Analyzing Evapotranspiration in Greenhouses: A Lysimeter-Based Calculation and Evaluation Approach

Author:

Shi Wei12,Zhang Xin2,Xue Xuzhang2,Feng Feng3,Zheng Wengang2,Chen Liping12

Affiliation:

1. School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China

2. National Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China

3. Department of Environmental Engineering, Yellow River Conservancy Technical Institute, Kaifeng 475004, China

Abstract

The absence of accurate measurement or calculation techniques for crop water requirements in greenhouses frequently results in over- or under-irrigation. In order to find a better method, this study analyzed the accuracy, data consistency and practicability of the Penman–Monteith (PM), Hargreaves–Samani (HS), Pan Evaporation (PAN), and Artificial Neural Network (ANN) models. Model-calculated crop evapotranspiration (ETC) was compared with lysimeter-measured crop evapotranspiration (ETC) in the National Precision Agriculture Demonstration Station in Beijing, China. The results showed that the actual ETC over the entire experimental period was 176.67 mm. The ETC calculated with the PM, HS, PAN, and ANN model were 146.07 mm, 189.45 mm, 197.03 mm, and 174.7 mm, respectively, which were different from the actual value by −17.32%, 7.23%, 11.52%, and −1.12%, respectively. The order of the calculation accuracy for the four models is as follows: ANN model > PAN model > PM model > HS model. By comprehensively evaluating the statistical indicators of each model, the ANN model was found to have a significantly higher calculation accuracy compared to the other three models. Therefore, the ANN model is recommended for estimating ETC under greenhouse conditions. The PM and PAN models can also be used after improvement.

Funder

Research and development of intelligent irrigation regulation equipment with deep integration of water and fertilizer information diagnosis, decision-making, and control

Innovation Ability Construction Project of the Beijing Academy of Agriculture and Forestry Sciences

Natural Science foundation of Henan Province

Construction Project of Beijing Engineering Laboratory of Agricultural Internet of Things Technology

Publisher

MDPI AG

Subject

Agronomy and Crop Science

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