Skip to main content

Advertisement

SpringerLink
Log in

Morphometric Analysis Using SRTM-DEM and GIS of Nagar River Basin, Indo-Bangladesh Barind Tract

  • Research Article
  • Published:
Journal of the Indian Society of Remote Sensing Aims and scope Submit manuscript

Abstract

Conceptualisation of geo-hydrological characteristic of a drainage basin quantitative measurement of morphometric parameters has been required. Assessment and understanding the hydrological characteristics of Nagar River Basin morphometric analysis has been carried out. Remote sensing and ArcGIS techniques have been used for measuring and calculating the morphometric characteristics of the Nagar River Basin. Total area of Nagar River Basin is 2381.69 sq.km with dendritic drainage pattern. This stream frequency of the Nagar River Basin is 0.09 km/sq.km. Probability of flooding is quite high with intense rainfall in dendritic type of drainage system. Monsoonal rainfall is the main cause for the formation of stream segment. Very coarse drainage texture has been found in this Nagar River Basin with T value 0.04. This river basin is highly elongated in nature. The presence of a large number of stream segments exhibits the soil erosion in this study area by surface runoff, and the eroded materials deposited into the river bed aggregated channel depth causing flooding in rainy season. Flood is one of the major natural hazards having massive damage every year all over the world. For constructing flood vulnerability mapping of Nagar River Basin, AHP method has been used by compiling some morphometric parameters with other flood-influencing factors of Nagar River Basin. It can be concluded that the lower portion of the Nagar River Basin is highly vulnerable to flooding.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Abrahams, A. (1984). Channel networks: A geomorphological perspective. Water Resources Research,20(2), 161–188. https://doi.org/10.1029/wr020i002p00161.

    Article  Google Scholar 

  • Agarwal, C. (1998). Study of drainage pattern through aerial data in Naugarh area of Varanasi district, U.P. Journal of the Indian Society of Remote Sensing,26(4), 169–175. https://doi.org/10.1007/bf02990795.

    Article  Google Scholar 

  • Altaf, F., Meraj, G., & Romshoo, S. (2013). Morphometric analysis to infer hydrological behaviour of Lidder Watershed, Western Himalaya, India. Geography Journal. https://doi.org/10.1155/2013/178021.

    Article  Google Scholar 

  • Asode, A., Sreenivasa, A., & Lakkundi, T. (2016). Quantitative morphometric analysis in the hard rock Hirehalla sub-basin, Bellary and Davanagere Districts, Karnataka, India using RS and GIS. Arabian Journal of Geosciences,9(5), 381. https://doi.org/10.1007/s12517-016-2414-x.

    Article  Google Scholar 

  • Astras, T., & Soulankellis, N. (1992) Contribution of digital image analysis techniques on Landsat-5 TM imageries for drainage delineation: A case study from the Olympus mountain, West Macedonia, Greece. In Proceedings of 18th Annual Conference Remote Sensing Society, University of Dundee, pp. 163–172

  • Avinash, K., Jayappa, K., & Deepika, B. (2011). Prioritization of sub-basins based on geomorphology and morphometricanalysis using remote sensing and geographic informationsystem (GIS) techniques. Geocarto International,26(7), 569–592. https://doi.org/10.1080/10106049.2011.606925.

    Article  Google Scholar 

  • Banerjee, A., Singh, P., & Pratap, K. (2015). Morphometric evaluation of Swarnrekha watershed, Madhya Pradesh, India: An integrated GIS-based approach. Applied Water Science,7(4), 1807–1815. https://doi.org/10.1007/s13201-015-0354-3.

    Article  Google Scholar 

  • Biswas, S., Sudhakar, S., & Desai, V. (1999). Prioritisation of subwatersheds based on morphometric analysis of drainage basin: A remote sensing and gis approach. Journal Of The Indian Society Of Remote Sensing,27(3), 155–166. https://doi.org/10.1007/bf02991569.

    Article  Google Scholar 

  • Chandrashekar, H., Lokesh, K., Sameena, M., Roopa, J., & Ranganna, G. (2015). GIS-based morphometric analysis of two reservoir catchments of Arkavati River, Ramanagaram District, Karnataka. Aquatic Procedia,4, 1345–1353. https://doi.org/10.1016/j.aqpro.2015.02.175.

