Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin

Water Resources Research

Volumn 50, Issue 1, 2014, Pages 386-408

  Yilmaz, M Tugrul ^a,b   Anderson, Martha C ^a   Zaitchik, Ben ^c   Hain, Chris R ^d   Crow, Wade T ^a   Ozdogan, Mutlu ^e   Chun, Jong Ahn ^f   Evans, Jason ^g  

^a AGRICULTURAL RESEARCH SERVICE   (United States)

^b SCIENCE SYSTEMS AND APPLICATIONS INC   (United States)

^c JOHNS HOPKINS UNIVERSITY   (United States)

^d UNIVERSITY OF MARYLAND   (United States)

^e UNIVERSITY OF WISCONSIN MADISON   (United States)

^f APEC Climate Center   (South Korea)

^g UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

diagnostic modeling; Nile; prognostic modeling; surface flux modeling

Indexed keywords

DIAGNOSTIC MODEL; LAND SURFACE TEMPERATURE; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER; NILE; PROGNOSTIC MODEL; REGIONAL EVAPOTRANSPIRATION; SPATIAL AND TEMPORAL DISTRIBUTION; SURFACE FLUX;

ATMOSPHERIC TEMPERATURE; ESTIMATION; RADIOMETERS; REMOTE SENSING; SATELLITE IMAGERY; WATERSHEDS;

SURFACE MEASUREMENT;

ACCURACY ASSESSMENT; DATA SET; ENERGY BALANCE; ESTIMATION METHOD; EVAPOTRANSPIRATION; PRECIPITATION (CLIMATOLOGY); REMOTE SENSING; RIVER BASIN; SURFACE FLUX; WATER BUDGET;

NILE BASIN;

EID: 84896718352     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2013WR014194     Document Type: Article

References (99)

