留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

共享社会经济路径下汉江流域产水和水质净化服务时空演变

陈泽怡 余珮珩 陈奕云 江颂 白少云 顾世祥

陈泽怡, 余珮珩, 陈奕云, 江颂, 白少云, 顾世祥. 共享社会经济路径下汉江流域产水和水质净化服务时空演变[J]. 中国生态农业学报(中英文), 2021, 29(10): 1800−1814 doi: 10.13930/j.cnki.cjea.210160
引用本文: 陈泽怡, 余珮珩, 陈奕云, 江颂, 白少云, 顾世祥. 共享社会经济路径下汉江流域产水和水质净化服务时空演变[J]. 中国生态农业学报(中英文), 2021, 29(10): 1800−1814 doi: 10.13930/j.cnki.cjea.210160
CHEN Z Y, YU P H, CHEN Y Y, JIANG S, BAI S Y, GU S X. Spatio-temporal changes of water resources ecosystem services in the Hanjiang River Basin based on the shared socioeconomic pathway[J]. Chinese Journal of Eco-Agriculture, 2021, 29(10): 1800−1814 doi: 10.13930/j.cnki.cjea.210160
Citation: CHEN Z Y, YU P H, CHEN Y Y, JIANG S, BAI S Y, GU S X. Spatio-temporal changes of water resources ecosystem services in the Hanjiang River Basin based on the shared socioeconomic pathway[J]. Chinese Journal of Eco-Agriculture, 2021, 29(10): 1800−1814 doi: 10.13930/j.cnki.cjea.210160

共享社会经济路径下汉江流域产水和水质净化服务时空演变

doi: 10.13930/j.cnki.cjea.210160
基金项目: 国家自然科学基金项目(41771440)和国家高分辨率对地观测系统重大科技专项(89-Y40-G19-9001-18/20-03)资助
详细信息
    作者简介:

    陈泽怡, 主要研究方向为地理信息科学与生态系统服务。E-mail: chen_zy@whu.edu.cn

    通讯作者:

    陈奕云, 主要研究方向为地理信息科学与可持续发展。E-mail: chenyy@whu.edu.cn

  • 中图分类号: X52

Spatio-temporal changes of water resources ecosystem services in the Hanjiang River Basin based on the shared socioeconomic pathway

Funds: The study was supported by the National Natural Science Foundation of China (41771440) and the Major Scientific and Technological Project of National High Resolution Earth Observation System of China (89-Y40-G19-9001-18/20-03)
More Information
  • 摘要: 面向流域治理与区域可持续发展, 提出一种耦合共享社会经济路径(SSPs)与土地利用模拟(FLUS)模型的流域生态系统服务综合评估框架, 以汉江流域为例, 开展不同社会发展情景下的未来土地利用模拟, 利用InVEST模型评估土地利用变化的水生态系统服务效应, 揭示流域水源涵养与水质净化服务对社会发展决策的响应及时空演变规律。研究结果表明: 1)2035年各SSPs情景下汉江流域的产水深度较2015年均大幅提高, 产水深度增加的地区多集中于汉江流域东南、中部及西部部分建设用地增加的区域; 2)由于人类活动频繁, 城市快速扩张, SSPs情景下产水深度增加的地区多集中于汉江流域东南、中部及西部部分建设用地增加的区域; 3) 2035年各SSPs情景下的流域氮磷元素负荷量较2015年均有所减少, 部分氮磷元素负荷量增加的地区主要集中于流域东南及西部; 4)汉江流域的社会经济活动以及农业活动是造成水环境污染的主要原因。研究结果可服务于汉江流域国土空间规划编制及可持续的水资源资产管理工作, 支撑汉江生态经济带建设, 推动长江流域水生态环境改善。
  • 图  1  汉江流域区位图

    Figure  1.  Location map of the Hanjiang River Basin

    图  2  耦合共享社会经济路径(Shared Socioeconomic Pathways, SSPs)与未来土地利用模拟模型(Future Land Use Simulation, FLUS)的流域生态系统服务综合评估框架

    SD: 系统动学; CA: 元胞自动机;ANN: 神经网络算法。

    Figure  2.  Comprehensive assessment framework of watershed ecosystem services integrated both Shared Socioeconomic Pathways (SPPs) and Future Land Use Simulation (FLUS) model

    SD: System Dynamics; CA: Cellular Automata; ANN: Artificial Neural Network.

