Water Resources Management

, Volume 22, Issue 10, pp 1325–1346 | Cite as

Spatial Distribution of Rainfall in Indian Himalayas – A Case Study of Uttarakhand Region



Continuous rainfall data in grid format are required to run models for hydrological and agricultural research as well as water resources planning and management. The present work attempts to prepare a normal annual rainfall map in Himalayan region of India lying in Uttarakhand state at 1 km spatial resolution which currently is not available. In the region, India Meteorological Department maintains observatories/raingauge stations and data from 44 stations were used in this study. A comparative analysis of interpolation techniques like Inverse Distance Weighted, Polynomial, Splines, Ordinary Kriging and Universal Kriging shows that Universal Kriging with hole-effect model and natural logarithmic transformation with constant trend having Root Mean Square Error (RMSE) of 328.7 is the best choice. This is followed by Ordinary Kriging (RMSE 329.1), Splines (RMSE 392.4), Inverse Distance Weighted (RMSE 409.8) and Polynomial Interpolation (RMSE 418.5). Cross validation of the results shows the largest over prediction at Tehri rainfall station (62.5%) and largest under prediction at Nainital station (−36.5%). Physiographic zone wise, the least errors occur in the plains and the largest in the Great Himalayas. The spatial average rainfalls are 1,472 mm for Terai/Bhabar, 1,782 mm for the Shivalik ranges, 1,591 mm for the Lesser Himalayas and 1,635 mm for the Great Himalayan region. The mean areal rainfall in the region is 1,608 mm.


