Impact of Land Use/Land Cover Change on Future Flash Flood Vulnerability and Monsoon Runoff in an Ungauged Himalayan Watershed
Publication: Journal of Hydrologic Engineering
Volume 29, Issue 3
Abstract
Hydrological extremes and land use are intimately connected, as land use alterations frequently exacerbate or mitigate the consequences of extreme events. Therefore, assessment and prediction of land use dynamics retain great significance in projected scenarios of hydrological extremes. This study aimed to quantify the impact of land use changes on future landslide-prone sites, flash flood vulnerable zones (FFVZs), and monsoon runoff. In this context, a Markov chain–cellular automata (MC-CA) model integrated with a multilayer perceptron–neural network (MLP-NN) model was designed to predict near-future land use/land cover changes (LULCC) using high-resolution existing land use/land cover (LULC) information. Uncorrected finer-scale Coupled Model Intercomparison Project Phase 6 (CMIP6) meteorological data sets and predicted LULC data were used to simulate daily runoff with the help of the Soil and Water Assessment Tool (SWAT). Statistical evaluation matrices were used to assess the efficacy of using uncorrected CMIP6 data sets for hydrological modeling. The methodology was evaluated for suitability in the ungauged high-altitude Ranikhola watershed. The prediction results showed that the watershed can be expected to be more susceptible to landslides and flash floods (9%). The most challenging discovery from this analysis was an anticipated 32.50% increase in average monsoon runoff from 2021 to 2032 compared to the observed period, 2015–2020. In addition, the runoff peak magnitude is projected to rise by 26.00%. Consequently, it is imperative to develop strategies and approaches for sustainable watershed management to address future challenges.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
We are thankful to the CWC, Sikkim Investigation Division, government of India, for providing daily observed discharge data (2015–2020). In addition, we are appreciative of Copernicus C3S for making their open data archives freely accessible data sets available. We are thankful to the NRSC in Hyderabad, India, for providing the high-resolution LISS-IV data. We are also grateful to the ASF, SoI, IMD, the Centre for Interdisciplinary Studies of Mountain and Hill Environment, University of Delhi, India, Environmental Information System (ENVIS) Centre, the Ministry of Environment and Forest, and the government of India for their freely available data sets in their open data archives.
Author contributions: Dibyandu Roy: conceptualization, methodology, investigation, software, visualization, and writing–original draft. Bharath H. Aithal: supervision, conceptualization, visualization, and writing. Anirban Dhar: supervision, conceptualization, and visualization. Venkappayya R. Desai: data and software acquisition and visualization.
References
Abbaszadeh, M., O. Bazrafshan, R. Mahdavi, E. R. Sardooi, and S. Jamshidi. 2023. “Modeling future hydrological characteristics based on land use/land cover and climate changes using the SWAT model.” Water Resour. Manage. 37 (10): 4177–4194. https://doi.org/10.1007/s11269-023-03545-6.
Abdulkareem, J. H., W. N. A. Sulaiman, B. Pradhan, and N. R. Jamil. 2018. “Relationship between design floods and land use land cover (LULC) changes in a tropical complex catchment.” Arabian J. Geosci. 11 (14): 376. https://doi.org/10.1007/s12517-018-3702-4.
Aburas, M. M., Y. M. Ho, M. F. Ramli, and Z. H. Ash’aari. 2016. “The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review.” Int. J. Appl. Earth Obs. Geoinf. 52 (Oct): 380–389. https://doi.org/10.1016/j.jag.2016.07.007.
Aithal, B. H., M. C. Chandan, S. Vinay, and T. V. Ramachandra. 2018. “Urbanization in India: Patterns, visualization of cities, and greenhouse gas inventory for developing an urban observatory.” In Urban remote sensing, 151–172. Boca Raton, FL: CRC Press.
Anh, T., T. Do, A. Ngoc, T. Do, and H. Duc. 2022. “Ecological informatics quantifying the spatial pattern of urban expansion trends in the period 1987–2022 and identifying areas at risk of flooding due to the impact of urbanization in Lao Cai city.” Ecol. Inf. 72 (Jul): 101912. https://doi.org/10.1016/j.ecoinf.2022.101912.
