黄河流域产水服务供需时空演变特征

Temporal and spatial evolution of supply and demand of water yield services in the Yellow River basin

摘要

为揭示黄河流域水资源产需平衡规律，支撑流域水资源精准调控，基于2000−2023年多源数据，采用生态系统服务与权衡综合评估（integrated valuation of ecosystem services and tradeoffs，InVEST）模型产水模块、定额法及空间自相关分析，量化评估流域产水服务供给量、需求量及供需匹配的演变特征。结果表明：研究期内流域平均产水量为45.67～93.11 mm，呈“波动增加”趋势，空间上表现为“南部高、北部低，上游高、中下游低”；需水量呈“先升后稳”特征，农业需水占比从75.1%降至60.9%，生活需水增幅达215%，空间上中下游需水量显著高于上游；供需指数均值为−0.396～−0.152，处于“供小于求”状态，空间分异为“上游局部超载-中游极端失衡-下游持续赤字”特征；产需水空间自相关显著，空间上“高-高”型集聚于上游西南湿润带，“低-高”型错位区集中于中下游城镇及灌区且伴随产业转移，“高-低”型稳定分布于生态保护区，凸显供需分异特征。研究可为黄河流域水资源统一调度与生态保护修复提供科学依据。

Abstract

This study quantitatively assessed the evolutionary characteristics of the supply, demand, and supply-demand matching of water production services in the Yellow River basin using the InVEST model's water production module, quota method, and spatial autocorrelation analysis based on multi-source data from the year 2000 to 2023 in order to uncover the law of water supply-demand balance in the basin and support accurate regulation of water resources. The results indicate that: (1) During the study period, the average annual water production in the basin ranged from 45.67 mm to 93.11 mm, highlighting a "fluctuating increasing" trend, with a spatial pattern of "high in the south and low in the north, high in the upper reaches and low in the middle and lower reaches"; (2) Water demand presented a "first increasing and then stable" characteristic, with the proportion of agricultural water demand decreasing from 75.1% to 60.9% and domestic water demand increasing by 215%, and spatially, water demand in the middle and lower reaches was significantly higher than that in the upper reaches; (3) The average supply-demand index (SDI) ranged from −0.396 to −0.152, indicating a state of "supply less than demand" with spatial differentiation characterized by "local overload in the upper reaches, extreme imbalance in the middle reaches, and continuous deficit in the lower reaches"; (4) Water supply and demand showed significant spatial autocorrelation. Spatially, the "high-high" type agglomerated in the humid zone of the upper reaches in the southwest, the "low-high" mismatched areas concentrated in cities, towns, and irrigation areas in the middle and lower reaches with industrial transfer, and the "high-low" type stably distributed in ecological protection areas, highlighting the features of spatial differentiation between supply and demand. This study can offer a scientific foundation for the coordinated management of water resources as well as ecological preservation and restoration in the Yellow river basin.

关键词

产水服务 / 黄河流域 / 供需平衡 / InVEST模型 / 时空演变

Key words

water yield service / Yellow River basin / supply-demand balance / InVEST model / temporal and spatial evolution

参考文献

[1] 李昂, 杨琰瑛, 师荣光, 等. 居民福祉及其与生态系统服务的关系研究进展[J]. 农业资源与环境学报, 2022, 39(5): 948-957. DOI: 10.13254/j.jare.2021.0372.

[2] Yu Yan, Sun Xiao, Wang Juan, et al. Using InVEST to evaluate water yield services in Shangri-La, northwestern Yunnan, China[J]. PeerJ, 2022, 10: e12804. DOI: 10.7717/peerj.12804.

[3] Wang Dahui, Tian Yanchao, Zhang Y L, et al. Evaluation and quantitative attribution analysis of water yield services in the Peak-cluster Depression basins in southwest of Guangxi, China[J]. Chinese Geographical Science, 2023, 33: 116-130. DOI: 10.1007/s11769-023-1329-1.

