HAND (height above nearest drainage) tool and satellite-based geospatial analysis of Hyderabad (India) urban floods, September 2016

  • C. M. BhattEmail author
  • G. Srinivasa Rao
Original Paper


Urban flooding needs to be understood holistically and addressed geospatially by all stakeholders. In the present study, an attempt is made to understand the problem of urban flooding in part of Hyderabad city (Zone-12) geospatially considering the satellite-based changes in land use/land cover between 1989 and 2016, identifying low-lying areas vulnerable to flooding using HAND (height above nearest drainage) model in conjunction with the analysis of high-resolution satellite images and ground based validation of affected locations during rains of September 2016. The study shows that Zone-12 has undergone significant increase in impervious cover by 42% between 1989 and 2016. The impact of urbanization has obliterated the footprints of stream network, significantly changing the hydrological landscape due to burial of channels and concretization of lake beds. The interconnected channel network and lake system acting as sinks to absorb high runoff during monsoons have been encroached upon aggravating the urban flooding problem. The study shows that HAND model can be an effective tool under data scarce environments, limited cloud-free high-resolution satellite data availability during floods to have first cut baseline information on flood vulnerable areas.


Urban HAND SRTM Satellite Floods Hyderabad 


  1. Alaghmand S, Bin Abdullah R, Abustan I, Vosoogh B (2010) GIS-based river flood hazard mapping in urban area (a case study in Kayu Ara River Basin, Malaysia). Int J Eng Technol 2(6):488–500Google Scholar
  2. Badarinath KVS, Chand TK, Madhavilatha K, Raghavaswamy V (2005) Studies on urban heat islands using ENVISAT AATSR data. J Indian Soc Remote Sens 33(4):495–501CrossRefGoogle Scholar
  3. Campana NA, Tucci EMC (2001) Predicting floods from urban development scenarios: case study of the Diluvio basin, Porto Alegre, Brazil. Urban water 3:113–124CrossRefGoogle Scholar
  4. Chavez PS (1996) Image-based atmospheric corrections-revisited and improved. Photogramm Eng Remote Sens 62(9):1025–1035Google Scholar
  5. Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ 37(1):35–46CrossRefGoogle Scholar
  6. Di Baldassarre G, Uhlenbrook S (2012) Is the current flood of data enough? A treatise on research needs for the improvement of flood modelling. Hydrol Process 26(1):153–158CrossRefGoogle Scholar
  7. Duan W, He B, Nover D, Fan J, Yang G, Chen W, Meng H, Liu C (2016) Floods and associated socioeconomic damages in China over the last century. Nat Hazards 82:401–413CrossRefGoogle Scholar
  8. Elmore AJ, Kaushal SS (2008) Disappearing headwaters: patterns of stream burial due to urbanization. Front Ecol Environ 6:308–312CrossRefGoogle Scholar
  9. Gupta K (2016) Issues of urban drainage—present status and the way forward. In: Urban hydrology, watershed management and socio-economic aspects. Springer International Publishing, pp 29–33Google Scholar
  10. Gupta AK, Nair SS (2011) Urban floods in Bangalore and Chennai: risk management challenges and lessons for sustainable urban ecology. Curr Sci:1638–1645Google Scholar
  11. Hagen E, Teufert JF (2009) Flooding in Afghanistan: A crisis. In Threats to Global Water Security. Springer, Dordrecht, p 179–185CrossRefGoogle Scholar
  12. Hagen E, Shroder JF, Lu XX, Teufert JF (2010) Reverse engineered flood hazard mapping in Afghanistan: a parsimonious flood map model for developing countries. Quat Int 226:82–91. CrossRefGoogle Scholar
  13. Horritt MS, Bates PD (2001) Predicting floodplain inundation: raster-based modelling versus the finite-element approach. Hydrol Process 15:825–842CrossRefGoogle Scholar
  14. Huang HJ, Cheng SJ, Wen JC, Lee JH (2008) Effect of growing watershed imperviousness on hydrograph parameters and peak discharge. Hydrol Process 22:2075–2085CrossRefGoogle Scholar
