基于InVEST模型的石羊河上游产水量驱动因素识别

生态学杂志

基于InVEST模型的石羊河上游产水量驱动因素识别

赵亚茹¹,周俊菊^1,4*,雷莉²,向鹃¹,黄美华¹,冯炜¹,朱国锋^1,5,魏伟¹,王静爱^3*

(¹西北师范大学地理与环境科学学院，兰州 730070；²甘肃省水利厅石羊河流域管理局，甘肃武威 733000；³北京师范大学地理科学学部，北京 100875；⁴甘肃省土地利用与综合整治工程研究中心，兰州 730070；⁵中国科学院寒区旱区环境与工程研究所冰冻圈科学国家重点实验室，兰州 730000)

出版日期:2019-12-10 发布日期:2019-12-10

Identification of drivers for water yield in the upstream of Shiyang River based on InVEST model.

ZHAO Ya-ru¹, ZHOU Jun-ju^1,4*, LEI Li², XIANG Juan¹, HUANG Mei-hua¹, FENG Wei¹, ZHU Guo-feng^1,5, WEI Wei¹, WANG Jing-ai^3*

(¹College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China; ²Management Bureau of Shiyang River Basin, Gansu Provincial Water Resources Bureau, Wuwei 733000, Gansu, China; ³Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; ⁴Gansu Engineering Research Center of Land Utilization and Comprehension Consolidation, Lanzhou 730070, China; ⁵Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China).

Online:2019-12-10 Published:2019-12-10

摘要/Abstract

摘要： 石羊河流域地处中国西北内陆，水资源匮乏，环境问题突出，是典型生态脆弱区，对其上游产水过程的研究将为区域生态系统服务可持续发展提供科学依据。基于InVEST模型，以1986、2000、2010和2015年土壤、气象及土地利用数据作为输入，对石羊河上游近30年产水量进行评估，并应用情景模拟法探讨其对气候和土地利用变化的响应。结果表明：石羊河上游产水高值区集中在西部和西南部，八大水系中，西营河的产水深度（220.97 mm）最大且产水能力（46.05%）最强；各土地利用类型中产水能力最强的是未利用地（55.49%），其次分别为草地（34.52%）、耕地（33.27%）和林地（31.59%）。1986—2015年石羊河上游产水量呈现先增后减再缓升的变化特征，八大水系变化特征差异显著。气候变化是影响产水量变化的主要因素，降水对其影响最为明显；土地利用变化主要通过改变下垫面状况影响实际蒸发量，从而影响产水量。

关键词: 生产能力指数, 生态系统质量, 生态系统稳定性, 生态系统承载力, 遥感, 疏勒河流域

Abstract:

Shiyang River basin, located in the inland of northwest China, is an ecologically fragile area with water shortage and prominent environmental problems. Understanding the upstream water production process of Shiyang River can provide scientific reference for regional sustainable development. Based on InVEST model, we evaluated annual water yield in the upstream of Shiyang River in the past 30 years with soil, meteorological and land use data in 1986, 2000, 2010 and 2015 as inputs and applied scenario simulation method to explore its response to climate and land use changes. The results showed that areas with high water yield in the upstream of Shiyang River were concentrated in the west and southwest regions. Among the eight major river systems, Xiying River had the largest water yield depth (220.97 mm) and the highest water yield capacity (46.05%). The unutilized land had the highest water production capacity (55.49%), followed by grassland (34.52%), cultivated land (33.27%), and woodland (31.59%). From 1986 to 2015, water yield in the upstream of Shiyang River showed a change pattern of increase first, then decrease, and then slow increase. The changes of the eight major river systems were significantly different. Climate change, especially precipitation change, is the main factor affecting the changes of water yield. Land use change affected actual evaporation by changing underlying surface condition, with consequence on water yield.

