Unraveling Apple Tree Water Needs: Why the Penman-Monteith Model Falls Short

Abstract

Accurate estimation of apple tree water requirements is crucial for effective irrigation management. This article explores the limitations of the Penman-Monteith (P-M) model in predicting evapotranspiration (ET) in apple orchards, highlighting the unique physiological and environmental factors that challenge conventional ET modeling. Key issues include the strong coupling between apple tree canopies and ambient humidity, which affects stomatal regulation, and the variability in transpiration due to factors like fruit load, tree age, and orchard management practices. The article discusses the need for real-time, component-based ET estimation and the development of crop coefficient-independent methodologies. It also presents alternative approaches, such as thermal-based ET estimation and the development of innovative indices like the Daylight Crop Water Stress Index (CWSI) and adaptive irrigation algorithms, which offer promising solutions for precise water management. The findings emphasize the importance of understanding apple tree-specific transpiration dynamics for improving irrigation strategies and promoting sustainable water use.

Introduction

Accurate determination of apple tree water requirements is paramount for effective irrigation management, yield prediction, and optimal water resource allocation. In 2012, a project was initiated to address these challenges, focusing on "detecting water stress, determining water needs, and irrigation scheduling in apple trees."

This research, contributing to a broader initiative funded by the National Institute of Food and Agriculture (NIFA), aimed to:

Develop a site-specific irrigation control and monitoring system.
Deploy a wireless sensor network for soil, weather, and plant data.
Establish real-time water requirement estimation.
Create and evaluate irrigation scheduling algorithms based on plant, soil, and weather data.

However, significant hurdles were encountered. Notably, conventional evapotranspiration (ET) models, such as the Penman-Monteith (P-M) model, failed to accurately represent stomatal regulation in apple trees due to the strong coupling between tree canopies and ambient humidity.

Furthermore, the application of automatic plant-based irrigation scheduling methods was largely unexplored in apple orchards and other tree crops. This article provides a concise overview of these challenges and highlights key findings, with detailed insights available in the cited publications.

The Limitations of the Penman-Monteith Model in Apple Trees

A fundamental issue encountered was the inadequacy of the P-M model in capturing the nuanced stomatal responses of apple trees to ambient humidity. This discrepancy underscores the need for real-time measurements of ET components.

As noted by Allen et al. (1998) in their comprehensive review of ET partitioning methods, future research should prioritize separate modeling and simulation of evaporation and transpiration. Furthermore, the reliance on crop coefficients for ET estimation has been widely criticized, emphasizing the necessity for developing crop coefficient-independent, real-time transpiration estimation methods.

Unique Characteristics of Apple Tree Transpiration

Apple trees exhibit distinct transpiration characteristics compared to crops like grass or alfalfa. Their transpiration is influenced by a multitude of canopy-related factors, including:

Canopy height and density, affecting boundary layer conductance.
Light interception.
Canopy optical and radiative properties, determining absorbed radiation.
Stomatal conductance, regulating water loss from leaves.

Unlike the radiation-driven transpiration of short, dense canopies like grass or alfalfa, apple tree transpiration is significantly affected by air vapor pressure deficit (VPD) due to the strong coupling between leaves and the surrounding air.

Moreover, factors such as training and irrigation systems, soil management, climate, tree age, and cultivar variations complicate ET estimation using a single crop coefficient, as prescribed by the FAO-56 method (Allen et al., 1998). Additionally, maximum crop ET values in apples demonstrate substantial inter-annual variability.

Stomatal conductance in apple leaves is also influenced by fruit load, with postharvest or low-yield periods leading to reduced transpiration. This phenomenon, often overlooked by weather-based ET models like CropSyst (Stockle et al., 2003), poses a challenge for accurate water use estimation.

Exploring Thermal-Based ET Estimation

Thermal-based ET estimation offers a promising alternative to the P-M approach. These methods account for factors like salinity, crop health, and water stress through canopy temperature measurements obtained using thermal cameras or sensors.

