Application of hydrological indices for erosion hazard mapping using Spatial Analyst tool

  • Imran Ahmad
  • Mithas Ahmad DarEmail author
  • Afera Halefom Teka
  • Tesfa Gebre
  • Ebissa Gadissa
  • Asirat Teshome Tolosa


Hydrological indices provide excellent input to geographic information systems for the successful mapping of erosion-prone areas. In this research, a digital elevation model was processed and analyzed to obtain the necessary hydrological indices necessary for erosion modeling. The indices (such as sediment transport index, compound topography index, and stream power index) along with other themes (Like Slope gradient, curvature, distance to channels, and channel density) were overlaid using the “Weighted Sum” overlay tool in the geographic information system. The results showed that 33.14 km2 of the test watershed (sub-basin of Abay, Ethiopia) falls in very high/severe erosion zone and needs immediate conservation measures. A total of 98.26 km2, 153.40 km2, and 263.17 km2 fall in high-, moderate-, and low-erosion hazard zones, respectively. Therefore, the primary and secondary derivatives of the digital elevation model along with morphometric parameters coupled with a Spatial Analyst tool proves to be a powerful integrated approach in demarcating erosion vulnerable zones and could be applied at regional and continental scale for proper watershed management.


Abay basin Erosion modeling Hydrologic indices Sediment transport index Stream power index 



  1. Ahmad, I. (2018). Digital elevation model (DEM) coupled with geographic information system (GIS): an approach towards erosion modeling of Gumara watershed, Ethiopia. Environmental Monitoring and Assessment, 190, 568. Scholar
  2. Burt, T., & Butcher, D. (1986). Stimulation from simulation: a teaching model of hillslope hydrology for use on microcomputers. Journal of Geography in Higher Education, 10, 23–39.CrossRefGoogle Scholar
  3. Chen, T., Niu, R. Q., Li, P. X., Zhang, L. P., & Du, B. (2011). Regional soil erosion risk mapping using RUSLE, GIS, and remote sensing: a case study in Miyun watershed. North China. Environmental Earth Sciences, 63, 533–541.CrossRefGoogle Scholar
  4. Dabral, P. P., Baithuri, N., & Pandey, A. (2008). Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Resources Management, 22(12), 1783–1798.CrossRefGoogle Scholar
  5. Dymond, J. R., & Harmsworth, G. R. (1994). Towards automated land resource mapping using digital models. ITC Journal, 2, 129–138.Google Scholar
  6. Eswaran, H., Lal, R., & Reich, P. F. (2001). Land degradation: an overview. In E. M. Bridges, I. D. Hannam, L. R. Oldeman, F. W. T. Penning-de-Vries, S. J. Scherr, & S. Sombatpanit (Eds.), Response to land degradation (pp. 20–35). Enfield, NH, USA: Science Publishers Inc..Google Scholar
  7. Lal, R. (2001). Soil degradation by erosion. Land Degradation and Development, 12(6), 519–539.CrossRefGoogle Scholar
  8. Lehmann J. G. (1816). Die Lehre der Situation- Zeichnung, oder Anweisung zum richtigen Erkennen und genauen Abbilden der Erdoberfläche in topographischen Karten und Situation-Planen.Google Scholar
  9. Lin, S., Jing, C., Coles, N. A., Chaplot, V., Moore, N. J., & Wu, J. (2013). Evaluating DEM source and resolution uncertainties in the Soil and Water Assessment Tool. Stochastic Environmental Research and Risk Assessment, 27(1), 209–221.CrossRefGoogle Scholar
  10. Mondal, A., Khare, D., Kundu, S., Meena, P. K., Mishra, P. K., & Shukla, R. (2014). Impact of climate change on future soil erosion in different slope, land use, and soil-type conditions in a part of the Narmada River Basin. India Journal of Hydrologic Engineering, 20, C5014003. Scholar
  11. Moore, I. D., Grayson, R. B., & Ladson, A. R. (1991). Digital terrain modeling: a review of hydrological, geomorphological, and biological applications. Hydrological Processes, 5, 3–30.CrossRefGoogle Scholar
  12. Moore, I. D., Gessler, P. E., Nielsen, G. A., & Peterson, G. A. (1993). Soil attribute prediction using terrain analysis (Vol. 57, pp. 443–452). Soil Science Society of America Journal.Google Scholar
  13. Pan, J., & Wen, Y. (2014). Estimation of soil erosion using RUSLE in Caijiamiao watershed, China. Natural Hazards, 71(3), 2187–2205. CrossRefGoogle Scholar
  14. Smith, M. J., Goodchild, M. F., Longley, P. A. (2012) Geospatial analysis: a comprehensive guide, Electronic book.
  15. Vrieling, A., (2007) Mapping erosion from space. Ph.D. Thesis Wageningen University, Germany, ISBN 978–90-8504-587-8.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Hydraulic and Water Resources EngineeringDebre Tabor UniversityDebre TaborEthiopia
  2. 2.Department for Management of Science and Technology DevelopmentTon Duc Thang UniversityHo Chi Minh CityVietnam
  3. 3.Faculty of Environment and Labour SafetyTon Duc Thang UniversityHo Chi Minh CityVietnam

Personalised recommendations