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Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards

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  • Xue, Jingyuan
  • Fulton, Allan
  • Kisekka, Isaya

Abstract

California’s weather is characterized by extreme droughts and floods. This has resulted in overdraft of groundwater aquifers as growers turn to this source of water for irrigation during droughts. California produces 99% of all walnuts in the US, walnut growers are under extreme pressure to optimize crop water use. Water use estimates at the field scale are crucial for growers to refine irrigation scheduling decisions. In this study, two single source remote sensing-based energy balance models (pySEBAL [python-based Surface Energy Balance Algorithm for Land] and SEBS [Surface Energy Balance System algorithm]) for estimating evapotranspiration (ETa) were evaluated against in-situ ETa measurements from surface renewal in two young walnut orchards in California’s Sacramento Valley. Strong correlations were obtained between the RS-based estimates and in-situ measurements for both pySEBAL and SEBS from 2017 to 2020, with R2 above 0.87, RMSE ranging from 0.79 to 1.05 mm, and NSE ranging from 0.79 to 0.88. SEBS out-performed pySEBAL on estimating time-series daily ETa for walnut at the field scale. During the mid-season characterized by high wind speed and high temperatures, pySEBAL and SEBS both underestimated ETa while the two models slightly overestimated ETa during the early growing season and post-harvest period. These results indicate the need for future research to focus on improving the performance of pySEBAL and SEBS when simulating time-series ETa under advection and sparse vegetation conditions, to provide more accurate ETa for both in-season and off-season irrigation water management. Comparisons of historical Kc and RS-based Kc were evaluated, and RS-based Kc matched better with the actual water use requirements of developing 2nd to 4th leaf young walnuts orchards. We observed substantial spatiotemporal variability of RS-based Kc in wo young walnut orchards at the CAPEX and Kauffman sites. For instance, Kc values for the north and south halves of the CAPEX orchard were above 1.2 and 0.9–1.1 respectively. Kc values for the north and south halves at the Kauffman site were in a range of 0.6–0.71 and 0.82–0.94 respectively. In other words, conventional irrigation management based on multiplying historical Kc and reference evapotranspiration is inadequate for site-specific walnut irrigation management due to spatial and temporal variability in Kc. ETa and Kc mapping from two single source models were similar in the spatial patterns and provided an overall visual characterization of the spatial variability in crop water use. Overall, RS-based ETa models using freely accessible satellite images and open-source algorithms could be used as an alternative to expensive in-situ measurements for enhancing site-specific young walnut irrigation management.

Suggested Citation

  • Xue, Jingyuan & Fulton, Allan & Kisekka, Isaya, 2021. "Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards," Agricultural Water Management, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:agiwat:v:256:y:2021:i:c:s0378377421004091
    DOI: 10.1016/j.agwat.2021.107132
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    1. Bhatti, Sandeep & Heeren, Derek M. & Barker, J. Burdette & Neale, Christopher M.U. & Woldt, Wayne E. & Maguire, Mitchell S. & Rudnick, Daran R., 2020. "Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery," Agricultural Water Management, Elsevier, vol. 230(C).
    2. Yuei-An Liou & Sanjib Kumar Kar, 2014. "Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review," Energies, MDPI, vol. 7(5), pages 1-29, April.
    3. Raziei, Tayeb & Pereira, Luis S., 2013. "Estimation of ETo with Hargreaves–Samani and FAO-PM temperature methods for a wide range of climates in Iran," Agricultural Water Management, Elsevier, vol. 121(C), pages 1-18.
    4. Xue, Jingyuan & Bali, Khaled M. & Light, Sarah & Hessels, Tim & Kisekka, Isaya, 2020. "Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize," Agricultural Water Management, Elsevier, vol. 238(C).
    5. Tasumi, Masahiro & Kimura, Reiji, 2013. "Estimation of volumetric soil water content over the Liudaogou river basin of the Loess Plateau using the SWEST method with spatial and temporal variability," Agricultural Water Management, Elsevier, vol. 118(C), pages 22-28.
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    1. Williams, Larry E. & Levin, Alexander D. & Fidelibus, Matthew W., 2022. "Crop coefficients (Kc) developed from canopy shaded area in California vineyards," Agricultural Water Management, Elsevier, vol. 271(C).

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