Nugroho, A.P. and Rahayu, D.E. and Sutiarso, L. and Murtiningrum, Murtiningrum and Fallah, M.A.F. and Okayasu, T. (2021) Development of short-term evapotranspiration forecasting model using time series method for supporting the precision agriculture management in tropics. In: The 2nd International Conference on Sustainable Agriculture for Rural Development, 20 October 2020, Purwokerto.
Full text not available from this repository. (Request a copy)Abstract
To support daily farm management through the environmental challenges, it is necessary to have short-term evapotranspiration forecasting to predict an n-hour step. Evapotranspiration (ET) is the sum of evaporation and transpiration from the soil surface and plant tissue that can be used to assess the water loss behaviour in open-field cultivation. The objective of this study was to develop a short-term evapotranspiration forecasting model using the time series method. The model is based on the Seasonal Autoregressive Integrated Moving Average (SARIMA). The environmental data of air temperature, relative humidity, and solar radiation were observed at Rejeki Tani Yogyakarta from January to August 2014. The ET was estimated using the FAO56 Penman-Monteith. A suitable parameter of non-seasonal autoregressive order (p), the degree of differencing (d), moving average order (q), and their seasonal parameter (P, D, Q)s were investigated to predict 12-hour ahead of ET. As the result, the suitable parameter was SARIMA(2, 1, 2)(1, 1, 1)24. From the six months model validation with the different monsoons, the MAE and RMSE ranged from 0.035636 to 0.063419, and 0.045893 to 0.079961 respectively. The R2 was between 0.8045 and 0.85902. The developed forecasting model can be used to predict the hourly evapotranspiration with acceptable error and accuracy. © Published under licence by IOP Publishing Ltd.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Additional Information: | Cited by: 0; All Open Access, Gold Open Access |
Uncontrolled Keywords: | Autoregressive moving average model; Cultivation; Forecasting; Precision agriculture; Regional planning; Sustainable development; Time series; Transpiration; Tropics; Agriculture management; Environmental challenges; Environmental data; Forecasting modeling; Model validation; Open field cultivations; Seasonal autoregressive integrated moving averages; Time series method; Evapotranspiration |
Subjects: | S Agriculture > S Agriculture (General) |
Divisions: | Faculty of Agricultural Technology > Agricultural and Biosystems Engineering |
Depositing User: | Sri JUNANDI |
Date Deposited: | 29 Sep 2024 09:01 |
Last Modified: | 29 Sep 2024 09:01 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/4348 |