Czasopismo
Tytuł artykułu
Treść / Zawartość
Warianty tytułu
Języki publikacji
Abstrakty
ABSTRACT Determination of reference evapotranspiration (ETo) in required for design, management and scheduling of irrigation water in fan and pad greenhouses. In actual practice estimation of (ETo) in fan and pad greenhouses is often made using the Penman-Monteith FAO-56-PM; method from external meteorological data. This requires availability of accurate meteorological input data (temperature, relative humidity, wind speed, and solar radiation). This is constrained by lack of such data which is a common problem in developing countries. In this study the proposed procedure to estimate ETo is based on using limited data of outdoor historically recorded climate elements of only temperature wind speed, and site characteristics (altitude, latitude and sun shine hours). In the proposed method radiation is to be predicted from data of air temperature difference rather than its direct measurement. This because radiation measurement using pyranometers and net radiometers is borne to errors calibration errors commonly plagued by hysteresis, and nonlinearity. The obtained results of the proposed alternative procedure were statistically validated in comparison with the standard method (FAO 56 PM) using unlimited input data measured inside the greenhouse and in reference to a directly measured ETo values by class-A-evaporation pan. The performance of the developed model was evaluated by the determination coefficient of the regression "R2 for goodness-of-fit" and by using the Root Mean Square Error (RMSE). The needed data is collected during three years in three sites in Khartoum North-Sudan El Alafoon, Halfaya, and Shambat. In each site three greenhouses were employed, and data is taken every three days for three months in each year. The obtained result reveals that the proposed limited data procedure to estimate the ETo inside greenhouses agree on statistical basis well with both pan measurement and PM estimation from measured indoor climate variables. The study reveals importance of temperature data for estimating ETo in greenhouses and calls for insuring high quality temperature data for calculating ETo in fan and pad greenhouses.
Czasopismo
Rocznik
Tom
Strony
49-59
Opis fizyczny
Twórcy
autor
- Departments of Agricultural Engineering, Collage of Agricultural Studies, Sudan University of Science and Technology, Khartoum, Sudan
autor
- Departments of Agricultural Engineering, Collage of Agricultural Studies, Sudan University of Science and Technology, Khartoum, Sudan
autor
- Department of Agricultural Engineering, Faculty of Agricultural Sciences, University of Gezira, Sudan
Bibliografia
- [1] Ababaei, B. (2014). Are weather generators robust tools to study daily reference evapotranspiration and irrigation requirement? Water Resources Management 28(4): 915–932
- [2] Allen R. G, Pereira L, Raes D, Smith M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56. Rome, Italy: Food and Agriculture Organization.
- [3] Allen R., Annandale J. Jovanovic N. and Benade´N.(2002). Software for missing data error analysis of Penman-Monteith reference evapotranspiration. Irrigation Science 21(2): 57–67
- [4] Allen, R. Garcia, M.; Raes, D.; Herbas, C. (2004). Dynamics of reference evapotranspiration in the Bolivian highlands (Altiplano). Agricultural and Forest Meteorology, 125: 67-82
- [5] Cai, J., Liu, Y. Lei, T. Pereira and L.S. (2007). Estimating reference evapotranspiration with the FAO Penman-Monteith equation using daily weather forecast messages. Agricultural and Forest Meteorology, 145: 22-35
- [6] D’Odorico P. Laio F. Porporato A. Ridolfi L., Rinaldo A. and Rodriguez-Iturbe I. (2010). Ecohydrology of terrestrial ecosystems. Bio-Science 60(11): 898–907
- [7] Donatelli M., Bellocchi G. and Carlini L. (2006). A software component for estimating solar radiation. Environ Model Software, 21(3): 411–416
- [8] Fisher J. B., Whittaker R.J. and Malhi Y. (2011). ET come home: Potential evapotranspiration in geographical ecology. Global Ecology and Biogeography 20(1): 1–18
- [9] Gocic M., Trajkovic S. (2010). Software for estimating reference evapotranspiration using limited weather data. Computers and Electronics in Agriculture 71(2): 158–162
- [10] Guo D. Westra S. and Maier H.R. (2015). An R package for modeling actual, potential and reference evapotranspiration. Environ Model Softw, 78: 216–224
- [11] Hargreaves G.H. Samani Z. (1985). Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1(2): 96–99
- [12] Hess T. (1999). Potential evapotranspiration programme for automatic weather stations. Version 3. Cranfield University Silsoe, Bedford.
