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Water
Volume 13
Issue 24
10.3390/w13243607
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Article

Simple and Two-Level Hierarchical Bayesian Approaches for Parameter Estimation with One- and Two-Layer Evapotranspiration Models of Crop Fields

by
Shutaro Shiraki
1,*,
Aung Kyaw Thu
2,
Yutaka Matsuno
3 and
Yoshiyuki Shinogi
4
1
Rural Development Division, Japan International Research Center for Agricultural Sciences, 1-1 Owashi, Tsukuba 305-8686, Japan
2
Department of Agricultural Research, Ministry of Agriculture, Livestock and Irrigation, Naypyitaw 15013, Myanmar
3
Department of Environmental Management, Faculty of Agriculture, Kinki University, 3327-204 Nakamachi, Nara 631-8505, Japan
4
Department of Agro-Environmental Sciences, Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Saseendran S. Anapalli
Water 2021, 13(24), 3607; https://doi.org/10.3390/w13243607
Received: 25 November 2021 / Revised: 10 December 2021 / Accepted: 14 December 2021 / Published: 15 December 2021
(This article belongs to the Special Issue Optimization of Water Use in Agricultural Systems)
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Abstract

The two-layer Shuttleworth–Wallace (SW) evapotranspiration (ET) model has been widely used for predicting ET with good results. Since the SW model has a large number of specific parameters, these parameters have been estimated using a simple non-hierarchical Bayesian (SB) approach. To further improve the performance of the SW model, we aimed to assess parameter estimation using a two-level hierarchical Bayesian (HB) approach that takes into account the variation in observed conditions through the comparison with a traditional one-layer Penman–Monteith (PM) model. The difference between the SB and HB approaches were evaluated using a field-based ET dataset collected from five agricultural fields over three seasons in Myanmar. For a calibration period with large variation in environmental factors, the models with parameters calibrated by the HB approach showed better fitting to observed ET than that with parameters estimated using the SB approach, indicating the potential importance of accounting for seasonal fluctuations and variation in crop growth stages. The validation of parameter estimation showed that the ET estimation of the SW model with calibrated parameters was superior to that of the PM model, and the SW model provided acceptable estimations of ET, with little difference between the SB and HB approaches. View Full-Text
Keywords: Bayesian inference; model parameterization; Shuttleworth–Wallace model Bayesian inference; model parameterization; Shuttleworth–Wallace model
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MDPI and ACS Style

Shiraki, S.; Thu, A.K.; Matsuno, Y.; Shinogi, Y. Simple and Two-Level Hierarchical Bayesian Approaches for Parameter Estimation with One- and Two-Layer Evapotranspiration Models of Crop Fields. Water 2021, 13, 3607. https://doi.org/10.3390/w13243607

AMA Style

Shiraki S, Thu AK, Matsuno Y, Shinogi Y. Simple and Two-Level Hierarchical Bayesian Approaches for Parameter Estimation with One- and Two-Layer Evapotranspiration Models of Crop Fields. Water. 2021; 13(24):3607. https://doi.org/10.3390/w13243607

Chicago/Turabian Style

Shiraki, Shutaro, Aung K. Thu, Yutaka Matsuno, and Yoshiyuki Shinogi. 2021. "Simple and Two-Level Hierarchical Bayesian Approaches for Parameter Estimation with One- and Two-Layer Evapotranspiration Models of Crop Fields" Water 13, no. 24: 3607. https://doi.org/10.3390/w13243607

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