Study on Modeling and Evaluating Alfalfa Yield and Optimal Water Use Efficiency in the Agro-Pastoral Ecotone of Northern China

被引:2
作者
Miao, Xiangyang [1 ,2 ]
Wang, Guoshuai [2 ,3 ]
Li, Ruiping [1 ]
Xu, Bing [2 ,3 ]
Zheng, Hexiang [2 ,3 ]
Tian, Delong [2 ,3 ]
Wang, Jun [2 ,3 ]
Ren, Jie [2 ,3 ]
Li, Zekun [2 ,3 ]
Zhou, Jie [1 ,2 ]
机构
[1] Inner Mongolia Agr Univ, Coll Water Conservancy & Civil Engn, Hohhot 010018, Peoples R China
[2] China Inst Water Resources & Hydropower Res, Yinshanbeilu Grassland Ecohydrol Natl Observat & R, Beijing 100038, Peoples R China
[3] Minist Water Resources, Inst Water Resources Pastoral Area, Hohhot 010020, Peoples R China
来源
PLANTS-BASEL | 2024年 / 13卷 / 02期
关键词
agro-pastoral ecotone; alfalfa; yield; Dssat-Forages-Alfalfa model; water use; WHEAT; SYSTEM; PLAIN;
D O I
10.3390/plants13020229
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
The agro-pastoral ecotone in northern China is the main production area of agriculture and animal husbandry, in which agricultural development relies entirely on groundwater. Due to the increasing water consumption of groundwater year by year, groundwater resources are becoming increasingly scarce. The substantial water demand and low germination rate in the first year are the main characteristics of alfalfa (Medicago sativa L.) yield in the agro-pastoral ecotone in northern China. Due to unscientific irrigation, water resources are seriously wasted, which restricts the development of local agriculture and animal husbandry. The study constructed the Dssat-Forages-Alfalfa model and used soil water content, leaf area index, and yield data collected with in situ observation experiments in 2022 and 2023 to calibrate and validate the parameters. The study found ARE < 10%, E-NRMS < 15%, and R-2 >= 0.85. The model simulation accuracy was acceptable. The study revealed that the water consumption at the surface soil layer (0-20 cm) was more than 6 similar to 12% and 13 similar to 31% than that at the 20-40 cm and 40-60 cm soil layers, respectively. The study showed when the irrigation quota was 30 mm, the annual yield of alfalfa (Medicago sativa L.) (7435 kg/ha) was consistent with that of the irrigation quota of 33 mm, and increased by 3.99% to 5.34% and 6.86% to 10.67% compared with that of irrigation quotas of 27 mm and 24 mm, respectively. To ensure the germination rate of alfalfa (Medicago sativa L.), it is recommended to control the initial soil water content at 0.8 theta(fc)similar to 1.0 theta(fc), with an irrigation quota of 30 mm, which was the best scheme for water-use efficiency and economic yield. The study aimed to provide technological support for the rational utilization of groundwater and the scientific improvement of alfalfa yield in the agro-pastoral ecotone in northern China.
引用
收藏
页数:17
相关论文
共 41 条
  • [1] Abayechaw D., 2021, Int. J. Intell. Inf. Syst, V10, P117, DOI [10.11648/j.ijiis.20211006.13, DOI 10.11648/J.IJIIS.20211006.13]
  • [2] Bao J., 2020, The Response of Alfalfa Planting and Harvesting Schemes to its Growth Periods
  • [3] Surrogate-based bilevel shape optimization for blended-wing-body underwater gliders
    Chen, Weixi
    Wang, Peng
    Dong, Huachao
    [J]. ENGINEERING OPTIMIZATION, 2023, 55 (06) : 998 - 1019
  • [4] Du J., 2019, Agric. Res. Arid Areas, V38, P166
  • [5] Duan D., 2023, Feed Res, V20, P169
  • [6] Duan Y., 2013, J. Arid Land Resour. Environ, V27, P1
  • [7] Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models
    Ge, Jiankun
    Yu, Zihui
    Gong, Xuewen
    Ping, Yinglu
    Luo, Jinyao
    Li, Yanbin
    [J]. PLANTS-BASEL, 2023, 12 (22):
  • [8] Hou C., 2022, Effect Mechanism of Water and Salt Stress on Water and NitrogenUtilization and Physiological Characteristics of Alfalfa in Hetao Irrigation Area
  • [9] The DSSAT cropping system model
    Jones, JW
    Hoogenboom, G
    Porter, CH
    Boote, KJ
    Batchelor, WD
    Hunt, LA
    Wilkens, PW
    Singh, U
    Gijsman, AJ
    Ritchie, JT
    [J]. EUROPEAN JOURNAL OF AGRONOMY, 2003, 18 (3-4) : 235 - 265
  • [10] Kang W., 2023, Tianjin Agric. Sci, V29, P13