Arnold, J., R. Srinivasan, C. Santhi, R. D. Harmel, and A. Van Griensven. 2012. “SWAT: Model use, calibration, and validation.” Trans. ASABE 55 (4): 1491–1508. https://doi.org/10.13031/2013.42256.
Arnold, J. G., R. Srinivasan, R. S. Muttiah, and J. R. Williams. 1998. “Large area hydrologic modeling and assessment Part I: Model development’ basin scale model called SWAT (soil and water speed and storage, advanced software debugging policy to meet the needs, and the management to the tank model.” JAWRA J. Am. Water Resour. Assoc. 34 (1): 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x.
Astuti, I. S., K. Sahoo, A. Milewski, and D. R. Mishra. 2019. “Impact of land use land cover (LULC) change on surface runoff in an increasingly urbanized tropical watershed.” Water Resour. Manage. 33 (12): 4087–4103. https://doi.org/10.1007/s11269-019-02320-w.
Bewket, W. 2002. “Land cover dynamics since the 1950s in Chemoga watershed, Blue Nile basin, Ethiopia.” Mt. Res. Dev. 22 (3): 263–269. https://doi.org/10.1659/0276-4741(2002)022[0263:LCDSTI]2.0.CO;2.
Bhattacharjee, K., and B. Behera. 2017. “Forest cover change and flood hazards in India.” Land Use Policy 67 (Dec): 436–448. https://doi.org/10.1016/j.landusepol.2017.06.013.
Chalise, S. R., S. R. Kansakar, G. Rees, K. Croker, and M. Zaidman. 2003. “Management of water resources and low flow estimation for the Himalayan basins of Nepal.” J. Hydrol. 282 (1): 25–35. https://doi.org/10.1016/S0022-1694(03)00250-6.
Chandan, M. C., G. Nimish, and H. A. Bharath. 2020. “Analysing spatial patterns and trend of future urban expansion using SLEUTH.” Spatial Inf. Res. 28 (1): 11–23. https://doi.org/10.1007/s41324-019-00262-4.
Chopard, B. 2009. “Cellular automata modeling of physical systems.” In Encyclopedia complexity system science, edited by R. A. Meyers, 865–892. New York: Springer.
Clarke, K. C., S. Hoppen, and L. Gaydos. 1997. “A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area.” Environ. Plann. B: Plann. Des. 24 (2): 247–261. https://doi.org/10.1068/b240247.
Cunha, E. R., C. A. G. Santos, R. M. da Silva, V. M. Bacani, and A. Pott. 2021. “Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil.” Land Use Policy 101 (Feb): 105141. https://doi.org/10.1016/j.landusepol.2020.105141.
Daide, F., R. Afgane, A. Lahrach, and A. A. Chaouni. 2022. “Beht watershed (Morocco) rainfall-runoff simulation with the HEC-HMS hydrological model.” Ecol. Eng. Environ. Technol. 23 (1): 142–155. https://doi.org/10.12912/27197050/142942.
Dale, V. H. 1997. “The relationship between land-use change and climate change.” Ecol. Appl. 7 (3): 753–769. https://doi.org/10.1890/1051-0761(1997)007[0753:TRBLUC]2.0.CO;2.
Dale, V. H., R. A. Efroymson, and K. L. Kline. 2011. “The land use–climate change–energy nexus.” Landscape Ecol. 26 (Jul): 755–773. https://doi.org/10.1007/s10980-011-9606-2.
Dey, A., R. Remesan, and R. Kumar. 2023. “Blue and green water re-distribution dependency on precipitation datasets for a tropical Indian River basin.” J. Hydrol.: Reg. Stud. 46 (Apr): 101361. https://doi.org/10.1016/j.ejrh.2023.101361.
Dey, N. N., A. Al Rakib, A. Al Kafy, and V. Raikwar. 2021. “Geospatial modelling of changes in land use/land cover dynamics using multi-layer perceptron Markov chain model in Rajshahi City, Bangladesh.” Environ. Challenges 4 (Aug): 100148. https://doi.org/10.1016/j.envc.2021.100148.