    Article  Google Scholar 

  • Chen, Y. R., Yeh, C. H., & Yu, B. (2011). Integrated application of the analytic hierarchy process and the geographic information system for flood risk assessment and flood plain management in Taiwan. Natural Hazards,59(3), 1261–1276.

    Google Scholar 

  • Chopra, R., Dhiman, R., & Sharma, P. (2005). Morphometric analysis of sub-watersheds in Gurdaspur district, Punjab using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing,33(4), 531–539. https://doi.org/10.1007/bf02990738.

    Article  Google Scholar 

  • Chorley, R. J. (1969a). Introduction to physical hydrology. Suffolk: Methuen and Co., Ltd.

    Google Scholar 

  • Chorley, R. J. (1969b). The drainage basin as the fundamental geomorphic unit. In R. J. Chorley (Ed.), Introduction to fluvial processes (pp. 30–52). London: Methuen Co. Ltd.

    Google Scholar 

  • Chorley, R. (1971). The drainage basin as the fundamental geomorphic unit. In R. Chorley (Ed.), Introduction to fluvial processes (pp. 30–32). London: Methuen and Co. Ltd.

    Google Scholar 

  • Chorley, R. (2019). Introduction to fluvial processes. Milton: Routledge.

    Google Scholar 

  • Chow, V. T. (1964). Handbook of hydrology. New York: McGraw-Hill Book Co. Inc.

    Google Scholar 

  • Clark, C. (1966). Morphometry from maps. Essay in geomorphology (pp. 235–274). New York: Elsevier Publication Company.

    Google Scholar 

  • Cloke, H., & Pappenberger, F. (2009). Ensemble flood forecasting: A review. Journal of Hydrology,375(3), 613–626.

    Google Scholar 

  • Dandapat, K., & Panda, G. K. (2017). Flood vulnerability analysis and risk assessment using analytical hierarchy process. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-017-0388-7.

    Article  Google Scholar 

  • Deen, M. (1982). Geomorphology and land use: A case study of Mewat. Thesis (PhD). JNU, New Delhi.

  • Dixon, B. (2005). Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: A GIS-based sensitivity analysis. Journal of Hydrology,309, 17–38.

    Google Scholar 

  • Easterbrook, D. (1993). Surface processes and landforms. Upper Saddle River: Prentice-Hall.

    Google Scholar 

  • Farr, T., Rosen, P., Caro, E., Crippen, R., Duren, R., Hensley, S., et al. (2007). The shuttle radar topography mission. Reviews of Geophysics. https://doi.org/10.1029/2005rg000183.

    Article  Google Scholar 

  • Hadley, R. F., & Schumm, S. A. (1961). Sediment sources and drainage basin characteristics in upper Cheyenne River basin. US Geological Survey, USGS water supply paper, 1531-B

  • Horton, R. (1932). Drainage-basin characteristics. Transactions, American Geophysical Union,13(1), 350. https://doi.org/10.1029/tr013i001p00350.

    Article  Google Scholar 

  • Horton, R. (1945). Erosional development of streams and their drainage basins; hydrophysical approach to quantitative morphology. Geological Society of America Bulletin,56(3), 275. https://doi.org/10.1130/0016-7606(1945)56%5b275:edosat%5d2.0.co;2.

    Article  Google Scholar 

  • Huggett, R., & Cheesman, J. (2002). Topography and the environment. Harlow: Prentice Hall.

    Google Scholar 

  • Islam, M. M., Sado, K., Owe, M., Brubaker, K., Ritchie, J., & Rango, A. (2001). Flood damage and management modelling using satellite remote sensing data with GIS: Case study of Bangladesh. IAHS Publication, pp. 455–457.

  • Jain, V., & Sinha, R. (2004). Fluvial dynamics of an anabranching river system in Himalayan foreland basin, Baghmati river, north Bihar plains, India. Geomorphology,60(1–2), 147–170. https://doi.org/10.1016/j.geomorph.2003.07.008.

    Article  Google Scholar 

  • Javed, A., Khanday, M., & Ahmed, R. (2009). Prioritization of sub-watersheds based on morphometric and land use analysis using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing,37(2), 261–274. https://doi.org/10.1007/s12524-009-0016-8.

