干旱区研究

干旱区研究 ›› 2023, Vol. 40 ›› Issue (12): 1918-1930.doi: 10.13866/j.azr.2023.12.05 cstr: 32277.14.j.azr.2023.12.05

• 水土资源 • 上一篇    下一篇

基于LMDI-SD耦合模型的关中地区水资源承载力动态预测与调控

贾琼1(),宋孝玉1(),宋淑红2,刘晓迪1,覃琳1,刘辉1   

  1. 1.西安理工大学省部共建西北旱区生态水利国家重点实验室，陕西 西安 710048
    2.陕西省水文水资源勘测中心，陕西 西安 710068
  • 收稿日期:2023-09-21 修回日期:2023-10-20 出版日期:2023-12-15 发布日期:2023-12-18
  • 作者简介:贾琼(1997-)，女，硕士研究生，研究方向为水文学及水资源. E-mail: Jiaqiong971002@163.com
  • 基金资助:
    国家重点研发计划项目(2016YFC0400301)

Dynamic prediction and regulation of the water resource carrying capacity in the Guanzhong region based on the LMDI-SD coupling model

JIA Qiong1(),SONG Xiaoyu1(),SONG Shuhong2,LIU Xiaodi1,QIN Lin1,LIU Hui1   

  1. 1. State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, Shaanxi, China
    2. Hydrology and Water Resources Investigation Center of Shaanxi Province, Xi’an 710068, Shaanxi, China
  • Received:2023-09-21 Revised:2023-10-20 Published:2023-12-15 Online:2023-12-18

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摘要：

为实现区域水资源承载力的动态预测与定量调控，构建LMDI-SD耦合模型。模型采用对数平均迪式指数（LMDI）分解法，识别用水量变化关键驱动因子；构建系统动力学（SD）模型，预测水资源承载力；以用水量变化关键驱动因子为调控指标，对经济社会用水进行全面调控；结合正交试验法，筛选最优调控方案。应用于2022—2035年关中地区水资源承载力的动态预测与调控，结果表明：（1） 强度效应是关中地区农业用水量减少、生活和生态用水量增加的关键驱动因子，规模效应是工业用水量增加的关键驱动因子；（2） 现状发展模式下，由于用水总量增加幅度（37.13%）远大于可供水量增加幅度（12.25%），关中地区水资源承载压力逐年变大，从2026年开始将处于超载状态；（3） 引汉济渭工程能从“供给侧”有效缓解关中地区水资源供需矛盾，但相对于快速增长的需求，部分城市水资源仍供不应求，还需从“需求侧”加以调控；（4） 最优调控方案下，关中地区水资源可调控至临界承载状态，且相较于生活、生态及农业用水水平，工业发展规模调控范围更大，应重点优先调控。模型对可持续发展框架下，区域水资源规划与管理具有较好的实际应用价值。

关键词: 水资源承载力, 动态预测, 定量调控, 系统动力学, 关中地区

Abstract:

To realize the dynamic prediction and quantitative regulation of water resource carrying capacity, an LMDI-SD coupling model based on the LMDI decomposition method, system dynamics (SD), and orthogonal test method was established. The coupling model uses the LMDI decomposition method to identify the driving factors of water consumption change, establishes the SD model to predict the water resource carrying capacity, takes the key driving factors of water consumption change of each department as the regulation index, comprehensively regulates the economic and social water use, and selects the optimal regulation scheme combined with the orthogonal test method. Applied to the dynamic prediction and regulation of water resource carrying capacity in the Guanzhong region between 2020 and 2035, the results show that the following: (1) the intensity effect is the key driving factor for the decrease in agricultural water consumption and the increase in domestic and ecological water consumption in the Guanzhong region between 2010 and 2019, whereas the scale effect is the key driving factor for the increase in industrial water consumption; (2) under the current development mode, the water resource bearing pressure of the whole Guanzhong region and cities will increase yearly from 2020 to 2035, and will be in an overloaded state by 2035 as the increase in total water consumption is far greater than the available water supply; (3) the Han to Wei River Diversion Project effectively alleviated the contradiction between supply and demand of water resources in the Guanzhong area from the supply side. However, compared with the rapidly growing demand, water resources in some cities remain limited; therefore, they should be regulated from the demand side; (4) by restricting the expansion speed of industrial development, improving the level of agricultural water use, and slowing down the growth trend of domestic and ecological water use, the water resources in the Guanzhong region can be bearable from 2020 to 2035. The LMDI-SD coupling model constructed in this study has good practical application value for regional water resource planning and management within the framework of sustainable development.

Key words: water resources carrying capacity, dynamic prediction, quantitative regulation, system dynamics, Guanzhong region