Actual Evapotranspiration (Water Use) Assessment of the Colorado River Basin at the Landsat Resolution Using the Operational Simplified Surface Energy Balance Model
Accurately estimating consumptive water use in the Colorado River Basin (CRB) is important for assessing and managing limited water resources in the basin. Increasing water demand from various sectors may threaten long-term sustainability of the water supply in the arid southwestern United States. We have developed a first-ever basin-wide actual evapotranspiration (ET a) map of the CRB at the Landsat scale for water use assessment at the field level. We used the operational Simplified Surface Energy Balance (SSEBop) model for estimating ET a using 328 cloud-free Landsat images acquired during 2010. Our results show that cropland had the highest ET a among all land cover classes except for water. Validation using eddy covariance measured ET a showed that the SSEBop model nicely captured the variability in annual ET a with an overall R 2 of 0.78 and a mean bias error of about 10%. Comparison with water balance-based ET a showed good agreement (R 2 = 0.85) at the sub-basin level. Though there was good correlation (R 2 = 0.79) between Moderate Resolution Imaging Spectroradiometer (MODIS)-based ET a (1 km spatial resolution) and Landsat-based ET a (30 m spatial resolution), the spatial distribution of MODIS-based ET a was not suitable for water use assessment at the field level. In contrast, Landsat-based ET a has good potential to be used at the field level for water management. With further validation using multiple years and sites, our methodology can be applied for regular production of ET a maps of larger areas such as the conterminous United States.
References
[1]
Christensen, N.S.; Wood, A.W.; Voisin, N.; Lettenmaier, D.P.; Palmer, R.N. The effects of climate change on the hydrology and water resources of the Colorado River Basin. Clim. Chang 2004, 62, 337–363.
[2]
McCabe, G.J.; Wolock, D.M. Warming may create substantial water supply shortages in the Colorado River Basin. Geophys. Res. Lett 2007, 34, L22708.
[3]
Bastiaanssen, W.G.M.; Molden, D.J.; Makin, I.W. Remote sensing for irrigated agriculture: Examples from research and possible applications. Agric. Water Manag 2000, 46, 137–155.
[4]
Nagler, P.L.; Glenn, E.P.; Didan, K.; Osterberg, J.; Jordan, F.; Cunningham, J. Wide-area estimates of stand structure and water use of Tamarix spp. on the Lower Colorado River: Implications for restoration and water management projects. Restor. Ecol 2008, 16, 136–145.
[5]
Gowda, P.H.; Chavez, J.L.; Colaizzi, P.D.; Evett, S.R.; Howell, T.A.; Tolk, J.A. ET Mapping for agricultural water management: Present status and challenges. Irrig. Sci 2008, 26, 223–237.
[6]
Menenti, M.; Chaudhury, B.J. Parameterization of Land Surface Evapotranspiration Using a Location Dependent Potential Evapotranspiration and Surface Temperature Range. Proceedings of the Exchange Processes at the Land Surface for a Range of Space and Time Scales; Bolle, H.J., Feddes, R.A., Kalma, J.D., Eds.; International Association of Hydrological Sciences: Rennes, France, 1993; 212, pp. 561–568.
[7]
Norman, J.M.; Kustas, W.P.; Humes, K.S. A two-source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperature. Agric. For. Meteorol 1995, 77, 263–293.
[8]
Bastiaanssen, W.G.M.; Menenti, M.; Feddes, R.A.; Holtslag, A.A.M. The surface energy balance algorithm for land (SEBAL): Part 1 Formulation. J. Hydrol 1998, 212–213, 198–212.
[9]
Roerink, G.J.; Su, Z.; Menenti, M. S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance. Phys. Chem. Earth Part B 2000, 25, 147–157.
[10]
Su, Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrol. Earth Syst. Scie 2002, 6, 85–99.
[11]
Loheide, S.P., II; Gorelick, S.M. A local-scale, high resolution evapotranspiration mapping algorithm (ETMA) with hydroecological applications at riparian meadow restoration sites. Remote Sens. Environ 2005, 98, 182–200.
[12]
Anderson, M.C.; Norman, J.M.; Mecikalski, J.R.; Otkin, J.A.; Kustas, W.P. A Climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1 Model formulation. J. Geophys. Res 2007, doi:10.1029/2006JD007506.
[13]
Allen, R.G.; Tasumi, M.; Trezza, R. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model. ASCE J. Irrig. Drain. Eng 2007, 133, 380–394.
[14]
Senay, G.B.; Budde, M.E.; Verdin, J.P.; Melesse, A.M. A coupled remote sensing and Simplified Surface Energy Balance (SSEB) approach to estimate actual evapotranspiration from irrigated fields. Sensors 2007, 7, 979–1000.
[15]
Singh, R.K.; Irmak, A. Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes. Hydrol. Sci. J 2011, 56, 895–906.