Din, A. U., W. Basharat, A. Malik, and R. H. Gavit. 2023. “Dynamics of land use and land cover in Northern India: A systematic review.” GeoJournal 88 (Mar): 4297–4324. https://doi.org/10.1007/s10708-023-10870-1.
Dinka, M. O., and A. Klik. 2019. “Effect of land use–land cover change on the regimes of surface runoff—The case of Lake Basaka catchment (Ethiopia).” Environ. Monit. Assess. 191 (5): 1–13. https://doi.org/10.1007/s10661-019-7439-7.
Erdbrügger, J., I. van Meerveld, K. Bishop, and J. Seibert. 2021. “Effect of DEM-smoothing and-aggregation on topographically-based flow directions and catchment boundaries.” J. Hydrol. 602 (Nov): 126717. https://doi.org/10.1016/j.jhydrol.2021.126717.
Faisal Koko, A., W. Yue, G. Abdullahi Abubakar, R. Hamed, and A. A. Noman Alabsi. 2021. “Analyzing urban growth and land cover change scenario in Lagos, Nigeria using multi-temporal remote sensing data and GIS to mitigate flooding.” Geomatics Nat. Hazards Risk 12 (1): 631–652. https://doi.org/10.1080/19475705.2021.1887940.
Femeena, P. V., R. Karki, R. Cibin, and K. P. Sudheer. 2022. “Reconceptualizing HRU threshold definition in the soil and water assessment tool.” J. Am. Water Resour. Assoc. 58 (4): 508–516. https://doi.org/10.1111/1752-1688.13000.
Feng, B., Y. Zhang, and R. Bourke. 2021. “Urbanization impacts on flood risks based on urban growth data and coupled flood models.” Nat. Hazards 106 (1): 613–627. https://doi.org/10.1007/s11069-020-04480-0.
Foody, G. M. 2020. “Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification.” Remote Sens. Environ. 239 (Jan): 111630. https://doi.org/10.1016/j.rse.2019.111630.
Geetha Raveendran Nair, A. N., S. D. Shamsudeen, M. G. Mohan, and A. Sankaran. 2023. “Basin-scale streamflow projections for greater Pamba river basin, India integrating GCM ensemble modelling and flow accumulation-weighted LULC overlay in deep learning environment.” Sustainable 15 (19): 1–27. https://doi.org/10.3390/su151914148.
Gharaibeh, A., A. Shaamala, R. Obeidat, and S. Al-Kofahi. 2020. “Improving land-use change modeling by integrating ANN with cellular automata-Markov chain model.” Heliyon 6 (9): e05092. https://doi.org/10.1016/j.heliyon.2020.e05092.
Gidey, E., O. Dikinya, R. Sebego, E. Segosebe, and A. Zenebe. 2017. “Cellular automata and Markov chain (CA_Markov) model-based predictions of future land use and land cover scenarios (2015–2033) in Raya, northern Ethiopia.” Model. Earth Syst. Environ. 3 (4): 1245–1262. https://doi.org/10.1007/s40808-017-0397-6.
Gogoi, P. P., V. Vinoj, D. Swain, G. Roberts, J. Dash, and S. Tripathy. 2019. “Land use and land cover change effect on surface temperature over eastern India.” Sci. Rep. 9 (1): 1–10. https://doi.org/10.1038/s41598-019-45213-z.
GSI (Geological Survey of India). 2023. “Bhukosh is a gateway to all geoscientific data.” Accessed February 1, 2024. https://bhukosh.gsi.gov.in.
Guan, D., H. Li, T. Inohae, W. Su, T. Nagaie, and K. Hokao. 2011. “Modeling urban land use change by the integration of cellular automaton and Markov model.” Ecol. Modell. 222 (20): 3761–3772. https://doi.org/10.1016/j.ecolmodel.2011.09.009.
Guo, L., L. Di, C. Zhang, L. Lin, F. Chen, and A. Molla. 2022. “Evaluating contributions of urbanization and global climate change to urban land surface temperature change: A case study in Lagos, Nigeria.” Sci. Rep. 12 (1): 1–11. https://doi.org/10.1038/s41598-022-18193-w.
