Читать книгу Global Drought and Flood - Группа авторов - Страница 42
REFERENCES
Оглавление1 Allen, R., Irmak, A., Trezza, R., Hendrickx, J.M.H., Bastiaanssen, W., & Kjaersgaard, J. (2011). Satellite‐based ET estimation in agriculture using SEBAL and METRIC. Hydrological Processes, 25(26), 4011–4027. doi:10.1002/hyp.8408
2 Allen, R.G., Tasumi, M., Morse, A., & Trezza, R. (2005). A Landsat‐based energy balance and evapotranspiration model in Western US water rights regulation and planning. Irrigation and Drainage Systems, 19, 251–268.
3 Allen, R.G., Tasumi, M., & Trezza, R. (2007). Satellite‐based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model. Journal of Irrigation and Drainage Engineering—ASCE, 133(4), 380–394. doi:10.1061/(asce)0733‐9437(2007)133:4(380)
4 Anderson, M.C., Hain, C., Otkin, J., Zhan, X., Mo, K., Svoboda, M., Wardlow, B., & Pimstein, A. (2013). An intercomparison of drought indicators based on thermal remote sensing and NLDAS‐2 simulations with U.S. Drought Monitor classifications. Journal of Hydrometeorology, 14, 1035–1056.
5 Anderson, M.C., Hain, C.R., Wardlow, B., Pimstein, A., Mecikalski, J.R., & Kustas, W.P. (2011). Evaluation of drought indices based on thermal remote sensing of evapotranspiration over the continental U.S. Journal of Climate, 24, 2025–2044.
6 Anderson, M.C., Norman, J.M., Diak, G.R., Kustas, W.P., & Mecikalski, J.R. (1997). A two‐source time‐integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sensing of the Environment, 60, 195–216.
7 Anderson, M.C., Norman, J.M., Kustas, W.P., Li, F., Prueger, J.H., & Mecikalski, J.R. (2005). Effects of vegetation clumping on two‐source model estimates of surface energy fluxes from an agricultural landscape during SMACEX. Journal of Hydrometeorology, 6, 892–909.
8 Anderson, M.C., Normal, J.M., Kustas, W.P., Li, F., Prueger, J.H., & Mecikalski, J.R. (2007). A climatological study of evapotranspiration and moisture stress across the continental United States: 1. Model formulation. Journal of Geophysical Research, 112(D10). https://doi.org/10.1029/2006JD007506
9 Barriopedro, D., Fischer, E.M., Luterbacher, J., Trigo, R.M., & García‐Herrera, R. (2011). The hot summer of 2010: Redrawing the temperature record map of Europe. Science, 332, 220–224.
10 Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A., & Holtslag, A.A.M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL)—1. Formulation. Journal of Hydrology, 212(1–4), 198–212. doi:10.1016/s0022‐1694(98)00253‐4
11 Bastiaanssen, W.G.M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J.F., Roerink, G.J., & van der Wal, T. (1998). A remote sensing surface energy balance algorithm for land (SEBAL) —2. Validation, Journal of Hydrology, 212(1–4), 213–229. doi:10.1016/s0022‐1694(98)00254‐6
12 Brutsaert, W. (1982). Evaporation into the atmosphere: Theory, history and applications (1st edn.). Springer.
13 Brutsaert, W. & Sugita, M. (1992). Application of self‐preservation in the diurnal evolution of the surface energy budget to determine daily evaporation. Journal of Geophysical Research, 97, 18377–18382.
14 Carlson, T.N., & Ripley, D.A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62, 241–252.
15 Courault, D., Clastre, P., Guinot, J.P., & Seguin, B. (1994). Analyse des s´echeresses de 1988 `a 1990 en France `a partir de l’analyse combin´ee de donn´ees satellitaires NOAA‐AVHRR et d’un mod`ele agrom´et´eorologique. Agronomie, 14, 41–56.
16 Courault, D., Seguin, B., & Olioso, A. (2005). Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches. Irrigation and Drainage Systems, 19, 223–249.
17 Crago, R.D. (1996). Comparison of the evaporative fraction and the Priestley–Taylor α for parameterizing daytime evaporation. Water Resources Research, 32, 1403–1409.
18 Culf, A.D. (1993). The potential for estimating regional sensible heat flux from convective boundary layer growth. Journal of Hydrology, 146, 235–244.
