Utilizing CMIP6-SSP scenarios with the VIC model to enhance agricultural and ecological water consumption predictions and deficit assessments in arid regions

IF 8.9 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Computers and Electronics in Agriculture Pub Date : 2025-02-11 DOI:10.1016/j.compag.2025.110083
Qingling Bao , Jianli Ding , Jinjie Wang , Lijing Han , Jiao Tan
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Abstract

Essential for economic development and ecological restoration in arid regions, water resources are currently facing unprecedented scarcity. Although future changes in surface water resources have been extensively examined, there has been limited focus on the balance between agricultural and ecological water consumption and water deficits, particularly in arid basins. A novel approach to estimating agricultural and ecological water consumption was introduced in this study using a physical process model (Variable Infiltration Capacity model, VIC) incorporating the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSPs) scenarios. Water consumption trends and deficits were analysed using historical data (1961–2014) and projected under the SSP126, SSP245, SSP370, and SSP585 scenarios for 2015–2100 in the Lake Ebinur basin. There was a significant increase in agricultural and ecological water consumption along with a growing water supply deficit, particularly under the SSP245 and SSP585 scenarios. Agricultural water consumption is projected to increase by 8.00% to 43.13%, ecological water consumption is expected to rise by 13.31% to 49.11%, and the water supply deficit is projected to increase by 45% to 113% relative to the baseline period. The average annual mean error of raw meteorological variables was reduced by 71.66% after applying bias correction, leading to an improvement of approximately 86.79% in the simulation accuracy of the VIC model compared with the uncorrected scenario. An increase in precipitation ranging from 4.00% to 33.56%, a maximum temperature increase of 230.88%, and a decrease in wind speed of 6.45% were projected for the mid-to-late 21st century under the SSP585 scenario. The water supply deficit was estimated to increase under the SSP245 scenario, with deficits projected to reach 1.35 billion m3 per year in the medium term and 1.59 billion m3 per year in the late term. Given the projected increase in agricultural and ecological water consumption and the growing future water supply deficit, quantifying these changes can provide critical insights into water resource management and sustainable development in arid regions.
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利用CMIP6-SSP情景和VIC模型加强干旱区农业和生态用水量预测和亏缺评估
水资源是干旱区经济发展和生态恢复的重要资源,目前面临着前所未有的短缺。虽然对地表水资源的未来变化进行了广泛的研究,但对农业和生态用水与缺水之间的平衡的关注有限,特别是在干旱盆地。本文介绍了一种估算农业和生态用水量的新方法,该方法使用了物理过程模型(可变入渗能力模型,VIC),并结合了最新的耦合模型比较项目第6阶段(CMIP6)共享社会经济路径(ssp)情景。利用历史数据(1961-2014年)分析了艾比湖流域2015-2100年的用水量趋势和赤字,并在SSP126、SSP245、SSP370和SSP585情景下进行了预测。在SSP245和SSP585情景下,农业和生态耗水量显著增加,供水短缺日益严重。与基准期相比,农业用水量预计增长8.00%至43.13%,生态用水量预计增长13.31%至49.11%,供水缺口预计增长45%至113%。经过偏差校正后,原始气象变量的年平均误差减小了71.66%,与未校正情景相比,VIC模式的模拟精度提高了约86.79%。在SSP585情景下,21世纪中后期降水增加4.00% ~ 33.56%,最高气温增加230.88%,风速减少6.45%。在SSP245情景下,供水短缺估计会增加,预计中期赤字将达到每年13.5亿立方米,后期赤字将达到每年15.9亿立方米。考虑到预计农业和生态用水的增加以及未来日益严重的供水短缺,量化这些变化可以为干旱地区的水资源管理和可持续发展提供重要的见解。
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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