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An Evaluation of Dryland Ulluco Cultivation Yields in the Face of Climate Change Scenarios in the Central Andes of Peru by Using the AquaCrop Model

Author

Listed:
  • Ricardo Flores-Marquez

    (Centro Experimental La Molina, Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), La Molina 1981, Lima 15024, Peru)

  • Jesús Vera-Vílchez

    (Estación Experimental Agraria Santa Ana, Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), Carretera Saños Grande—Hualahoyo Km 8, Huancayo 12007, Peru)

  • Patricia Verástegui-Martínez

    (Estación Experimental Agraria Santa Ana, Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), Carretera Saños Grande—Hualahoyo Km 8, Huancayo 12007, Peru)

  • Sphyros Lastra

    (Centro Experimental La Molina, Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), La Molina 1981, Lima 15024, Peru)

  • Richard Solórzano-Acosta

    (Centro Experimental La Molina, Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), La Molina 1981, Lima 15024, Peru
    Facultad de Ciencias Ambientales, Universidad Científica del Sur (UCSUR), Lima 15067, Peru)

Abstract

Ullucus tuberosus is an Andean region crop adapted to high-altitude environments and dryland cultivation. It is an essential resource that guarantees food security due to its carbohydrate, protein, and low-fat content. However, current change patterns in precipitation and temperatures warn of complex scenarios where climate change will affect this crop. Therefore, predicting these effects through simulation is a valuable tool for evaluating this crop’s sustainability. This study aims to evaluate ulluco’s crop yield under dryland conditions at 3914 m.a.s.l. considering climate change scenarios from 2024 to 2100 by using the AquaCrop model. Simulations were carried out using current meteorological data, crop agronomic information, and simulations for SSP1-2.6, SSP3-7.0, and SSP5-8.5 of CMIP 6. The results indicate that minimum temperature increases and seasonal precipitation exacerbation will significantly influence yields. Increases in rainfall and environmental CO 2 concentrations show an opportunity window for yield increment in the early stages. However, a negative trend is observed for 2050–2100, mainly due to crop temperature stress. These findings highlight the importance of developing more resistant ulluco varieties to heat stress conditions, adapting water management practices, continuing modeling climate change effects on crops, and investing in research on smallholder agriculture to reach Sustainable Development Goals 1, 2, and 13.

Suggested Citation

  • Ricardo Flores-Marquez & Jesús Vera-Vílchez & Patricia Verástegui-Martínez & Sphyros Lastra & Richard Solórzano-Acosta, 2024. "An Evaluation of Dryland Ulluco Cultivation Yields in the Face of Climate Change Scenarios in the Central Andes of Peru by Using the AquaCrop Model," Sustainability, MDPI, vol. 16(13), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5428-:d:1422728
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    References listed on IDEAS

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    1. Geerts, S. & Raes, D. & Garcia, M. & Taboada, C. & Miranda, R. & Cusicanqui, J. & Mhizha, T. & Vacher, J., 2009. "Modeling the potential for closing quinoa yield gaps under varying water availability in the Bolivian Altiplano," Agricultural Water Management, Elsevier, vol. 96(11), pages 1652-1658, November.
    2. Gennifer Meldrum & Dunja Mijatović & Wilfredo Rojas & Juana Flores & Milton Pinto & Grover Mamani & Eleuterio Condori & David Hilaquita & Helga Gruberg & Stefano Padulosi, 2018. "Climate change and crop diversity: farmers’ perceptions and adaptation on the Bolivian Altiplano," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(2), pages 703-730, April.
    3. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    4. Wellens, Joost & Raes, Dirk & Fereres, Elias & Diels, Jan & Coppye, Cecilia & Adiele, Joy Geraldine & Ezui, Kodjovi Senam Guillaume & Becerra, Luis-Augusto & Selvaraj, Michael Gomez & Dercon, Gerd & H, 2022. "Calibration and validation of the FAO AquaCrop water productivity model for cassava (Manihot esculenta Crantz)," Agricultural Water Management, Elsevier, vol. 263(C).
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