19 Diak, G.R. (1990). Evaluation of heat flux, moisture flux and aerodynamic roughness at the land surface from knowledge of the PBL height and satellite‐derived skin temperatures. Agriculture and Forest Meteorology, 52, 181–198.
20 Diak, G.R. & Whipple, M.S. (1995) A note on estimating surface sensible heat fluxes using surface temperatures measured from a geostationary satellite during FIFE 1989. Journal of Geophysical Research, 100, 25453–25461.
21 Engman, E.T. (1991). Applications of microwave remote sensing of soil moisture for water resources and agriculture. Remote Sensing of Environment, 35, 213–226.
22 Entekhabi, D., Njoku, E.G. Houser, P., Spencer, M., Doiron, T., Yunjin, K., et al. (2004). The hydrosphere state (hydros) satellite mission: an Earth system pathfinder for global mapping of soil moisture and land freeze/thaw. IEEE Transactions on Geoscience and Remote Sensing, 42, 2184–2195.
23 Fang, L., Hain, C.R., Zhan, X., & Anderson, M.C. (2016). An inter‐comparison of soil moisture data products from satellite remote sensing and a land surface model. International Journal of Applied Earth Observation and Geoinformation, 48, 37–50.
24 Fisher, J.B., Tu, K.P., & Baldocchi, D.D. (2008). Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP‐II data, validated at 16 FLUXNET sites. Remote Sensing of Environment, 112, 901–919.
25 Gash, J.H.C. (1987). An analytical framework for extrapolating evaporation measurements by remote sensing surface temperatures. International Journal of Remote Sensing, 8, 1245–1249.
26 Grigg, N.S. (2014). The 2011–2012 drought in the United States: new lessons from a record event. International Journal of Water Resources Development, 30, 183–199.
27 Gurney, R.J., & Hsu, A.Y. (1990). Relating evaporative fraction to remotely sensed data at the FIFE site (pp. 7–9). Symposium on FIFE: First ISLSCP Field Experiment, February, Boston, MA.
28 Hain, C., Anderson, M., Schull, M.A., & Neal, C.M.U. (2017). A framework for mapping global evapotranspiration using 375‐m VIIRS LST [H52G‐02]. AGU Fall Meeting, December, New Orleans, LA.
29 Hain, C.R., Crow, W., Mecikalski, J.R., Anderson, M.C., & Holmes, T.R.H. (2011) An intercomparison of available soil moisture estimates from thermal‐infrared and passive microwave remote sensing and land‐surface modeling. Journal of Geophysical Research, 116(D15). https://doi.org/10.1029/2011JD015633
30 Hall, F.G., Huemmrich, K.F., Goetz, S.J., Sellers, P.J., & Nickerson, J.E. (1992). Satellite remote sensing of surface energy balance: Success, failures and unresolved issues in FIFE. Journal of Geophysical Research, 97, 19061–19089.
31 Hoerling, M., Eischeid, J., Kumar, A., Leung, R., Mariotti, A., Mo, K., Schubert, S., & Seager, R. (2014). Causes and predictability of the 2012 Great Plains drought. Bulletin of the American Meteorological Society, 95, 269–282.
32 Holmes, T.R.H., De Jeu, R.A.M., Owe, M., & Dolman, A.J. (2009). Land surface temperature from Ka band (37 GHz) passive microwave observations. Journal of Geophysical Research, 114, D04113. doi:10.1029/2008JD010257
33 Idso, S.B., Jackson, R.D., Pinter, P.J., & Hatfield, J.H. (1981). Normalizing the stress‐degree‐day parameter for environmental variability. Agricultural Meteorology, 24(1), 45–55.
34 Idso, S.B., Schmugge, T.J., Jackson, R.D., & Reginato, R.J. (1975). The utility of surface temperature measurements for the remote sensing of surface soil water status. Journal of Geophysical Research, 80, 3044–3049.
35 Jackson, R.D. (1982). Soil moisture inferences from thermal‐infrared measurements of vegetation temperatures. IEEE Transactions of Geosciences Remote Sensing, 33, 1475–1484.
36 Jackson, R.D., Reginato, R.J., & Idso, S.B. (1977). Wheat canopy temperature: A practical tool for evaluating water requirements. Water Resources Research, 13, 651–656.
37 Jackson, T.J. (1993). III. Measuring surface soil moisture using passive microwave remote sensing. Hydrological Processes, 7, 139–152.