[16]
Senay, G.B.; Bohms, S.; Singh, R.K.; Gowda, P.H.; Velpuri, N.M.; Alemu, H.; Verdin, J.P. Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. J. Am. Water Resourc. Assoc 2013, 49, 577–591.
[17]
Gowda, P.H.; Chavez, J.L.; Colaizzi, P.D.; Evett, S.R.; Howell, T.A.; Tolk, J.A. Remote sensing based energy balance algorithms for mapping ET: Current status and future challenges. Trans. Am. Soc. Agric. Biol. Eng 2007, 50, 1639–1644.
[18]
Kalma, J.D.; McVicar, T.R.; McCabe, M.F. Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surv. Geophys 2008, 29, 421–469.
[19]
Glenn, E.P.; Neale, C.M.U.; Hunsaker, D.J.; Nagler, P.L. Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems. Hydrol. Process 2011, 25, 4050–4062.
[20]
US Geological Survey (USGS). Facing Tomorrow’S Challenges—U.S. Geological Survey Science in the Decade 2007–2017. US Geol. Surv. Circ 2007, 1309, 1–69.
[21]
US Department of the Interior (DOI). Fiscal Year 2011 The Interior Budget in Brief. In WaterSMART: Departmental Highlights; US Department of the Interior: Washington, DC, USA, 2010; pp. 19–25.
[22]
Bruce, B.W. WaterSMART—The Colorado River Basin Focus Area Study; US Geological Survey: Washington, DC, USA.
[23]
Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; FAO: Rome, Italy, 1998.
[24]
Fry, J.; Xian, G.; Jin, S.; Dewitz, J.; Homer, C.; Yang, L.; Barnes, C.; Herold, N.; Wickham, J. Completion of the 2006 national land cover database for the conterminous United States. Photogramm. Eng. Remote Sens 2011, 77, 858–864.
[25]
Bureau of Reclamation (BOR). Lower Colorado River Accounting System, Demonstration of Technology; Lower Colorado Regional Office: Boulder City, NV, 1997.
[26]
Congalton, R.G.; Balogh, M.; Bell, C.; Green, K.; Milliken, J.A.; Ottman, R. Mapping and monitoring agricultural crops and other land cover in the Lower Colorado River Basin. Photogramm. Eng. Remote Sens 1998, 64, 1107–1114.
[27]
Kumar, M.; Duffy, C.J. Detecting hydroclimatic change using spatio-temporal analysis of time series in Colorado River Basin. J. Hydrol 2009, 374, 1–15.
[28]
Chander, G.; Markham, B.L.; Helder, D.L. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens. Environ 2009, 113, 893–903.
[29]
Tasumi, M.; Allen, R.; Trezza, R. At-surface reflectance and albedo from satellite for operational calculation of land surface energy balance. J. Hydrol. Eng 2008, 13, 51–63.
[30]
Daly, C.; Gibson, W.P.; Taylor, G.H.; Johnson, G.L.; Pasteris, P. A knowledge-based approach to the statistical mapping of climate. Clim. Res 2002, 22, 99–113.
[31]
US Geological Survey (USGS). Waterwatch–Maps, Graphs, and Tables of Current, Recent, and Past Streamflow Conditions. Available online: http://pubs.usgs.gov/fs/2008/3031/ (accessed on 31 December 2012).
[32]
Reuter, H.I.; Nelson, A.; Jarvis, A. An evaluation of void filling interpolation methods for SRTM data. Int. J. Geogr. Inf. Sci 2007, 21, 983–1008.
[33]
Senay, G.B; Verdin, J.P.; Lietzow, R.; Melesse, A.M. Global reference evapotranspiration modeling and evaluation. J. Am. Water Resourc. Assoc 2008, 44, 969–979.
[34]
Kanamitsu, M. Description of the NMC global data assimilation and forecast system. Weather Forecast 1989, 4, 335–342.
[35]
Jung, M.; Reichstein, M.; Bondeau, A. Towards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model. Biogeosciences 2009, 6, 2001–2013.
[36]
Singh, R.K. Geospatial Approach for Estimating Land Surface EvapotranspirationPh.D. Dissertation. University of Nebraska-Lincoln, Lincoln, NE, USA, 2009.
Dore, S.; Montes-Helu, M.; Hart, S.C.; Hungate, B.A.; Koch, G.W.; Moon, J.B.; Finkral, A.J.; Kolb, T.E. Recovery of ponderosa pine ecosystem carbon and water fluxes from thinning and stand-replacing fire. Glob. Chang. Biol 2012, 18, 3171–3185.
[39]
Kurc, S.A.; Benton, L.M. Digital image-derived greenness links deep soil moisture to carbon uptake in a creosotebush-dominated shrubland. J. Arid Environ 2010, 74, 585–594.