    Article  Google Scholar 

  • Kaliraj, S., Chandrasekar, N., & Magesh, N. (2014). Morphometric analysis of the River Thamirabarani sub-basin in Kanyakumari District, South west coast of Tamil Nadu, India, using remote sensing and GIS. Environmental Earth Sciences,73(11), 7375–7401. https://doi.org/10.1007/s12665-014-3914-1.

    Article  Google Scholar 

  • Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope-Evros region, Greece. Science of the Total Environment,538, 555–563. https://doi.org/10.1016/j.scitotenv.2015.08.055.

    Article  Google Scholar 

  • Kia, M. B., Pirasteh, S., Pradhan, B., Mahmud, A. R., Sulaiman, W. N. A., & Moradi, A. (2012). An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environmental Earth Sciences,67, 251–264.

    Google Scholar 

  • Kisi, O., Nia, A. M., Gosheh, M. G., Tajabadi, M. R. J., & Ahmadi, A. (2012). Intermittent streamflow forecasting by using several data driven techniques. Water Resource Management,26(2), 457–474.

    Google Scholar 

  • Kowalzig, Jan. (2008). Climate, poverty, and justice: What the Poznań UN climate conference needs to deliver for a fair and effective global deal. Oxfam Policy and Practice: Climate Change and Resilience,4(3), 117–148.

    Google Scholar 

  • Krishnamurthy, J., Srinivas, G., Jayaraman, V., & Chandrasekhar, M. G. (1996). Influence of rock types and structures in the development of drainage networks in typical hard rock terrain. ITC Journal,3(4), 52–259.

    Google Scholar 

  • Kumar Rai, P., Narayan Mishra, V., & Mohan, K. (2017). A study of morphometric evaluation of the Son basin, India using geospatial approach. Remote Sensing Applications: Society And Environment,7, 9–20. https://doi.org/10.1016/j.rsase.2017.05.001.

    Article  Google Scholar 

  • Lee, M. J., Kang, J. E., & Jeon, S. (2012) Application of frequency ratio model and validation for predictive flooded area susceptibility mapping using GIS. In Proceedings of Geoscience and Remote Sensing Symposium (IGARSS), IEEE International. Munich, pp. 895–898.

  • Leopold, L. B., Wolman, M. G., & Miller, J. P. (1992). Fluvial Processes in Geomorphology (p. 69). San Francisco: Freeman.

    Google Scholar 

  • Liao, X., & Carin, L. (2009). Migratory logistic regression for learning concept drift between two data sets with application to UXO sensing. IEEE Transactions on Geoscience and Remote Sensing,47, 1454–1466.

    Google Scholar 

  • Liu, Y., & De Smedt, F. (2005). Flood modeling for complex terrain using GIS and remote sensed information. Water Resource Management,19, 605–624. https://doi.org/10.1007/s11269-005-6808-x.

    Article  Google Scholar 

  • Macka, Z. (2001). Determination of texture of topography from large scale contour maps. Geografski Vestnik,73(2), 53–62.

    Google Scholar 

  • Magesh, N., & Chandrasekar, N. (2012). GIS model-based morphometric evaluation of Tamiraparani subbasin, Tirunelveli district, Tamil Nadu, India. Arabian Journal of Geosciences,7(1), 131–141. https://doi.org/10.1007/s12517-012-0742-z.

    Article  Google Scholar 

  • Magesh, N., Chandrasekar, N., & Soundranayagam, J. (2010). Morphometric evaluation of Papanasam and Manimuthar watersheds, parts of Western Ghats, Tirunelveli district, Tamil Nadu, India: A GIS approach. Environmental Earth Sciences,64(2), 373–381. https://doi.org/10.1007/s12665-010-0860-4.

    Article  Google Scholar 

  • Magesh, N., Jitheshlal, K., Chandrasekar, N., & Jini, K. (2012). GIS based morphometric evaluation of Chimmini and Mupily watersheds, parts of Western Ghats, Thrissur District, Kerala, India. Earth Science Informatics,5(2), 111–121. https://doi.org/10.1007/s12145-012-0101-3.

    Article  Google Scholar 

  • Magesh, N., Jitheshlal, K., Chandrasekar, N., & Jini, K. (2013). Geographical information system-based morphometric analysis of Bharathapuzha river basin, Kerala, India. Applied Water Science,3(2), 467–477. https://doi.org/10.1007/s13201-013-0095-0.