Interpolation Kriging Rainfall distribution Himalaya Uttarakhand 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Arora M, Singh P, Goel NK, Singh RD (2006) Spatial distribution and seasonal variability of rainfall in a mountainous basin in the Himalayan region. Water Resour Manage 20:459–508CrossRefGoogle Scholar
  2. Barry RG (1981) Mountain weather and climate. Methuen & Co. Ltd, New YorkGoogle Scholar
  3. Brunsdon C, McClatchey J, Unwin DJ (2001) Spatial variations in the average rainfall–altitude relationship in Great Britain: an approach using geographically weighted regression. Int J Climatol 21:455–466CrossRefGoogle Scholar
  4. Burrough PA, McDonnel RA (1998) Principles of geographical information systems. Oxford University Press, New YorkGoogle Scholar
  5. Campling P, Gobin A, Feyen J (2001) Temporal and spatial rainfall analysis across a humid tropical catchment. Hydrol Process 15:359–375CrossRefGoogle Scholar
  6. Chang KT (2002) Introduction to geographic information systems. Tata McGraw Hill Publishing Company Limited, New DelhiGoogle Scholar
  7. Cheng SJ, Hsieh HH, Wang YM (2007) Geostatistical interpolation of space–time rainfall on Tamshui River basin, Taiwan. Hydrol Process 21:3136–3145CrossRefGoogle Scholar
  8. Chua SH, Bras RL (1982) Optimal estimators of mean areal precipitation in regions of orographic influence. J Hydrol 57:23–48CrossRefGoogle Scholar
  9. Climate of Uttar Pradesh (1989) India Meteorological Department, Govt. of India, Pune, p 380Google Scholar
  10. Creutin JD, Obled C (1982) Objective analyses and mapping techniques for rainfall fields: an objective comparison. Water Resour Res 18(2):413–431CrossRefGoogle Scholar
  11. Daly C (2006) Guidelines for assessing the suitability of spatial climate data sets. Int J Climatol 26:707–721CrossRefGoogle Scholar
  12. Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33(2):140–158CrossRefGoogle Scholar
  13. Daly C, Gibson WP, Taylor GH, Johnson GL, Pasteris P (2002) A knowledge-based approach to the statistical mapping of climate. Clim Res 22:99–113CrossRefGoogle Scholar
  14. Delfiner P, Delhomme JP (1973) Optimum interpolation by kriging. In: Davis JC, McCullagh MJ (eds) Display and analysis of spatial data. Nato Advanced Study Institute, John Wiley and Sons, LondonGoogle Scholar
  15. Delhomme JP (1978) Kriging in the hydrosciences. Adv Water Resour 1(5):251–266CrossRefGoogle Scholar
  16. Dhar ON, Bhattacharya BK (1976) Variation of rainfall with elevation in the Himalayas – a pilot study. Indian J Power River Val Dev XXVI(6):179–185Google Scholar
  17. Diodato N (2005) The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Int J Climatol 25:351–363CrossRefGoogle Scholar
  18. Dirks KN, Hay JE, Stow CD, Harris D (1998) High-resolution studies of rainfall on Norfolk Island, Part II: interpolation of rainfall data. J Hydrol 208(3–4):187–193CrossRefGoogle Scholar
  19. Goovaerts P (1997) Geostatistics for natural resources evaluation. Oxford University Press, New YorkGoogle Scholar
  20. Goovaerts P (1999) Performance comparison of geostatistical algorithms for incorporating elevation into the mapping of precipitation. Geocomputation 99. http://www.geovista.psu.edu/sites/geocomp99/Gc99/023/gc_023.htm. Accessed June 2004
  21. Goovaerts P (2000) Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J Hydrol 228:113–129CrossRefGoogle Scholar
  22. Guenni L, Hutchinson MF (1998) Spatial interpolation of the parameters of a rainfall model from ground based data. J Hydrol 212–213:335–347CrossRefGoogle Scholar
  23. Gyalistras D (2003) Development and validation of a high resolution monthly gridded temperature and precipitation data set for Switzerland (1951–2000). Clim Res 25:55–83CrossRefGoogle Scholar
  24. Hevesi JA, Flint AL, Istok JD (1992) Precipitation estimation in mountainous terrain using multivariate geostatistics. Part II: isohyetal maps. J Appl Meteorol 31:677–688CrossRefGoogle Scholar
  25. Higuchi K, Ageta Y, Yasunari T, Inoue J (1982) Characteristics of precipitation during the monsoon season in high-mountain areas of Nepal Himalaya. Hydrological Aspects of Alpine and High Mountain areas, IAHS Publication No. 138, 21–30Google Scholar
  26. Hutchinson MF, Gessler PE (1994) Splines – more than just a smooth interpolator. Geoderma 62:45–67CrossRefGoogle Scholar
  27. Hutchinson MF (1998) Interpolation of rainfall data with thin plate smoothing splines – Part I: Two dimensional smoothing of data with short range correlation. J Geogr Inf Decis Anal 2(2):139–151Google Scholar
  28. Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New YorkGoogle Scholar
  29. Johansson B, Chen D (2003) The influence of wind and topography on precipitation distribution in Sweden: statistical analysis and modelling. Int J Climatol 23:1523–1535CrossRefGoogle Scholar
  30. Johnston K, Jay M, Hoef V, Krivoruchko K, Lucas N (2001) Using ArcGIS geostatistical analyst, ESRIGoogle Scholar
  31. Joshi SC (2004) Uttaranchal: environment and development – a geo-ecological overview. Gyanodaya Prakashan, Nainital, Uttarakhand, p 426Google Scholar