    图  3  基于系统动力学模型的汉江流域土地利用流程图

    Figure  3.  Land use flow chart of the Hanjiang River Basin based on System Dynamics model

    图  4  汉江流域2015年土地利用现状与2035年不同共享社会经济路径(SSPs)情景下土地利用的模拟结果

    Figure  4.  Land use status in 2015 and land use simulation results under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    图  5  2015年和2035年共享社会经济路径(SSPs)情景下汉江流域年最大、最小与平均产水深度

    Figure  5.  Annual maximum, minimum and average water production depths in 2015 and simulated results under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basins

    图  6  2015年汉江流域产水深度与2035年共享社会经济路径(SSPs)情景下汉江流域产水深度变化

    Figure  6.  Water production depth in 2015 and the change of water production depths under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    图  7  2015年和2035年不同共享社会经济路径(SSPs)情景下汉江流域不同用地类型平均产水深度

    Figure  7.  Average water production depths of different land use types in 2015 and under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    图  8  2015年和2035年不同共享社会经济路径(SSPs)情景下汉江流域年最大、最小与平均单位面积总氮和总磷元素负荷量

    Figure  8.  Annual maximum, minimum and average nitrogens and phosphorus loads in 2015 and under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    图  10  2015年汉江流域磷元素负荷量与2035年不同共享社会经济路径(SSPs)情景下汉江流域磷元素负荷变化量

    Figure  10.  Phosphorus load in 2015 and the change of phosphorus load under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    图  9  2015年汉江流域氮元素负荷量与2035年不同共享社会经济路径(SSPs)情景下汉江流域氮元素负荷变化量

    Figure  9.  Nitrogen load in 2015 and the change of nitrogen load under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    图  11  2015年和2035年不同共享社会经济路径(SSPs)情景下汉江流域不同用地类型平均氮磷元素负荷量

    Figure  11.  Average nitrogen and phosphorus loads of different land use types in 2015 and under the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin

    表  1  不同土地利用类型的氮磷元素输出相关参数

    Table  1.   Output parameters of nitrogen and phosphorus of differnt land use types

    用地类型
    Land use type
    总氮元素负荷
    Load total nitrogen (t∙km−2)
    总磷元素负荷
    Load total phosphorus (t∙km−2)
    去除效率
    Retention efficiency (%)
    耕地 Cropland3.270.36425
    林地 Woodland0.3480.03570
    草地 Grassland1.10.06848
    水域 Water area1.50.0365
    建设用地 Urbanized land1.10.0255
    未利用地 Barren land0.8560.0025
    下载: 导出CSV

    表  2  2035年共享社会经济路径(SSPs)下的汉江流域各类土地利用类型面积预测结果

    Table  2.   Area prediction results of various land use types based on the Shared Socioeconomic Pathways (SSPs) scenarios in 2035 of the Hanjiang River Basin ×103 hm2 

    用地类型
    Land use type
    SSP1SSP2SSP3SSP4SSP5
    耕地 Cropland 6797.1 6847.4 7047.1 6890.4 6754.6
    林地 Woodland 7152.9 7135.4 7028.1 7127.4 7131.8
    草地 Grassland 3377.4 3372.4 3385.9 3377.4 3378.5
    水域 Water area 650.6 643.5 620.5 632.5 643.0
    建设用地 Urbanized land 979.5 957.9 875.7 930.0 1049.7
    未利用地 Barren land 12.3 13.2 12.3 12.1 12.2
    下载: 导出CSV

    表  3  2015—2035年不同共享社会经济路径(SSPs)情景下汉江流域土地利用面积转移矩阵

    Table  3.   Land use transfer matrix of the Hanjiang River Basin based from 2015 to 2035 under the Shared Socioeconomic Pathways (SSPs) scenarios ×103 hm2 

