Next Article in Journal
Attention-Based CNN and Bi-LSTM Model Based on TF-IDF and GloVe Word Embedding for Sentiment Analysis
Previous Article in Journal
Ensemble Voting-Based Multichannel EEG Classification in a Subject-Independent P300 Speller
Article

Predicting Climate Change Impact on Water Productivity of Irrigated Rice in Malaysia Using FAO-AquaCrop Model

1
Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia
2
Department of Soil and Water, Faculty of Agriculture, Sebha University, Sebha, Libya
3
Department of Irrigation and Water Management, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
4
Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia
*
Author to whom correspondence should be addressed.
Academic Editor: Cheng-Yu Ku
Appl. Sci. 2021, 11(23), 11253; https://doi.org/10.3390/app112311253
Received: 16 August 2021 / Revised: 6 November 2021 / Accepted: 13 November 2021 / Published: 26 November 2021
(This article belongs to the Section Agricultural Science and Technology)
Water productivity (WP) is a key indicator of agricultural water management, since it affects the quantity of water used for crop yield in various management scenarios. This study evaluated the WP of irrigated rice due to a changing climate in the Northwest Selangor Rice Irrigation Scheme (NSRIS) by using field experimental data and the FAO-AquaCrop Model. Pertinent soil, water, climate, and crop data were acquired by executing a field investigation during the off-season (dry season, January–April) and main season (wet season, July–October) in 2017. The AquaCrop 6.0 model was calibrated and validated using the measured data. A Climate-smart Decision Support System (CSDSS) with an ensemble of 10 Global Climate Models (GCMs) was used to downscale climate variables under RCP4.5, RCP6.0, and RCP8.5 emission scenarios during baseline (1976 to 2005) and future (2020 to 2099) periods. The AquaCrop model fairly predicted rice yields under field conditions with root-mean-square error (RMSE), mean absolute error (MAE), prediction error (PE) and index of agreement (d) between the observed and estimated yields of 0.173, 0.157, −0.31 to 5.4 and 0.78, respectively for the off-season; and 0.167, 0.127, −5.6 to 2.3 and 0.73, respectively for the main season. It predicted a 10% decrease in actual crop evapotranspiration (ETc) in both crop seasons in the future. The WP of rice based on total water input (WPIrr+RF), applied irrigation (WPIrr), and actual crop evapotranspiration (WPETc) will likely increase by 14–24%, 14–19%, and 17–29%, respectively under the three RCP emission scenarios in the off-season. The likely increase in WP for the corresponding base is 13–22%, 15–24%, and 14–25% in the main season. Various agronomic management options linked to WP will most likely become important in making crucial decisions to cope with the risk of impacts on climate change. View Full-Text
Keywords: water productivity; rice irrigation; climatic impact; AquaCrop model; CSDSS; Malaysia water productivity; rice irrigation; climatic impact; AquaCrop model; CSDSS; Malaysia
Show Figures

Graphical abstract

MDPI and ACS Style

Houma, A.A.; Kamal, M.R.; Mojid, M.A.; Zawawi, M.A.M.; Rehan, B.M. Predicting Climate Change Impact on Water Productivity of Irrigated Rice in Malaysia Using FAO-AquaCrop Model. Appl. Sci. 2021, 11, 11253. https://doi.org/10.3390/app112311253

AMA Style

Houma AA, Kamal MR, Mojid MA, Zawawi MAM, Rehan BM. Predicting Climate Change Impact on Water Productivity of Irrigated Rice in Malaysia Using FAO-AquaCrop Model. Applied Sciences. 2021; 11(23):11253. https://doi.org/10.3390/app112311253

Chicago/Turabian Style

Houma, Abdusslam A., Md R. Kamal, Md A. Mojid, Mohamed A.M. Zawawi, and Balqis M. Rehan. 2021. "Predicting Climate Change Impact on Water Productivity of Irrigated Rice in Malaysia Using FAO-AquaCrop Model" Applied Sciences 11, no. 23: 11253. https://doi.org/10.3390/app112311253

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop