Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin, Western Ghats, India

Abstract

In this study, the effects of changes in historical and projected land use land cover (LULC) on monthly streamflow and sediment yield for the Netravati river basin in the Western Ghats of India are explored using land use maps from six time periods (1972, 1979, 1991, 2000, 2012, and 2030) and the soil and water assessment tool (SWAT). The LULC for 2030 is projected using the land change modeller with the assumption of normal growth. The sensitivity analysis, model calibration, and validation indicated that the SWAT model could reasonably simulate streamflow and sediment yield in the river basin. The results showed that the spatial extent of the LULC classes of urban (1.80–9.96%), agriculture (31.38–55.75%), and water bodies (1.48–2.66%) increased, whereas that of forest (53.04–27.03%), grassland (11.17–4.41%), and bare land (1.09–0.16%) decreased from 1972 to 2030. The streamflow increased steadily (7.88%) with changes in LULC, whereas the average annual sediment yield decreased (0.028%) between 1972 and 1991 and increased later (0.029%) until 2012. However, it may increase by 0.43% from 2012 to 2030. The results indicate that LULC changes in urbanization and agricultural intensification have contributed to the increase in runoff, amounting to 428.65 and 58.67 mm, respectively, and sediment yield, amounting to 348 and 43 ton/km2, respectively, in the catchment area from 1972 to 2030. The proposed methodology can be applied to other river basins for which temporal digital LULC maps are available for better water resource management plans.

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References

  1. Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J et al (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333(2):413–430

    Article  Google Scholar 

  2. Abbaspour KC, Rouholahnejad E, Vaghefi S, Srinivasan R, Yang H, Kløve B (2015) A continental-scale hydrology and water quality model for Europe: calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 524:733–752

    Article  Google Scholar 

  3. Aichele SS (2005) Effects of urban land-use change on streamflow and water quality in Oakland County, Michigan, 1970–2003, as inferred from urban gradient and temporal analysis. US geological survey scientific investigations report 2005-5016

  4. Bagnold RA (1977) Bedload transport in natural rivers. Water Resour Res 13(2):303–312

    Article  Google Scholar 

  5. Bhagyanagar R, Kawal BM, Dwarakish GS, Surathkal S (2012) Land use/land cover change and urban expansion during 1983–2008 in the coastal area of Dakshina Kannada district, South India. J Appl Remote Sens 6(1):063576-1

    Article  Google Scholar 

  6. Cai T, Li Q, Yu M, Lu G, Cheng L, Wei X (2011) Investigation into the impacts of land-use change on sediment yield characteristics in the upper Huaihe River basin, China. Phys Chem Earth 53–54:1–9

    Google Scholar 

  7. De Girolamo AM, Lo Porto A, Pappagallo G, Tzoraki O, Gallart F (2015) The hydrological status concept: application at a temporary river (Candelaro, Italy). River Res Appl 31(7):892–903

    Article  Google Scholar 

  8. Deng Z, Zhang X, Li D, Pan G (2015) Simulation of land use/land cover change and its effects on the hydrological characteristics of the upper reaches of the Hanjiang basin. Environ Earth Sci 73(3):1119–1132

    Article  Google Scholar 

  9. Dooge JCI (1992) Hydrologic model and climate change. J Geophys Res 97(D3):2677–2686

    Article  Google Scholar 

  10. EAWAG (2007) SWAT-CUP (2012): SWAT calibration and uncertainty programs—a user manual. Swiss Federal Institute of Aquatic Science and Technology, Switzerland

  11. FAO/IIASA/ISRIC/ISSCAS/JRC (2012) Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria

  12. Faramarzi M, Abbaspour KC, Schulin R, Yang H (2009) Modeling blue and green water availability in Iran. Hydrol Process 23(3):486–501

    Article  Google Scholar 

  13. Franczyk J, Chang H (2009) The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA. Hydrol Process 23(6):805–815

    Article  Google Scholar 

  14. Fukhrudin KM, Assefs MM, Patrick B, Karen BG (2013) Modeling the impact of land use changes on runoff and sediment yield in the Le Sueur watershed, Minnesota using GeoWEPP. Catena 107:35–45

    Article  Google Scholar 

  15. Hao FH, Cheng LQ, Liu CM, Dai D (2004) Impact of land use change on runoff and sediment yield. J Soil Water Conserv 18(3):5–8

    Google Scholar 

  16. Jayanth J, Kumar AT, Koliwad S, Krishnashastry S (2015) Identification of land cover changes in the coastal area of Dakshina Kannada district, South India during the year 2004–2008. Egypt J Remote Sens Space Sci 19:73–93

    Google Scholar 

  17. Jensen JR (2005) Introductory digital image processing: a remote sensing perspective, 3rd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  18. Jha CS, Dutt CBS, Bawa KS (2000) Deforestation and land use changes in Western Ghats, India. Curr Sci 79(2):231–238

    Google Scholar 

  19. Krause P (2002) Quantifying the impact of land use changes on the water balance of large catchments using the J2000 model. Phys Chem Earth Parts A/B/C 27(9):663–673

    Article  Google Scholar 

  20. Kumar A, Jayappa KS, Deepika B (2010) Application of remote sensing and geographic information system in change detection of the Netravati and Gurpur river channels, Karnataka, India. Geocarto Int 25(5):397–425

