to disaster risk reduction. Landslides, 20(10): 2031−2037. DOI:  10.1007/s10346-023-02140-5.
    Ali S, Haider R, Abbas W, et al. 2021. Empirical assessment of rockfall and debris flow risk along the Karakoram Highway, Pakistan. Natural Hazards, 106: 2437−2460. DOI:  10.1007/s11069-021-04549-4.
    Bartelt P, Bühler Y, Christen M, et al. 2015. RAMMS-DF User Manual. WSL Institute for Snow and Avalanche Research SLF, Davos, Birmensdorf, Switzerland. Available on http://ramms.slf.ch/ramms/, last access, 28.
    Bezak N, Sodnik J, Mikoš M. 2019. Impact of a random sequence of debris flows on torrential fan formation. Geosciences, 9(2): 64. DOI:  10.3390/geosciences9020064.
    Cabral V, Reis F, Veloso V, et al. 2023. A multi-step hazard assessment for debris-flow prone areas influenced by hydroclimatic events. Engineering Geology, 313: 106961. DOI:  10.1016/j.enggeo.2022.106961.
    Cai S, Zhang Z, Yang X, et al. 2025. The modified theoretical model for debris flows predication with multiple rainfall characteristic parameters. Scientific Reports, 15(1): 12402. DOI:  10.1038/s41598-024-84199-1.
    Cao C, Xu P, Chen J, et al. 2017. Hazard assessment of debris-flow along the baicha river in Heshigten Banner, Inner Mongolia, China. International Journal of Environmental Research and Public Health, 14(1): 30. DOI:  10.3390/ijerph14010030.
    Chen M, Tang C, Xiong J, et al. 2024. Spatio-temporal mapping and long-term evolution of debris flow activity after a high magnitude earthquake. Catena, 236: 107716. DOI:  10.1016/j.catena.2023.107716.
    Chen TL, Wu YH, Chiu YH. 2025. Debris flow risk characteristics and potential spatial mitigation strategies under extreme rainfall events. Climate Services, 40: 100618. DOI:  10.1016/j.cliser.2025.100618.
    Christen M, Kowalski J, Bartelt P. 2010. RAMMS: Numerical simulation of dense snow avalanches in three-dimensional terrain. Cold Regions Science and Technology, 63(1): 1−14. DOI:  10.1016/j.coldregions.2010.04.005.
    Dash RK, Kanungo DP, Malet JP. 2021. Runout modelling and hazard assessment of Tangni debris flow in Garhwal Himalayas, India. Environmental Earth Sciences, 80: 1−19. DOI:  10.1007/s12665-021-09637-z.
    Eckert N, Corona C, Giacona F, et al. 2024. Climate change impacts on snow avalanche activity and related risks. Nature Reviews Earth and Environment, 5(5): 369−389. DOI:  10.1038/s43017-024-00540-2.
    Fan J, Galoie M. 2025. Assessment of physical parameters impacts on debris flow modeling with RAMMS. Scientific Reports, 15(1): 36393. DOI:  10.1038/s41598-025-20303-3.
    Gan J, Zhang YS. 2019. Numerical simulation of debris flow runout using Ramms: A case study of Luzhuang Gully in China. Computer Modeling in Engineering and Sciences, 981−1009. DOI:  10.32604/cmes.2019.07337.
    Gardezi H, Bilal M, Cheng Q, et al. 2021. A comparative analysis of attabad landslide on january 4, 2010, using two numerical models. Natural Hazards, 107: 519−538. DOI:  10.1007/s11069-021-04593-0.
    Gu Z, Yao X, Zhu X. 2025. Debris flow susceptibility in the Jinsha River Basin, China: a Bayesian assessment framework based on geomorphodynamic parameters. Natural Hazards and Earth System Sciences, 25(10): 3957−3975. DOI:  10.5194/nhess-25-3957-2025.
    Holub M, Suda J, Fuchs S. 2012. Mountain hazards: reducing vulnerability by adapted building design. Environmental Earth Sciences, 66: 1853−1870. DOI:  10.1007/s12665-011-1410-4.