    Article  Google Scholar 

  • Melton, M. (1958). Correlation structure of morphometric properties of drainage systems and their controlling agents. The Journal of Geology,66(4), 442–460. https://doi.org/10.1086/626527.

    Article  Google Scholar 

  • Melton, M. (1966). The geomorphic and paleoclimatic significance of alluvial deposits in Southern Arizona: A reply. The Journal of Geology,74(1), 102–106. https://doi.org/10.1086/627147.

    Article  Google Scholar 

  • Messner, F., & Meyer, V. (2006). Flood damage, vulnerability and risk perception—challenges for flood damage research (pp. 149–167). Amsterdam: Springer.

    Google Scholar 

  • Miller, V. C. (1953). A quantitative geomorphic study on drainage basin characteristics in the Clinch mountain area, Virginia and Tennessee, Project NR 389-042. Technical report 3. Columbia University, New York.

  • Moglen, G., Eltahir, E., & Bras, R. (1998). On the sensitivity of drainage density to climate change. Water Resources Research,34(4), 855–862. https://doi.org/10.1029/97wr02709.

    Article  Google Scholar 

  • Moore, I. D., Grayson, R. B., & Ladspm, A. R. (1991). Digital terrain modelling: A review of hydrological, geomorphological and biological applications. Hydrological Processes,5, 3–30.

    Google Scholar 

  • Morisawa, M. (1962). Quantitative geomorphology of some watersheds in the Appalachian Plateau. Geological Society of America Bulletin,73(9), 1025. https://doi.org/10.1130/0016-7606(1962)73%5b1025:qgoswi%5d2.0.co;2.

    Article  Google Scholar 

  • Nag, S. (1998). Morphometric analysis using remote sensing techniques in the Chaka sub-basin, Purulia district, West Bengal. Journal of the Indian Society Of Remote Sensing,26(1–2), 69–76. https://doi.org/10.1007/bf03007341.

    Article  Google Scholar 

  • Nag, S., & Chakraborty, S. (2003). Influence of rock types and structures in the development of drainage network in hard rock area. Journal of the Indian Society of Remote Sensing,31(1), 25–35. https://doi.org/10.1007/bf03030749.

    Article  Google Scholar 

  • Nautiyal, M. (1994). Morphometric analysis of a drainage basin using aerial photographs: A case study of Khairkuli Basin, District Dehradun, U.P. Journal of the Indian Society of Remote Sensing,22(4), 251–261. https://doi.org/10.1007/bf03026526.

    Article  Google Scholar 

  • Neuhauser, B., Damm, B., & Terhorst, B. (2011). GIS-based assessment of landslide susceptibility on the base of the weights of evidence model. Landslides,9, 511–528. https://doi.org/10.1007/s10346-011-0305-5.

    Article  Google Scholar 

  • Olszevski, N., Fernandes Filho, E., Costa, L., Schaefer, C., Souza, E., & Costa, O. (2011). Morfologia e aspectos hidrológicos da bacia hidrográfica do rio Preto, divisa dos estados do Rio de Janeiro e de Minas Gerais. Revista Árvore,35(3), 485–492. https://doi.org/10.1590/s0100-67622011000300011.

    Article  Google Scholar 

  • Ozdemir, A., & Altural, T. (2013). A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey. Journal of Asian Earth Sciences,64, 180–197. https://doi.org/10.1016/j.jseaes.2012.12.014.

    Article  Google Scholar 

  • Pal, B., Samanta, S., & Pal, D. K. (2012). Morphometric and hydrological analysis and mapping for Watut watershed using remote sensing and GIS techniques. International Journal of Advances in Engineering & Technology,2(1), 357–368.

    Google Scholar 

  • Pankaj, A., & Kumar, P. (2009). GIS-based morphometric analysis of five major sub-watersheds of Song River, Dehradun District, Uttarakhand with special reference to landslide incidences. Journal of the Indian Society Of Remote Sensing,37(1), 157–166. https://doi.org/10.1007/s12524-009-0007-9.

    Article  Google Scholar 

  • Pareta, K., & Pareta, U. (2011). Quantitative morphometric analysis of a watershed ofYamuna Basin, India using SRTM (DEM) Data and GIS. International Journal of Geomatics and Geosciences,2(1), 248–269.

