Abstract
In recent years, deep learning algorithms have been successfully applied in the development of decision support systems in various aspects of agriculture, such as yield estimation, crop diseases, weed detection, etc. Agriculture is the largest consumer of freshwater. Due to challenges such as lack of natural resources and climate change, an efficient decision support system for irrigation is crucial. Evapotranspiration and soil water content are the most critical factors in irrigation scheduling. In this paper, the ability of Long Short-Term Memory (LSTM) and Bidirectional LSTM (BLSTM) to model daily reference evapotranspiration and soil water content is investigated. The application of these techniques to predict these parameters was tested for three sites in Portugal. A single-layer BLSTM with 512 nodes was selected. Bayesian optimization was used to determine the hyperparameters, such as learning rate, decay, batch size, and dropout size.The model achieved the values of mean square error values within the range of 0.014 to 0.056 and R2 ranging from 0.96 to 0.98. A Convolutional Neural Network (CNN) model was added to the LSTM to investigate potential performance improvement. Performance dropped in all datasets due to the complexity of the model. The performance of the models was also compared with CNN, traditional machine learning algorithms Support Vector Regression, and Random Forest. LSTM achieved the best performance. Finally, the impact of the loss function on the performance of the proposed models was investigated. The model with the mean square error as loss function performed better than the model with other loss functions.
Highlights
The world’s population living in urban areas will increase by 13% by 2050 [1]
Evapotranspiration is the amount of water that evaporates from the Earth and plant surface
The Penman–Monteith equation recommended by the Food and Agriculture Organization (FAO) is the most commonly used equation for calculating ET [6]
Summary
With the current agricultural production method, the capacity of the Earth is already exceeded [2]. Improving agricultural production and feeding the world without exceeding natural sources such as water remains the main problem in agriculture. It is the largest consumer of water as it consumes on average 70% of all freshwater [3]. Many factors need to be considered when scheduling irrigation. The amount of water available in the soil and reference evapotranspiration (ETo) are two critical factors [4,5]. Evapotranspiration is the amount of water that evaporates from the Earth and plant surface. The Penman–Monteith equation recommended by the Food and Agriculture Organization (FAO) is the most commonly used equation for calculating ET [6]
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