    Hou S, Cao P, Li A, et al. 2021. In Debris flow hazard assessment of the Eryang River watershed based on numerical simulation. IOP Conference Series: Earth and Environmental Science. IOP Publishing: 062002. DOI:  10.1088/1755-1315/861/6/062002.
    Hussin H, Quan Luna B, Van Westen C, et al. 2012. Parameterization of a numerical 2-D debris flow model with entrainment: A case study of the Faucon catchment, Southern French Alps. Natural Hazards and Earth System Sciences, 12(10): 3075−3090. DOI:  10.5194/nhess-12-3075-2012.
    Islam MA, Chattoraj SL. 2023. Modelling landslides in the Lesser Himalaya region using geospatial and numerical simulation techniques. Arabian Journal of Geosciences, 16(8): 480. DOI:  10.1007/s12517-023-11541-8.
    Khan MA, Haneef M, Khan AS, et al. 2013. Debris-flow hazards on tributary junction fans, Chitral, Hindu Kush Range, northern Pakistan. Journal of Asian Earth Sciences, 62: 720−733. DOI:  10.1016/j.jseaes.2012.11.025.
    Khan MA, Mustaffa Z, Harahap ISH, et al. 2022. Assessment of physical vulnerability and uncertainties for debris flow hazard: A review concerning climate change. Land, 11(12): 2240. DOI:  10.3390/land11122240.
    Khan MU, Tian S, Chen N, et al. 2025. Understanding the formation mechanism of rainfall and snowmelt jointly induced Bicharh Nallah debris flow, North Pakistan. Environmental Earth Sciences, 84(3): 86. DOI:  10.1007/s12665-024-12054-7.
    Knight J. 2022. Scientists' warning of the impacts of climate change on mountains. PeerJ, 10: e14253. DOI:  10.7717/peerj.14253.
    Krishnapriya V, Rajaneesh A, Sajinkumar K, et al. 2024. A rapid run-out assessment methodology for the 2024 Wayanad debris flow. Npj Natural Hazards, 1(1): 41. DOI:  10.1038/s44304-024-00044-5.
    Li L, Lin H, Qiang Y, et al. 2024. A combination weighting method for debris flow risk assessment based on t-distribution and linear programming optimization algorithm. Plos one, 19(6): e0303698. DOI:  10.1371/journal.pone.0303698.
    Li Y, Zou Q, Hao J, et al. 2023. Risk assessment of debris flows along the Karakoram Highway (Kashgar-Khunjerab Section) in the context of climate change. International Journal of Disaster Risk Science, 14(4): 586−599. DOI:  10.1007/s13753-023-00501-1.
    Martini M, Baggio T, D'Agostino V. 2023. Comparison of two 2-D numerical models for snow avalanche simulation. Science of The Total Environment, 896: 165221. DOI:  10.1016/j.scitotenv.2023.165221.
    Melo R, van Asch T, Zêzere JL. 2018. Debris flow run-out simulation and analysis using a dynamic model. Natural Hazards and Earth System Sciences, 18(2): 555−570. DOI:  10.5194/nhess-18-555-2018.
    Mikoš M, Bezak N. 2021. Debris flow modelling using RAMMS model in the Alpine environment with focus on the model parameters and main characteristics. Frontiers in Earth Science, 8: 605061. DOI:  10.3389/feart.2020.605061.
    Ouyang C, Wang Z, An H, et al. 2019. An example of a hazard and risk assessment for debris flows—A case study of Niwan Gully, Wudu, China. Engineering Geology, 263: 105351. DOI:  10.1016/j.enggeo.2019.105351.
    Qiao Z, Li T, Simoni A, et al. 2023. Numerical modelling of an alpine debris flow by considering bed entrainment. Frontiers in Earth Science, 10: 1059525. DOI:  10.3389/feart.2022.1059525.
    Qing F, Zhao Y, Meng X, et al. 2020. Application of machine learning to debris flow susceptibility mapping along the China–Pakistan Karakoram Highway. Remote Sensing, 12(18): 2933. DOI:  10.3390/rs12182933.
    Qodri MF, Noviardi N, Mase LZ. 2021. Numerical modelling based on Digital Elevation Model (DEM) analysis of debris flow at Rinjani Volcano, West Nusa Tenggara, Indonesia. Journal of the Civil Engineering Forum, 7(3): 279−288. Petra Christian University. DOI:  10.22146/jcef.63417.