Hannah, D. M., S. R. Kansakar, A. J. Gerrard, and G. Rees. 2005. “Flow regimes of Himalayan rivers of Nepal: Nature and spatial patterns.” J. Hydrol. 308 (1): 18–32. https://doi.org/10.1016/j.jhydrol.2004.10.018.
Harik, G., I. Alameddine, M. A. Najm, and M. El-Fadel. 2023. “Modified SWAT to forecast water availability in mediterranean mountainous watersheds with snowmelt dominated runoff.” Water Resour. Manage. 37 (5): 1985–2000. https://doi.org/10.1007/s11269-023-03466-4.
Hassan, Z., R. Shabbir, S. S. Ahmad, A. H. Malik, N. Aziz, A. Butt, and S. Erum. 2016. “Dynamics of land use and land cover change (LULCC) using geospatial techniques: A case study of Islamabad Pakistan.” Springerplus 5 (1): 1–11. https://doi.org/10.1186/s40064-016-2414-z.
Her, Y., J. Frankenberger, I. Chaubey, and R. Srinivasan. 2015. “Threshold effects in HRU definition of the soil and water assessment tool.” Trans. ASABE 58 (2): 367–378. https://doi.org/10.13031/trans.58.10805.
Hertel, T. W., S. K. Rose, and R. S. J. Tol. 2009. Economic analysis of land use in global climate change policy. Oxfordshire, UK: Routledge.
Hosseini, S. H., and M. R. Khaleghi. 2020. “Application of SWAT model and SWAT-CUP software in simulation and analysis of sediment uncertainty in arid and semi-arid watersheds (case study: The Zoshk–Abardeh watershed).” Model. Earth Syst. Environ. 6 (4): 2003–2013. https://doi.org/10.1007/s40808-020-00846-2.
Hyandye, C. 2015. “GIS and logit regression model applications in land use/land cover change and distribution in Usangu catchment.” Am. J. Remote Sens. 3 (1): 6. https://doi.org/10.11648/j.ajrs.20150301.12.
Hyandye, C., and L. W. Martz. 2017. “A Markovian and cellular automata land-use change predictive model of the Usangu catchment.” Int. J. Remote Sens. 38 (1): 64–81. https://doi.org/10.1080/01431161.2016.1259675.
Islam, M. D., K. S. Islam, R. Ahasan, M. R. Mia, and M. E. Haque. 2021. “A data-driven machine learning-based approach for urban land cover change modeling: A case of Khulna city corporation area.” Remote Sens. Appl.: Soc. Environ. 24 (Sep): 100634. https://doi.org/10.1016/j.rsase.2021.100634.
Kafy, A., N. N. Dey, A. Al Rakib, Z. A. Rahaman, N. M. R. Nasher, and A. Bhatt. 2021a. “Modeling the relationship between land use/land cover and land surface temperature in Dhaka, Bangladesh using CA-ANN algorithm.” Environ. Challenges 4 (Jun): 100190. https://doi.org/10.1016/j.envc.2021.100190.
Kafy, A., M. N. H. Naim, G. Subramanyam, A. Al Faisal, N. U. Ahmed, A. Al Rakib, M. A. Kona, and G. S. Sattar. 2021b. “Cellular automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh.” Environ. Challenges 4 (Mar): 100084. https://doi.org/10.1016/j.envc.2021.100084.
Kozak, J., U. Gimmi, T. Houet, and J. Bolliger. 2017. “Current practices and challenges for modelling past and future land use and land cover changes in mountainous regions.” Reg. Environ. Change 17 (8): 2187–2191. https://doi.org/10.1007/s10113-017-1217-2.
Kumar, M., D. M. Denis, A. Kundu, N. Joshi, and S. Suryavanshi. 2022. “Understanding land use/land cover and climate change impacts on hydrological components of Usri watershed, India.” Appl. Water Sci. 12 (3): 1–14. https://doi.org/10.1007/s13201-021-01547-6.
