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Temporal change in land use by irrigation source in Tamil Nadu and management implications

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Abstract

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.

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Notes

  1. AWD is an irrigation practice to reduce irrigation water from 15 to 35 % without any yield penalty by letting the rice field dry intermittently at the stage when the crop is not so sensitive to water stress.

References

  • Badhwar, G. D. (1984). Automatic corn-soybean classification using landsat MSS data. I. Near-harvest crop proportion estimation. Remote Sensing of Environment, 14, 15–29.

    Article  Google Scholar 

  • 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.

  • Bhutta, M. N., & Van der Velde, E. J. (1992). Equity of water distribution along secondary canals in Punjab, Pakistan. Irrigation and Drainage Systems, 6(2), 161–177.

    Article  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.

    Article  Google Scholar 

  • Biggs, T. W., Gangadhara Rao, P., & Bharati, L. (2010). Mapping agricultural responses to water supply shocks in large irrigation systems, southern India. Agricultural Water Management, 97, 924–932.

    Article  Google Scholar 

  • CBIP, (2007). Water resources map of India (Map No. 27). Central Board of Irrigation and Power. New Delhi - 110 021.

  • Congalton, R. G., & Green, K. (1999). Assessing the accuracy of remotely sensed data: principles and practices. New York: Lewis.

    Google Scholar 

  • Droogers, P., & Allen, R. G. (2002). Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and Drainage Systems, 16, 33–45.

    Article  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 

  • Gaur, A., Biggs, T. W., Gumma, M. K., Parthasaradhi, G. R., & Turral, H. (2008). Water scarcity effects on equitable water distribution and land use in Major Irrigation Project - A Case study in India. Journal of irrigation and Drainage Engineering, 134(1), 26–35.

    Article  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., Gauchan, D., Nelson, A., Pandey, S., & Rala, A. (2011a). Temporal changes in rice-growing area and their impact on livelihood over a decade: a case study of Nepal. Agriculture Ecosystems & Environment, 142, 382–392.

    Article  Google Scholar 

  • Gumma, M. K., Nelson, A., Thenkabail, P. S., & Singh, A. N. (2011b). Mapping rice areas of South Asia using MODIS multitemporal data. Journal of Applied Remote Sensing, 5, 053547.

    Article  Google Scholar 

  • 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.

    Article  Google 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 

  • Karimov, A., Smakhtin, V., Mavlonov, A., & Gracheva, I. (2010). Water ‘banking’ in Fergana valley aquifers—a solution to water allocation in the Syrdarya river basin. Agricultural Water Management, 97, 1461–1468.

    Article  Google Scholar 

  • Karimov, A., Molden, D., Khamzina, T., Platonov, A., & Ivanov, Y. (2012). A water accounting procedure to determine the water savings potential of the Fergana Valley. Agricultural Water Management, 108, 61–72.

    Article  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.

  • 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.

  • Shah, T. (2012). Community response to aquifer development: distinct patterns in India’s alluvial and hard rock aquifer areas. Irrigation and Drainage, 61(S1), 14–25.

    Article  Google Scholar 

  • Singh, A. (1989). Review Article Digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing, 10, 989–1003.

    Article  Google Scholar 

  • Teillet, P. M., Staenz, K., & William, D. J. (1997). Effects of spectral, spatial, and radiometric characteristics on remote sensing vegetation indices of forested regions. Remote Sensing of Environment, 61, 139–149.

    Article  Google Scholar 

  • Thenkabail, P. S., Schull, M., & Turral, H. (2005). Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data. Remote Sensing of Environment, 95, 317–341.

    Article  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.

    Article  Google 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 

  • Torbick, N., Lusch, D., Qi, J., Moore, N., Olson, J., & Ge, J. (2006). Developing land use/land cover parameterization for climate–land modelling in East Africa. International Journal of Remote Sensing, 27, 4227–4244.

    Article  Google Scholar 

  • Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127–150.

    Article  Google Scholar 

Download references

Acknowledgments

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.

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Authors and Affiliations

  1. International Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502324, India

    Murali Krishna Gumma, Irshad A. Mohammed & Anthony M. Whitbread

  2. Aoyama Gakuin University, Tokyo, Japan

    Kei Kajisa

  3. International Rice Research Institute, Los Baños, Philippines

    Andrew Nelson & Arnel Rala

  4. International Water Management Institute (IWMI) c/o ICRISAT, Patancheru, 502324, Hyderabad, India

    K. Palanisami

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  1. Murali Krishna Gumma
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  5. Andrew Nelson
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Correspondence to Murali Krishna Gumma.

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The spatial distribution of temporal irrigated agricultural area was derived at high accuracy from MODIS time series data using a combination of methods consisting of spectral matching techniques and intensive field plot information. Results contribute to spatial information about temporal changes in irrigated areas where regulation of water use and remediation measures should be taken up. This may result in suggesting new cropping pattern and alternative water management practices from field level to sub-basin level.

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Gumma, M.K., Kajisa, K., Mohammed, I.A. et al. Temporal change in land use by irrigation source in Tamil Nadu and management implications. Environ Monit Assess 187, 4155 (2015). https://doi.org/10.1007/s10661-014-4155-1

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