38 Janssen, P. A. E. M., S. Abdalla, H. Hersbach & J.‐R. Bidlot (2007). Error Estimation of Buoy, Satellite, and Model Wave Height Data. Journal of Atmospheric and Oceanic Technology, 24, 1665–1677.
39 Kalluri, S.N.V., Townshend, J.R.G., & Doraiswamy, P. (1998). A simple single layer model to estimate transpiration from vegetation using multi‐spectral and meteorological data. International Journal of Remote Sensing, 19, 1037–1053.
40 Kogan, F., Adamenko, T., & Guo, W. (2013). Global and regional drought dynamics in the climate warming era. Remote Sensing Letters, 4, 364–372.
41 Kustas, W.P. (1990). Estimates of evapotranspiration with a one‐ and two‐layer model of heat transfer over partial canopy cover. Journal of Applied Meteorology, 29, 704–715.
42 Kustas, W.P., & Norman, J.M. (1996). Use of remote sensing for evapotranspiration monitoring over land surfaces. Hydrological Sciences Journal, 41, 495–516.
43 Kustas, W.P., & Norman, J.M. (1997). A two‐source approach for estimating turbulent fluxes using multiple angle thermal infrared observations. Water Resources Research, 33, 1495–1508.
44 Lagouarde, J.‐P. (1991). Use of NOAA AVHRR data combined with an agrometeorological model for evaporation mapping. International Journal of Remote Sensing, 12, 1853–1864.
45 Loague, K.M. & Freeze, R.A. (1985). A Comparison of Rainfall‐Runoff Modeling Techniques on Small Upland Catchments. Water Resources Research, 21, 229–248.
46 McFarland, M.J., R. L. Miller & C. M. U. Neale (1990). Land surface temperature derived from the SSM/I passive microwave brightness temperatures. IEEE Transactions on Geoscience and Remote Sensing, 28, 839–845.
47 McNaughton, K.J. & T. W. Spriggs (1986). A mixed‐layer model for regional evaporation Boundary‐Layer Meteorology, 74, 243–262.
48 Mecikalski, J.M., Diak, G.R. M.C. Anderson & J.M., Norman (1999). Estimating fluxes on continental scales using remotely sensed data in an atmosphere‐land exchange model. Journal of Applied Meteorology, 38, 1352–1369.
49 Miralles, D.G., Crow, W.T. & Cosh, M.H. (2010). Estimating Spatial Sampling Errors in Coarse‐Scale Soil Moisture Estimates Derived from Point‐Scale Observations. Journal of Hydrometeorology, 11, 1423–1429.
50 Monteith, J.L. (1964). Evaporation and environment. The state of movement of water in living organisms. In Symposium of the society of experimental biology, 205−234.
51 Monteith, J.L. (1988). Does transpiration limit the growth of vegetation or vice versa? Journal of Hydrology, 100, 57–68.
52 Moran, M.S., Clarke, T.R., Inoue, Y., & Vidal, A. (1994). Estimating crop water deficit using the relation between surface‐air temperature and spectral vegetation index, Remote Sensing of the Environment, 49, 246–263.
53 Mu, Q., Heinsch, F.A., Zhao, M., & Running, S.W. (2007). Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sensing of Environment, 111, 519536.
54 Neale, C.M.U., Jayanthi, H., & Wright, J.L. (2005). Irrigation water management using high resolution airborne remote sensing. Irrigation and Drainage Systems, 19, 321–336.
55 Norman, J.M., & Becker, F. (1995). Terminology in thermal infrared remote sensing of natural surfaces. Agricultural and Forest Meteorology, 77, 153–166.
56 Norman, J.M., Kustas, W.P., & Humes, K.S. (1995). A two‐source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperatures. Agricultural and Forest Meteorology, 77, 263–293.
57 Otkin, J.A., Anderson, M.C., Hain, C.R., & Svoboda, M. (2014). Using temporal changes in drought indices to generate probabilistic drought intensification forecasts. Journal of Hydrometeorology, 16(1), 110–125.
58 Penman, H.L. (1948). Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London, Series A, Mathematical and Physical Sciences, 193, 120–145.
59 Price, J.C. (1980). The potential of remotely sensed thermal infrared data to infer surface soil moisture and evaporation. Water Resources Research, 16, 787–795.
60 Price, J.C. (1982). Estimation of regional scale evapotranspiration through analysis of satellite thermal‐infrared data. IEEE Transactions on Geoscience and Remote Sensing, GE‐20, 286–292.
