Methods for estimation of missing meteodata required by scheduling irrigation models
Keywords:
evapotranspiration; irrigation scheduling; meteodata; missing dataAbstract
Irrigation scheduling models require a full set of meteorological data to determine the time to irrigate and amount of irrigation water for agricultural crops. Determination of evapotranspiration is part of these models and they require the availability of real current data. Frequently, some of the indicators are missing from the meteodata required by the irrigation models. Then the task of their estimation appears. Various cheap stationary or mobile weather stations and instruments are available in the market, but they are able to provide just some of the necessary data. If any of the required weather data are missing or cannot be calculated, it is strongly recommended that the user estimate the missing data. Procedures to estimate missing air temperature, humidity, radiation, wind speed and precipitation data are given in the article with some examples.
References
Acock, M.C., & Pachepsky, Y.A. (2000). Estimating missing weather data for agricultural simulations us ing group method of data handling. Journal of Applied Meteorology, 39(7), 1176-1184.
Allen, R.G., Pereira, L.S., Raes, D., & Smith, M. (1988). Crop evapotranspiration - Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56. FAO. ISBN 92-5-104219-5.
Chatterjee, C., & Singh, R. (2014). Watershed Hydrology. Lesson 7 - Estimation of Missing Rainfall Data. http:// ecoursesonline.iasri.res.in/mod/page/view.php?id=2210.
Dimas, F., Gilani, S., & Aris, M. (2011, February). Hourly solar radiation estimation from limited meteorological data to complete missing solar radiation data. In: Pro ceedings of the International Conference on Enviroment Science and Engineering IPCBEE, Singapore, vol. 8, 14-18.
Dumais, R.E., & Young, K.C. (1995). Using a self-learning algorithm for single-station quantitative precipitation forecasting in Germany. Weather and Forecasting, 10(1), 105-113.
El-Sebaii, A. A., Al-Ghamdi, A.A., Al-Hazmi, F.S., & Faidah, A.S. (2009). Estimation of global solar radiation on horizontal surfaces in Jeddah, Saudi Arabia. Energy Policy, 37(9), 3645-3649.
Hozo, S.P., Djulbegovic, B., & Hozo, I. (2005). Estimating the mean and variance from the median, range, and the size of a sample. BMC Medical Research Methodol ogy, 5(1), 13.
Jamal, H. (2017). Estimation and Analysis of Missing Precipitation Data. https://www.aboutcivil.org/analysis of-precipitation-data.html.
Jensen, M.E. (1967). Empirical methods of estimating or predicting evapotranspiration using radiation. In: Proc. ASAE Conf. “Evapotranspiration and Its Role in Water Resources Management”. USA-IL-Chicago, 1966/12/05 06, pp. 49-53.
Jensen, M.E. (1969). Scheduling irrigation with comput ers. Journal of Soil and Water Conservation, 24(5), 193-195.
Jensen, M.E. (1981). Summary and challenges. In: Irriga tion Scheduling for Water and Energy Conservation in the 80th, 194-201.
Jensen, M.E., Robb, D.C., & Franzoy, C.E. (1970). Sched uling irrigations using climate-crop-soil data. Proceed ings of the American Society of Civil Engineers, Journal of the Irrigation and Drainage Division, 96(IRI), 25-38.
Krafti, G., Sadovski, A., Khristov, I., & Kolev, B. (1980). The prognosis and management of irrigation regime. Rastenievadni Nauki, 17(4), 135-143.
Lawrence, M.G. (2005). The relationship between relative humidity and the dewpoint temperature in moist air: A simple conversion and applications. Bulletin of the American Meteorological Society, 86(2), 225-234.
López-Moreno, J.I., Hess, T.M., & White, S.M. (2009). Estimation of reference evapotranspiration in a moun tainous mediterranean site using the Penman-Monteith equation with limited meteorological data. Pirineos, 164, 7-31.
Meteoblue. (2018). Weather history download - Panicheri 42.48°N, 24.58°E. https://content.meteoblue.com/en/ service-specifications/data-sources.
Penman, H.L. (1948). Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193(1032), 120-145.
Sadovski, A. (2018). Basic natural factors influencing sustainable agriculture. Ecological Engineering and Environment Protection, (1), 66-72.
Sadovski, A., & Christov, I. (2018). Decision support sys tem for irrigated crops growers. Ecological Engineering and Environment Protection, 38-45 (Bg).
Teegavarapu, R.S., Tufail, M., & Ormsbee, L. (2009). Optimal functional forms for estimation of missing pre cipitation data. Journal of Hydrology, 374(1-2), 106-115.
Zhang, Q., Cui, N., Feng, Y., Gong, D., & Hu, X. (2018). Improvement of Makkink model for reference evapo transpiration estimation using temperature data in Northwest China. Journal of Hydrology, 566, 264-273
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2019 Bulgarian Journal of Crop Science
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