    Google Scholar 

  • Pati, J. K., Malviya, V. P., & Prakash, K. (2006). Basement re-activation and its relation to neotectonic activity in and around Allahabad, Ganga Plain. Journal of Indian Society of Remote Sensing,34, 47–56.

    Google Scholar 

  • Prabhakaran, A., & Jawahar Raj, N. (2018). Drainage morphometric analysis for assessing form and processes of the watersheds of Pachamalai hills and its adjoinings, Central Tamil Nadu, India. Applied Water Science,8(1), 31. https://doi.org/10.1007/s13201-018-0646-5.

    Article  Google Scholar 

  • Pradhan, B. (2010). Flood susceptible mapping and risk area estimation using logistic regression, GIS an dremote sensing. Journal of Spatial Hydrology,9(2), 2–12.

    Google Scholar 

  • Pradhan, B., & Buchroithner, M. F. (2010). Comparison and validation of landslide susceptibility maps using an artificial neural network model for three test areas in Malaysia. Environmental and Engineering Geoscience,16(2), 107–126.

    Google Scholar 

  • Prakash, K., Mohanty, T., Singh, S., Chaubey, K., & Prakash, P. (2016a). Drainage morphometry of the Dhasan river basin, Bundelkhand craton, central India using remote sensing and GIS techniques. Journal of Geomatics,10, 21–132.

    Google Scholar 

  • Prakash, K., Singh, S., & Shukla, U. K. (2016b). Morphometric changes of the Varuna river basin, Varanasi district, Uttar Pradesh. Journal of Geomatics,10, 48–54.

    Google Scholar 

  • Rahmati, O., Pourghasemi, H. R., & Zeinivand, H. (2015). Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran. Geocarto International,31(1), 42–70. https://doi.org/10.1080/10106049.2015.1041559.

    Article  Google Scholar 

  • Rai, P., Chandel, R., Mishra, V., & Singh, P. (2018). Hydrological inferences through morphometric analysis of lower Kosi river basin of India for water resource management based on remote sensing data. Applied Water Science,8(1), 15. https://doi.org/10.1007/s13201-018-0660-7.

    Article  Google Scholar 

  • Rai, P., Chaubey, P., Mohan, K., & Singh, P. (2017). Geoinformatics for assessing the inferences of quantitative drainage morphometry of the Narmada Basin in India. Applied Geomatics,9(3), 167–189. https://doi.org/10.1007/s12518-017-0191-1.

    Article  Google Scholar 

  • Rai, P., Mohan, K., Mishra, S., Ahmad, A., & Mishra, V. (2014). A GIS-based approach in drainage morphometric analysis of Kanhar River Basin, India. Applied Water Science,7(1), 217–232. https://doi.org/10.1007/s13201-014-0238-y.

    Article  Google Scholar 

  • Rama, V. A. (2014). Drainage basin analysis for characterization of 3rd order watersheds using Geographic Information System (GIS) and SRTM data. Journal of Geomatic,8(2), 200–210.

    Google Scholar 

  • Rao, L., Ansari, Z., Sadiq Mirza, M., & Yusuf, A. (2015). Morphometric studies using remote sensing and GIS Techniques in Bah Tehsil, Agra district, Uttar Pradesh. Journal of the Geological Society of India,85(2), 197–205. https://doi.org/10.1007/s12594-015-0206-7.

    Article  Google Scholar 

  • Reddy, G., Maji, A., & Gajbhiye, K. (2004). Drainage morphometry and its influence on landform characteristics in a basaltic terrain, Central India—A remote sensing and GIS approach. International Journal of Applied Earth Observation and Geoinformation,6(1), 1–16. https://doi.org/10.1016/j.jag.2004.06.003.

    Article  Google Scholar 

  • Regmi, N. R., Giardino, J. R., & Vitek, J. D. (2010a). Assessing susceptibility to landslide: Using models to understand observed changes in slopes. Geomorphology,122, 25–38. https://doi.org/10.1016/j.geomorph.2010.05.009.

    Article  Google Scholar 

  • Regmi, N. R., Giardino, J. R., & Vitek, J. D. (2010b). Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA. Geomorphology,115(1–2), 172–187.

    Google Scholar 

  • Ritter, D. F. (1986). Process geomorphology (2nd ed.). Dubuque: William C. Brown Company Publishers.

