Drought risk assessment for maize/peanut intercropping based on crop model and SPEI

被引:0
|
作者
Guo, Yajiaoxue [1 ]
Sun, Zhanxiang [2 ,3 ]
Bai, Wei [2 ,3 ]
Zhang, Zhe [2 ,3 ]
Zhang, Yue [4 ]
Du, Hongjun [1 ]
Sun, Tianran [1 ]
Zhang, Jinyu [1 ]
Peng, Pu [1 ]
Ji, Yafei [1 ]
Cai, Qian [2 ,3 ]
Dong, Zhi [2 ,3 ]
Zhang, Xu [5 ]
Feng, Liangshan [2 ]
Feng, Chen [2 ,3 ,6 ]
Zhang, Lizhen [1 ]
机构
[1] China Agr Univ, Coll Resources & Environm Sci, Agr Meteorol Dept, Beijing 100193, Peoples R China
[2] Liaoning Acad Agr Sci, Tillage & Cultivat Res Inst, Shenyang 110161, Liaoning, Peoples R China
[3] Natl Agr Expt Stn Agr Environm, Fuxin 123102, Liaoning, Peoples R China
[4] Northwest A&F Univ, Coll Agron, Yangling 712100, Shaanxi, Peoples R China
[5] Fuxin Meteorol Bur, Fuxin 123000, Liaoning, Peoples R China
[6] Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Liaoning, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
APSIM-strip model; Drought risk; Intercrop; Rain-fed agriculture; Standardized precipitation evapotranspiration; index; Vulnerability; WATER-USE EFFICIENCY; SPECIES INTERACTIONS; CLIMATE-CHANGE; N-2; FIXATION; WHEAT; DISASTER; INDEXES; APSIM; YIELD; PEA;
D O I
10.1016/j.agsy.2024.104144
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Context: Drought occurs frequently under climate change and is considered a huge threat especially for the rainfed agricultural region. Intercropping systems are promoted as an adaptation to mitigate drought stress due to the interspecific complementarity of intercropped species and improved water use efficiency. Objective: The aim of this study was to select a drought risk assessment model for maize/peanut strip intercropping to quantitatively evaluate whether intercropping can mitigate drought risk compared to sole stands, using the daily Standardized Precipitation Evapotranspiration Index (SPEI) for analysis. Methods: The Agricultural Production Systems Simulator (APSIM) is widely used to assess the potential impacts of climate change on crop yield. In this study, we employed the APSIM model, integrated with a light interception model for strip intercrops, to quantify yield losses caused by crop droughts in four maize/peanut strip intercropping treatments from 1951 to 2020. Additionally, we developed physical vulnerability curves and the corresponding drought hazard indices. Results and conclusions: Based on the drought risk assessment index, intercropping decreased drought risk by 2.16 % compared with sole stands across all testing row configurations. In this study, we found that maize/peanut strip intercropping reduced drought risk by 5.7 % over the past 35 years, outperforming the previous 35 years. We concluded that the intercropping could be a risk management strategy in rain-fed agriculture, and among the four tested intercropping systems, including 2 rows of maize and 2 rows of peanut, 4 rows of maize and 4 rows of peanut, 6 rows of maize and 6 rows of peanut, and 8 rows of maize and 8 rows of peanut, strip intercropping with 2 rows of maize and 2 rows of peanut was the best. Significance: Our long-term simulations confirmed that intercropping could reduce drought risk in rain-fed agriculture under global climate change. Overall, this study introduces drought risk quantification methods in ecosystem biodiversity. However, further field experiments are still needed to explore the impact of resource competition on intercropping system performance. Additional data from other locations will enhance the spatial representation in future research. Future research should also combine crop physiology and ecological theories to study intercropping drought resistance from a crop mechanism perspective.
引用
收藏
页数:12
相关论文
共 50 条
  • [11] Risk Assessment of Maize Drought in China Based on Physical Vulnerability
    Chen, Fang
    Jia, Huicong
    Pan, Donghua
    JOURNAL OF FOOD QUALITY, 2019, 2019
  • [12] Dynamic agricultural drought risk assessment for maize using weather generator and APSIM crop models
    Yaxu Wang
    Juan Lv
    Hongquan Sun
    Huiqiang Zuo
    Hui Gao
    Yanping Qu
    Zhicheng Su
    Xiaojing Yang
    Jianming Yin
    Natural Hazards, 2022, 114 : 3083 - 3100
  • [13] Dynamic agricultural drought risk assessment for maize using weather generator and APSIM crop models
    Wang, Yaxu
    Lv, Juan
    Sun, Hongquan
    Zuo, Huiqiang
    Gao, Hui
    Qu, Yanping
    Su, Zhicheng
    Yang, Xiaojing
    Yin, Jianming
    NATURAL HAZARDS, 2022, 114 (03) : 3083 - 3100
  • [14] Maize-common bean intercropping to optimize maize-based crop production
    Alemayehu, A.
    Tamado, T.
    Nigussie, D.
    Yigzaw, D.
    Kinde, T.
    Wortmann, C. S.
    JOURNAL OF AGRICULTURAL SCIENCE, 2017, 155 (07): : 1124 - 1136
  • [15] Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize
    Guo, Hao
    Zhang, Xingming
    Lian, Fang
    Gao, Yuan
    Lin, Degen
    Wang, Jing'ai
    SUSTAINABILITY, 2016, 8 (08)
  • [16] Dynamic drought risk assessment using crop model and remote sensing techniques
    Sun, H.
    Su, Z.
    Lv, J.
    Li, L.
    Wang, Y.
    INTERNATIONAL SYMPOSIUM ON EARTH OBSERVATION FOR ONE BELT AND ONE ROAD (EOBAR), 2017, 57
  • [17] Belowground Interactions Impact the Soil Bacterial Community, Soil Fertility, and Crop Yield in Maize/Peanut Intercropping Systems
    Li, Qisong
    Chen, Jun
    Wu, Linkun
    Luo, Xiaomian
    Li, Na
    Arafat, Yasir
    Lin, Sheng
    Lin, Wenxiong
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2018, 19 (02)
  • [18] Border-row proportion determines strength of interspecific interactions and crop yields in maize/peanut strip intercropping
    Wang, Ruonan
    Sun, Zhanxiang
    Zhang, Lizhen
    Yang, Ning
    Feng, Liangshan
    Bai, Wei
    Zhang, Dongsheng
    Wang, Qi
    Evers, Jochem B.
    Liu, Yang
    Ren, Jianhong
    Zhang, Yue
    van der Werf, Wopke
    FIELD CROPS RESEARCH, 2020, 253
  • [19] Assessing the vulnerability and risk of maize to drought in China based on the AquaCrop model
    Zhu, Xiufang
    Xu, Kun
    Liu, Ying
    Guo, Rui
    Chen, Lingyi
    AGRICULTURAL SYSTEMS, 2021, 189
  • [20] Drought loss assessment combining remote sensing and a crop growth model for maize in Yunnan Province, China
    Gao, Maofang
    Li, Zhao-Liang
    Liu, Sanchao
    Gao, Ya
    Leng, Pei
    Duan, Sibo
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 40 (5-6) : 2151 - 2165