    Rajaneesh A, Krishnapriya V, Sajinkumar K, et al. 2025. Predicting debris flow pathways using volume-based thresholds for effective risk assessment. Npj Natural Hazards, 2(1): 1. DOI:  10.1038/s44304-024-00055-2.
    Rybchenko AA, Kadetova AV, Kozireva EA. 2018. Relation between basin morphometric features and dynamic characteristics of debris flows – a case study in Siberia, Russia. Journal of Mountain Science, 15(3): 618−630. DOI:  10.1007/s11629-017-4547-0.
    Saaty TL. 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1): 83−98. DOI:  10.1504/ijssci.2008.017590.
    Salm B. 1993. Flow, flow transition and runout distances of flowing avalanches. Annals of Glaciology, 18: 221−226. DOI:  10.3189/s0260305500011551.
    Sattar A, Haritashya UK, Kargel JS, et al. 2022. Transition of a small Himalayan glacier lake outburst flood to a giant transborder flood and debris flow. Scientific Reports, 12(1): 12421. DOI:  10.1038/s41598-022-16337-6.
    Scheuner T, Schwab S, McArdell B. 2011. Application of a two-dimensional numerical model in risk and hazard assessment in Switzerland. Italian Journal of Engineering Geology and Environment, 993−1001. DOI:  10.4408/IJEGE.2011-03.B-108.
    Searle MP. 2011. Geological evolution of the Karakoram Ranges. Italian Journal of Geosciences, 130(2): 147−159. DOI:  10.3301/ijg.2011.08.
    Shafique M, van der Meijde M, Khan MA. 2016. A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective. Journal of Asian Earth Sciences, 118: 68−80. DOI:  10.1016/j.jseaes.2016.01.002.
    Shah NA, Shafique M, Ishfaq M, et al. 2023. Integrated approach for landslide risk assessment using geoinformation tools and field data in Hindukush Mountain Ranges, Northern Pakistan. Sustainability, 15(4): 3102. DOI:  10.3390/su15043102.
    Shah NA, Shafique M, Owen LA, et al. 2025. Morphometric analysis of debris flow hazard and risk assessment in the mountain terrains of northern Pakistan using remote sensing and field data. Earth Science Informatics, 18(3): 295. DOI:  10.1007/s12145-025-01807-y.
    Shahzad L, Ali M, Sharif F, et al. 2024. Managing disasters in mountains: Challenges in the Era of Global Warming. Warming Mountains: Implications for Livelihood and Sustainability. Springer: 213−233. DOI:  10.1007/978-3-031-62197-0_11.
    Simoni A, Mammoliti M, Graf C. 2012. Performance Of 2D debris flow simulation model RAMMS. Annual International Conference on Geological and Earth Sciences GEOS. DOI:  10.5176/2251-3361_geos12.59.
    Tang C, Liu XL, Zhu J. 1993. The evaluation and application of risk degree for debris flow inundation on alluvial fans. Journal of Natural Disasters, 2(4): 79−84.
    Tang Y, Guo Z, Wu L, et al. 2022. Assessing debris flow risk at a catchment scale for an economic decision based on the LiDAR DEM and numerical simulation. Frontiers in Earth Science, 10: 821735. DOI:  10.3389/feart.2022.821735.
    Turbessi L, Taboni B, Umili G, et al. 2025. Modeling debris flow events in the Rio Inferno Watershed (Italy) through UAV-based geomorphological survey and rainfall data analysis. Sensors, 25(7): 1980. DOI:  10.3390/s25071980.
    Ullah I, Shafique M, Khattak GA, et al. 2024. Debris flow simulations for hazard, vulnerability and risk assessment in the Karakorum mountain ranges, northern Pakistan. Remote Sensing Applications: Society and Environment, 36: 101389. DOI:  10.1016/j.rsase.2024.101389.
    Utley I, Hales T, Hussain E, et al. 2025. Transformations in exposure to debris flows in post-earthquake Sichuan, China. Natural Hazards and Earth System Sciences, 25(8): 2699−2716. DOI:  10.5194/nhess-25-2699-2025.