    Google Scholar 

  • Rozos, D., Bathrellos, G. D., & Skillodimou, H. D. (2011). Comparison of the implementation of rock engineering system and analytic hierarchy process methods, upon landslide susceptibility mapping, using GIS: A case study from the Eastern Achaia County of Peloponnesus, Greece. Environmental Earth Sciences,63, 49–63.

    Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.

    Google Scholar 

  • Samal, D., Gedam, S., & Nagarajan, R. (2015). GIS based drainage morphometry and its influence on hydrology in parts of Western Ghats region, Maharashtra, India. Geocarto International,30(7), 755–778. https://doi.org/10.1080/10106049.2014.978903.

    Article  Google Scholar 

  • Samanta, R. K., Bhunia, G. S., Shit, P. K., & Pourghasemi, H. R. (2018a). Flood susceptibility mapping using geospatial frequency ratio technique: A case study of Subarnarekha River Basin. India: Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-018-0427-z.

    Book  Google Scholar 

  • Samanta, S., Pal, D. K., & Palsamanta, B. (2018b). Flood susceptibility analysis through remote sensing, GIS and frequency ratio model. Applied Water Science,8, 66. https://doi.org/10.1007/s13201-018-0710-1.

    Article  Google Scholar 

  • Sar, N., Chatterjee, S., & Adhikari, M. D. (2015). Integrated remote sensing and GIS based spatial modelling through analytical hierarchy process (AHP) for water logging hazard, vulnerability and risk assessment in Keleghai river basin, India. Modeling Earth Systems and Environment,1, 31. https://doi.org/10.1007/s40808-015-0039-9.

    Article  Google Scholar 

  • Sarangi. (2003). Development of user Interface in ArcGIS for estimation of water-shed geomorphology. CSAE/SCGR2003 meeting, pp 03-120

  • Sarmah, K. (2012). Morphometric analysis of a highland microwatershed in East Khasi Hills District of Meghalaya, India: Using remote sensing and geographic information system (GIS) techniques. Journal of Geography and Regional Planning,5(5), 142–150. https://doi.org/10.5897/jgrp11.120.

    Article  Google Scholar 

  • Sarkar, D. (2018). Identification of channel migration behaviour and delineation of historical channel migration zone of Kulik river within the Barind tract of Indo-Bangladesh. Review of Research, 7(11). ISSN: 2249894X.

  • Schumm, S. (1956). Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geological Society of America Bulletin,67(5), 597. https://doi.org/10.1130/0016-7606(1956)67%5b597:eodsas%5d2.0.co;2.

    Article  Google Scholar 

  • Selvan, M. T., Ahmad, S., & Rashid, S. M. (2011). Analysis of the Geomorphometric parameters in high altitude Glacierised terrain using SRTM DEM data in Central Himalaya, India. ARPN Journal of Science and Technology,1(1), 22–27.

    Google Scholar 

  • Singh, S. (1998). Geomorphology. Allahabad: Prayag pustak bhawan.

    Google Scholar 

  • Singh, S. (2000). Geomorphology. Allahabad: Prayag Pustak Bhawan.

    Google Scholar 

  • Singh, S., & Dubey, A. (1994). Geoenvironmental planning of watersheds in India. Allahabad: Chugh.

    Google Scholar 

  • Singh, S., Kanhaiya, S., Singh, A., & Chaubey, K. (2018a). Drainage network characteristics of the Ghaghghar River Basin (GRB), Son Valley, India. Geology, Ecology, and Landscape. https://doi.org/10.1080/24749508.2018.1525670.

    Article  Google Scholar 

  • Singh, S., Kumar, S., Mittal, P., Kanhaiya, S., Prakash, P., & Kumar, R. (2018b). Drainage basin parameters of Bagh river, a sub-basin of Narmada river, Central India: Analysis and implications. Journal of Applied Geochemistry,20(1), 91–102.

    Google Scholar 

  • Singh, S., & Singh, M. C. (1997). Morphometric analysis of Kanhar river basin. National Geographical Journal of lndia,43(1), 31–43.

    Google Scholar 

  • Smith, K. (1950). Standards for grading texture of erosional topography. American Journal of Science,248(9), 655–668. https://doi.org/10.2475/ajs.248.9.655.