    2035用地类型
    Land use type
    2015
    耕地
    Cropland
    林地
    Woodland
    草地
    Grassland
    水域
    Water area
    建设用地
    Urbanized land
    未利用地
    Barren land
    总计
    Total
    SSP1耕地 Cropland6797.1000006797.1
    林地 Woodland81.26983.580.65.81.807152.9
    草地 Grassland48.3117.43208.71.31.703377.4
    水域 Water area36.391.4597.95.30.7650.6
    建设用地 Urbanized land123.912940.664.1620.51.4979.5
    未利用地 Barren land0.60.300.20.111.112.3
    总计 Total7087.47239.23331.3669.3629.413.218 969.8
    SSP2耕地 Cropland6847.4000006847.4
    林地 Woodland84.4696182.75.3207135.4
    草地 Grassland49.1116.93203.11.61.703372.4
    水域 Water area20.291.3608.54.50643.5
    建设用地 Urbanized land86.3152.344.253.9621.20957.9
    未利用地 Barren land0000013.213.2
    总计 Total7087.47239.23331.3669.3629.413.218 969.8
    SSP3耕地 Cropland7047.1000007047.1
    林地 Woodland15.15802.81159.131.2200.17028.3
    草地 Grassland23.31224.42121.96.210.103385.9
    水域 Water area1.424.94.8575.812.31.3620.5
    建设用地 Urbanized land0.518745.555.7586.90.1875.7
    未利用地 Barren land00.100.40.111.712.3
    总计 Total7087.47239.23331.3669.3629.413.218 969.8
    SSP4耕地 Cropland6890.4000006890.4
    林地 Woodland696970.879.16.51.90.17127.4
    草地 Grassland49116.53208.71.81.403377.4
    水域 Water area8.69.31.7608.73.80.4632.5
    建设用地 Urbanized land70142.241.851.9622.31.8930
    未利用地 Barren land0.40.400.4010.912.1
    总计 Total7087.47239.23331.3669.3629.413.218 969.8
    SSP5耕地 Cropland6754.6000006754.6
    林地 Woodland84.26960.679.15.72.207131.8
    草地 Grassland50.61183206.61.61.60.13378.5
    水域 Water area35.59.21.1592.24.70.3643
    建设用地 Urbanized land161.9151.344.569.6620.91.51049.7
    未利用地 Barren land0.60.100.2011.312.2
    总计 Total7087.47239.23331.3669.3629.413.218 969.8
    下载: 导出CSV
  • [1] GC D. Nature’s services: Societal dependence on natural ecosystems [M]. Washington DC: Island Press, 1997: 3–6
    [2] 余珮珩, 冯明雪, 刘斌, 等. 顾及生态安全格局的流域生态保护红线划定及管控研究−以云南杞麓湖流域为例[J]. 湖泊科学, 2020, 32(1): 89−99 doi: 10.18307/2020.0109

    YU P H, FENG M X, LIU B, et al. Demarcation and administration of watershed ecological protection red line considering the ecological security pattern — A case of the Qilu Lake watershed, Yunnan Province[J]. Journal of Lake Sciences, 2020, 32(1): 89−99 doi: 10.18307/2020.0109
    [3] COSTANZA R, D’ ARGE R, DE GROOT R, et al. The value of the world’s ecosystem services and natural capital[J]. Nature, 1997, 387(6630): 253−260 doi: 10.1038/387253a0
    [4] TERRADO M, ACUÑ A V, ENNAANAY D, et al. Impact of climate extremes on hydrological ecosystem services in a heavily humanized Mediterranean basin[J]. Ecological Indicators, 2014, 37: 199−209 doi: 10.1016/j.ecolind.2013.01.016
    [5] 叶延琼, 章家恩, 陈丽丽, 等. 广州市水生态系统服务价值[J]. 生态学杂志, 2013, 32(5): 1303−1310

    YE Y Q, ZHANG J E, CHEN L L, et al. Value evaluation of aquatic ecosystem services in Guangzhou, South China[J]. Chinese Journal of Ecology, 2013, 32(5): 1303−1310
    [6] 段锦, 康慕谊, 江源. 东江流域生态系统服务价值变化研究[J]. 自然资源学报, 2012, 27(1): 90−103 doi: 10.11849/zrzyxb.2012.01.010