    Xiao H, Tang X, Zhang H. 2020. Risk assessment of debris flow in longchi area of dujiangyan based on GIS and AHP. IOP Conference Series: Earth and Environmental Science, IOP Publishing, 474(4): 042010. DOI:  10.1088/1755-1315/474/4/042010.
    Xiao Q, Wang S, He N, et al. 2024. Risk zoning method of potential sudden debris flow based on deep neural network. Water, 16(4): 518. DOI:  10.3390/w16040518.
    Yamanoshita M. 2019. IPCC special report on climate change and land: JSTOR.
    Zhou W, Qiu H, Wang L, et al. 2022. Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction. Catena, 213: 106199. DOI:  10.1016/j.catena.2022.106199.
    Zhou Y, Yue D, Liang G, et al. 2022. Risk assessment of debris flow in a mountain-basin area, western China. Remote Sensing, 14(12): 2942. DOI:  10.3390/rs14122942.
    Zou Q, Cui P, Chao Z, et al. 2016. Dynamic process-based risk assessment of debris flow on a local scale. Physical Geography, 37: 132−152. DOI:  10.1080/02723646.2016.1169477.
  • 2305-7068/© Journal of Groundwater Science and Engineering Editorial Office. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0)

  • Relative Articles

    [1] Jian-feng Li, Yuan-jing Zhang, Ya-ci Liu, Qi-chen Hao, Chun-lei Liu, Sheng-wei Cao, Zheng-hong Li, 2026: Application of the DITAPH model coupling human activities and groundwater dynamics for nitrate vulnerability assessment: A case study in Quanzhou, China, Journal of Groundwater Science and Engineering, 14, 32-48.  doi: 10.26599/JGSE.2026.9280069
    [2] Mounir Atoui, Belgacem Agoubi, 2026: Vulnerability assessment in fractured aquifer using improved vulnerability index: Applied to Gabes aquifer, Southeastern Tunisia, Journal of Groundwater Science and Engineering, 14, 69-82.  doi: 10.26599/JGSE.2026.9280073
    [3] Hayder H. Kareem, Shahla Abdulqader Nassrullah, 2025: Impact of climate changes on Arizona State precipitation patterns using high-resolution climatic gridded datasets, Journal of Groundwater Science and Engineering, 13, 34-46.  doi: 10.26599/JGSE.2025.9280037
    [4] Jing-tao Shi, Ge Gao, Jun-jian Liu, Yu-ge Jiang, Bo Li, Xiao-yan Hao, Jun-chao Zhang, Zhao-yi Li, Huan Sun, 2025: Ecological vulnerability assessment and driving force analysis of small watersheds in Hilly Regions using sensitivity-resilience-pressure modeling, Journal of Groundwater Science and Engineering, 13, 209-224.  doi: 10.26599/JGSE.2025.9280050
    [5] Parvaiz Ahmad Ganie, Ravindra Posti, Garima, Kishor Kunal, Nityanand Pandey, Pramod Kumar Pandey, 2024: Morphometric analysis and hydrological implications of the Himalayan River Basin, Goriganga, India, using Remote Sensing and GIS techniques, Journal of Groundwater Science and Engineering, 12, 360-386.  doi: 10.26599/JGSE.2024.9280028
    [6] Stephen Pitchaimani V, Narayanan MSS, Abishek RS, Aswin SK, Jerin Joe RJ, 2024: Delineation of groundwater potential zones using remote sensing and Geographic Information Systems (GIS) in Kadaladi region, Southern India, Journal of Groundwater Science and Engineering, 12, 147-160.  doi: 10.26599/JGSE.2024.9280012
    [7] Masoud H Hamed, Rebwar N Dara, Marios C Kirlas, 2024: Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq, Journal of Groundwater Science and Engineering, 12, 16-33.  doi: 10.26599/JGSE.2024.9280003
    [8] Edmealem Temesgen, Demelash Wendmagegnehu Goshime, Destaw Akili, 2023: Determination of groundwater potential distribution in Kulfo-Hare watershed through integration of GIS, remote sensing, and AHP in Southern Ethiopia, Journal of Groundwater Science and Engineering, 11, 249-262.  doi: 10.26599/JGSE.2023.9280021