[4] Basha U, Pandey M, Nayak D, et al. Spatial-temporal assessment of annual water yield and impact of land use changes on upper Ganga basin, India, using InVEST model[J]. Journal of Hazardous, Toxic, and Radioactive Waste, 2024, 28(2): 04024003. DOI: 10.1061/(ASCE)HZ.1944-8301.0000317.

[5] 吴峰, 冼伟信, 赵筱青, 等. 基于“水-能源-粮食”纽带的生态系统服务供需关系时空分布研究: 以长三角生态绿色一体化发展示范区为例[J]. 生态学报, 2023, 43(15): 6123-6135. DOI: 10.5846/stxb202209232716.

[6] 魏培洁, 吴明辉, 贾映兰. 基于InVEST模型的疏勒河上游产水量时空变化特征分析[J]. 生态学报, 2022, 42(15): 6418-6429. DOI: 10.5846/stxb202105011149.

[7] 杨宜男, 李敬, 王立, 等. 长三角地区城市化对典型生态系统服务供需的影响[J]. 自然资源学报, 2022, 37(6): 1555-1571. DOI: 10.31497/zrzyxb.20220613.

[8] 陈登帅, 李晶, 张渝萌, 等. 延河流域水供给服务供需平衡与服务流研究[J]. 生态学报, 2020, 40(1): 112-122. DOI: 10.5846/stxb201811132456.

[9] 张霄林, 李阳兵, 熊康宁, 等. 基于供需关系的西南喀斯特区生态系统服务空间流动研究[J]. 生态学报, 2024, 44(12): 5123-5135. DOI: 10.5846/stxb202306151428.

[10] Huang Ping, Zhao Xiao, Pu Jing, et al. Defining the land use area threshold and optimizing its structure to improve supply-demand balance state of ecosystem services[J]. Journal of Geographical Sciences, 2024, 34(5): 891-920. DOI: 10.1007/s11442-024-2232-0.

[11] Carrasco-Valencia L, Vilca-Campana K, Iruri-Ramos C, et al. Effect of LULC changes on annual water yield in the urban section of the Chili River, Arequipa, using the InVEST model[J]. Water, 2024, 16(5): 664. DOI: 10.3390/w16050664.

[12] Chen Xin, Huang Xin, Li Yang, et al. Spatial-temporal patterns and driving forces of water yield service supply-demand balance in the Yangtze River Economic Belt[J]. Science of the Total Environment, 2024, 889: 164782. DOI: 10.1016/j.scitotenv.2024.164782.

[13] Sharafatmandrad M, Khosravi Mashizi A. Temporal and spatial assessment of supply and demand of the water-yield ecosystem service for water scarcity management in arid to semi-arid ecosystems[J]. Water Resources Management, 2021, 35(1): 63-82. DOI: 10.1007/s11269-020-02673-3.

[14] 宋心馨, 张守志, 王淑琪, 等. 基于PLUS模型的图们江流域生态系统服务价值情景模拟及驱动因素研究[J]. 水利水电技术（中英文）, 2025, 56(3): 186-201. DOI: 10.13928/j.cnki.wrahe.2025.03.015.

[15] Yin Da, Yu Hui, Shi Yu, et al. Matching supply and demand for ecosystem services in the Yellow River basin, China: A perspective of the water-energy-food nexus[J]. Journal of Cleaner Production, 2023, 384: 135469. DOI: 10.1016/j.jclepro.2023.135469.

[16] 王佳琦, 王坤, 严登华, 等. 基于CMIP6的黄河流域三级水资源区未来气候变化预估[J]. 南水北调与水利科技（中英文）, 2025, 23(2): 242-250. DOI: 10.13476/j.cnki.nsbdqk.2025.0031.

[17] Song Meng, Jiang Xia, Lei Ying, et al. Spatial and temporal variation characteristics of extreme hydrometeorological events in the Yellow River basin and their effects on vegetation[J]. Natural Hazards, 2023, 116(2): 1863-1878. DOI: 10.1007/s11069-023-05828-0.

