Temporal change in land use by irrigation source in Tamil Nadu and management implications
- 500 Downloads
Interannual variation in rainfall throughout Tamil Nadu has been causing frequent and noticeable land use changes despite the rapid development in groundwater irrigation. Identifying periodically water-stressed areas is the first and crucial step to minimizing negative effects on crop production. Such analysis must be conducted at the basin level as it is an independent water accounting unit. This paper investigates the temporal variation in irrigated area between 2000–2001 and 2010–2011 due to rainfall variation at the state and sub-basin level by mapping and classifying Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day composite satellite imagery using spectral matching techniques. A land use/land cover map was drawn with an overall classification accuracy of 87.2 %. Area estimates between the MODIS-derived net irrigated area and district-level statistics (2000–2001 to 2007–2008) were in 95 % agreement. A significant decrease in irrigated area (30–40 %) was observed during the water-stressed years of 2002–2003, 2003–2004, and 2009–2010. Major land use changes occurred three times during 2000 to 2010. This study demonstrates how remote sensing can identify areas that are prone to repeated land use changes and pin-point key target areas for the promotion of drought-tolerant varieties, alternative water management practices, and new cropping patterns to ensure sustainable agriculture for food security and livelihoods.
KeywordsLand use change Irrigated areas Tamil Nadu MODIS Spectral matching techniques NDVI
This research was supported by the “Green Super Rice” (GSR) and CGIAR Research Program: Water Land Ecosystems (WLE). The authors thank Dr. Amit Chakravarty, science editor/publisher, ICRISAT, for editing this article. We would like to thank three anonymous reviewers who helped in substantially improving the quality of this paper.
- Bastiaanssen, W. G. M., Molden, D. J., Thiruvengadachari, S., Smit, A. A. M. F. R., & Mutuwatte, L., G., J. (1999). Remote sensing and hydrologic models for performance assessment in Sirsa Irrigation Circle, India, in: 27, R.R. (Ed.). International Water Management Institute.Google Scholar
- Biggs, T. W., Thenkabail, P. S., Gumma, M. K., Scott, C. A., Parthasaradhi, G. R., & Turral, H. N. (2006). Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India. International Journal of Remote Sensing, 27, 4245–4266.CrossRefGoogle Scholar
- CBIP, (2007). Water resources map of India (Map No. 27). Central Board of Irrigation and Power. New Delhi - 110 021.Google Scholar
- Congalton, R. G., & Green, K. (1999). Assessing the accuracy of remotely sensed data: principles and practices. New York: Lewis.Google Scholar
- EISC (2011). Environmental Information System Centre. http://tnenvis.nic.in/agri_environmental_concerns.htm. Accessed 2 Jan 2012.
- FAO (2007). Adaptation to climate change in agriculture, forestry and fisheries: perspective, framework and priorities. ftp://ftp.fao.org/docrep/fao/009/j9271e/j9271e.pdf. Accessed 19 Jun 2012.
- Fishman, R. M., Siegfried, T., Raj, P., Modi, V., & Lall, U. (2011). Over-extraction from shallow bedrock versus deep alluvial aquifers: Reliability versus sustainability considerations for India’s groundwater irrigation. Water Resources Research, 47(6), W00L05.Google Scholar
- GTDES (2011). Statistical Hand Book 2012. Government of Tamil Nadu Department of Economics and Statistics. http://www.tn.gov.in/crop/chareafg5yrs.htm. Accessed 14 May 2012.
- Gumma, M. K., Thenkabail, P. S., Muralikrishna, I. V., Velpuri, M. N., Gangadhararao, P. T., Dheeravath, V., Biradar, C. M., Acharya Nalan, S., & Gaur, A. (2011c). Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna River basin (India). International Journal of Remote Sensing, 32, 3495–3520.CrossRefGoogle Scholar
- Indira, P., Stephen, S., & Inbanathan, K. (2013). Studies on the trend and chaotic behaviour of Tamil Nadu rainfall. Journal of Indian Geophysical Union, 17(4), 335–339.Google Scholar
- MOWR (2006). Minor Irrigation census by Ministry of water resources, 2006-07. Governmnent of India. New Delhi. Appendix - I. Concept and definition. http://micensus.gov.in/concepts.pdf. Accessed 5 Jan 2014.
- OECD (2006). Promoting pro-poor growth: policy guidance for donors. http://www.oecd.org/dataoecd/9/60/37922155.pdf. Accessed 19 Jun 2012.
- Palanisami, K., Ranganathan, C. R., Vidhyavathi, A., Rajkumar, M., Ajjan, N., & Report, F. (2011). Performance of agriculture in river basins of Tamil Nadu in the last three decades—a total factor productivity approach. In G.o.I. (Ed.), Planning Commission, Planning Commission, Government of India. P171, March, 2011.Google Scholar
- Rouse, J., Haas, R., Schell, J., & Deering, D. (1973). Monitoringvegetation systems in the great plains with ERTS. Third ERTS Symposium, NASASP-351 (Vol. 1, pp. 309–317). Washington, DC: NASA.Google Scholar
- Shah, T. (2010). Taming the anarchy: groundwater governance in South Asia. Washington, DC: Routledge.Google Scholar
- Thenkabail, P. S., GangadharaRao, P., Biggs, T., Gumma, M. K., & Turral, H. (2007). Spectral matching techniques to determine historical land use/land cover (LULC) and irrigated areas using time-series AVHRR pathfinder datasets in the Krishna River Basin, India. Photogrammetric Engineering and Remote Sensing, 73, 1029–1040.Google Scholar
- Thenkabail, P. S., Biradar, C. M., Noojipady, P., Dheeravath, V., Li, Y., Velpuri, M., Gumma, M., Gangalakunta, O. R. P., Turral, H., Cai, X., Vithanage, J., Schull, M. A., & Dutta, R. (2009). Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium. International Journal of Remote Sensing, 30, 3679–3733.CrossRefGoogle Scholar
- Thiruvengadachari, S., & Sakthivadivel, R. (1997). Satellite remote sensing for assessment of irrigation system performance: a case study in India. Research Report 9. Colombo, Sri Lanka: International Irrigation Management Institute.Google Scholar