  15. Hunter NM, Bates PD, Horritt MS, Wilson MD (2007) Simple spatially distributed models for predicting flood inundation: a review. Geomorphology 90:208–225CrossRefGoogle Scholar
  16. Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogramm Eng Remote Sens 54(11):1593–1600Google Scholar
  17. Laituri M, Kodrich K (2008) On line disaster response community: people as sensors of high magnitude disasters using internet GIS. Sensors 8(5):3037–3055CrossRefGoogle Scholar
  18. Lillesand T, Kiefer RW, Chipman J (2015) Remote sensing and image interpretation, 7th ed. Wiley. ISBN: 978-1-118-34328-9Google Scholar
  19. Manfré LA, Hirata E, Silva JB, Shinohara EJ, Giannotti MA, Larocca APC, Quintanilha JA (2012) An analysis of geospatial technologies for risk and natural disaster management. ISPRS Int J Geo-Information 1(2):166–185CrossRefGoogle Scholar
  20. Nirupama N, Simonovic SP (2007) Increase of flood risk due to urbanization: a Canadian example. Nat Hazards 40:25–41CrossRefGoogle Scholar
  21. Nobre AD, Cuartas LA, Hodnett M, Rennó C, Rodrigues GO, Silveira A, Waterloo M, Saleska S (2011) Height above the nearest drainage–a hydrologically relevant new terrain model. J Hydrol 404:13–29. CrossRefGoogle Scholar
  22. O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vis Graphics Image Process 28(3):323–344CrossRefGoogle Scholar
  23. O’Driscoll M, Clinton S, Jefferson A, Manda A, McMillan S (2010) Urbanization effects on watershed hydrology and in-stream processes in the southern United States. Water 2(3):605–648CrossRefGoogle Scholar
  24. Ouma YO, Tateishi R (2014) Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: methodological overview and case study assessment. Water 6(6):1515–1545CrossRefGoogle Scholar
  25. Pulvirenti L, Chini M, Pierdicca N, Boni G (2016) Use of SAR data for detecting floodwater in urban and agricultural areas: the role of the interferometric coherence. IEEE Trans Geosci Remote Sens 54(3):1532–1544CrossRefGoogle Scholar
  26. Rabindra O, Shigenobu T, Tooshikazu T (2008) Flood hazard mapping in developing countries: problems and prospects. Disaster Prev Manag 17:104113. CrossRefGoogle Scholar
  27. Ramachandraiah C, Prasad S (2004) Impact of urban growth on water bodies: the case of Hyderabad. Centre for Economic and Social Studies, HyderabadGoogle Scholar
  28. Rennó CD, Nobre AD, Cuartas LA, Soares JV, Hodnett MG, Tomasella J, Waterloo MJ (2008) HAND, a new terrain descriptor using SRTM-DEM: mapping terra-firme rainforest environments in Amazonia. Remote Sens Environ 112(9):3469–3481CrossRefGoogle Scholar
  29. Saghafian B, Farazjoo H, Bozorgy B, Yazdandoost F (2008) Flood intensification due to changes in land use. Water Resour Manag 22:1051–1067CrossRefGoogle Scholar
  30. Shaw R, Izumi T, Shiwaku K (2018) Science and technology in disaster risk reduction in Asia: post Sendai developments. In Science and technology in disaster risk reduction in Asia, pp 3–16CrossRefGoogle Scholar
  31. Sheng J, Wilson JP (2009) Watershed urbanization and changing flood behavior across the Los Angeles metropolitan region. Nat Hazards 48(1):41–57CrossRefGoogle Scholar
  32. United Nations (2008) United Nations expert group meeting on population distribution, urbanization, internal migration and development. United Nations Population Division.
  33. United Nations (2014) World urbanization prospects: the 2014 revision. United Nations Publication, New York CrossRefGoogle Scholar
  34. Xu Z, Zhao G (2016) Impact of urbanization on rainfall-runoff processes: case study in the Liangshui River Basin in Beijing, China. Proc Int Assoc Hydrol Sci 373:7–12Google Scholar
  35. Werner MGF (2004) Spatial flood extent modelling. A performance based comparison. PhD Thesis. Delft University Press, p 191Google Scholar

Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  1. 1.Indian Institute of Remote Sensing (IIRS) Campus, Indian Space research Organization (ISRO), Department of Space, Government of IndiaDehradunIndia
  2. 2.Regional Remote Sensing Centre – East, NRSC, ISROKolkataIndia

Personalised recommendations