[18] 娄梦婕, 史明昌, 郭虹扬, 等. 基于InVEST模型的白洋淀−大清河流域水源涵养分析[J]. 中国水土保持科学（中英文）, 2022, 20(5): 118-123. DOI: 10.16843/j.sswc.2022.05.015.

[19] Li Cong, Jiang Dong, Wollenweber B, et al. Waterlogging pretreatment during vegetative growth improves tolerance to waterlogging after anthesis in wheat[J]. Plant Science, 2011, 180(5): 672-678. DOI: 10.1016/j.plantsci.2011.02.009.

[20] 陈鑫, 林思吟, 田杰, 等. 基于InVEST-Geoda-Gephi网络的产水服务流模拟研究: 以武夷山脉为例[J]. 生态学报, 2024, 44(18): 7892-7905. DOI: 10.5846/stxb202311082837.

[21] 张欣, 张保祥, 李冰, 等. 基于用水定额的区域节水评价方法及应用[J]. 南水北调与水利科技（中英文）, 2023, 21(1): 95-106. DOI: 10.13476/j.cnki.nsbdqk.2023.0011.

[22] 陈骏宇, 王慧敏, 刘钢, 等. “水-能-粮”视角下杭嘉湖区域生态系统服务供需测度及政策研究[J]. 长江流域资源与环境, 2019, 28(3): 542-553. DOI: 10.11870/cjlyzyyhj201903004.

[23] 钟孟君, 蒋贵国, 陆忆文, 等. 中巴经济走廊巴基斯坦段产水服务供需风险评价及分区[J]. 水土保持通报, 2023, 43(3): 225-233. DOI: 10.13961/j.cnki.stbctb.2023.03.032.

[24] 左其亭, 杨振龙, 路振广, 等. 引江济淮工程河南受水区水资源利用效率及其空间自相关性分析[J]. 南水北调与水利科技（中英文）, 2023, 21(1): 39-47. DOI: 10.13476/j.cnki.nsbdqk.2023.0005.

[25] 闫奕飞, 白强, 孙虎, 等. 黄河流域植被变化和产水服务的时空特征分析[J]. 水土保持学报, 2024, 38(1): 130-139. DOI: 10.13870/j.cnki.stbcxb.2024.01.017.

[26] 方露露, 许德华, 王伦澈, 等. 长江, 黄河流域生态系统服务变化及权衡协同关系研究[J]. 地理研究, 2021, 40(3): 821-838. DOI: 10.11821/dlyj202103003.

[27] 李文静, 王盛, 李庆, 等. 气候和土地利用变化对北三河流域生态系统水源供给服务功能的影响[J]. 华东师范大学学报（自然科学版）, 2021(4): 99-108. DOI: 10.3969/j.issn.1000-5641.2021.04.008.

[28] Balist J, Malekmohammadi B, Jafari H R, et al. Detecting land use and climate impacts on water yield ecosystem service in arid and semi-arid areas: A study in Sirvan River basin, Iran[J]. Applied Water Science, 2022, 12: 1-14. DOI: 10.1007/s13201-022-01793-1.

[29] Zhao Xiao, Xu Yang, Pu Jing, et al. Achieving the supply-demand balance of ecosystem services through zoning regulation based on land use thresholds[J]. Land Use Policy, 2024, 139: 107056. DOI: 10.1016/j.landusepol.2024.107056.

[30] 李嘉欣, 彭少明. 黄河流域用水现状及需水预测研究[J]. 人民黄河, 2024, 46(7): 66-71. DOI: 10.3969/j.issn.1000-1379.2024.07.012.

[31] 雍琦. 土地生态系统产水服务的供需匹配、空间流动及补偿研究: 以汉江流域为例[D]. 武汉: 华中农业大学, 2024.

[32] 赵奕博, 于洋, 孙保平. 山西省产水服务供需时空变化[J]. 水土保持学报, 2023, 37(6): 126-133. DOI: 10.13870/j.cnki.stbcxb.2023.06.015.

基金资助

国家自然科学基金面上项目(52279028)