Paper Titles in Periodical
International Letters of Chemistry, Physics and Astronomy
Volume 54

Subscribe

Subscribe to our Newsletter and get informed about new publication regulary and special discounts for subscribers!

ILCPA > Volume 54 > Temporal and Spatial Dynamics of Rainfall in...
Temporal and Spatial Dynamics of Rainfall in Satluj River Basin, Himachal Pradesh, India
< Back to Volume

Temporal and Spatial Dynamics of Rainfall in Satluj River Basin, Himachal Pradesh, India

Full Text PDF

Abstract:

Temporally and Spatially distributed measurements of precipitation have gained renewed interest in connection with climate change impact studies. The complex relationship between topography and precipitation in mountainous regions such as Himalayas is evident from the pattern of rainfall distribution. The variation in precipitation with altitude is controlled by mean height of clouds and decrease in water vapours with altitude. Precipitation values are usually available from a limited number of gauge stations and their spatial estimates can be obtained by interpolation techniques such as Inverse Distance Weighted (IDW), Kriging and Spline. In the present study, precipitation-elevation relationship can be established using Digital Elevation Model (DEM) (Advanced Spaceborne Thermal Emission and Reflection Radiometer-ASTER, 30m resolution), Spline interpolation technique in Geographical Information System (GIS) environment and point data from various gauge stations spread over the Satluj River Basin. Changes of spatial distribution of precipitation with elevation show a distinct shift. Bhakra Dam to Rampur, there is continuous variation in rainfall with increase in altitude. But beyond Rampur, variation is very high. Swarghat shows exceptional rainfall, may be due to position of mountains and their orographic effects. Maximum rainfall was observed in the lower Himalayas i.e. Shiwalik range. Negligible rainfall was observed beyond, above the elevation of around 3756 m. The general trend of rainfall exhibits that the lower and middle parts experience good rainfall whereas the upper part experiences less rainfall. Such spatial and temporal distribution of rainfall with elevation provides an important platform for hydrologic analysis, planning and management of water resources.

Info:

Periodical:
International Letters of Chemistry, Physics and Astronomy (Volume 54)
Pages:
150-165
DOI:
https://doi.org/10.18052/www.scipress.com/ILCPA.54.150
Citation:
S. Kumar and Santosh, "Temporal and Spatial Dynamics of Rainfall in Satluj River Basin, Himachal Pradesh, India", International Letters of Chemistry, Physics and Astronomy, Vol. 54, pp. 150-165, 2015
Online since:
July 2015
Authors:
Sandeep Kumar, Santosh
Keywords:
DEM, GIS, Himalayas, Interpolation, Orographic Effect, Precipitation, Satluj River Basin
Export:
RIS, BibTeX, Text
Distribution:
Open Access

Creative Commons License
This work is licensed under a
Creative Commons Attribution 4.0 International License

References:

[1] B. Bacchi, N.T. Kottegoda (1995) Identification and calibration of spatial correlation patterns of rainfall: Journal of Hydrology, 165(1-4): 311-348.

DOI: https://doi.org/10.1016/0022-1694(94)02590-8

[2] S.K. Bartarya, N.S. Virdi, M.P. Sah (1996) Landslide hazards: Some case studies from the Satluj Valley, Himachal Pradesh: Himalayan Geology, 17: 193-207.

[3] A. Basistha, D.S. Arya, N.K. Goel (2008) Spatial distribution of rainfall in Indian Himalayas – A case study of Uttarakhand Region: Water Resources Management, 22: 1325–1346.

DOI: https://doi.org/10.1007/s11269-007-9228-2

[4] F.C. Collins, P.V. Bolstad (1996).

[5] O.N. Dhar, PR Rakhecha (1981) The effect of elevation on monsoon rainfall distribution in the Central Himalayas, Proc. International Symposium on Monsoon Dynamics: Cambridge University Press, pp.253-260.

DOI: https://doi.org/10.1017/cbo9780511897580.020

[6] B.A. Eckstein (1989) Evaluation of spline and weighted average interpolation algorithms: Computational Geosciences, 15: 79–94.