1. Allen R. G., M. Tasumi, A. Morse, R. Trezza, J. Wright, W. G. M. Bastiaanssen, W. Kramber, I. Lorite, and, C. W. Robson, (2007), Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-applications, J. Irrig. Drain. Eng., 133 (4), 395-405.
2. Allen, R. G., L. S. Pereira, T. A. Howell, and, M. E. Jensen, (2011a), Evapotranspiration information reporting: I. Factors governing measurement accuracy, Agric. Water Manage., 98, 899-920.
3. Allen, R. G., L. S. Pereira, T. A. Howell, and, M. E. Jensen, (2011b), Evapotranspiration information reporting: II recommended documentation, Agric. Water Manage., 98, 921-929.
4. Anderson, M. C., J. M. Norman, G. R. Diak, W. P. Kustas, J. R. Mecikalski, (1997), A two-source time-integrated model for estimating surface fluxes from thermal infrared satellite observations, Remote Sens. Environ., 60, 195-216.
5. Anderson, M. C., W. P. Kustas, and, J. M. Norman, (2007a), Upscaling flux observations from local to continental scales using thermal remote sensing, Agron. J., 99, 240-254.
6. Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. P. Otkin, and, W. P. Kustas, (2007b), A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: I. Model formulation, J. Geophys. Res., 112, D10117, doi: 10.1029/2006JD007506.
7. Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. P. Otkin, and, W. P. Kustas, (2007c), A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: II. Surface moisture climatology, J. Geophys. Res., 112, D11112, doi: 10.1029/2006JD007507.
8. Anderson, M. C., et al. (2011), Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery, Hydrol. Earth Syst. Sci., 15, 223-239.
9. Anderson, M. C., W. P. Kustas, J. G. Alfieri, C. R. Hain, J. H. Prueger, S. R. Evett, P. D. Colaizzi, T. A. Howell, and, J. L. Chavez, (2012), Mapping daily evapotranspiration at Landsat spatial scales during the BEAREX'08 field campaign, Adv. Water Resour., 50, 162-177.
10. Anderson, M. C., W. P. Kustas, C. R. Hain, C. Cammalleri, F. Gao, M. T. Yilmaz, I. E. Mladenova, J. Otkin, M. Schull, and, R. Houborg, (2013), Mapping surface fluxes and moisture conditions from field to global scales using ALEXI/DisALEXI, in Remote Sensing of Energy Fluxes and Soil Moisture Content, Chap. 8, edited by G. P. Petropoulos, pp. 207-232, CRC Press, Boca Raton, Fla.
11. Ayenew, T., (2003), Evapotranspiration estimation using thematic mapper spectral satellite data in the Ethiopian rift and adjacent highlands, J. Hydrol., 279, 83-93.
12. Bashir, M. A., H. Tanakamaru, and, A. Tada, (2009), Remote sensing-based estimates of evapotranspiration for managing scarce water resources in the Gezira scheme, Sudan, in From Headwaters to the Ocean: Hydrological Change and Water Management-Hydrochange 2008, 1-3 October 2008, Kyoto, Japan, p. 381.
13. Bastiaanssen, W. G. M., E. J. M. Noordman, H. Pelgrum, G. Davids, B. P. Thoreson, and, R. G. Allen, (2005), SEBAL model with remotely sensed data to improve water-resources management under actual field conditions, J. Irrig. Drain. Eng., 131 (1), 85-93.
14. Betts, A. K., F. Chen, K. E. Mitchell, and, Z. I. Janjic, (1997), Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta model using FIFE data, Mon. Weather Rev., 125, 2896-2916.
15. Bindlish, R., W. P. Kustas, A. N. French, G. R. Diak, and, J. R. Mecikalski, (2001), Influence of near-surface soil moisture on regional scale heat fluxes: Model results using microwave remote sensing data from SGP97, IEEE Trans. Geosci. Remote Sens., 39, 1719-1728.
16. Cammalleri, C., M. C. Anderson, G. Ciraolo, G. D'Urso, W. P. Kustas, G. La Loggia, and, M. Minacapilli, (2012), Applications of a remote sensing-based two-source energy balance algorithm for mapping surface fluxes without in situ air temperature observations, Remote Sens. Environ., 124, 502-515.
17. Cammalleri, C., M. C. Anderson, F. Gao, C. R. Hain, W. P. Kustas, (2013a), A data fusion approach for mapping daily evapotranspiration at field scale, Water Resour. Res., 49, 4672-4686, doi: 10.1002/wrcr.20349.
