Remote sensing based water management from the watershed to the field level
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Remote sensing based water management from the watershed to the field level

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Remote sensing –Beyond images ...

Remote sensing –Beyond images
Mexico 14-15 December 2013

The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

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Remote sensing based water management from the watershed to the field level Remote sensing based water management from the watershed to the field level Presentation Transcript

  • Remote sensing based water management from the watershed to the field level Stephan J. Maas Nithya Rajan Texas Tech University Texas A&M AgriLife Research Texas A&M AgriLife Research Vernon, TX Lubbock, TX
  • Water Use A key factor in water resource management is information on how much water vegetation (crops, pastures, rangelands and natural ecosystems) is using. For example, for irrigation scheduling you need to know how much water the crop is using so you can schedule irrigation to replace it. There are several ways to measure or estimate water use-• Lysimeters • Eddy covariance systems • Crop coefficient methods
  • Standard Crop Coefficient Method Standard crop coefficients are designed to estimate crop ET under “standard conditions” which represent “the upper envelope of crop ET where no limitations are placed on crop growth or ET due to water shortage, crop density, or disease, weed, insect, or salinity pressures” (Allen et al., FAO-56,1998). So, the standard crop coefficient approach can tell you how much water a crop would be using if it were growing under “standard” (non-limited) conditions, but it can’t tell you how much water the crop in a particular field is actually using.
  • Spectral Crop Coefficient Method Daily water use (WU) of vegetation can be estimated using the “spectral crop coefficient” method: WU = Ksp * PETfc * Fstress Ksp is the spectral crop coefficient (value 0-1) PETfc is the potential ET (well-watered full canopy) Fstress is a stress factor (value 0-1) Ksp is equivalent to the vegetation ground cover (GC). Details of the procedure can be found in: Rajan, N., S. J. Maas, and J. Kathilankal. 2010. Estimating crop water use of cotton in the Texas High Plains. Agronomy Journal, Vol. 102, No. 6, p. 16411651.
  • Calculation of PETfc Weather data for calculating PETfc can be obtained from standard observing stations. Air temperature Humidity Solar irradiance Wind speed
  • Spectral Crop Coefficient Vegetation GC (Ksp) can be estimated from readily available multispectral remote sensing imagery. Details of the procedure can be found in: Maas, S. J., and N. Rajan. 2008. Estimating ground cover of field crops using mediumresolution multispectral satellite imagery. Agronomy Journal. 100(2): 320-327.
  • Spectral Crop Coefficient Details of the procedure can be found in: Rajan, N., and S. Maas. 2009. Mapping crop ground cover using airborne multispectral digital imagery. Precision Agriculture. 10:304-318.
  • Validation of Ksp Method Cotton 2008 2010 Rajan, N., and S. Maas. Spectral crop coefficient approach for estimating daily crop water use. Agricultural Water Management. (in review).
  • Validation of Ksp Method For irrigated crops or non-irrigated vegetation (such as dryland crops or pastures) that are acclimated to their environment, Fstress ≈ 1.
  • Seasonal Water Use For seasonal WU, you can sum daily WU estimates. To get GC values between dates with RS observations— • Interpolate (if you have relatively frequent RS observations) • Use infrequent RS observations to scale basal spectral crop coefficient curves To develop basal Ksp curves, all you need is historic RS data.
  • Application By choosing the appropriate source of remote sensing imagery, you can estimate the WU of crops or other vegetation at a variety of spatial scales. Sub-field scale Field scale Regional or watershed scale Remember-- to evaluate vegetation GC (Ksp), you only need image DC data in the red and NIR spectral bands, which is available from a wide variety of sensor platforms.
  • Application- Sub-field Scale Objective: Seasonal CWU for a 120-acre center-pivot irrigated cotton field in the Texas High Plains Source of RS data: Landsat TM
  • Application- Field Scale Objective: Seasonal CWU for fields comprising the Texas Alliance for Water Conservation (TAWC) Demonstration Project in the Texas High Plains Source of RS data: Landsat TM
  • Application- Field Scale Comparison of the water used by different crops. Comparison of the water used by a crop under different types of irrigation.
  • Application- Regional Scale Objective: Seasonal WU for entire TAWC Project area Source of RS data: Landsat TM Vegetation accounted for a total of 18,370 acre-ft of water lost from the project area during the May-Oct growing season in 2005.
  • Application- Watershed Scale Objective: Seasonal WU for Walnut Gulch Experimental Watershed near Tombstone, Arizona Source of RS data: AVHRR
  • SUMMARY and CONCLUSIONS The spectral crop coefficient method is effective in estimating the actual water use of crops and other vegetation on a field-by-field basis. This method uses the same weather data required by the standard crop coefficient approach. The only additional information required is an estimate of vegetation ground cover. Estimates of ground cover can be obtained from a variety of remote sensing platforms. It provides a way to evaluate the water use of vegetation at a variety of spatial scales, from the field to the watershed scale.
  • Acknowledgements The authors wish to thank the Texas Alliance for Water Conservation Demonstration Project, funded by the Texas Water Development Board, for the resources necessary for conducting many of their projects.