Proceedings of the 3rd International Conference on Public Management and Big Data Analysis, PMBDA 2023, December 15–17, 2023, Nanjing, China

Research Article

Analysis of Sampling Point Irrigation Area Selection Path for Agricultural Irrigation Water Consumption Statistics

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  • @INPROCEEDINGS{10.4108/eai.15-12-2023.2345353,
        author={Jinhui  Wang and Yajun  Guo},
        title={Analysis of Sampling Point Irrigation Area Selection Path for Agricultural Irrigation Water Consumption Statistics},
        proceedings={Proceedings of the 3rd International Conference on Public Management and Big Data Analysis, PMBDA 2023, December 15--17, 2023, Nanjing, China},
        publisher={EAI},
        proceedings_a={PMBDA},
        year={2024},
        month={5},
        keywords={agricultural irrigation; water consumption statistics; sample irrigation area; path analysis; geographic information system; crop growth model; hydrological model},
        doi={10.4108/eai.15-12-2023.2345353}
    }
    
  • Jinhui Wang
    Yajun Guo
    Year: 2024
    Analysis of Sampling Point Irrigation Area Selection Path for Agricultural Irrigation Water Consumption Statistics
    PMBDA
    EAI
    DOI: 10.4108/eai.15-12-2023.2345353
Jinhui Wang1, Yajun Guo1,*
  • 1: Gansu Shule River Basin water resources utilization center Gansu Jiuquan
*Contact email: ymzgyj@icloud.com

Abstract

The purpose of this study was to select the sample irrigation area suitable for agricultural irrigation water consumption statistics, and to determine the best selection strategy by analyzing the path. We use a multidisciplinary approach, including geographic information systems (GIS), crop growth models and hydrological models. Firstly, we evaluated the existing irrigated areas and found that different irrigated areas have different characteristics of land use type, crop planting structure, water resource use efficiency and so on. On this basis, we use GIS technology to determine the priority of irrigation area by analyzing the geographical features, landforms, soil types and so on. Secondly, we use crop growth model to simulate crop growth in irrigated areas, combined with historical rainfall data and irrigation data, to predict crop water requirements in different seasons.