Accurate estimation; Canopy interception; Evapotranspiration models; General circulation model; Meteorological variables; Rainfall estimates; Retrieval algorithms; Space measurements; Earth and Planetary Sciences (all)
Abstract :
[en] Evaporation of intercepted water by canopies accounts for a non-negligible portion of total land surface evapotranspiration. While monitoring evapotranspiration from space technology is increasingly demanded, most evapotranspiration retrieval algorithms face the problem of providing accurate estimation of evaporation from canopy interception. Because of the operations constraints or of the uncertain quality of the near-real-time rainfall estimates from satellites, the implementation of a diagnostic method is preferred to a dynamical model based on a differential equation ruling the evolution of the water storage on the canopy. In this contribution, an empirical model detecting and quantifying intercepted water on canopies, based on one meteorological variable, is optimized with forecasts from a general circulation model. This diagnostic model of interception is implemented in an evapotranspiration retrieval algorithm using mostly space measurements and its impact is commented.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Ghilain, Nicolas ; Université de Liège - ULiège > Sphères ; Meteorological and Climatological Research, Royal Meteorological Institute of Belgium, Brussels, Belgium
Arboleda, A.; Meteorological and Climatological Research, Royal Meteorological Institute of Belgium, Brussels, Belgium
Barrios, J.M.; Meteorological and Climatological Research, Royal Meteorological Institute of Belgium, Brussels, Belgium
Gellens-Meulenberghs, F.; Meteorological and Climatological Research, Royal Meteorological Institute of Belgium, Brussels, Belgium
Language :
English
Title :
Water interception by canopies for remote sensing based evapotranspiration models
Anjum, M. N., Y., Ding, D., Shangguan, M. W., Ijaz, and S., Zhang. 2016. “Evaluation of High-Resolution Satellite-Based Real-Time and Post-Real-Time Precipitation Estimates during 2010 Extreme Flood Event in Swat River Basin, Hindukush Region.” Advances in Meteorology 2016 (Article ID 2604980): 8. doi:10.1155/2016/2604980.
Bregaglio, S., M., Donatelli, R., Confalonieri, M., Acutis, and O., Orlandini. 2011. “Multi Metric Evaluation of Leaf Wetness Models for Large Area Application of Plant Disease models.” Agricultural and Forest Meteorology 151: 1163–1172. doi:10.1016/j.agrformet.2011.04.003.
Czikowsky, M. J., and D. R., Fitzjarrald. 2009. “Detecting Rainfall Interception in an Amazonian Rain Forest with Eddy Flux Measurements.” Journal of Hydrology 377: 92–105. doi:10.1016/j.jhydrol.2009.08.002.
Fisher, J. B., F., Melton, E., Middleton, C., Hain, M., Anderson, R., Allen, M. F., McCabe, et al. 2017. “The Future of Evapotranspiration: Global Requirements for Ecosystem Functioning, Carbon and Climate Feedbacks, Agricultural Management, and Water Resources.” Water Resources Research 53: 2618–2626. doi:10.1002/2016WR020175.
Fisher, J. B., K. P., Tu, and D. D., Baldocchi. 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 (3): 901–919. doi:10.1016/j.rse.2007.06.025.
Gash, J. H. C., 1979. “An Analytical Model of Rainfall Interception in Forests.” Quarterly Journal of the Royal Meteorological Society 105: 43–55. doi:10.1002/qj.49710544304.
Ghilain, N., A., Arboleda, and F., Gellens-Meulenberghs. 2011. “Evapotranspiration Modelling at Large Scale Using Near-real Time MSG SEVIRI Derived Data.” Hydrology and Earth System Sciences 15: 771–786. doi:10.5194/hess-15-771-2011.
Huffman, G. J., D. T., Bolvin, D., Braithwaite, K., Hsu, R., Joyce, C., Kidd, E. J., Nelkin, and P., Xie. 2015. “Algorithm Theoretical Basis Document (ATBD) Version 4.5. NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) NASA.”
Kim, K. S., S. E., Taylor, M. L., Gleason, and K. J., Koehler. 2002. “Model to Enhance Site-specific Estimation of Leaf Wetness Duration.” Plant Disease 86: 179–185. doi:10.1094/PDIS.2002.86.2.179.
Michel, D., C., Jimenez, D. G., Miralles, M., Jung, M., Hirschi, A., Ershadi, B., Martens, et al. 2016. “The WACMOS-ET Project Part 1: Tower-scale Evaluation of Four Remote-sensing-based Evapotranspiration Algorithms.” Hydrology and Earth System Sciences 20: 803–822. doi:10.5194/hess-20-803-2016.
Miralles, D. G., J. H., Gash, T. R. H., Holmes, R. A. M., de Jeu, and A. J., Dolman. 2010. “Global Canopy Interception from Satellite Observations.” Journal of Geophysical Research 115: D16122. doi:10.1029/2009JD013530.
Mu, Q., M., Zhao, and S. W., Running. 2011. “Improvements to a MODIS Global Terrestrial Evapotranspiration Algorithm.” Remote Sensing of Environment 115: 1781–1800. doi:10.1016/j.rse.2011.02.019.
Simmons, A., S., Uppala, D., Dee, and S., Kobayashi. 2006. “ERA-Interim: New ECMWF Reanalysis Products from 1989 Onwards.” ECMWF Newsletter 10: 26–35.
Trigo, I. F., C. C., DaCamara, P., Viterbo, J.-L., Roujean, F., Olesen, C., Barroso, F., Camacho-de Coca, et al. 2011. “The Satellite Application Facility on Land Surface Analysis.” International Journal of Remote Sensing 32 (10): 2725–2744. doi:10.1080/01431161003743199.
Zhou, T., B., Nijssen, G. J., Huffman, and D. P., Lettenmaier. 2014. “Evaluation of Real-time Satellite Precipitation Data for Global Drought Monitoring.” Journal of Hydrometeorology 15: 1651–1660. doi:10.1175/JHM-D-13-0128.1.