However, challenges such as soil background interference and limited resolution, particularly in sparse canopies, can introduce errors. Plant feedback or adjustment factors are needed to enhance estimations, especially during early canopy development. Complementary measurements, such as soil moisture, are also vital for validating thermal data.

Developing Advanced Transpiration Models and Irrigation Strategies

Our research focused on developing theoretical models for potential and actual apple tree transpiration, based on energy budget and leaf radiative properties (Osroosh et al., 2014, 2015).

These models incorporated sub-models for canopy temperature and total canopy conductance, utilizing microclimatic data and empirical coefficients. Furthermore, we introduced:

Daylight Crop Water Stress Index (CWSI), a novel index for continuous water status monitoring (Osroosh et al., 2016).
CWSI-DT, an adaptive irrigation scheduling algorithm with a dynamic threshold determined by plant feedback (Osroosh et al., 2015).

These innovations demonstrated high sensitivity to soil water content variations and stability under transitional weather conditions, offering promising tools for automatic irrigation scheduling in apple orchards (Mohamed et al., 2020, Osroosh et al., 2018, 2019).

Summary and Conclusion

The complexities of apple tree transpiration, driven by unique canopy characteristics and environmental interactions, reveal the limitations of traditional ET models like the Penman-Monteith. Our research highlights the necessity for real-time, component-based ET estimation and the development of crop coefficient-independent methodologies.

Thermal-based approaches, coupled with innovative indices and adaptive irrigation algorithms such as the Daylight CWSI and CWSI-DT, offer promising pathways for precise water management in apple orchards. These advancements, based on detailed understanding of apple tree physiology and microclimatic interactions, pave the way for improved irrigation strategies and sustainable water resource utilization.

Citation

Osroosh, Y., 2021. Unraveling Apple Tree Water Needs: Why the Penman-Monteith Model Falls Short. EnviTronics Lab Blog, Mar 03.

References

Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration: guidelines for computing crop water requirements. Irrigation and Drainage Paper No. 56. FAO, Rome, Italy, 300 pp.

Mohamed, A.Z., Osroosh, Y., Peters, R.T., Bates, T., Campbell, C., Ferrer-Alegre, F., 2020. Monitoring water status in apple trees using a sensitive morning crop water stress index. Irrigation and Drainage, 2020: 1–15.

Osroosh, Y. et al., 2019. Detecting fruit surface wetness using a custom-built low-resolution thermal-RGB imager. Computers and Electronics in Agriculture, 157: 509-517.

Osroosh, Y. et al., 2018. Economical thermal-RGB imaging system for monitoring agricultural crops. Computers and Electronics in Agriculture, 147: 34–43.

Osroosh, Y., Peters, R.T., Campbell, C., Zhang, Q., 2016. Comparison of irrigation automation algorithms for drip-irrigated apple trees. Computers and Electronics in Agriculture, 128: 87–99.

Osroosh, Y., Peters, R.T., Campbell, C., 2016. Daylight crop water stress index for continuous monitoring of water status in apple trees. Irrigation Science, 34(3): 209–219.

Osroosh, Y., Peters, R.T., Campbell, C., Zhang, Q., 2015. Automatic irrigation scheduling of apple trees using theoretical crop water stress index with an innovative dynamic threshold. Computers and Electronics in Agriculture, 118: 193–203.

Osroosh, Y., Peters, R.T., Campbell, C., 2015. Estimating potential transpiration of apple trees using theoretical non-water-stressed baselines. Journal of Irrigation and Drainage Engineering, 141(9): 04015009.

Osroosh, Y., Peters, R.T., Campbell, C., 2014. Estimating actual transpiration of apple trees based on infrared thermometry. Journal of Irrigation and Drainage Engineering, 141(8): 04014084.

Stockle, C.O., Donatelli, M., Nelson, R., 2003. CropSyst, a cropping systems simulation model. Eur. J. Agron., 18:289–307.