18. Cammalleri, C., M. C. Anderson, and, W. P. Kustas, (2013), Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications, Hydrol. Earth Syst. Sci. Discuss., 10, 7325-7350, doi: 10.5194/hessd-10-7325-2013.
19. Chen, F., and, J. Dudhia, (2001), Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569-585.
20. Chen, F., K. Mitchell, J. Schaake, Y. Xue, H. Pan, V. Koren, Y. Duan, M. Ek, and, A. Betts, (1996), Modeling of land-surface evaporation by four schemes and comparison with FIFE observations, J. Geophys. Res., 101, 7251-7268.
21. Cheung, W. H., G. B. Senay, and, A. Singh, (2008), Trends and spatial distribution of annual and seasonal rainfall in Ethiopia, Int. J. Climatol., 28, 1723-1734.
22. Crow, W. T., F. Li, and, W. P. Kustas, (2005), Inter-comparison of spatially distributed models for predicting surface energy flux patterns during SMACEX, J. Hydrometeorol., 6, 941-953.
23. Crow, W. T., M. J. van Den Berg, G. F. Huffman, and, T. Pellarin, (2011), Correcting rainfall using satellite-based surface soil moisture retrievals: The soil moisture analysis rainfall tool (SMART), Water Resour. Res., 47, W08521, doi: 10.1029/2011WR010576.
24. de Bruin, H. A. R., I. F. Trigo, M. A. Jitan, N. Temesgen Enku, C. van der Tol, and, A. S. M. Gieske, (2010), Reference crop evapotranspiration derived from geo-stationary satellite imagery: A case study for the Fogera flood plain, NW-Ethiopia and the Jordan Valley, Jordan, Hydrol. Earth Syst. Sci., 14, 2219-2228.
25. Decharme, B., and, H. Douville, (2006), Uncertainties in the GSWP-2 precipitation forcing and their impacts on regional and global hydrological simulations, Clim. Dyn., 27, 695-713.
26. Dirmeyer, P. A., (2003), The role of the land surface background state in climate predictability, J. Hydrometeorol., 4, 599-610.
27. Dirmeyer, P. A., X. Gao, M. Zhao, Z. Guo, T. Oki, and, N. Hanasaki, (2006), GSWP-2: Multimodel analysis and implications for our perception of the land surface, Bull. Am. Meteorol. Soc., 87, 1381-1397.
28. Droogers, P., W. Immerzeel, and, C. Perry, (2009), Application of remote sensing in national water plans: Demonstration cases for Egypt, Saudi-Arabia and Tunisia, World Bank Rep. 80, FutureWater.
29. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grummann, V. Koren, G. Gayno, and, J. D. Tarpley, (2003), Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108 (D22), 8851, doi: 10.1029/2002JD003296.
30. Elhag, M., A. Psilovikos, I. Manakos, and, K. Perakis, (2011), Application of the SEBS water balance model in estimating daily evapotranspiration and evaporative fraction from remote sensing data over the Nile Delta, Water Resour. Manage., 25, 2731-2742.
31. El Haj El Tahir, M., W. Wenzhong, C.-Y. Xu, Z. Youjing, and, V. P. Singh, (2012), Comparison of methods for estimation of regional actual evapotranspiration in data scarce regions: Blue Nile Region, Eastern Sudan, J. Hydrol. Eng., 17 (4), 578-589.
32. Evans, J. P., and, B. F. Zaitchik, (2008), Modeling the large-scale water balance impact of different irrigation systems, Water Resour. Res., 44, W08448, doi: 10.1029/2007WR006671.
33. Gad, H. E., and, S. M. El-Gayar, (2010), Climate parameters used to evaluate the evapotranspiration in delta central zone of Egypt, paper presented at Fourteenth International Water Technology Conference, IWTC14 2010, Cairo.
34. Gao, F., J. Masek, M. Schwaller, and, F. G. Hall, (2006), On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance, IEEE Trans. Geosci. Remote Sens., 44, 2207-2218.
35. Godfrey, C. M., and, D. J. Stensrud, (2010), An empirical latent heat flux parameterization for the Noah land surface model, J. Appl. Meteor. Climatol., 49, 1696-1713.
36. Gowda, P. H., J. L. Chavez, P. D. Colaizzi, S. R. Evett, T. A. Howell, and, J. A. Tolk, (2008), ET mapping for agricultural water management: Present status and challenges, Irrig. Sci., 26, 223-237.
37. Gutmann, E. D., and, E. E. Small, (2007), A comparison of land surface model soil hydraulic properties estimated by inverse modeling and pedotransfer functions, Water Resour. Res., 43, W05418, doi: 10.1029/2006WR005135.