61 Priestley, C.H.B., & Taylor, R.J. (1972). On the assessment of surface heat flux and evaporation using large‐scale parameters. Monthly Weather Review, 100(2), 81–92. doi:10.1175/1520‐0493(1972)100<0081:OTAOSH>2.3.CO;2
62 Rabin, R.M., Stadler, S. Wetzel, P.J., Stensrud, D.J., & Gregory, M. (1990). Observed effects of landscape variability on convective clouds. Bulletin of the American Meteorological Society, 71, 272–280.
63 Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., & Wagner, W. (2008). A possible solution for the problem of estimating the error structure of global soil moisture data sets, Geophysical Research Letters, 35, L24403. doi:10.1029/2008GL035599
64 Sellers, P.J., Rasool, S.I., & Bolle, H.‐J. (1990), A review of satellite data algorithms for studies of the land surface. Bulletin of the American Meteorological Society, 71, 1429–1447.
65 Shuttleworth, W.J., Gurney, R.J., Hsu, A.Y., & Ormsby, J.P. (1989). FIFE, the variation on energy partition at surface flux sites. Washington, DC: Proceedings of IAHS Third International Assembly, International Association of Hyrological Scientists.
66 Stoffelen, A. (1998). Toward the true near‐surface wind speed: Error modeling and calibration using triple collocation. Journal of Geophysical Research: Oceans, 103, 7755–7766.
67 Su, H., McCabe, M.F., Wood, E.F., Su, Z., & Prueger, J.H. (2005). Modeling evapotranspiration during SMACEX: Comparing two approaches for local‐ and regional‐scale prediction. Journal of Hydrometeorology, 6, 910–922.
68 Sugita, M. & Brutsaert, W. (1991). Daily evaporation over a region from lower boundary layer profiles measured with radiosondes. Water Resources Research, 27, 747–752.
69 Tadesse, T., Wardlow, B.D., Brown, J.F., Svoboda, M.D., Hayes, M.J., Fuchs, B., & Gutzmer, D. (2015). Assessing the vegetation condition impacts of the 2011 drought across the U.S. Southern Great Plains using the Vegetation Drought Response Index (VegDRI). Journal of Applied Meteorology and Climatology, 54, 153–169.
70 Tang, Q., Peterson, S., Cuenca, R.H., Hagimoto, Y., & Lettenmaier,D.P. (2009). Satellite‐based near‐real‐time estimation of irrigated crop water consumption, Journal of Geophysical Research, 114, D05114. doi:10.1029/2008JD010854
71 Tanner, C.B. & Jury, W.A. (1976). Estimating evaporation and transpiration from a row crop during incomplete cover. Agronomy Journal, 68, 239243.
72 Tennekes, H. (1973). A model for the dynamics of the inversion above a convective boundary layer. Journal of Atmospheric Science, 30, 558–567.
73 Thornthwaite, C.W. (1948). An approach toward a rational classification of climate. Geographical Review, 38, 55–94.
74 Vinukollu, R.K., Wood, E.F., Ferguson, C.R., & Fisher, J.B. (2011). Global estimates of evapotranspiration for climate studies using multi‐sensor remote sensing data: Evaluation of three process‐based approaches. Remote Sensing of Environment, 115, 801–823.
75 Wang, K. & Dickinson, R.E. (2012). A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Reviews of Geophysics, 50. https://doi.org/10.1029/2011RG000373
76 Wetzel, P.J., Atlas, D., & Woodward, R.H. (1984). Determining soil moisture from geosynchronous satellite infrared data: A feasibility study. Journal of Climate and Applied Meteorology, 23, 375–391. https://doi.org/10.1175/1520‐0450(1984)023<0375:DSMFGS>2.0.CO;2
77 Yin, J., Zhan, X., Hain, C.R., Liu, J., & Anderson, M.C. (2018). A method for objectively integrating soil moisture satellite observations and model simulations toward a blended drought index. Water Resources Research, 54. https://doi.org/10.1029/2017WR021959
78 Zhan, X., Kustas, W.P., & Humes, K.S. (1996). An intercomparison study on models of sensible heat flux over partial canopy surfaces with remotely sensed surface temperature. Remote Sensing of Environment, 58, 242–256.
79 Zhang, L. & Lemeur, R. (1995). Evaluation of daily evapotranspiration estimates from instantaneous measurements. Agricultural Forestry and Meteorology, 74, 139–154.