- [13] Jensen M.E., Burman R.D. and Allen RG. (1990). Evapotranspiration and irrigation water requirements. ASCE manuals and reports on engineering practices no. 70. Am. Soc. Civil Engrs., New York, pp 60.
- [14] Jensen, D. T., Hargreaves, G. H., Temesgen, B., and Allen, R. G. (1997). Computation of ET0 under nonideal conditions. J. Irrig. Drain. Eng. 123(5), 394–400
- [15] Kisi O. Cengiz TM. (2013). Fuzzy genetic approach for estimating reference evapotranspiration of Turkey: Mediterranean region. Water Resources Management 27(10): 3541–3553
- [16] Kra E.Y. (2010) An empirical simplification of the temperature Penman-Monteith model for the tropics. J Agric Sci 2(1): 162–171
- [17] Midgley G.F., Hannah L., Millar D., Rutherford M.C. and Powrie LW. (2002). Assessing the vulnerability of species richness to anthropogenic climate change in a biodiversity hotspot. Global Ecology and Biogeography 11(6): 445–451
- [18] Nash, J. E.; Sutcliffe, J. V. (1970). River flow forecasting through conceptual models’ part I - A discussion of principles. Journal of Hydrology 10(3): 282–290
- [19] Pandey P. K. and Pandey V. (2016) Evaluation of temperature-based Penman–Monteith (TPM) model under the humid environment. Model. Earth Syst. Environ. 2: 152
- [20] Pandey P.K., Dabral P.P. and Pandey V. (2016). Evaluation of reference evapotranspiration methods for the northeastern region of India. Int Soil Water Conserv. Res. Volume 4, Issue 1, Pages 52-63
- [21] Senay G.B., Asante K. and Artan G. (2009). Water balance dynamics in the Nile Basin. Hydrological Processes 3681: 3675–3681
- [22] Slavisa Trajkovic and Srdjan Kolakovic (2009). Estimating Reference Evapotranspiration Using Limited Weather Data. Journal of Irrigation and Drainage Engineering Volume 135, Issue 4. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000094
- [23] Sudheer, K. P., Gosain, A. K., and Ramasastri, K. S. (2003). Estimating actual evapotranspiration from limited climatic data using neural computing technique. J. Irrig. Drain. Eng. 129(3), 214–221
- [24] Todorovic M., Karic B. and Pereira L.S. (2013). Reference evapotranspiration estimate with limited weather data across a range of Mediterranean climates. J Hydrol 481: 166–176
- [25] Trajkovic, S. (2005). Temperature-based approaches for estimating reference evapotranspiration. J. Irrig. Drain. Journal of Irrigation and Drainage Engineering Volume 131, Issue 4. https://doi.org/10.1061/(ASCE)0733-9437(2005)131:4(316)
- [26] Turney, S. (2023, June 22). Chi-Square (Χ²) Tests Types, Formula & Examples. Scribbr. Retrieved November 8, 2023, from https://www.scribbr.com/statistics/chi-square-tests/
- [27] Va´zquez R.F., Hampel H. (2014). Prediction limits of a catchment hydrological model using different estimates of ETp. Journal of Hydrology 513: 216–228.
- [28] Xing Z., Chow L., Meng F.R., Rees H.W., Steve L. and Monteith J. (2008). Validating evapotranspiration equations using Bowen ratio in New Brunswick, Maritime, Canada. Sensors 8(1): 412–428
- [29] Xu CY, Singh V.P. (2002). Cross comparison of empirical equations for calculating potential evapotranspiration with data from Switzerland. Water Resour Manage 16: 197–219
- [30] Yoder R.E., Odhiambo L.O. and Wright W.C. (2005). Evaluation of methods for estimating daily reference crop evapotranspiration at a site in the humid southeast United States. Appl Eng Agric 21(2): 197–202
Typ dokumentu
article
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.psjd-504ff664-e70d-4f80-bfc6-fb613bc668be