基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测

杨智勇; 牛健植; 樊登星; 张卓佩; 杜洲; 赵春光

doi:10.13870/j.cnki.stbcxb.2024.01.028

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基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测

更新时间：2025-03-12

- 基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测
- Response and Prediction of Runoff to Land Use Change in Kuye River Basin Based on SWAT and PLUS Models
- 水土保持学报 2024年38卷第1期页码：289-299
- 作者机构：
  
  1. 北京林业大学水土保持学院, 水土保持国家林业和草原局重点实验室,北京,100083
  2. 林业生态工程教育部工程研究中心,北京,100083
  3. 鄂尔多斯市水旱灾害防御技术中心,内蒙古,鄂尔多斯,017000
- 作者简介：
  
  [ "杨智勇(1999—),男,硕士研究生,主要从事森林水文与土壤侵蚀研究。E-mail:3209194423@qq.com" ]
- 基金信息：
  
  国家重点研发计划项目(2022YFF1300804)
- DOI：10.13870/j.cnki.stbcxb.2024.01.028
  中图分类号： P333.5
- 纸质出版：2024
- 稿件说明：
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杨智勇, 牛健植, 樊登星, 等. 基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测[J]. 水土保持学报, 2024,38(1):289-299.

YANG Zhiyong, NIU Jianzhi, FAN Dengxin, et al. Response and Prediction of Runoff to Land Use Change in Kuye River Basin Based on SWAT and PLUS Models[J]. 2024, 38(1): 289-299.
杨智勇, 牛健植, 樊登星, 等. 基于SWAT和PLUS模型的窟野河流域径流对土地利用变化的响应及预测[J]. 水土保持学报, 2024,38(1):289-299. DOI： 10.13870/j.cnki.stbcxb.2024.01.028.

YANG Zhiyong, NIU Jianzhi, FAN Dengxin, et al. Response and Prediction of Runoff to Land Use Change in Kuye River Basin Based on SWAT and PLUS Models[J]. 2024, 38(1): 289-299. DOI： 10.13870/j.cnki.stbcxb.2024.01.028.

摘要

[目的] 为揭示窟野河流域径流对土地利用变化的响应

并预测未来径流变化。[方法] 以窟野河流域为研究区

基于SWAT和PLUS模型

通过2000年、2005年、2010年、2015年、2020年和预测得到的自然发展情景下2025年、2030年7期土地利用数据

定量分析径流在不同土地利用情景下的变化。[结果] (1)SWAT模型率定期和验证期的R2和NS均＞0.7;PLUS模型总体精度为0.877 4

Kappa系数为0.802 1

2个模型在窟野河流域适用性较好;(2)2000—2020年

窟野河流域林地、建设用地面积分别增加102.92

600.90 km2

耕地、草地、水域和未利用地分别减少277.15

366.25

40.44

19.98 km2;(3)窟野河流域年平均径流深整体呈现"上游低

下游高

西部低

东部高"的空间分布格局;(4)在保证其他输入数据不变的情况下

改变土地利用数据

情景分析结果表明

林地、草地面积减少会促进径流

建设用地面积增加同样会促进径流;(5)自然发展情景下

2025年和2030年窟野河流域土地利用空间分布格局未发生显著变化

仍以耕地和草地为主

年平均径流量较2020年分别增加3.21%

5.00%。[结论] 土地利用与径流变化关系密切

情景分析角度下

林地、草地对径流起抑制作用

建设用地对径流起促进作用。未来自然发展情景下

随土地利用变化

径流呈增加态势

研究结果可为窟野河流域的土地利用结构优化和水土资源的合理规划提供科学依据。

Abstract

[Objective] The study is aimed at revealing the response of runoff to land use change in the Kuye River Basin and predicting future runoff change. [Methods] Taking the Kuye River Basin as the study area

based on the SWAT and PLUS models

the changes of runoff under different land use scenarios were quantitatively analyzed by using the land use data of 2000

2005

2010

2015

2020 and the data of 2025 and 2030 that were predicted from the natural development scenario. [Results] (1) The R2 and NS of the SWAT model during the periodic and validation periods were greater than 0.7. The overall accuracy of PLUS model was 0.877 4

and the Kappa coefficient was 0.802 1. The two models had good applicability in the Kuye River Basin. (2) From 2000 to 2020

forest land and construction land increased by 102.92 and 600.90 km2

respectively

while cultivated land

grassland

water area

and unused land decreased by 277.15

366.25

40.44 and 19.98 km2

respectively. (3) The average annual runoff depth in the Kuye River Basin presented a spatial distribution pattern of "lower in the upper reaches

higher in the lower reaches

lower in the west

and higher in the east". (4) Changing land use data while ensuring that other input data remains unchanged

the results of scenario analysis showed that the decrease of forest land and grassland area would promote runoff

and the increase of construction land area would also promote runoff. (5) Under the natural development scenario

there was no significant change in the spatial distribution pattern of land use in the Kuye River Basin in 2025 and 2030

and the land use was still dominated by cultivated land and grassland

with the average annual runoff increasing by 3.21% and 5.00%

respectively

compared with 2020. [Conclusion] There was a close relationship between land use and runoff change. From the perspective of scenario analysis

forest land and grassland inhibited runoff

while construction land promoted runoff. Under the future natural development scenario

runoff increased with land use change. The research could provide scientific basis for the optimization of land use structure and rational planning of water and soil resources in the Kuye River Basin.