Lehmann, P., J. von Ruette, and D. Or. 2019. “Deforestation effects on rainfall-induced shallow landslides: Remote sensing and physically-based modeling.” Water Resour. Res. 55 (11): 9962–9976. https://doi.org/10.1029/2019WR025233.
Li, G., Y. Lei, H. Yao, S. Wu, and J. Ge. 2017. “The influence of land urbanization on landslides: An empirical estimation based on Chinese provincial panel data.” Sci. Total Environ. 595 (Oct): 681–690. https://doi.org/10.1016/j.scitotenv.2017.03.258.
Li, S. H., B. X. Jin, X. Y. Wei, Y. Y. Jiang, and J. L. Wang. 2015. “Using CA-MARKOV model to model the spatiotemporal change of land use/cover in Fuxian Lake for decision support.” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2 (4): 163–168. https://doi.org/10.5194/isprsannals-II-4-W2-163-2015.
Liu, J., Z. Wu, and H. Zhang. 2021. “Analysis of changes in landslide susceptibility according to land use over 38 years in Lixian county, China.” Sustainability 13 (19): 1–23. https://doi.org/10.3390/su131910858.
Lovino, M. A., M. J. Pierrestegui, O. V. Müller, E. H. Berbery, G. V. Müller, and M. Pasten. 2021. “Evaluation of historical CMIP6 model simulations and future projections of temperature and precipitation in Paraguay.” Clim. Change 164: 1–24.
Maher, M., T. Nasrallah, M. Rabah, and F. Abdelhaleem. 2022. “Watershed delineation and runoff estimation of Wadi Tayyibah, South Sinai using Arc-GIS and HEC-HMS model.” Port-Said Eng. Res. J. 26 (2): 61–71. https://doi.org/10.21608/pserj.2022.111930.1155.
Mansour, S., M. Al-Belushi, and T. Al-Awadhi. 2020. “Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques.” Land Use Policy 91 (Jun): 104414. https://doi.org/10.1016/j.landusepol.2019.104414.
Mas, J. F., M. Kolb, M. Paegelow, M. T. Camacho Olmedo, and T. Houet. 2014. “Inductive pattern-based land use/cover change models: A comparison of four software packages.” Environ. Modell. Software 51 (Sep): 94–111. https://doi.org/10.1016/j.envsoft.2013.09.010.
Maurya, S., P. K. Srivastava, L. Zhuo, A. Yaduvanshi, and R. K. Mall. 2023. “Future climate change impact on the streamflow of Mahi River basin under different general circulation model scenarios.” Water Resour. Manage. 2023 (Jan): 1–22. https://doi.org/10.1007/s11269-022-03372-1.
Meneses, B. M., S. Pereira, and E. Reis. 2019. “Effects of different land use and land cover data on the landslide susceptibility zonation of road networks.” Nat. Hazards Earth Syst. Sci. 19 (3): 471–487. https://doi.org/10.5194/nhess-19-471-2019.
Merz, J., P. M. Dangol, M. P. Dhakal, B. S. Dongol, G. Nakarmi, and R. Weingartner. 2006. “Rainfall-runoff events in a middle mountain catchment of Nepal.” J. Hydrol. 331 (3): 446–458. https://doi.org/10.1016/j.jhydrol.2006.05.030.
Mesgari, E., S. A. Hosseini, M. S. Hemmesy, M. Houshyar, and L. G. Partoo. 2022. “Assessment of CMIP6 models’ performances and projection of precipitation based on SSP scenarios over the MENAP region.” J. Water Clim. Change 13 (10): 3607–3619.
Mishra, V. N., and P. K. Rai. 2016. “A remote sensing aided multi-layer perceptron-Markov chain analysis for land use and land cover change prediction in Patna district (Bihar), India.” Arabian J. Geosci. 9 (4): 1–18. https://doi.org/10.1007/s12517-015-2138-3.
Mondal, M. S., N. Sharma, P. K. Garg, and M. Kappas. 2016. “Statistical independence test and validation of CA Markov land use land cover (LULC) prediction results.” Egypt. J. Remote Sens. Space Sci. 19 (2): 259–272. https://doi.org/10.1016/j.ejrs.2016.08.001.