    Article  Google Scholar 

  • Soni, S. (2016). Assessment of morphometric characteristics of Chakrar watershed in Madhya Pradesh India using geospatial technique. Applied Water Science,7(5), 2089–2102. https://doi.org/10.1007/s13201-016-0395-2.

    Article  Google Scholar 

  • Sreedevi, P., Owais, S., Khan, H., & Ahmed, S. (2009). Morphometric analysis of a watershed of South India using SRTM data and GIS. Journal of the Geological Society of India,73(4), 543–552. https://doi.org/10.1007/s12594-009-0038-4.

    Article  Google Scholar 

  • Sreedevi, P., Sreekanth, P., Khan, H., & Ahmed, S. (2012). Drainage morphometry and its influence on hydrology in an semi arid region: Using SRTM data and GIS. Environmental Earth Sciences,70(2), 839–848. https://doi.org/10.1007/s12665-012-2172-3.

    Article  Google Scholar 

  • Sreedevi, P., Subrahmanyam, K., & Ahmed, S. (2004). The significance of morphometric analysis for obtaining groundwater potential zones in a structurally controlled terrain. Environmental Geology,47(3), 412–420. https://doi.org/10.1007/s00254-004-1166-1.

    Article  Google Scholar 

  • Sreedevi, P., Subrahmanyam, K., & Ahmed, S. (2005). Integrated approach for delineating potential zones to explore for groundwater in the Pageru River basin, Cuddapah District, Andhra Pradesh, India. Hydrogeology Journal,13(3), 534–543. https://doi.org/10.1007/s10040-004-0375-8.

    Article  Google Scholar 

  • Srinivasa Vittala, S., Govindaiah, S., & Honne Gowda, H. (2004). Morphometric analysis of sub-watersheds in the Pavagada area of Tumkur district, South India using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing,32(4), 351–362. https://doi.org/10.1007/bf03030860.

    Article  Google Scholar 

  • Srivastava, V. (1997). Study of drainage pattern of Jharia Coalfield (Bihar), India, through Remote Sensing technology. Journal of the Indian Society of Remote Sensing,25(1), 41–46. https://doi.org/10.1007/bf02995417.

    Article  Google Scholar 

  • Stefanidis, S., & Stathis, D. (2013). Assessment of food hazard based on natural and anthropogenic factors using analytical hierarchy process (AHP). Natural Hazards,68(2), 569–585. https://doi.org/10.1007/s11069-013-0639-5.

    Article  Google Scholar 

  • Strahler, A. (1952). Hypsometric (area-altitude) analysis of erosional topography. Geological Society Of America Bulletin,63(11), 1117. https://doi.org/10.1130/0016-7606(1952)63%5b1117:haaoet%5d2.0.co;2.

    Article  Google Scholar 

  • Strahler, A. (1957). Quantitative analysis of watershed geomorphology. Transactions, American Geophysical Union,38(6), 913. https://doi.org/10.1029/tr038i006p00913.

    Article  Google Scholar 

  • Strahler, A. (1958). Dimensional analysis applied to fluvially eroded landforms. Geological Society of America Bulletin,69(3), 279. https://doi.org/10.1130/0016-7606(1958)69%5b279:daatfe%5d2.0.co;2.

    Article  Google Scholar 

  • Strahler, A. N. (1964). Quantitative geomorphology of drainage basins and channel networks, section 4II. In V. T. Chow (Ed.), Handbook of applied hydrology. New York: McGraw Hill.

    Google Scholar 

  • Suresh, R. (2000). Soil and water conservation engineering, 3rd edn. 24. Watershed-concept and management, pp. 785–813

  • Talei, A., Chua, L. H. C., & Quek, C. (2010). A novel application of a neurofuzzy computational technique in event-based rainfall–runoff modeling. Expert Systems with Applications,37(12), 7456–7468.

    Google Scholar 

  • Tehrany, M. S., Lee, M. J., Pradhan, B., Jebur, M. N., & Lee, S. (2014a). Flood susceptibility mapping using integrated bivariate and multivariate statistical models. Environmental Earth Sciences,72, 4001–4015.

    Google Scholar 

  • Tehrany, M. S., Pradhan, B. M., & Jebur, M. N. (2013). Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology,504(2013), 69–79. https://doi.org/10.1016/j.jhydrol.2013.09.034.

    Article  Google Scholar 

  • Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2014b). Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. Journal of Hydrology,512, 332–343.

