Skip to main content
SpringerLink
Log in

Assessing Impact of Flood on River Dynamics and Susceptible Regions: Geomorphometric Analysis

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Natural climatic hazards like flood, an important hydro-geomorphic process of earth’s surface, have different regional and local impacts with significant socio-economic consequences. Similar was the case in Gujarat State, India during last week of June 2005. This study is about assessing the impact of Gujarat flood on river dynamics. It deals with extraction of water bodies information using radiance image and standard water indices i.e., Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) for pre- and post-flooding periods. Geomorphometric analysis along with drainage network extraction was done using two different Digital Elevation Models (DEMs) i.e., Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) and Shuttle Radar Topographic Mission (SRTM) and compared. Finally, depressions mapping and comparative analysis of magnitude and directional change of drainage networks was carried out. Results confirmed better accuracy of MNDWI in separating water bodies. The water bodies area increased by 10.4 % in post-flood monsoon compared to pre-flood monsoon and by 3.8 % in post-flood dry season compared to pre-flood dry season. Geomorphometric analysis indicated that ASTER DEM gave more values of maximum slope, average slope, and standard deviation as compared to SRTM. Aspects distribution algorithm did not work well in low relief regions. The drainage network generated using SRTM DEM was more accurate. The depressions identified were more susceptible to flood events. Change analysis of drainage network (deviating 100–300 m) indicated that 5.22 % points deviated between October, 2004 and 2005 and 3.18 % between February, 2005 and 2006.

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
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  • Beven KJ, Moore ID (eds) (1993) Terrain analysis and distributed modelling in hydrology. Advances in hydrological processes. Wiley, Chichester

    Google Scholar 

  • Bhagwat TN, Shetty A, Hegde VS (2011) Spatial variation in drainage characteristics and geomorphic instantaneous unit hydrograph (GIUH); implications for watershed management - a case study of the Varada River basin, Northern Karnataka. Catena 87(1):52–59

    Article  Google Scholar 

  • Bishop MP, Shroder JF (2004) Geographic information science and mountain geomorphology. Springer Praxis Books, Heidelberg, p 486

    Google Scholar 

  • Bishop MP, James LA, Shroder JF, Walsh SJ (2012) Geospatial technologies and digital geomorphological mapping: concepts, issues and research. Geomorphology 136:5–26

    Article  Google Scholar 

  • Chander G, Coan MJ, Scaramuzza PL (2008) Evaluation and comparison of the IRS-P6 and the Landsat sensors. IEEE Trans Geosci Remote Sens 46(1):209–221

    Article  Google Scholar 

  • Chen X, Vierling L, Deering D (2005) A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sens Environ 98:63–79

    Article  Google Scholar 

  • Frankel KL, Dolan JF (2007) Characterizing arid region alluvial fan surface roughness with airborne laser swath mapping digital topographic data. J Geophys Res 112, F02025. doi:10.1029/2006JF000644

    Google Scholar 

  • Gao B (1996) NDWI - a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens Environ 58:257–266

    Article  Google Scholar 

  • Guth PL (1995) Slope and aspect calculations on gridded digital elevation models: examples from a geomorphometric toolbox for personal computers. Z Geomorphol NF Suppl Band 101:31–52

    Google Scholar 

  • Henshaw AJ, Gurnell AM, Bertoldi W, Drake NA (2013) An assessment of the degree to which Landsat TM data can support the assessment of fluvial dynamics, as revealed by changes in vegetation extent and channel position, along a large river. Geomorphology. doi:10.1016/j.geomorph.2013.01.011

    Google Scholar 

  • Hutchinson MF, Gallant JC (2000) Digital elevation models and representation of terrain shape. In: Wilson JP, Gallant JC (eds) Terrain analysis: principles and applications. Wiley, New York, pp 51–85

    Google Scholar 

  • Jackson T, Chen D, Cosh M, Li F, Anderson M, Walthall C, Doriaswamy P, Hunt ER (2004) Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sens Environ 92:475–482

    Article  Google Scholar 

  • James LA, Watson DG, Hansen WF (2007) Using LiDAR data to map gullies and headwater streams under forest canopy: South Carolina, USA. Catena 71:132–144

    Article  Google Scholar 

  • Jensen JR (2007) Remote sensing of the environment: an earth resource perspective, 2nd edn. Prentice-Hall, Upper Saddle River, p 592

    Google Scholar 

  • Ji L, Zhang L, Wylie B (2009) Analysis of dynamic thresholds for the Normalized Difference Water Index. Photogramm Eng Remote Sens 75:1307–1317

    Article  Google Scholar 

  • Jones AF, Brewer PA, Johnstone E, Macklin MG (2007) High-resolution interpretative geomorphological mapping of river valley environments using airborne LiDAR data. Earth Surf Process Landf 32:1574–1592

    Article  Google Scholar 

  • Kundzewicz ZW, Hirabayashi Y, Kanae S (2009) River floods in the changing climate -observations and projections. Water Resour Manag 24(11):2633–2646

    Article  Google Scholar 

  • Lacaux JP, Tourre YM, Vignolles C, Ndione JA, Lafaye M (2007) Classification of ponds from high-spatial resolution remote sensing: application to rift valley fever epidemics in Senegal. Remote Sens Environ 106(1):66–74

    Article  Google Scholar 

  • Leica Geosystems (2008) ERDAS field guide, vol 2. Leica Geosystems Geospatial Imaging, LLC, Norcross, p 384