38. Hain, C. R., J. R. Mecikalski, and, M. C. Anderson, (2009), Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part i: Methodology and validation, J. Hydrometeorol., 10, 665-683.
39. Hain, C. R., W. T. Crow, J. R. Mecikalski, M. C. Anderson, and, T. Holmes, (2011), An inter-comparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling, J. Geophys. Res., 116, D15107, doi: 10.1029/2011JD015633.
40. Hain, C. R., W. T. Crow, M. C. Anderson, and, J. R. Mecikalski, (2012), An EnKF dual assimilation of thermal-infrared and microwave satellite observations of soil moisture into the Noah land surface model, Water Resour. Res., 48, W11517, doi: 10.1029/2011WR011268.
41. Hogue, T., L. Bastidas, H. Gupta, S. Soroshian, K. Mitchell, and, W. Emmerich, (2005), Evaluation and transferability of the Noah land surface model in semiarid environments, J. Hydrometeorol., 6, 68-84.
42. Huffman, G. J., R. F. Adler, D. T. Bolvin, and, E. J. Nelkin, (2010), The TRMM Multi-satellite Precipitation Analysis (TMPA), in Satellite Rainfall Applications for Surface Hydrology, chap. 1, edited by, F. Hossain, and, M. Gebremichael, pp. 3-22, Springer, Dordrecht.
43. Ingwersen, J., et al. (2011), Comparison of Noah simulations with eddy covariance and soil water measurements at a winter wheat stand, Agric. For. Meteorol., 151 (3), 345-355.
44. Jiang, L., and, S. Islam, (2003), An inter-comparison of regional latent heat flux estimation using remote sensing data, Int. J. Remote Sens., 24 (11), 2221-2236.
45. Jimenez, C., et al. (2011), Global inter-comparison of 12 land surface heat flux estimates, J. Geophys. Res., 116, D02102, doi: 10.1029/2010JD014545.
46. Joyce, R. J., J. E. Janowiak, P. A. Arkin, and, P. Xie, (2004), CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution, J. Hydrometeorol., 5, 487-503.
47. Kalma, J. D., T. R. McVicar, and, M. McCabe, (2008), Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data, Surv. Geophys., 29 (4-5), 421-469.
48. Kite, G. W., and, P. Droogers, (2000), Comparing evapotranspiration estimates fromsatellites, hydrologicalmodels and field data, J. Hydrol., 229, 3-18.
49. Kongoli, C., W. P. Kustas, M. C. Anderson, J. M. Norman, J. G. Alfieri, G. N. Flerchinger, and, D. Marks, (2013), Evaluation of a two-source snow-vegetation energy balance model for estimating surface energy fluxes in a rangeland ecosystem, J. Hydrometeorol., doi: 10.1175/JHMD-12-0153.1, in press.
50. Koren, V., J. Schaake, K. Mitchell, Q.-Y. Duan, and, F. Chen, (1999), A parameterization of snowpack and frozen ground intended for NCEP weather and climate models, J. Geophys. Res., 104, 19,569-19,585.
51. Kustas, W. P., and, J. M. Norman, (1997), A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations, Water Resour. Res., 33, 1495-1508.
52. Kustas, W. P., R. Bindlish, A. N. French, and, T. J. Schmugge, (2003), Comparison of energy balance modeling schemes using microwave-derived soil moisture and radiometric surface temperature, Water Resour. Res., 39 (2), 1039, doi: 10.1029/2002WR001361.
53. Kustas, W. P., F. Li, T. J. Jackson, J. H. Prueger, J. I. MacPherson, and, M. Wolde, (2004), Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa, Remote Sens. Environ., 92, 535-547.
54. Kustas, W. P., J. L. Hatfield, and, J. H. Prueger, (2005), The Soil Moisture-Atmosphere Coupling Experiment (SMACEX): Background, hydrometeorological conditions, and preliminary findings, J. Hydrometeorol., 6, 791-804.
55. Kurkowski, P., Nicole, D. J., Stensrud, and M. E., Baldwin, (2003), Assessment of implementing satellite-derived land cover data in the Eta model, Weather Forecasting, 18, 404-416.
56. Lamberts, E., (2009), The effects of Jonglei Canal operation scenarios on the Sudd swamps in southern Sudan, MS thesis, Univ. of Twente, Netherlands. [Available at http://essay.utwente.nl/59163/1/scriptie-E-Lamberts.pdf.]
57. LeMone, M. A., M. Tewari, F. Chen, J. G. Alfieri, and, D. Niyogi, (2008), Evaluation of the Noah land surface model using data from a fair-weather IHOP-2002 day with heterogeneous surface fluxes, Mon. Weather Rev., 136, 4915-4941.
