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Quantitative sensitivity of crop productivity and water productivity to precipitation during growth periods in the Agro-Pastoral Ecotone of Shanxi Province, China, based on APSIM

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  • Yang, Xuan
  • Jia, Pengfei
  • Hou, Qingqing
  • Zhu, Min

Abstract

Cropping systems in the Agro-Pastoral Ecotone (APE) of Shanxi Province will face uncertainty over sustainability. For dealing with climate risks and providing information regarding adoption of climate-resistant cropping systems, this study aimed to i) calibrate and validate APSIM for predicting production of maize (Zea mays), potato (Solanum tuberosum), forage oats (Avena sativa) and feed soybean (Glycine max); ii) estimate sensitivity of yield and water productivity (WP) in response to different precipitation conditions associated with typical seasons; iii) evaluate changes of food yield caused by given treatments with typical stages. Results showed that: i) APSIM calibration and validation had generally satisfactory results with 4.09–29.98 % of NMRSE values; ii) due to less water retention, maize-based systems showed lower yield and WP than others. By linear regressions, maize yield showed high sensitivity with Standardized Precipitation Index (SPI) of stage 1 (May) and 2 (June and July; R2 = 0.0002–0.5176, a ≥ 315.94) in drought season, while markedly effects of precipitation on WP were presented in stage 1 and 2 for drought and wet season, respectively; iii) the key for moisture demand determining high potato and forage productivity is from emergency to floral initiation, therefore yield and WP showed positive relevance with SPI in stage 2 in most cases (R2 = 0.0203–0.8391, with absolute “a” values of 460.29–2746.7 and 0.9687–3.8206 for yield and WP, respectively); iv) food yields under various systems were non-significantly lower or higher than the most widely used rotation (maize-potato), but these changes expanded when crops undergoing typical drought in stage 2 by reductions of 3.0–42.5 %. Altogether, traditional potato-maize rotation and continuous maize should be avoided for mitigating negative effects of drought in stage 1 or 2, while supplementary irrigation in June, July and August is warranted for producing acceptable food and forage yield.

Suggested Citation

  • Yang, Xuan & Jia, Pengfei & Hou, Qingqing & Zhu, Min, 2023. "Quantitative sensitivity of crop productivity and water productivity to precipitation during growth periods in the Agro-Pastoral Ecotone of Shanxi Province, China, based on APSIM," Agricultural Water Management, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:agiwat:v:283:y:2023:i:c:s0378377423001749
    DOI: 10.1016/j.agwat.2023.108309
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    1. Wang, Jialin & Pan, Zhihua & Pan, Feifei & He, Di & Pan, Yuying & Han, Guolin & Huang, Na & Zhang, Ziyuan & Yin, Wenjuan & Zhang, Jiale & Peng, Ruiqi & Wang, Zizhong, 2020. "The regional water-conserving and yield-increasing characteristics and suitability of soil tillage practices in Northern China," Agricultural Water Management, Elsevier, vol. 228(C).
    2. Ojeda, Jonathan J. & Volenec, Jeffrey J. & Brouder, Sylvie M. & Caviglia, Octavio P. & Agnusdei, Mónica G., 2018. "Modelling stover and grain yields, and subsurface artificial drainage from long-term corn rotations using APSIM," Agricultural Water Management, Elsevier, vol. 195(C), pages 154-171.
    3. Mthembu, Sizwe Goodman & Magwaza, Lembe Samukelo & Mashilo, Jacob & Mditshwa, Asanda & Odindo, Alfred, 2022. "Drought tolerance assessment of potato (Solanum tuberosum L.) genotypes at different growth stages, based on morphological and physiological traits," Agricultural Water Management, Elsevier, vol. 261(C).
    4. Tang, Jianzhao & Xiao, Dengpan & Wang, Jing & Fang, Quanxiao & Zhang, Jun & Bai, Huizi, 2021. "Optimizing water and nitrogen managements for potato production in the agro-pastoral ecotone in North China," Agricultural Water Management, Elsevier, vol. 253(C).
    5. Elli, Elvis Felipe & Huth, Neil & Sentelhas, Paulo Cesar & Carneiro, Rafaela Lorenzato & Alvares, Clayton Alcarde, 2020. "Ability of the APSIM Next Generation Eucalyptus model to simulate complex traits across contrasting environments," Ecological Modelling, Elsevier, vol. 419(C).
    6. Amarasingha, R.P.R.K. & Suriyagoda, L.D.B. & Marambe, B. & Rathnayake, W.M.U.K. & Gaydon, D.S. & Galagedara, L.W. & Punyawardena, R. & Silva, G.L.L.P. & Nidumolu, U. & Howden, M., 2017. "Improving water productivity in moisture-limited rice-based cropping systems through incorporation of maize and mungbean: A modelling approach," Agricultural Water Management, Elsevier, vol. 189(C), pages 111-122.
    7. Ojeda, J.J. & Pembleton, K.G. & Islam, M.R. & Agnusdei, M.G. & Garcia, S.C., 2016. "Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia," Agricultural Systems, Elsevier, vol. 143(C), pages 61-75.
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