Key words: ecosystem quality, ecosystem productivity index, remote sensing., ecosystem stability, ecosystem bearing capacity, , Shule River basin

赵亚茹,周俊菊,雷莉,向鹃,黄美华,冯炜,朱国锋,魏伟,王静爱. 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.

ZHAO Ya-ru, ZHOU Jun-ju, LEI Li, XIANG Juan, HUANG Mei-hua, FENG Wei, ZHU Guo-feng, WEI Wei, WANG Jing-ai. Identification of drivers for water yield in the upstream of Shiyang River based on InVEST model.[J]. cje.

[1]	郭贝贝, 崔莹雪. 基于RSEVI和地理探测器的安徽省5A级景区生态脆弱性评价 [J]. 生态学杂志, 2024, 43(2): 550-563.
[2]	何洋, 赵喜萍. 基于标准化遥感生态指数的汾河流域生态评价与时序分析 [J]. 生态学杂志, 2024, 43(2): 564-575.
[3]	刘浦东, 王远轲, 张冬, 刘建涛. 基于多源数据的小清河流域生态环境时空变化分析 [J]. 生态学杂志, 2024, 43(2): 600-608.
[4]	赵开鑫, 李雪梅, 王桂钢, 孙旭伟. 基于GEE平台的黄河源区生态环境质量动态评价 [J]. 生态学杂志, 2024, 43(1): 290-298.
[5]	张云霞, 汪仕美, 李焱, 高秉丽, 巩杰. 2000—2020年青藏高原生态质量时空变化 [J]. 生态学杂志, 2023, 42(6): 1464-1473.
[6]	董鑫, 陈效锐, 李艳忠, 古晓东, 杨存建. 基于地理探测器的四川省大熊猫国家公园生态环境时空变化及其归因分析 [J]. 生态学杂志, 2023, 42(4): 946-955.
[7]	吴小波, 范晓雨, 刘晓敬, 肖林, 马启民, 贺宁, 郜思卓, 乔雨亭. 基于Google Earth Engine云平台的成渝城市群生态环境质量时空变化 [J]. 生态学杂志, 2023, 42(3): 759-768.
[8]	张鹏超, 梁宇, 刘波, 马天啸, 吴苗苗. 基于随机森林模型的青藏高原森林地上生物量遥感估算 [J]. 生态学杂志, 2023, 42(2): 415-424.
[9]	张惠婷, 孟凡浩, 萨楚拉, 罗敏, 王牧兰, 李晨昊. 2001—2019年蒙古高原生态系统质量时空格局变化及归因分析 [J]. 生态学杂志, 2023, 42(2): 425-435.
[10]	何天星, 田宁, 周锐, 马群, 张洁, 高峻. 基于GEE和RSEI的长三角一体化示范区生态环境质量动态评估 [J]. 生态学杂志, 2023, 42(2): 436-444.
[11]	周喆, 胡夏嵩, 刘昌义, 付江涛, 赵吉美, 邢光延, 何伟鹏. 基于GEE的黄河上游生态环境质量动态监测与评价：以龙羊峡至积石峡段为例 [J]. 生态学杂志, 2023, 42(10): 2545-2554.
[12]	王朝阳, 师银芳, 侯诚. 基于Sentinel-2A影像的枸杞种植区域识别 [J]. 生态学杂志, 2022, 41(5): 1033-1040.
[13]	王婷, 辛丽雨, 马铁帅, 朱志红, 杜岩功. 系统发育多样性对青藏高原高寒草甸的稳定性影响 [J]. 生态学杂志, 2022, 41(12): 2368-2373.
[14]	于冬雪, 韩广轩, 王晓杰, 张保华. 互花米草入侵对黄河口潮沟形态特征和植物群落分布的影响 [J]. 生态学杂志, 2022, 41(1): 42-49.
[15]	焉恒琦, 毛德华, 朱卫红, 王宗明, 李兰. 鸭绿江河口湿地近40年景观格局变化：中朝对比 [J]. 生态学杂志, 2021, 40(9): 2883-2894.