    Google Scholar 

  • Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2015a). Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stochastic Environmental Research and Risk Assessment,29, 1149–1165. https://doi.org/10.1007/s00477-015-1021-9.

    Article  Google Scholar 

  • Tehrany, M. S., Pradhan, B., Mansor, S., & Ahmad, N. (2015b). Flood susceptibility assessment using GIS-based support vector machine model with different kernel types. CATENA,125, 91–101.

    Google Scholar 

  • Tehrany, M. S., Shabani, F., Jebur, M. N., Hong, H., Chen, W., & Xie, X. (2017). GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques. Geomatics, Natural Hazards and Risk,8(2), 1538–1561. https://doi.org/10.1080/19475705.2017.1362038.

    Article  Google Scholar 

  • Tribhuvan, P. R., & Sonar, M. A. (2016). Morphometric analysis of a Phulambri River Drainage Basin (Gp8 Watershed), Aurangabad District (Maharashtra) using Geographical Information System. International Journal of Advanced Remote Sensing and GIS,5(1), 1813–1828. https://doi.org/10.23953/cloud.ijarsg.62.

    Article  Google Scholar 

  • Vandana, M. (2013). Morphometric analysis and watershed prioritization: A case study of Kabani river basin, Wayanad district, Kerala, India. Indian Journal of Geo-Marine Science,42, 211–222.

    Google Scholar 

  • Vincy, M., Rajan, B., & Pradeepkumar, A. (2012). Geographic information system–based morphometric characterization of sub-watersheds of Meenachil river basin, Kottayam district, Kerala, India. Geocarto International,27(8), 661–684. https://doi.org/10.1080/10106049.2012.657694.

    Article  Google Scholar 

  • Wang, L. J., Guo, M., Sawada, K., Lin, J., & Zhang, J. (2015). A comparative study of landslide susceptibility maps using logistic regression, frequency ratio, decision tree, weights of evidence and artificial neural network. Geoscience Journal. https://doi.org/10.1007/s12303-015-0026-1.

    Article  Google Scholar 

  • Withanage, W., Dayawansa, N. D. K., & De Silva, R. P. (2014). Morphometric analysis of the Gal Oya river basin using spatial data derived from GIS. Tropical Agricultural Research,26, 175–188.

    Google Scholar 

  • Wu, S. J., Lien, H. C., & Chang, C. H. (2010). Modeling risk analysis for forecasting peak discharge during flooding prevention and warning operation. Stochastic Environmental Research and Risk Assessment,24(8), 1175–1191.

    Google Scholar 

  • Yilmaz, I. (2009). Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat-Turkey). Computers & Geosciences,35, 1125–1138.

    Google Scholar 

  • Youssef, A. M., Pradhan, B., & Sefry, S. A. (2016). Flash flood susceptibility assessment in Jeddah city (Kingdom of Saudi Arabia) using bivariate and multivariate statistical models. Environmental Earth Sciences,75, 12. https://doi.org/10.1007/s12665-015-4830-8.

    Article  Google Scholar 

  • Yu, J., Qin, X., & Larsen, O. (2013). Joint Monte Carlo and possibilistic simulation for flood damage assessment. Stochastic Environmental Research and Risk Assessment,27(3), 725–735.

    Google Scholar 

  • Zou, Q., Zhou, J., Zhou, C., Song, L., & Guo, J. (2013). Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP. Stochastic Environmental Research and Risk Assessment,27(2), 525–546.

    Google Scholar 

Download references

Acknowledgements

The authors express their deepest gratitude to Dr. Gopal Chandra Debnath, Senior Fellow I.C.S.S.R, for helping in the present study.

Author information

Authors and Affiliations

  1. Department of Geography, Raiganj University, Raiganj, India

    Debabrata Sarkar, Prolay Mondal, Subhasish Sutradhar & Pranab Sarkar

Authors
  1. Debabrata Sarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prolay Mondal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Subhasish Sutradhar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pranab Sarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Debabrata Sarkar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarkar, D., Mondal, P., Sutradhar, S. et al. Morphometric Analysis Using SRTM-DEM and GIS of Nagar River Basin, Indo-Bangladesh Barind Tract. J Indian Soc Remote Sens 48, 597–614 (2020). https://doi.org/10.1007/s12524-020-01106-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12524-020-01106-7

Keywords

Search

Navigation