58. Li, Z.-L., R. Tang, Z. Wan, Y. Bi, C. Zhou, B. Tang, G. Yan, and, X. Zhang, (2009), A review of current methodologies for regional evapotranspiration estimation from remotely sensed data, Sensors, 9, 3801-3853.
59. Mahfouf, J. F., and, J. Noilhan, (1991), Comparative study of various formulations of evaporations from bare soil using in situ data, J. Appl. Meteorol., 30, 1354-1365.
60. Mahrt, L., and, M. Ek, (1984), The influence of atmospheric stability on potential evaporation, J. Clim. Appl. Meteorol., 23, 222-234.
61. Mecikalski, J. R., G. R. Diak, M. C. Anderson, and, J. M. Norman, (1999), Estimating fluxes on continental scales using remotely-sensed data in an atmospheric-land exchange model, J. Appl. Meteorol., 38, 1352-1369.
62. McCabe, M., E. Wood, R. Wõjcik, M. Pan, J. Sheffield, H. Gao, and, H. Su, (2008), Hydrological consistency using multi sensor remote sensing data for water and energy cycle studies, Remote Sens. Environ., 112, 430-444.
63. Mohamed, Y. A., W. G. M. Bastiaanssen, and, H. H. G. Savenije, (2004), Spatial variability of evaporation and moisture storage in the swamps of the upper Nile studied by remote sensing techniques, J. Hydrol., 289, 145-164.
64. Mohamed, Y. A., B. J. J. M. van den Hurk, H. H. G. Savenije, and, W. G. M. Bastiaanssen, (2005a), Hydroclimatology of the Nile: Results from a regional climate model, Hydrol. Earth Syst. Sci., 9, 263-278.
65. Mohamed, Y. A., B. J. J. M. van den Hurk, H. H. G. Savenije, and, W. G. M. Bastiaanssen, (2005b), The impact of the Sudd wetland on the Nile hydroclimatology, Water Resour. Res., 41, W08420, doi: 10.1029/2004WR003792.
66. Mohamed, Y. A., W. G. M. Bastiaanssen, and, B. J. J. M. van den Hurk, (2006), New lessons on the Sudd hydrology learned from remote sensing and climate modeling, Hydrol. Earth Syst. Sci., 10 (4), 507-518.
67. Monteith, J. L., (1965), Evaporation and environment. In Symp. Soc. Exp. Biol. 19, No. 205-23, p. 4.
68. Mu, Q., F. A. Heinsch, M. Zhao, and, S. W. Running, (2007), Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519-536.
69. Mu, Q., M. Zhao, and, S. W. Running, (2011), Improvements to a MODIS global terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781-1800.
70. Mueller, B., et al. (2011), Evaluation of global observations-based evapotranspiration datasets and IPCC AR4 simulations, Geophys. Res. Lett., 38, L06402, doi: 10.1029/2010GL046230.
71. Niu, G.-Y., et al. (2011), The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res., 116, D12109, doi: 10.1029/2010JD015139.
72. Norman, J. M., W. P. Kustas, and, K. S. Humes, (1995). A two-source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperature, Agric. For. Meteorol., 77, 263-293.
73. Overgaard, J., D. Rosbjerg, and, M. B. Butts, (2006), Land-surface modelling in hydrological perspective-A review, Biogeosciences, 3, 229-241.
74. Ozdogan, M., M. Rodell, H. K. Beaudoing, and, D. Toll, (2010), Simulating the effects of irrigation over the United States in a land surface model based on satellite-derived agricultural data, J. Hydrometeorol., 11, 171-184.
75. Pan, M., and, E. F. Wood, (2006), Data assimilation for estimating the terrestrial water budget using a constrained ensemble Kalman filter, J. Hydrometeorol., 7, 534-547.
76. Petersen, G., and, N. Fohrer, (2010), Flooding and drying mechanisms of the seasonal Sudd flood plains along the Bahr el Jebel in Southern Sudan, Hydrol. Sci. J., 55 (1), 4-16.
77. Peters-Lidard, C. D., S. V. Kumar, D. M. Mocko, and, Y. Tian, (2011), Estimating evapotranspiration with land data assimilation systems, Hydrol. Processes, 25, 3979-3992.
78. Priestley, C. H. B., and, R. J. Taylor, (1972), On the assessment of surface heat flux and evaporation using large scale parameters, Mon. Weather Rev., 100, 81-92.
79. Rana, G., and, N. Katerji, (2000), Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: A review, Eur. J. Agron., 13, 125-153.
80. Rebelo, L.-M., G. B. Senay, and, M. P. McCartney, (2012), Flood pulsing in the Sudd wetland: Analysis of seasonal variations in inundation and evaporation in South Sudan, Earth Interact., 16, 1-19, doi: 10.1175/2011EI382.1.