    DUAN J, KANG M Y, JIANG Y. Dynamic valuation on ecosystem services of Dongjiang River Basin[J]. Journal of Natural Resources, 2012, 27(1): 90−103 doi: 10.11849/zrzyxb.2012.01.010
    [7] 马良, 金陶陶, 文一惠, 等. InVEST模型研究进展[J]. 生态经济, 2015, 31(10): 126−131, 179 doi: 10.3969/j.issn.1671-4407.2015.10.027

    MA L, JIN T T, WEN Y H, et al. The research progress of InVEST model[J]. Ecological Economy, 2015, 31(10): 126−131, 179 doi: 10.3969/j.issn.1671-4407.2015.10.027
    [8] 唐尧, 祝炜平, 张慧, 等. InVEST模型原理及其应用研究进展[J]. 生态科学, 2015, 34(3): 204−208

    TANG Y, ZHU W P, ZHANG H, et al. A review on principle and application of the InVEST model[J]. Ecological Science, 2015, 34(3): 204−208
    [9] 吴瑞, 刘桂环, 文一惠. 基于InVEST模型的官厅水库流域产水和水质净化服务时空变化[J]. 环境科学研究, 2017, 30(3): 406−414

    WU R, LIU G H, WEN Y H. Spatiotemporal variations of water yield and water quality purification service functions in Guanting Reservoir Basin based on InVEST model[J]. Research of Environmental Sciences, 2017, 30(3): 406−414
    [10] 贾芳芳. 基于InVEST模型的赣江流域生态系统服务功能评估[D]. 北京: 中国地质大学(北京), 2014

    JIA F F. Invest model based ecosystem services evaluation with case study on Ganjiang River Basin[D]. Beijing: China University of Geosciences, 2014
    [11] 李屹峰, 罗跃初, 刘纲, 等. 土地利用变化对生态系统服务功能的影响−以密云水库流域为例[J]. 生态学报, 2013, 33(3): 726−736 doi: 10.5846/stxb201205280787

    LI Y F, LUO Y C, LIU G, et al. Effects of land use change on ecosystem services: a case study in Miyun reservoir watershed[J]. Acta Ecologica Sinica, 2013, 33(3): 726−736 doi: 10.5846/stxb201205280787
    [12] 顾晋饴, 李一平, 杜薇. 基于InVEST模型的太湖流域水源涵养能力评价及其变化特征分析[J]. 水资源保护, 2018, 34(3): 62−67 doi: 10.3880/j.issn.1004-6933.2018.03.10

    GU J Y, LI Y P, DU W. Evaluation on water source conservation capacity and analysis of its variation characteristics of Taihu Lake Basin based on InVEST model[J]. Water Resources Protection, 2018, 34(3): 62−67 doi: 10.3880/j.issn.1004-6933.2018.03.10
    [13] 张舒瑾, 余珮珩, 白少云, 等. 面向国土空间规划的流域景观时空分异特征及驱动因子研究[J]. 生态经济, 2020, 36(10): 219−227

    ZHANG S J, YU P H, BAI S Y, et al. Study on the spatio-temporal stratified heterogeneity and driving factors of watershed landscape for national spatial planning[J]. Ecological Economy, 2020, 36(10): 219−227
    [14] 田贺, 梁迅, 黎夏, 等. 基于SD模型的中国2010―2050年土地利用变化情景模拟[J]. 热带地理, 2017, 37(4): 547−561

    TIAN H, LIANG X, LI X, et al. Simulating multiple land use scenarios in China during 2010-2050 based on system dynamic model[J]. Tropical Geography, 2017, 37(4): 547−561
    [15] 杨俊, 解鹏, 席建超, 等. 基于元胞自动机模型的土地利用变化模拟−以大连经济技术开发区为例[J]. 地理学报, 2015, 70(3): 461−475 doi: 10.11821/dlxb201503009