National Remote Sensing Center. 2023. “Bhuvan: Indian Geo Platform of ISRO.” Accessed October 10, 2023. https://bhuvan-app1.nrsc.gov.in.
Neitsch, S., J. Arnold, J. Kiniry, and J. Williams. 2011. Soil & water assessment tool theoretical documentation version 2009, 1–647. College Station, TX: Texas Water Resources Institute.
Ngoma, H., W. Wen, B. Ayugi, H. Babaousmail, R. Karim, and V. Ongoma. 2021. “Evaluation of precipitation simulations in CMIP6 models over Uganda.” Int. J. Clim. 41 (9): 4743–4768.
Pai, D. S., L. Sridhar, M. Rajeevan, O. P. Sreejith, N. S. Satbhai, and B. Mukhopadhyay. 2014. “Development of a new high spatial resolution (0.25° × 0.25°) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region.” Mausam 65 (1): 1–18. https://doi.org/10.54302/mausam.v65i1.851.
Parsamehr, K., M. Gholamalifard, and Y. Kooch. 2020. “Comparing three transition potential modeling for identifying suitable sites for REDD+ projects.” Spatial Inf. Res. 28 (2): 159–171. https://doi.org/10.1007/s41324-019-00273-1.
Patil, N. S., and M. Nataraja. 2020. “Effect of land use land cover changes on runoff using hydrological model: A case study in Hiranyakeshi watershed.” Model. Earth Syst. Environ. 6 (4): 2345–2357. https://doi.org/10.1007/s40808-020-00808-8.
Pisano, L., V. Zumpano, M. C. M. Rosskopf, and M. Parise. 2017. “Variations in the susceptibility to landslides, as a consequence of land cover changes: A look to the past, and another towards the future.” Sci. Total Environ. 601–602 (Dec): 1147–1159. https://doi.org/10.1016/j.scitotenv.2017.05.231.
Prasad, A. S., B. W. Pandey, W. Leimgruber, and R. M. Kunwar. 2016. “Mountain hazard susceptibility and livelihood security in the upper catchment area of the river Beas, Kullu Valley, Himachal Pradesh, India.” Geoenviron. Disasters 3 (1): 1–17. https://doi.org/10.1186/s40677-016-0037-x.
Puente-Sotomayor, F., A. Mustafa, and J. Teller. 2021. “Landslide susceptibility mapping of urban areas: Logistic regression and sensitivity analysis applied to Quito, Ecuador.” Geoenviron. Disasters 8 (1): 19. https://doi.org/10.1186/s40677-021-00184-0.
Quevedo, P., A. Velastegui-Montoya, N. Montalván-Burbano, F. Morante-Carballo, O. Korup, and C. Daleles Rennó. 2023. “Land use and land cover as a conditioning factor in landslide susceptibility: A literature review.” Landslides 20 (5): 967–982. https://doi.org/10.1007/s10346-022-02020-4.
Rahman, M. S., M. S. Anower, M. R. Hasan, M. B. Hossain, and M. I. Haque. 2017. “Design and numerical analysis of highly sensitive Au--graphene based hybrid surface plasmon resonance biosensor.” Opt. Commun. 396 (Jan): 36–43. https://doi.org/10.1016/j.optcom.2017.03.035.
Rocha, J., J. C. Ferreira, J. Simões, and J. A. Tenedório. 2007. “Modelling coastal and land use evolution patterns through neural network and cellular automata integration.” J. Coastal Res. 2007 (50): 827–831.
Rohan, T., E. Shelef, B. Mirus, and T. Coleman. 2023. “Prolonged influence of urbanization on landslide susceptibility.” Landslides 20 (Mar): 1433–1447. https://doi.org/10.1007/s10346-023-02050-6.
Roy, D., A. Dhar, and V. R. Desai. 2023. “A grey fuzzy analytic hierarchy process-based flash flood vulnerability assessment in an ungauged Himalayan watershed.” Environ. Dev. Sustainability 2023 (Jun): 1–26. https://doi.org/10.1007/s10668-023-03385-9.