    Google Scholar 

  • Mark DM (1984) Automatic detection of drainage networks from digital elevation models. Cartographica 21:168–178

    Article  Google Scholar 

  • Martz LW, Garbrecht J (2007) Automated extraction of drainage network and watershed data from digital elevation models. J Am Water Resour Assoc 29:901–908

    Article  Google Scholar 

  • Mason DC, Scott TR, Wang HJ (2006) Extraction of tidal channel networks from airborne scanning laser altimetry. ISPRS J Photogramm Remote Sens 61:67–83

    Article  Google Scholar 

  • McFeeters SK (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens 17:1425–1432

    Article  Google Scholar 

  • Ministry of Water Resources (2002) National water policy. Ministry of Water Resources, Government of India, New Delhi, p 10

    Google Scholar 

  • Mukherjee S, Joshi PK, Mukherjee S, Ghosh A, Garg RD, Mukhopadhyay A (2013) Evaluation of vertical accuracy of open source Digital Elevation Model (DEM). Int J Appl Earth Obs Geoinf 21:205–217

    Article  Google Scholar 

  • Notebaert B, Verstraeten G, Govers G, Poesen J (2009) Qualitative and quantitative applications of LiDAR imagery in fluvial geomorphology. Earth Surf Process Landf 34:217–231

    Article  Google Scholar 

  • Ozdemir H, Bird D (2009) Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods. Environ Geol 56:1405–1415

    Article  Google Scholar 

  • Patel DP, Srivastava PK (2013) Flood hazards mitigation analysis using remote sensing and GIS: correspondence with town planning scheme. Water Resour Manag 27:2353–2368

    Article  Google Scholar 

  • Reddy GPO, Maji A, Gajbhiye KS (2004) Drainage morphometry and its influence on landform characteristics in basaltic terrain, central India—a remote sensing and GIS approach. Int J Appl Earth Obs Geoinf 6:1–16

    Article  Google Scholar 

  • Robinove CJ (1982) Computation with physical values from Landsat digital data. Photogramm Eng Remote Sens 48(5):781–784

    Google Scholar 

  • Saran S, Sterk G, Peters P, Dadhwal VK (2010) Evaluation of digital elevation model for delineation of hydrological response units in a Himalayan Watershed. Geocarto Int 25:105–122

    Article  Google Scholar 

  • Schroeder TA, Cohen WB, Song C, Canty MJ, Yang Z (2006) Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon. Remote Sens Environ 103:16–26

    Article  Google Scholar 

  • Serra P, Pons X, Saurí D (2008) Land-cover and land-use change in a Mediterranean landscape: a spatial analysis of driving forces integrating biophysical and human factors. Appl Geogr 28:189–209

    Article  Google Scholar 

  • Sharma CS, Behera MD, Mishra A, Panda SN (2011) Assessing flood induced landcover changes using remote sensing and fuzzy approach in eastern Gujarat (India). Water Resour Manag 25(13):3219–3246

    Article  Google Scholar 

  • Song C, Woodcock CE, Seto KC, Lenney MP, Macomber SA (2001) Classification and change detection using Landsat TM data: when and how to correct atmospheric effects? Remote Sens Environ 75(2):230–244

    Article  Google Scholar 

  • Strahler AN (1952) Hypsometric (area-altitude) analysis of erosional topography. Geol Soc Am Bull 63:1117–1141

    Article  Google Scholar 

  • Thomas J, Sabu J, Thrivikramaji KP (2010) Morphometric aspects of a small tropical mountain river system, the Southern Western Ghats, India. Int J Digit Earth 3:135–156

    Article  Google Scholar 

  • Thomas J, Joseph S, Thrivikramji K, Abe G, Kannan N (2012) Morphometrical analysis of two tropical mountain river basins of contrasting environmental settings, the southern Western Ghats. India. Environ Earth Sci 66(8):2353–2366

    Article  Google Scholar 

  • Tribe A (1992) Automated recognition of valley lines and drainage networks from grid digital evolution models: a review and a new method. J Hydrol 139:263–293

    Article  Google Scholar 

  • Wilson JP (2012) Digital terrain modeling. Geomorphology 137:107–121

    Article  Google Scholar 

  • Wilson JP, Gallant JC (eds) (2000) Terrain analysis: principles and applications. Wiley, New York

    Google Scholar 

  • Wu S, Li J, Huang GH (2008) Characterization and evaluation of elevation data uncertainty in water resources modeling with GIS. Water Resour Manag 22:959–972

    Article  Google Scholar 

  • Xu H (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27:3025–3033

    Article  Google Scholar 

  • Zhang W, Montgomery DR (1994) Digital elevation model grid size, landscape representation, and hydrologic simulation. Water Resour Res 30(4):1019–1028

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Agricultural and Food Engineering, Indian Institute of Technology, Kharagpur, 721 302, West Bengal, India

    C. S. Sharma

  2. International Water Management Institute, Southern Africa Office, 141, Cresswell Street, Weavind Park, Silverton, Pretoria, South Africa

    A. Mishra

  3. Division of Climatology and Water Resources, Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori, 680-0001, Japan

    S. N. Panda

Authors
  1. C. S. Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Mishra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. N. Panda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Mishra.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sharma, C.S., Mishra, A. & Panda, S.N. Assessing Impact of Flood on River Dynamics and Susceptible Regions: Geomorphometric Analysis. Water Resour Manage 28, 2615–2638 (2014). https://doi.org/10.1007/s11269-014-0630-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-014-0630-2

Keywords

Search

Navigation