    YANG J, XIE P, XI J C, et al. LUCC simulation based on the cellular automata simulation: a case study of Dalian Economic and Technological Development Zone[J]. Acta Geographica Sinica, 2015, 70(3): 461−475 doi: 10.11821/dlxb201503009
    [16] 张大川, 刘小平, 姚尧, 等. 基于随机森林CA的东莞市多类土地利用变化模拟[J]. 地理与地理信息科学, 2016, 32(5): 29−36 doi: 10.3969/j.issn.1672-0504.2016.05.005

    ZHANG D C, LIU X P, YAO Y, et al. Simulating spatiotemporal change of multiple land use types in Dongguan by using random forest based on cellular automata[J]. Geography and Geo-Information Science, 2016, 32(5): 29−36 doi: 10.3969/j.issn.1672-0504.2016.05.005
    [17] 卞子浩, 马小雪, 龚来存, 等. 不同非空间模拟方法下CLUE-S模型土地利用预测−以秦淮河流域为例[J]. 地理科学, 2017, 37(2): 252−258

    BIAN Z H, MA X X, GONG L C, et al. Land use prediction based on CLUE-S model under different non-spatial simulation methods: a case study of the Qinhuai River Watershed[J]. Scientia Geographica Sinica, 2017, 37(2): 252−258
    [18] 李桢, 刘淼, 薛振山, 等. 基于CLUE-S模型的三江平原景观格局变化及模拟[J]. 应用生态学报, 2018, 29(6): 1805−1812

    LI Z, LIU M, XUE Z S, et al. Landscape pattern change and simulation in the Sanjiang Plain based on the CLUE-S model[J]. Chinese Journal of Applied Ecology, 2018, 29(6): 1805−1812
    [19] 汪佳莉, 吴国平, 范庆亚, 等. 基于CA-Markov模型的山东省临沂市土地利用格局变化研究及预测[J]. 水土保持研究, 2015, 22(1): 212−216

    WANG J L, WU G P, FAN Q Y, et al. Change and prediction of the land use in Linyi City, Shandong Province, based on CA-Markov model[J]. Research of Soil and Water Conservation, 2015, 22(1): 212−216
    [20] 许月卿, 田媛, 孙丕苓. 基于Logistic回归模型的张家口市土地利用变化驱动力及建设用地增加空间模拟研究[J]. 北京大学学报: 自然科学版, 2015, 51(5): 955−964

    XU Y Q, TIAN Y, SUN P L. Study on driving forces and spatial simulation of land use change in Zhangjiakou City based on logistic regression model[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2015, 51(5): 955−964
    [21] LIU X P, LIANG X, LI X, et al. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects[J]. Landscape and Urban Planning, 2017, 168: 94−116 doi: 10.1016/j.landurbplan.2017.09.019
    [22] JIANG L W, O’NEILL B C. Global urbanization projections for the Shared Socioeconomic Pathways[J]. Global Environmental Change, 2017, 42: 193−199 doi: 10.1016/j.gloenvcha.2015.03.008
    [23] O’NEILL B C, KRIEGLER E, EBI K L, et al. The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century[J]. Global Environmental Change, 2017, 42: 169−180 doi: 10.1016/j.gloenvcha.2015.01.004
    [24] 丁小江, 钟方雷, 毛锦凰, 等. 共享社会经济路径下中国各省城市化水平预测[J]. 气候变化研究进展, 2018, 14(4): 392−401 doi: 10.12006/j.issn.1673-1719.2018.018

    DING X J, ZHONG F L, MAO J H, et al. Provincial urbanization projected to 2050 under the shared socioeconomic pathways in China[J]. Climate Change Research, 2018, 14(4): 392−401 doi: 10.12006/j.issn.1673-1719.2018.018
    [25] 姜彤, 王艳君, 袁佳双, 等. “一带一路”沿线国家2020—2060年人口经济发展情景预测[J]. 气候变化研究进展, 2018, 14(2): 155−164

    JIANG T, WANG Y J, YUAN J S, et al. Projection of population and economy in the Belt and Road countries (2020−2060)[J]. Climate Change Research, 2018, 14(2): 155−164
    [26] 潘金玉, 苏布达, 翟建青, 等. 基于共享社会经济路径的中国经济发展趋势及其影响要素分析[J]. 气候变化研究进展, 2019, 15(6): 607−616 doi: 10.12006/j.issn.1673-1719.2019.028

