Satellite Sensing for Evaluation of an Irrigation System in Cotton - Wheat Zone

Authors: Sadia Iqbal, Faheem Iqbal, Furqan Iqbal

Abstract:

Efficient utilization of existing water is a pressing need for Pakistan. Due to rising population, reduction in present storage capacity and poor delivery efficiency of 30 to 40% from canal. A study to evaluate an irrigation system in the cotton-wheat zone of Pakistan, after the watercourse lining was conducted. The study is made on the basis of cropping pattern and salinity to evaluate the system. This study employed an index-based approach of using Geographic information system with field data. The satellite images of different years were use to examine the effective area. Several combinations of the ratio of signals received in different spectral bands were used for development of this index. Near Infrared and Thermal IR spectral bands proved to be most effective as this combination helped easy detection of salt affected area and cropping pattern of the study area. Result showed that 9.97% area under salinity in 1992, 9.17% in 2000 and it left 2.29% in year 2005. Similarly in 1992, 45% area is under vegetation it improves to 56% and 65% in 2000 and 2005 respectively. On the basis of these results evaluation is done 30% performance is increase after the watercourse improvement.

Keywords: Salinity, remote sensing index, salinity index, cropping pattern.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1332378

References:

[1] Birth, G. S. and Mcvey, G. (1968). Measuring the colour of Growing Turf with a Reflectance Spectrometer, Agronomy Journal, 60: 640-643.
[2] Burhan, H., Saleem. M. and M. Faruq. (2005). Evaluat ion and compar i son of spr inkler , dri p, bed and fur row i r r igat ion. Mona Reclamati on Exper imental Project WAPDA, Bhalwal, Distr i c t Sargodah. Paki s tan Wat e r and Power Development Authori ty. Pub 268.
[3] Deering, D. W., J. W. Rouse, Jr., R. H. Haas and J. S. Schell, (1975). Measuring forage production of grazing units from Landsat MSS data. Proc. Tenth International Symposium on Remote Sensing of the Environment, Ann Arbor, MI, 1169-1178.
[4] Hue t e , A.R. Huete (1988). A soil ad ju sted vegetation i ndex (SAVI ) . Rem. Sens. Environ. 25 (1988), pp . 295- 309.
[5] Iqbal, F. and Mehdi, M.R. (2008). Detection of suitable soils for Zero- Till Wheat Cultivation in Pakistan using GITs. International Workshop on Earth Observation and Remote Sensing Applications, 1: 1-6.
[6] Khan, M. N., Rastoskuev, V. V., Sato, Y. and Shiozawa, S. (2005). Assesment of hydrosaline land degradation by using a simple approach of remote sensing indicators. Agricultural Water Management, 77: 96- 109.
[7] Rock, B. N., Vogelmann, J. E, Williams, D. L., Voglemann, A. F. and Hoshizaki, T. (1986). Remote Detection of Forest Damage. Bioscience, 36: 439- 440.
[8] Richards, J .A., J i a , X . , (1999). Remote Sensing Digi t al Image Analysis: An Introduction . Springer , Berl in , 363 pp.