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Dynamic Management Zones for Irrigation Scheduling

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  • Fontanet, Mireia
  • Scudiero, Elia
  • Skaggs, Todd H.
  • Fernàndez-Garcia, Daniel
  • Ferrer, Francesc
  • Rodrigo, Gema
  • Bellvert, Joaquim

Abstract

Irrigation scheduling decision-support tools can improve water use efficiency by matching irrigation recommendations to prevailing soil and crop conditions within a season. Yet, little research is available on how to support real-time precision irrigation that varies within-season in both time and space. We investigate the integration of remotely sensed NDVI time-series, soil moisture sensor measurements, and root zone simulation forecasts for in-season delineation of dynamic management zones (MZ) and for a variable rate irrigation scheduling in order to improve irrigation scheduling and crop performance. Delineation of MZ was conducted in a 5.8-ha maize field during 2018 using Sentinel-2 NDVI time-series and an unsupervised classification. The number and spatial extent of MZs changed through the growing season. A network of soil moisture sensors was used to interpret spatiotemporal changes of the NDVI. Soil water content was a significant contributor to changes in crop vigor across MZs through the growing season. Real-time cluster validity function analysis provided in-season evaluation of the MZ design. For example, the total within-MZ daily soil moisture relative variance decreased from 85% (early vegetative stages) to below 25% (late reproductive stages). Finally, using the Hydrus-1D model, a workflow for in-season optimization of irrigation scheduling and water delivery management was tested. Data simulations indicated that crop transpiration could be optimized while reducing water applications between 11 and 28.5% across the dynamic MZs. The proposed integration of spatiotemporal crop and soil moisture data can be used to support management decisions to effectively control outputs of crop × environment × management interactions.

Suggested Citation

  • Fontanet, Mireia & Scudiero, Elia & Skaggs, Todd H. & Fernàndez-Garcia, Daniel & Ferrer, Francesc & Rodrigo, Gema & Bellvert, Joaquim, 2020. "Dynamic Management Zones for Irrigation Scheduling," Agricultural Water Management, Elsevier, vol. 238(C).
    • Handle: RePEc:eee:agiwat:v:238:y:2020:i:c:s0378377419319821
    DOI: 10.1016/j.agwat.2020.106207
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    1. Zurweller, B.A. & Rowland, D.L. & Mulvaney, M.J. & Tillman, B.L. & Migliaccio, K. & Wright, D. & Erickson, J. & Payton, P. & Vellidis, G., 2019. "Optimizing cotton irrigation and nitrogen management using a soil water balance model and in-season nitrogen applications," Agricultural Water Management, Elsevier, vol. 216(C), pages 306-314.
    2. Autovino, Dario & Rallo, Giovanni & Provenzano, Giuseppe, 2018. "Predicting soil and plant water status dynamic in olive orchards under different irrigation systems with Hydrus-2D: Model performance and scenario analysis," Agricultural Water Management, Elsevier, vol. 203(C), pages 225-235.
    3. Liang, Xi & Liakos, Vasilis & Wendroth, Ole & Vellidis, George, 2016. "Scheduling irrigation using an approach based on the van Genuchten model," Agricultural Water Management, Elsevier, vol. 176(C), pages 170-179.
    4. Segovia-Cardozo, Daniel Alberto & Rodríguez-Sinobas, Leonor & Zubelzu, Sergio, 2019. "Water use efficiency of corn among the irrigation districts across the Duero river basin (Spain): Estimation of local crop coefficients by satellite images," Agricultural Water Management, Elsevier, vol. 212(C), pages 241-251.
    5. Toureiro, Célia & Serralheiro, Ricardo & Shahidian, Shakib & Sousa, Adélia, 2017. "Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition," Agricultural Water Management, Elsevier, vol. 184(C), pages 211-220.
    6. Sakaguchi, A. & Yanai, Y. & Sasaki, H., 2019. "Subsurface irrigation system design for vegetable production using HYDRUS-2D," Agricultural Water Management, Elsevier, vol. 219(C), pages 12-18.
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    2. Hongbo Wang & Hui Cao & Fuchang Jiang & Xingpeng Wang & Yang Gao, 2022. "Analysis of Soil Moisture, Temperature, and Salinity in Cotton Field under Non-Mulched Drip Irrigation in South Xinjiang," Agriculture, MDPI, vol. 12(10), pages 1-15, October.
    3. Aigul Shaimerdenova & Faya Shulenbayeva & Adaskhan Daribayeva & Karylgash Chakeyeva & Aziya Kulubekova, 2024. "Features of the application of geoinformation systems to increase the yield of agricultural land," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 4(13 (130)), pages 75-83, August.
    4. Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Lena, Bruno & Diamantopoulos, Efstathios & Ortiz, Brenda & Takhellambam, Bijoychandra & Morata, Guilherme & Bondesan, Luca, 2023. "A methodology to optimize site-specific field capacity and irrigation thresholds," Agricultural Water Management, Elsevier, vol. 286(C).
    5. Bai, Jianduo & Wang, Nan & Hu, Bifeng & Feng, Chunhui & Wang, Yuzhen & Peng, Jie & Shi, Zhou, 2023. "Integrating multisource information to delineate oasis farmland salinity management zones in southern Xinjiang, China," Agricultural Water Management, Elsevier, vol. 289(C).

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