    PAN J Y, SU B D, ZHAI J Q, et al. Development of economy and its influencing factors in China under the shared socioeconomic pathways[J]. Climate Change Research, 2019, 15(6): 607−616 doi: 10.12006/j.issn.1673-1719.2019.028
    [27] DONG N, YOU L, CAI W J, et al. Land use projections in China under global socioeconomic and emission scenarios: Utilizing a scenario-based land-use change assessment framework[J]. Global Environmental Change, 2018, 50: 164−177 doi: 10.1016/j.gloenvcha.2018.04.001
    [28] 翁宇威, 蔡闻佳, 王灿. 共享社会经济路径(SSPs)的应用与展望[J]. 气候变化研究进展, 2020, 16(2): 215−222

    WENG Y W, CAI W J, WANG C. The application and future directions of the Shared Socioeconomic Pathways (SSPs)[J]. Climate Change Research, 2020, 16(2): 215−222
    [29] CHEN J, LIU Y J, PAN T, et al. Population exposure to droughts in China under 1.5 ℃ global warming target[J]. Earth System Dynamics Discussions, 2017: 1−13
    [30] 姜彤, 赵晶, 景丞, 等. IPCC共享社会经济路径下中国和分省人口变化预估[J]. 气候变化研究进展, 2017, 13(2): 128−137 doi: 10.12006/j.issn.1673-1719.2016.249

    JIANG T, ZHAO J, JING C, et al. National and provincial population projected to 2100 under the shared socioeconomic pathways in China[J]. Climate Change Research, 2017, 13(2): 128−137 doi: 10.12006/j.issn.1673-1719.2016.249
    [31] 陈华, 郭生练, 郭海晋, 等. 汉江流域1951—2003年降水气温时空变化趋势分析[J]. 长江流域资源与环境, 2006, 15(3): 340−345 doi: 10.3969/j.issn.1004-8227.2006.03.014

    CHEN H, GUO S L, GUO H J, et al. Temporal and spatial trend in the precipitation and temperature from 1951 to 2003 in the Hanjiang basin[J]. Resources and Environment in the Yangtze Basin, 2006, 15(3): 340−345 doi: 10.3969/j.issn.1004-8227.2006.03.014
    [32] YANG N, ZHANG K, HONG Y, et al. Evaluation of the TRMM multisatellite precipitation analysis and its applicability in supporting reservoir operation and water resources management in Hanjiang basin, China[J]. Journal of Hydrology, 2017, 549: 313−325 doi: 10.1016/j.jhydrol.2017.04.006
    [33] 卢金友, 林莉. 汉江生态经济带水生态环境问题及对策[J]. 环境科学研究, 2020, 33(5): 1179−1186

    LU J Y, LIN L. Problems and countermeasures on water eco-environment in Hanjiang River Ecological Economic Belt[J]. Research of Environmental Sciences, 2020, 33(5): 1179−1186
    [34] 李斌, 李丽娟, 覃驭楚, 等. 基于Budyko假设评估洮儿河流域中上游气候变化的径流影响[J]. 资源科学, 2011, 33(1): 70−76

    LI B, LI L J, QIN Y C, et al. Impacts of climate variability on streamflow in the upper and middle reaches of the Tao’er River based on the Budyko hypothesis[J]. Resources Science, 2011, 33(1): 70−76
    [35] TALLIS H, RICKETTS T, GUERRY A, et al. InVEST 3.2.0 User’s Guide: Integrated Valuation of Environmental Services and Tradeoffs[M]. Stanford: the Natural Capital Project, 2015: 124–125
    [36] 范亚宁. 秦岭北麓及周边生态系统水源涵养与水质净化功能评估[D]. 西安: 西北大学, 2017

    FAN Y N. Evaluation of water retention and water purification function in the northern slope of Qinling mountains and the surrounding ecosystem[D]. Xi’an: Northwest University, 2017
    [37] 吴哲. 基于InVEST模型的海南岛氮磷营养物负荷的风险评价[D]. 海口: 海南大学, 2014