Roy, J., and S. Saha. 2022. “Ensemble hybrid machine learning methods for gully erosion susceptibility mapping: K-fold cross validation approach.” Artif. Intell. Geosci. 3 (Mar): 28–45. https://doi.org/10.1016/j.aiig.2022.07.001.
Saha, P., R. Mitra, K. Chakraborty, and M. Roy. 2022. “Application of multi layer perceptron neural network Markov chain model for LULC change detection in the sub-Himalayan north Bengal.” Remote Sens. Appl.: Soc. Environ. 26 (Nov): 100730. https://doi.org/10.1016/j.rsase.2022.100730.
Sajikumar, N., and R. S. Remya. 2015. “Impact of land cover and land use change on runoff characteristics.” J. Environ. Manage. 161 (Sep): 460–468. https://doi.org/10.1016/j.jenvman.2014.12.041.
Sharma, P., and S. C. Rai. 2004. “Streamflow, sediment and carbon transport from a Himalayan watershed.” J. Hydrol. 289 (1): 190–203. https://doi.org/10.1016/j.jhydrol.2003.11.023.
Shi, L., P. Feng, B. Wang, D. L. Liu, H. Zhang, J. Liu, and Q. Yu. 2022. “Assessing future runoff changes with different potential evapotranspiration inputs based on multi-model ensemble of CMIP5 projections.” J. Hydrol. 612 (Aug): 128042. https://doi.org/10.1016/j.jhydrol.2022.128042.
Shukla, S., S. K. Jain, and M. L. Kansal. 2021. “Hydrological modelling of a snow/glacier-fed western Himalayan basin to simulate the current and future streamflows under changing climate scenarios.” Sci. Total Environ. 795 (Nov): 148871. https://doi.org/10.1016/j.scitotenv.2021.148871.
Singh, V., N. Bankar, S. S. Salunkhe, A. K. Bera, and J. R. Sharma. 2013. “Hydrological stream flow modelling on tungabhadra catchment: Parameterization and uncertainty analysis using SWAT CUP.” Curr. Sci. 104 (9): 1187–1199.
Sisodia, P. S., V. Tiwari, and A. Kumar. 2014. “Analysis of supervised maximum likelihood classification for remote sensing image.” In Proc., Int. Conf. on Recent Advances and Innovations in Engineering (ICRAIE-2014), 9–12. New York: IEEE.
Slack, R. B., and R. Welch. 1980. “Soil conservation service runoff curve number estimates from Landsat data.” JAWRA J. Am. Water Resour. Assoc. 16 (5): 887–893. https://doi.org/10.1111/j.1752-1688.1980.tb02504.x.
Soheili Majd, M., E. Simonetto, and L. Polidori. 2012. “Maximum likelihood classification of high-resolution SAR images in urban area.” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 44 (Jun): 309–312. https://doi.org/10.5194/isprsarchives-xxxviii-4-w19-309-2011.
Souza-e-Silva, H., W. Savino, R. A. Feijóo, and A. T. R. Vasconcelos. 2009. “A cellular automata-based mathematical model for thymocyte development.” PLoS One 4 (12): e8233. https://doi.org/10.1371/journal.pone.0008233.
Srinivasan, R., X. Zhang, and J. Arnold. 2010. “SWAT ungauged: Hydrological budget and crop yield prediction in the upper Mississippi river basin.” Trans. ASABE 53 (5): 1533–1546. https://doi.org/10.13031/2013.34903.
Strahler, A. N. 1964. “Quantitative geomorphology of drainage basins and channel networks.” In Handbook of applied hydrology, 4–39. New York: McGraw-Hill.
Subedi, P., K. Subedi, and B. Thapa. 2013. “Application of a hybrid cellular automaton–Markov (CA-Markov) model in land-use change prediction: A case study of saddle creek drainage basin, Florida.” Appl. Ecol. Environ. Sci. 1 (6): 126–132. https://doi.org/10.12691/aees-1-6-5.
Sun, Z., T. Lotz, and Q. Huang. 2021. “An ET-based two-phase method for the calibration and application of distributed hydrological models.” Water Resour. Manage. 35 (3): 1065–1077. https://doi.org/10.1007/s11269-021-02774-x.