DOI: https://doi.org/10.1016/0098-3004(89)90056-3

[7] P.K. Garg (1991) Development of a catchment scale erosion model for semiarid environment and its implementation through remote sensing: Ph.D. Thesis, University of Bristol, UK.

[8] P. Goovaerts (2000) Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall: Journal of Hydrology, 228: 113–29.

DOI: https://doi.org/10.1016/s0022-1694(00)00144-x

[9] L. Guenni, M.F. Hutchinson (1998) Spatial interpolation of the parameters of a rainfall model from ground based data: Journal of Hydrology, 212-213: 335-347.

DOI: https://doi.org/10.1016/s0022-1694(98)00215-7

[10] V. Gupta, M.P. Sah (2008) Impacts of the Trans-Himalayan Landslide Lake Outburst Flood (LLOF) in the Satluj catchment, Himachal Pradesh, India: Natural Hazards, 45: 379-390.

DOI: https://doi.org/10.1007/s11069-007-9174-6

[11] V. Gupta, M.P. Sah, N.S. Virdi, S.K. Bartarya (1994) Landslide hazard zonation in the Upper Satluj Valley, District. Kinnaur, Himachal Pradesh: Journal of Himalayan Geology, 4(1): 81-93.

[12] K. Higuchi, Y. Ageta, T. Yasunari, J. Inoue (1982) Characteristics of precipitation during monsoon season in high mountain areas of the Nepal Himalayas: Hydrological Aspects of Alpine and High Mountain Areas, IAHS, 138: 21-30.

[13] S.A. Hill (1881) The meteorology of North-West Himalaya: Indian Meteorological Memoir, I(VI): 377- 429.

[14] M.F. Hutchinson (1993) On thin plate smoothing splines and kriging: Computer Science Statistics, 25: 55–62.

[15] M.F. Hutchinson (1998) Interpolation of rainfall data with thin plate smoothing splines, Part I: Two dimensional smoothing of data with short range co-relation: Journal of Geographic Information and Decision Analysis, 2: 152–167.

[16] M.F. Hutchinson (1998) Interpolation of rainfall data with thin plate smoothing splines, Part II: Analysis of topographic dependence: Journal of Geographic Information and Decision Analysis, 2: 168–185.

[17] I.P.C.C. (2001a) Climate change 2001: Synthesis Report, In: (eds. Watson et al. ), Intergovernmental Panel on Climate Change: Cambridge University Press, Cambridge, UK and New York, USA, p.398.

[18] I.D. Moore, P.E. Gessler, G.A. Nielson (1993) Soil attribute prediction using terrain analysis: Soil Science Society of America Journal, 57: 443-452.

DOI: https://doi.org/10.2136/sssaj1993.572npb

[19] D.T. Price, D.W. McKenney, I.A. Nalder, M.F. Hutchinson, J.L. Kesteven JL (1999) A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data: Agricultural and Forest Meteorology, 101: 81–94.

DOI: https://doi.org/10.1016/s0168-1923(99)00169-0

[20] P. Singh, N. Kumar (1997) Impact assessment of climate change on the hydrological response of a snow and glacier melt runoff dominated Himalayan River: Journal of Hydrology, 193: 316-350.

DOI: https://doi.org/10.1016/s0022-1694(96)03142-3

[21] P. Singh, N. Kumar (1997b) Effect of orography on precipitation in the western Himalayan region: Journal of Hydrology, 199: 183-206.

[22] P. Singh, K.S. Ramasastri, N. Kumar (1995), Topographical Influence on precipitation distribution in different ranges of Western Himalayas: Nordic Hydrology, 26: 259-284.

[23] W. Taesombat, N. Sriwongsitanon (2009) Areal rainfall estimation using spatial interpolation techniques: Science Asia, 35: 268–275.

[24] S. Taher, A. Alshaikh (1998) Spatial analysis of rainfall in Southwest of Saudi Arabia using GIS: Nordic Hydrology, 29 (2): 91-104.

[25] G. Wahba, J. Wendelberger (1980) Some new mathematical methods for variational obj-ective analysis using splines and cross-validation: Monthly Weather Review, 108: 1122–1145.

DOI: https://doi.org/10.1175/1520-0493(1980)108<1122:snmmfv>2.0.co;2
Show More Hide