    WU Z. Risk assessment of nitrogen and phosphorus loads in Hainan island based on InVEST model[D]. Haikou: Hainan University, 2014
    [38] ZHANG L, HICKEL K, DAWES W R, et al. A rational function approach for estimating mean annual evapotranspiration[J]. Water Resources Research, 2004, 40(2): W02502
    [39] 张凯. 内陆河流域水资源开发利用潜力研究——以黑河流域中游地区为例[D]. 兰州: 西北师范大学, 2004

    ZHANG K. Study on the potential of water resources exploitation and utilization in the inland river basin—A case study of the middle reaches of Heihe River Valley[D]. Lanzhou: Northwest Normal University, 2004
    [40] 张晓琳, 熊立华, 林琳, 等. 五种潜在蒸散发公式在汉江流域的应用[J]. 干旱区地理, 2012, 35(2): 229−237

    ZHANG X L, XIONG L H, LIN L, et al. Application of five potential evapotranspiration equations in Hanjiang Basin[J]. Arid Land Geography, 2012, 35(2): 229−237
    [41] 周文佐, 刘高焕, 潘剑君. 土壤有效含水量的经验估算研究−以东北黑土为例[J]. 干旱区资源与环境, 2003, 17(4): 88−95 doi: 10.3969/j.issn.1003-7578.2003.04.017

    ZHOU W Z, LIU G H, PAN J J. Soil available water capacity and it’s empirical and statistical models—with s special reference to black soils in northeast China[J]. Journal of Arid Land Resources & Environment, 2003, 17(4): 88−95 doi: 10.3969/j.issn.1003-7578.2003.04.017
    [42] WIJESEKARA G N, GUPTA A, VALEO C, et al. Assessing the impact of future land-use changes on hydrological processes in the Elbow River watershed in southern Alberta, Canada[J]. Journal of Hydrology, 2012, 412/413: 220−232 doi: 10.1016/j.jhydrol.2011.04.018
    [43] 王亚慧, 戴尔阜, 马良, 等. 横断山区产水量时空分布格局及影响因素研究[J]. 自然资源学报, 2020, 35(2): 371−386 doi: 10.31497/zrzyxb.20200210

    WANG Y H, DAI E F, MA L, et al. Spatiotemporal and influencing factors analysis of water yield in the Hengduan Mountain region[J]. Journal of Natural Resources, 2020, 35(2): 371−386 doi: 10.31497/zrzyxb.20200210
    [44] 赵亚茹, 周俊菊, 雷莉, 等. 基于InVEST模型的石羊河上游产水量驱动因素识别[J]. 生态学杂志, 2019, 38(12): 3789−3799

    ZHAO Y R, ZHOU J J, LEI L, et al. Identification of drivers for water yield in the upstream of Shiyang River based on InVEST model[J]. Chinese Journal of Ecology, 2019, 38(12): 3789−3799
    [45] 张建, 雷刚, 漆良华. 南水北调中线水源区丹江口市域景观格局变化及氮磷净化能力[J]. 生态学报, 2021, 41(6): 2261−2271

    ZHANG J, LEI G, QI L H. Change of landscape pattern and nitrogen and phosphorus removal in Danjiangkou City, the Middle Route of the South-to-North Water Diversion Project[J]. Acta Ecologica Sinica, 2021, 41(6): 2261−2271
    [46] 杨旭. 气候和土地利用变化背景下中国西北干旱区产水和水质净化服务评估[D]. 上海: 华东师范大学, 2020

    YANG X. Assessment of water yield and water purification services in arid inland river basins of northwest China under the background of climate and land use change[D]. Shanghai: East China Normal University, 2020
  • 加载中
图(11) / 表(3)
计量
  • 文章访问数:  37
  • HTML全文浏览量:  14
  • PDF下载量:  8
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-03-16
  • 录用日期:  2021-06-04
  • 网络出版日期:  2021-08-13
  • 刊出日期:  2021-10-01

目录

    /

    返回文章
    返回