81. Reichle, R. H., W. T. Crow, R. D. Koster, H. O. Sharif, and, S. P. P. Mahanama, (2008), Contribution of soil moisture retrievals to land data assimilation products, Geophys. Res. Lett., 35, L01404, doi: 10.1029/2007GL031986.
82. Reichle, R. H., S. V. Kumar, S. P. P. Mahanama, R. D. Koster, and, Q. Liu, (2010), Assimilation of satellite-derived skin temperature observations into land surface models, J. Hydrometeorol., 11, 1103-1122.
83. Senay, G. B., M. Budde, J. P. Verdin, and, A. M. Melesse, (2007), A coupled remote sensing and simplified surface energy balance approach to estimate actual evapotranspiration from irrigated fields, Sensors, 7, 979-1000.
84. Senay, G. B., K. Asante, and, G. Artan, (2009), Water balance dynamics in the Nile basin, Hydrol. Processes, 23, 3675-3681.
85. Senay, G. B., S. Leake, P. L. Nagler, G. Artan, J. Dickinson, J. T. Cordova, and, E. P. Glenn, (2011), Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods, Hydrol. Processes, 25, 4037-4049, doi: 10.1002/hyp.8379.
86. Simane, B., B. F. Zaitchik, and, D. Mesfin, (2012), Building climate resilience in the Blue Nile/Abay Highlands: A framework for action, Int. J. Environ. Res. Public Health., 9 (2), 610-631.
87. Simonneaux, V., M. A. A. Abdrabbo, S. M. Saleh, M. K. Hassanein, A. F. Abou-Hadid, and, A. Chehbouni, (2010), MODIS estimates of annual evapotranspiration of irrigated crops in the Nile delta based on the FAO method: Application to the Nile river budget, in Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, Proc. of SPIE Vol. 7824, 78241S, edited by Christopher M. U. Neale, Antonino Maltese, doi: 10.1117/12.865066.
88. Sridhar, V., R. L. Elliott, F. Chen, and, J. A. Brotzge, (2002), Validation of the Noah-OSU land surface model using surface flux measurements in Oklahoma, J. Geophys. Res., 107 (D20), 4418, doi: 10.1029/2001JD001306.
89. Su, H., E. F. Wood, M. F. McCabe, and, Z. Su, (2007), Evaluation of remotely sensed evapotranspiration over the CEOP EOP-1 reference sites, J. Meteorol. Soc. Jpn., 85A, 439-459.
90. Sutcliffe, J. V., and, Y. P. Parks, (1999), The Hydrology of the Nile, edited by H. Salz, Z. W. Kundzewicz, IAHS Spec. Publ. 5, IAHS Press, Wallingford, U. K.
91. Vinukollu, R. K., E. F. Wood, C. R. Ferguson, and, J. B. Fisher, (2011), Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches, Remote Sens. Environ., 115, 801-823.
92. Wan, Z., and, J. Dozier, (1996), A generalized split-window algorithm for retrieving land-surface temperature from space. Geoscience and Remote Sensing, IEEE Transactions on, 34 (4), 892-905.
93. Wei, H., Y. Xia, K. E. Mitchell, and, M. B. Ek, (2012), Improvement of the Noah land surface model for warm season processes: Evaluation of water and energy flux simulation, Hydrol. Processes, 27, 297-303. doi: 10.1002/hyp.9214.
94. Yilmaz, M. T., and, W. T. Crow, (2013), The optimality of potential rescaling approaches in land data assimilation, J. Hydrometeorol., 14, 650-660 doi: 10.1175/JHM-D-12-052.1.
95. Yilmaz, M. T., T. DelSole, and, P. R. Houser, (2011), Improving land data assimilation performance with a water budget constraint, J. Hydrometeorol., 12, 1040-1055.
96. Yilmaz, M. T., T. DelSole, and, P. R. Houser, (2012a), Reducing water imbalance in land data assimilation: Ensemble filtering without perturbed observations, J. Hydrometeorol., 13 (1), 413-420.
97. Yilmaz, M. T., W. T. Crow, M. C. Anderson, and, C. Hain, (2012b), An objective methodology for merging satellite- and model-based soil moisture products, Water Resour. Res., 48, W11502, doi: 10.1029/2011WR011682.
98. Zaitchik, B. F., J. Evans, R. B. Smith, (2005), MODIS-derived boundary conditions for a mesoscale climate model: Application to irrigated agriculture in the Euphrates basin, Mon. Wea. Rev., 133, 1727-1743, doi:10.1175/MWR2947.1.
99. Zaitchik, B. F., B. Simane, S. Habib, M. C. Anderson, M. Ozdogan, and, J. D. Foltz, (2012), Building climate resilience in the Blue Nile/Abay Highlands: A role for earth system sciences, Int. J. Environ. Res. Public Health, 9 (2), 435-461.