  32. Kansakar SR, Hannah DM, Gerrard J, Rees G (2004) Spatial pattern in the precipitation regime of Nepal. Int J Climatol 24:1645–1659CrossRefGoogle Scholar
  33. Lebel T, Bastin G, Obled C, Creutin JD (1987) On the accuracy of areal rainfall estimation: a case study. Water Resour Res 23(11):2123–2134CrossRefGoogle Scholar
  34. Lloyd CD (2005) Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain. J Hydrol 308:128–150CrossRefGoogle Scholar
  35. Martinez-Cob A (1995) Estimation of mean annual precipitation as affected by elevation using multivariate geostatistics. Water Resour Manage 9:139–159CrossRefGoogle Scholar
  36. Martinez-Cob A (1996) Multivariate geostatistical analysis of evapotranspiration and precipitation in mountainous terrain. J Hydrol 174:19–35CrossRefGoogle Scholar
  37. Naoum, Tsanis (2003) Temporal and spatial variation of annual rainfall on the island of Crete, Greece. Hydrol Process 17:1899–1922CrossRefGoogle Scholar
  38. Naoum S, Tsanis IK (2004) Orographic precipitation modelling with multiple linear regression. J Hydrol Eng 9(2):79–102CrossRefGoogle Scholar
  39. Nguyen RT, Prentiss D, Shively JE (1998) Rainfall Interpolation for Santa Barbara County. http://www.geog.ucsb.edu/dylan/rainfall/rainfall.html. Accessed September 2004
  40. Papamichail DM, Metaxa IG (1996) Geostatistical analysis of spatial variability of rainfall and optimal design of a rain gauge network. Water Resour Manage 10:107–127CrossRefGoogle Scholar
  41. Philips DL, Dolph J, Marks D (1992) A comparison of geostatistical procedures for spatial analysis of precipitation in mountainous terrain. Agric For Meteorol 58:119–141CrossRefGoogle Scholar
  42. Price DT, McKenney DW, Nalder IA, Hutchinson MF, Kesteven JL (2000) A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data. Agric For Meteorol 101:81–94CrossRefGoogle Scholar
  43. Prudhomme C, Reed DW (1998) Relationships between extreme daily precipitation and topography in a mountainous region: a case study in Scotland. Int J Climatol 18:1439–1453CrossRefGoogle Scholar
  44. Prudhomme C, Reed DW (1999) Mapping extreme rainfall in a mountainous region using geostatistical techniques: a case study in Scotland. Int J Climatol 19:1337–1356CrossRefGoogle Scholar
  45. Rajagopalan B, Lall U (1998) Locally weighted polynomial estimation of spatial precipitation. J Geogr Inf Decis Anal 2(2):44–51Google Scholar
  46. Saveliev AA, Mucharamova SS, Piliugin GA (1998) Modeling of the daily rainfall values using surface under tension and kriging. J Geogr Inf Decis Anal 22:52–64Google Scholar
  47. Singh P, Kumar N (1997) Effect of orography on precipitation in the Western Himalayan Region. J Hydrol 199:183–206CrossRefGoogle Scholar
  48. Singh P, Ramasastri KS, Kumar N (1995) Topographical influence on precipitation distribution in different ranges of Westerns Himalayas. Nord Hydrol 26:259–284Google Scholar
  49. Skirvin SM, Marsh SE, McClaran MP, Meko D (2003) Climate spatial variability and data resolution in a semi-arid watershed, South-eastern Arizona. J Arid Environ 54:667–686CrossRefGoogle Scholar
  50. Subyani AM (2004) Geostatistical study of annual and seasonal mean rainfall patterns in the Southwest Saudi Arabia. Hydrol Sci J 49(5):803–817CrossRefGoogle Scholar
  51. Tabios GQ, Salas JD (1985) A comparative analysis of techniques for spatial interpolation of precipitation. Water Resour Bull, Am Water Resour Assoc 21(3):365–380CrossRefGoogle Scholar
  52. Tang C, Shindo S, Machida I (1998) Topographical effects on distributions of rainfall and 18O distributions: a case in Miyake Island, Japan. Hydrol Process 12:673–682CrossRefGoogle Scholar
  53. Thomas A, Herzfeld UC (2004) REGEOTOP: new climatic data fields for East Asia based on localized relief information and geostatistical methods. Int J Climatol 24:1283–1306CrossRefGoogle Scholar
  54. Tomczak M (1998) Spatial interpolation and its uncertainty using automated anisotropic Inverse Distance Weighting (IDW)-Cross-Validation/Jack knife Approach. J Geogr Inf Decis Anal 2(2):18–30Google Scholar
  55. Unwin DJ (1969) The areal extension of rainfall records: an alternative model. J Hydrol 7:404–414CrossRefGoogle Scholar
  56. Upadhyay, Bahadur (1982) On some hydro meteorological aspects of precipitation in Himalayas. Proc. International Symposium on Hydrological Aspects of Mountainous Watersheds, School of Hydrology, University of Roorkee, Manglik Prakashan, Saharanpur, U.P., Vol.-I, I-58–I-65Google Scholar
  57. Vicente-Serrano SM, Saz-Sanchez MA, Cuadrat JM (2003) Comparative analysis of interpolation methods in the Middle Ebro Valley (Spain): application to annual precipitation and temperature. Clim Res 24:161–180CrossRefGoogle Scholar
  58. Wei H, Li JL, Liang TG (2005) Study on the estimation of precipitation resources for rainwater harvesting agriculture in semi-arid land of China. Agric Water Manag 71:33–45CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.Department of HydrologyIndian Institute of Technology RoorkeeRoorkeeIndia

Personalised recommendations