    Article  Google Scholar 

  21. Li X, Yeh AGO (2000) Modelling sustainable urban development by the integration of constrained cellular automata and GIS. Int J Geogr Inf Sci 14(2):131–152

    Article  Google Scholar 

  22. Melih O, Nadim KC, Ali KS (2013) Modeling the impact of land use change on the hydrology of a rural watershed. J Hydrol 497:97–109

    Article  Google Scholar 

  23. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

    Article  Google Scholar 

  24. Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858

    Article  Google Scholar 

  25. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) SWAT user manual, version 2009. Texas Water Resources Institute, Technical report. A and M University, Texas, USA

  26. Nie WM, Yuan YP, Kepner W, Nash MS, Jackson M, Erickson C (2011) Assessing impacts of landuse changes on hydrology for the upper San Pedro watershed. J Hydrol 407:105–114

    Article  Google Scholar 

  27. Niraula R, Meixner T, Norman LM (2015) Determining the importance of model calibration for forecasting absolute/relative changes in streamflow from LULC and climate changes. J Hydrol 522:439–451

    Article  Google Scholar 

  28. Noorazuan MH, Rainis R, Juahir H, Zain SM, Jaafar N (2003) GIS application in evaluating land use-land cover change and its impact on hydrological regime in Langat River basin, Malaysia. In: 2nd annual Asian conference of map Asia, pp 14–15

  29. Orr HG, Carling PA (2006) Hydro-climatic and land use changes in the River Lune catchment, North West England, implications for catchment management. River Res Appl 22(2):239–255

    Article  Google Scholar 

  30. Putty MRY, Prasad R (2000) Runoff processes in headwater catchments—an experimental study in Western Ghats, South India. J Hydrol 235(1):63–71

    Article  Google Scholar 

  31. Roth V, Nigussie TK, Lemann T (2016) Model parameter transfer for streamflow and sediment loss prediction with SWAT in a tropical watershed. Environ Earth Sci 75(19):1321

    Article  Google Scholar 

  32. Saxton KE, Rawls WJ (2006) Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci Soc Am J 70:1569–1578

    Article  Google Scholar 

  33. USDA SCS (1972) National engineering handbook section 4. Hydrology

  34. Van Griensven A, Meixner T, Grunwald S, Bishop T, Diluzio M, Srinivasan R (2006) A global sensitive analysis tool for the parameters of multi variable catchment models. J Hydrol 324:10–23

    Article  Google Scholar 

  35. Weng Q (2002) Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. J Environ Manag 64(3):273–284

    Article  Google Scholar 

  36. Williams JR (1995) The EPIC model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publication, Highlands Ranch, pp 909–1000

    Google Scholar 

  37. Wilson CO, Weng Q (2011) Simulating the impacts of future land use and climate changes on surface water quality in the Des Plaines River watershed, Chicago Metropolitan Statistical Area, Illinois. Sci Total Environ 409(20):4387–4405

    Article  Google Scholar 

  38. Woldesenbet TA, Elagib NA, Ribbe L, Heinrich J (2016) Hydrological responses to land use/cover changes in the source region of the Upper Blue Nile Basin, Ethiopia. Sci Total Environ 575:724–741

    Article  Google Scholar 

  39. Wolfram S (1998) Cellular automata as models of complexity. In: Nonlinear physics for beginners: fractals, chaos, solitons, pattern formation, cellular automata, complex systems, vol 311, p 197

  40. Wu X, Hu Y, He HS, Bu R, Onsted J, Xi F (2009) Performance evaluation of the SLEUTH model in the Shenyang metropolitan area of north eastern China. Environ Model Assess 14(2):221–230

    Article  Google Scholar 

  41. Xu ZX, Pang JP, Liu CM, Li JY (2009) Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model. Hydrol Process 23:3619–3630

    Article  Google Scholar 

  42. Yan B, Fang NF, Zhang PC, Shi ZH (2013) Impact of land use change on watershed stream flow and sediment yield: an assessment using hydrologic modeling and Partial least regression. J Hydrol 484:26–37

    Article  Google Scholar 

  43. Yesuf HM, Assen M, Alamirew T, Melesse AM (2015) Modeling of sediment yield in Maybar gauged watershed using SWAT, northeast Ethiopia. Catena 127:191–205

    Article  Google Scholar 

  44. Zhang HJ, Cheng JH, Chen ZW (2007) Effect of forest variety on runoff and sediment in the three Gorge Region of Yangtze River. Res Soil Water Conserv 14:1–6

    Google Scholar 

Download references

Acknowledgements

The authors acknowledge the Department of Science and Technology (DST) for financial support to this study. The first author is sincerely thankful to Prof. Subimal Ghosh for his suggestions, helps, and valuable guidance and also thanks to Dr. K. G. Sreeja for her invaluable support. We wish to express our sincere gratitude to Central Water Commission and Indian Meteorological Department, India, for providing hydrological and meteorological data. Authors express their sincere thanks to the reviewers for the valuable comments, which significantly improved the manuscript.

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Correspondence to T. I. Eldho.

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Sinha, R.K., Eldho, T.I. Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin, Western Ghats, India. Environ Earth Sci 77, 111 (2018). https://doi.org/10.1007/s12665-018-7317-6

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Keywords

  • Land use/land cover
  • River basin
  • Streamflow
  • Sediment yield
  • Modelling