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Monitoring Changes in Croplands Due to Water Stress in the Krishna River Basin Using Temporal Satellite Imagery

Author

Listed:
  • Venkata Ramana Murthy Reddi

    (Remote sensing/GIS lab, Innovation Systems for the Drylands Program (ISD), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India
    Department of Geo Engineering, College of Engineering Andhra University, Visakhapatnam 530003, Andhra Pradesh, India)

  • Murali Krishna Gumma

    (Remote sensing/GIS lab, Innovation Systems for the Drylands Program (ISD), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India)

  • Kesava Rao Pyla

    (National Institute of Rural Development, Rajendranagar, Hyderabad 500068, India)

  • Amminedu Eadara

    (Department of Geo Engineering, College of Engineering Andhra University, Visakhapatnam 530003, Andhra Pradesh, India)

  • Jai Sankar Gummapu

    (Department of Geo Engineering, College of Engineering Andhra University, Visakhapatnam 530003, Andhra Pradesh, India)

Abstract

Remote sensing-based assessments of large river basins such as the Krishna, which supplies water to many states in India, are useful for operationally monitoring agriculture, especially basins that are affected by abiotic stress. Moderate-Resolution Imaging Spectroradiometer (MODIS) time series products can be used to understand cropland changes at the basin level due to abiotic stresses, especially water scarcity. Spectral matching techniques were used to identify land use/land cover (LULC) areas for two crop years: 2013–2014, which was a normal year, and 2015–2016, which was a water stress year. Water stress-affected crop areas were categorized into three classes—severe, moderate and mild—based on the normalized difference vegetation index (NDVI) and intensity of damage assessed through field sampling. Furthermore, ground survey data were used to assess the accuracy of MODIS-derived classification individual products. Water inflows into and outflows from the Krishna river basin during the study period were used as direct indicators of water scarcity/availability in the Krishna Basin. Furthermore, ground survey data were used to assess the accuracy of MODIS-derived LULC classification of individual year products. Rainfall data from the tropical rainfall monitoring mission (TRMM) was used to support the water stress analysis. The nine LULC classes derived using the MODIS temporal imagery provided overall accuracies of 82% for the cropping year 2013–2014 and 85% for the year 2015–2016. Kappa values are 0.78 for 2013–2014 and 0.82 for 2015–2016. MODIS-derived cropland areas were compared with national statistics for the cropping year 2013–2014 with a R 2 value of 0.87. Results show that both rainfed and irrigated areas in 2015–2016 saw significant changes that will have significant impacts on food security. It has been also observed that the farmers in the basin tend to use lower inputs and labour per ha during drought years. Among all, access to water is the major driver determining the crop choice and extent of input-use in the basin.

Suggested Citation

  • Venkata Ramana Murthy Reddi & Murali Krishna Gumma & Kesava Rao Pyla & Amminedu Eadara & Jai Sankar Gummapu, 2017. "Monitoring Changes in Croplands Due to Water Stress in the Krishna River Basin Using Temporal Satellite Imagery," Land, MDPI, vol. 6(4), pages 1-18, October.
    • Handle: RePEc:gam:jlands:v:6:y:2017:i:4:p:72-:d:115842
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    References listed on IDEAS

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    1. Biggs, Trent W. & Gangadhara Rao, Pardhasaradhi & Bharati, Luna, 2010. "Mapping agricultural responses to water supply shocks in large irrigation systems, southern India," Agricultural Water Management, Elsevier, vol. 97(6), pages 924-932, June.
    2. Murali Krishna Gumma & Kesava Rao Pyla & Prasad S. Thenkabail & Venkataramana Murthy Reddi & Gundapaka Naresh & Irshad A. Mohammed & Ismail M. D. Rafi, 2014. "Crop Dominance Mapping with IRS-P6 and MODIS 250-m Time Series Data," Agriculture, MDPI, vol. 4(2), pages 1-19, April.
    3. Thiruvengadachari, S. & Sakthivadivel, R., 1997. "Satellite remote sensing for assessment of irrigation system performance: a case study in India," IWMI Research Reports H020351, International Water Management Institute.
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