[40]
Scott, R.L.; Jenerette, G.D.; Potts, D.L.; Huxman, T.E. Effects of seasonal drought on net carbon dioxide exchange from a woody-plant-encroached semiarid grassland. J. Geophys. Res.: Biogeosci 2009, 114, G04004.
[41]
Scott, R.L.; Hamerlynck, E.P.; Jenerette, G.D.; Moran, M.S.; Barron-Gafford, G. Carbon dioxide exchange in a semidesert grassland through drought-induced vegetation change. J. Geophys. Res.: Biogeosci 2010, doi:10.1029/2010JG001348.
[42]
Scott, R.L.; Edwards, E.A.; Shuttleworth, W.J.; Huxman, T.E.; Watts, C.; Goodrich, D.C. Interannual and seasonal variation in fluxes of water and carbon dioxide from a riparian woodland ecosystem. Agric. For. Meteorol 2004, 122, 65–84.
[43]
Baldocchi, D.; Falge, E.; Gu, L.; Olson, R.; Hollinger, D.; Running, S.; Anthoni, P.; Bernhofer, C.; Davis, K.; Evans, R.; et al. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bull. Am. Meteorol. Soc 2001, 82, 2415–2431.
[44]
Barron-Gafford, G.A.; Scott, R.L.; Jenerette, G.D.; Hamerlynck, E.P.; Huxman, T.E. Temperature and precipitation controls over leaf and ecosystem-level CO2 flux along a woody plant encroachment gradient. Glob. Chang. Biol 2012, 18, 1389–1400.
[45]
Wickham, J.D.; Stehman, S.V.; Gass, L.; Dewitz, J.; Fry, J.A.; Wade, T.G. Accuracy assessment of NLCD 2006 land cover and impervious surface. Remote Sens. Environ 2013, 130, 294–304.
[46]
Stehman, S.V.; Milliken, J.A. Estimating the effect of crop classification error on evapotranspiration derived from remote sensing in the Lower Colorado River basin, USA. Remote Sens. Environ 2007, 106, 217–227.
[47]
Haddeland, I.; Lettenmaier, D.P.; Skaugen, T. Effects of irrigation on the water and energy balances of the Colorado and Mekong River basins. J. Hydrol 2006, 324, 210–223.
[48]
Westenburg, C.L.; Harper, D.P.; DeMeo, G.A. Evapotranspiration by Phreatophytes along the Lower Colorado River at Havasu National Wildlife Refuge, Arizona; US Geological Survey Scientific Investigations Report 2006–5043; US Department of the Interior: Washington, DC, USA, 2006; p. 44.
[49]
Doody, T.M.; Nagler, P.M.; Glenn, E.P.; Moore, G.W.; Morino, K.; Hultine, K.R.; Benyon, R.G. Potential for water salvage by removal of non-native woody vegetation from dryland river systems. Hydrol. Process 2011, 25, 4117–4131.
[50]
Nagler, P.L.; Scott, R.L.; Westenburg, C.; Cleverly, J.R.; Glenn, E.P.; Huete, A.R. Evapotranspiration on western US rivers estimated using the enhanced vegetation index from MODIS and data from eddy covariance and Bowen ratio flux towers. Remote Sens. Environ 2005, 97, 337–351.
[51]
Leclerc, M.Y.; Thurtell, G.W. Footprint prediction of scalar fluxes using a Markovian analysis. Bound.-Lay. Meteorol 1990, 52, 247–258.
[52]
Bastiaanssen, W.G. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. J. Hydrol 2000, 229, 87–100.
Wilson, K.; Goldstein, A.; Falge, E.; Aubinet, M.; Baldocchi, D.; Berbigier, P.; Bernhofer, C.; Ceulemans, R.; Dolman, H.; Field, C.; et al. Energy balance closure at FLUXNET sites. Agric. For. Meteoro 2002, 113, 223–243.
[55]
Hollinger, D.Y.; Richardson, A.D. Uncertainty in eddy covariance measurements and its application to physiological models. Tree Physiol 2005, 25, 873–885.
[56]
Velpuri, N.M.; Senay, G.B.; Singh, R.K.; Bohms, S.; Verdin, J.P. A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: Using point and gridded FLUXNET and water balance ET. Remote Sens. Environ 2013, 139, 35–49.
[57]
Thornton, P.E.; Running, S.W.; White, M.A. Generating surfaces of daily meteorological variables over large regions of complex terrain. J. Hydrol 1997, 190, 214–251.
[58]
Mitchell, K.E.; Lohmann, D.; Houser, P.R.; Wood, E.F.; Schaake, J.C.; Robock, A.; Cosgrove, B.A.; Sheffield, J.; Duan, Q.; Luo, L.; et al. The multi-institution North American land data assimilation system (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res 2004, doi:10.1029/2003JD003823.