    [9] Muthamilselvan A Dr, Sekar Anamika, Ignatius Emmanuel, 2022: Identification of groundwater potential in hard rock aquifer systems using Remote Sensing, GIS and Magnetic Survey in Veppanthattai, Perambalur, Tamilnadu, Journal of Groundwater Science and Engineering, 10, 367-380.  doi: 10.19637/j.cnki.2305-7068.2022.04.005
    [10] Kessar Cherif, Benkesmia Yamina, Blissag Bilal, Wahib Kébir Lahsen, 2021: Delineation of groundwater potential zones in Wadi Saida Watershed of NW-Algeria using remote sensing, geographic information system-based AHP techniques and geostatistical analysis, Journal of Groundwater Science and Engineering, 9, 45-64.  doi: 10.19637/j.cnki.2305-7068.2021.01.005
    [11] Negar Fathi, Mohammad Bagher Rahnama, Mohammad Zounemat Kermani, 2020: Spatial analysis of groundwater quality for drinking purpose in Sirjan Plain, Iran by fuzzy logic in GIS, Journal of Groundwater Science and Engineering, 8, 67-78.  doi: 10.19637/j.cnki.2305-7068.2020.01.007
    [12] Fatima Zahra FAQIHI, Anasse BENSLIMANE, Abderrahim LAHRACH, Mohamed CHIBOUT, Mohamed EL MOKHTAR, 2020: Recognition of the hydrogeological potential using electrical sounding in the KhemissetTiflet region, Morocco, Journal of Groundwater Science and Engineering, 8, 172-179.  doi: 10.19637/j.cnki.2305-7068.2020.02.008
    [13] LI Lu-lu, SU Chen, HAO Qi-chen, SHAO Jing-li, 2018: Numerical simulation of response of groundwater flow system in inland basin to density changes, Journal of Groundwater Science and Engineering, 6, 7-17.  doi: 10.19637/j.cnki.2305-7068.2018.01.002
    [14] Alhassan H Ismai, Muntasir A Shareef, Wesam Mahmood, 2018: Hydrochemical characterization of groundwater in Balad district, Salah Al-Din Governorate, Iraq, Journal of Groundwater Science and Engineering, 6, 306-322.  doi: 10.19637/j.cnki.2305-7068.2018.04.006
    [15] TONG Shao-qing, DONG Yan-hui, ZHANG Qian, SONG Fan, 2017: Visualizing complex pore structure and fluid flow in porous media using 3D printing technology and LBM simulation, Journal of Groundwater Science and Engineering, 5, 254-265.
    [16] ZHU Yu-chen, ZHANG Yi-long, HAO Qi-chen, 2017: Assessment of shallow groundwater vulnerability in Dahei River Plain based on AHP and DRASTIC, Journal of Groundwater Science and Engineering, 5, 266-277.
    [17] CHENG Tang-pei, LIU Xing-wei, SHAO Jing-Li, CUI Ya-li, 2016: Review of the algebraic linear methods and parallel implementation in numerical simulation of groundwater flow, Journal of Groundwater Science and Engineering, 4, 12-17.
    [18] LIU Jun, CHENG Jian-mei, JIANG Fang-yuan, 2015: Methodological study of coastal geological hazard assessment based on GIS, Journal of Groundwater Science and Engineering, 3, 77-85.
    [19] Liang ZHU, Wei-dong KANG, Ji-chao SUN, Jing-tao LIU, 2014: Quantitative Calculation of Groundwater Vulnerability Assessment Based on Quantification Theory III, Journal of Groundwater Science and Engineering, 2, 78-85.
    [20] Jiankang Zhang, Yanpei Cheng, Hua Dong, Qingshi Guo, Kun Liu, Fawang Zhang, 2013: Study on Ecological Environment and Sustainable Land Use Based on Satellite Remote Sensing, Journal of Groundwater Science and Engineering, 1, 89-96.
  • 加载中

Catalog

    Figures(15)  / Tables(6)

    Article Metrics

    Article views (10) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return