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Modeling the crop transpiration using an optimality-based approach

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons62555

Schymanski,  S. J.
Terrestrial Biosphere, Research Group Biospheric Theory and Modelling, Dr. A. Kleidon, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Lei, H. M., Yang, D. W., Schymanski, S. J., & Sivapalan, M. (2008). Modeling the crop transpiration using an optimality-based approach. Science in China Series E - Technological Sciences, 51(Suppl 2), 60-75.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000E-D6E3-E
Abstract
Evapotranspiration constitutes more than 80% of the long-term water balance in Northern China. In this area, crop transpiration due to large areas of agriculture and irrigation is responsible for the majority of evapotranspiration. A model for crop transpiration is therefore essential for estimating the agricultural water consumption and understanding its feedback to the environment. However, most existing hydrological models usually calculate transpiration by relying on parameter calibration against local observations, and do not take into account crop feedback to the ambient environment. This study presents an optimality-based ecohydrology model that couples an ecological hypothesis, the photosynthetic process, stomatal movement, water balance, root water uptake and crop senescence, with the aim of predicting crop characteristics, CO2 assimilation and water balance based only on given meteorological data. Field experiments were conducted in the Weishan Irrigation District of Northern China to evaluate performance of the model. Agreement between simulation and measurement was achieved for CO2 assimilation, evapotranspiration and soil moisture content. The vegetation optimality was proven valid for crops and the model was applicable for both C-3 and C-4 plants. Due to the simple scheme of the optimality-based approach as well as its capability for modeling dynamic interactions between crops and the water cycle without prior vegetation information, this methodology is potentially useful to couple with the distributed hydrological model for application at the watershed scale. [References: 41]