Swain, S., S. K. Mishra, A. Pandey, A. C. Pandey, A. Jain, and S. K. Chauhan. 2022. “Hydrological modelling through SWAT over a Himalayan catchment using high-resolution geospatial inputs.” Environ. Challenges 8 (Jun): 100579. https://doi.org/10.1016/j.envc.2022.100579.
Tayal Senzeba, K., A. Bhadra, and A. Bandyopadhyay. 2015. “Snowmelt runoff modelling in data scarce Nuranang catchment of eastern Himalayan region.” Remote Sens. Appl. Soc. Environ. 1 (5): 20–35. https://doi.org/https://doi.org/10.1016/j.rsase.2015.06.001.
Teng, H., S. Chen, B. Hu, and Z. Shi. 2023. “Future changes and driving factors of global peak vegetation growth based on CMIP6 simulations.” Ecol. Inf. 75 (Nov): 102031. https://doi.org/10.1016/j.ecoinf.2023.102031.
Thavhana, M. P., M. J. Savage, and M. E. Moeletsi. 2018. “SWAT model uncertainty analysis, calibration and validation for runoff simulation in the Luvuvhu river catchment, South Africa.” Phys. Chem. Earth 105 (Jan): 115–124. https://doi.org/10.1016/j.pce.2018.03.012.
The Hindu. 2023. “Sikkim flash floods: Eight soldiers killed; search on for 14 missing.” October 7, 2023.
Tola, S. Y., and A. Shetty. 2021. “Land cover change and its implication to hydrological regimes and soil erosion in Awash River basin, Ethiopia: A systematic review.” Environ. Monit. Assess. 193 (12): 1–19. https://doi.org/10.1007/s10661-021-09599-6.
Twisa, S., and M. F. Buchroithner. 2019. “Land-use and land-cover (LULC) change detection in Wami River basin, Tanzania.” Land 8 (9): 136. https://doi.org/10.3390/land8090136.
Veh, G., O. Korup, S. von Specht, S. Roessner, and A. Walz. 2019. “Unchanged frequency of moraine-dammed glacial lake outburst floods in the Himalaya.” Nat. Clim. Change 9 (5): 379–383. https://doi.org/10.1038/s41558-019-0437-5.
Wang, S. W., L. Munkhnasan, and W. K. Lee. 2021. “Land use and land cover change detection and prediction in Bhutan’s high altitude city of Thimphu, using cellular automata and Markov Chain.” Environ. Challenges 2 (Dec): 100017. https://doi.org/10.1016/j.envc.2020.100017.
Xu, Y., Y. Chen, Y. Ren, Z. Tang, X. Yang, and Y. Zhang. 2023. “Attribution of streamflow changes considering spatial contributions and driver interactions based on hydrological modeling.” Water Resour. Manage. 37 (5): 1859–1877. https://doi.org/10.1007/s11269-023-03459-3.
Xue, P., C. Zhang, Z. Wen, E. Park, and H. Jakada. 2022. “Climate variability impacts on runoff projection under quantile mapping bias correction in the support CMIP6: An investigation in Lushi basin of China.” J. Hydrol. 614 (5): 128550. https://doi.org/10.1016/j.jhydrol.2022.128550.
Yadav, B. P., R. Saxena, A. K. Das, S. K. Manik, and S. K. Asok Raja. 2017. Rainfall statistics of India-2017. New Delhi, India: Hydromet Division, Indian Meteorological Department, Ministry of Earth Sciences.
Zhao, Y., D. Xie, X. Zhang, and S. Ma. 2021. “Integrating spatial Markov chains and geographically weighted regression-based cellular automata to simulate urban agglomeration growth: A case study of the Guangdong–Hong Kong–Macao greater bay area.” Land 10 (6): 633. https://doi.org/10.3390/land10060633.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 29 • Issue 3 • June 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Sep 11, 2023
Accepted: Dec 20, 2023
Published online: Mar 8, 2024
Published in print: Jun 1, 2024
Discussion open until: Aug 8, 2024
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.