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| Calculation and Simulation of Evapotranspiration of Applied Water |
| Richard L Snyder, Morteza Orang, Sara Sarreshteh |
1.Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
2.School of Environment and Energy, Shenzhen Graduate School, Peking University, Shenzhen 518055, P.R.China
3.Department of Plant Sciences, University of California, Davis, CA 95616, USA
4.California Department of Water Resources, Division of Statewide Integrated Water Management, Water Use and Efficiency, Sacramento,
CA 94236, USA |
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摘要 The University of California, Davis and the California Department of Water Resources have developed a weather generator application program “SIMETAW” to simulate weather data from climatic records and to estimate reference evapotranspiration (ETo) and crop evapotranspiration (ETc) with the generated simulation data or with observed data. A database of default soil depth and water holding characteristics, effective crop rooting depths, and crop coefficient (Kc) values to convert ETo to ETc are input into the program. After calculating daily ETc, the input and derived data are used to determine effective rainfall and to generate hypothetical irrigation schedules to estimate the seasonal and annual evapotranspiration of applied water (ETaw), where ETaw is the net amount of irrigation water needed to produce a crop. In this paper, we will discuss the simulation model and how it determines ETaw for use in water resources planning.
Abstract The University of California, Davis and the California Department of Water Resources have developed a weather generator application program “SIMETAW” to simulate weather data from climatic records and to estimate reference evapotranspiration (ETo) and crop evapotranspiration (ETc) with the generated simulation data or with observed data. A database of default soil depth and water holding characteristics, effective crop rooting depths, and crop coefficient (Kc) values to convert ETo to ETc are input into the program. After calculating daily ETc, the input and derived data are used to determine effective rainfall and to generate hypothetical irrigation schedules to estimate the seasonal and annual evapotranspiration of applied water (ETaw), where ETaw is the net amount of irrigation water needed to produce a crop. In this paper, we will discuss the simulation model and how it determines ETaw for use in water resources planning.
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Received: 16 November 2011
Accepted:
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Corresponding Authors:
Correspondence Shu Geng, Tel: +86-755-26032802, E-mail: sgeng@ucdavis.edu, gengxu@pkusz.edu.cn
E-mail: sgeng@ucdavis.edu
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Cite this article:
Richard L Snyder, Morteza Orang, Sara Sarreshteh.
2012.
Calculation and Simulation of Evapotranspiration of Applied Water. Journal of Integrative Agriculture, 12(3): 489-501.
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| [1]Allen R G, Pereira L S, Raes D, Smith M. 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper. 56, FAO, Rome. [2]Allen R G, Walter I A, Elliott R L, Howell T A, Itenfisu D, Jensen M E, Snyder R L. 2005. The ASCE Standardized Reference Evapotranspiration Equation. American Society of Civil Engineers. Reston, Virginia. p. 192. Berman M B. 1971. Generating Gamma Distributed Variates for Computer Simulation. 12, 1241-1247. [3]Doorenbos J, Pruitt W O. 1977. Guidelines for predicting crop water requirements. FAO Irrigation and Drainage Paper. 24, FAO, Rome. Duffie J A, Beckman W A. 1980. Solar Engineering of Thermal Processes. John Wiley and Sons, New York. pp. 1-109. [4]Gabriel K R, Neumann J. 1962. A markov chain model for daily rainfall occurrence at Tel Aviv. Quarterly Journal of the Royal Meteorological Society, 88, 90-95. [5]Geng S, Penning de Vries F W T, Supit I. 1986. A simple method for generating daily rainfall data. Agricultural and Forest Meteorology, 36, 363-376. [6]Geng S, Auburn J. 1987. Weather simulation models based on summaries of long-term data. In: International Symposium on Impact of Weather Parameters on the Growth and Yield of Rice. April 7-10, 1986. [7]IRRI. Manila, Philippines. Larsen G A, Pense R B. 1982. Stochastic simulation of daily climate data for agronomic models. Agronomy Journal, 74, 510-514. [8]Snyder R L, Bali K, Ventura F, Gomez-MacPherson H. 2000. Estimating evaporation from bare or nearly bare soil. Journal of Irrigation and Drainage Engineering, 126, 399-403. [9]Snyder R L, Pruitt W O. 1992. Evapotranspiration data management in California. In: Irrigation and Drainage Session Proceedings Water Forum 1992. Baltimore, MD, USA. pp. 128-133. [10]Richardson C W, Wright D A. 1984. WGEN: a Model for Generations Daily Weather Variables. USDA-ARS-8, Springfield, VA. Stern R D. 1980. The calculation of probability distribution for models of daily precipitation. Archiv für Meteorologie, Geophysik und Bioklimatologie (Serie B). vol. 28. Spring-Verlag, New York. pp. 137-147. [11]Stroosnijder L. 1987. Soil evaporation: test of a practical approach under semi-arid conditions. Netherlands Journal of Agricultural Science, 35, 417-426. [12]Ventura F, Snyder R L, Bali K M. 2006. Estimating evaporation from bare soil using soil moisture data. Journal of Irrigation and Drainage Engineering, 132, 153-158. |
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