关键词

Keywords

references

李红波,黄悦,高艳丽.武汉城市圈生态网络时空演变及管控分析[J].生态学报,2021,41(22):9008-9019. LI H B, HUANG Y, GAO Y L. Analysis on the spatio-temporal evolution and regulation of the ecological network in Wuhan metropolitan area[J].Acta Ecologica Sinica,2021,41(22):9008-9019.

ZHOU D, LIN Z, MA S, et al. Assessing an ecological security network for a rapid urbanization region in Eastern China[J].Land Degradation and Development,2021,32(8):2642-2660.

刘晓阳,魏铭,曾坚,等.闽三角城市群生态网络分析与构建[J].资源科学,2021,43(2):357-367. LIU X Y, WEI M, ZENG J, et al. Ecological network analysis and construction: A case study of the urban agglomeration of the Min River Delta, China[J].Resources Science,2021,43(2):357-367.

吴钰茹,吴晶晶,毕晓丽,等.综合模型法评估黄河三角洲湿地景观连通性[J].生态学报,2022,42(4):1315-1326. WU Y R, WU J J, BI X L,et al. Application of the least cost distance model and the circuit theory model in the evaluation of wetland landscape connectivity in the Yellow River Delta[J].Acta Ecologica Sinica,2022,42(4):1315-1326.

赵先超,田一豆,张潇湘.长株潭城市群土地利用碳排放与生态系统服务价值时空关系分析[J].水土保持学报,2023,37(5):215-225. ZHAO X C, TIAN Y D, ZHANG X X. Spatio-temporal relationship between land use carbon emissions and ecosystem service value in Changzhutan urban agglomeration[J].Journal of Soil and Water Conservation, 2023,37(5):215-225.

方创琳,张国友,薛德升.中国城市群高质量发展与科技协同创新共同体建设[J].地理学报,2021,76(12):2898-2908. FANG C L, ZHANG G Y, XUE D S. High-quality development of urban agglomerations in China and construction of science and technology collaborative innovation community[J]Acta Geographica Sinica,2021,76(12):2898-2908.

苟登文,宫清华,陈爱兵,等.粤港澳大湾区生态协同治理策略研究综述[J].生态科学,2022,41(2):249-258. GOU D W, GONG Q H, CHEN A B, et al. A review of ecological coordination governance strategies in Guangdong-Hong Kong-Macao Greater Bay Area[J].Ecological Science,2022,41(2):249-258.

朱治双,廖华.京津冀及周边大气污染联防联控政策实施效果评估[J].中国地质大学学报(社会科学版),2022,22(2):142-156. ZHU Z S, LIAO H. Evaluation on the effects of joint prevention and control of air pollution in Beijing-Tianjin-Hebei region and its surrounding areas[J].Journal of China University of Geosciences (Social Sciences Edition), 2022,22(2):142-156.

冯舒,唐正宇,俞露,等.城市群生态网络协同构建场景要素与路径分析[J].生态学报,2022,42(20):8223-8237. FENG S, TANG Z Y, YU L, et al. Collaborative construction of ecological network in urban agglomerations[J].Acta Ecologica Sinica,2022,42(20):8223-8237.

刘智勇,贾先文,潘梦启.省际跨域生态环境协同治理实践及路径研究[J].东岳论丛,2022,43(11):184-190. LIU Z Y, JIA X W, PAN Q M. Study on the practice and path of inter-provincial cross-regional ecological and environmental collaborative management[J].Dongyue Tribune,2022,43(11):184-190.

马才学,杨蓉萱,柯新利,等.基于生态压力视角的长三角地区生态安全格局构建与优化[J].长江流域资源与环境,2022, 31(1):135-147. MA C X, YANG R X, KE X L, et al. Construction and optimization of ecological security pattern in Yangtze River Delta based on the perspective of ecological pressure[J].Resources and Environment in the Yangtze Basin,2022,31(1):135-147.

王玉莹,沈春竹,金晓斌,等.基于MSPA和MCR模型的江苏省生态网络构建与优化[J].生态科学,2019,38(2):138-145. WANG Y Y, SHEN C Z, JIN X B, et al. Developing and optimizing ecological networks based on MSPA and MCR model[J].Ecological Science,2019,38(2):138-145.

XU H, WANG M, SHI T, et al. Prediction of ecological effects of potential population and impervious surface increases using a remote sensing based ecological index (RSEI)[J].Ecological Indicators,2018,93:730-740.

杜雨阳,王征强,于庆和,等.基于生境质量模型和电路理论的区域生态安全格局构建[J].农业资源与环境学报,2022,39(5):1069-1078. DU Y Y, WANG Z Q, YU Q H, et al. Construction of a regional ecological security pattern based on a habitat quality model and circuit theory[J].Journal of Agricultural Resources and Environment,2022,39(5):1069-1078.

MIAO Z, PAN L, WANG Q, et al. Research on urban ecological network under the threat of road networks: A case study of Wuhan[J].ISPRS International Journal of Geo-Information,2019,8(8):e342.

KALEV S, JURI J, ARE K,et al.Development of national ecological networks in the Baltic countries in the framework of the pan-European Ecological Network[M].Warsaw: IUCN Office for Central Europe,2002.

PINTO-COELHO D, MARTINS M, GUIMARAES JUNIOR P R. Network analyses reveal the role of large snakes in connecting feeding guilds in a species-rich Amazonian snake community[J].Ecology and Evolution,2021,11(11):6558-6568.

殷炳超,何书言,李艺,等.基于陆海统筹的海岸带城市群生态网络构建方法及应用研究[J].生态学报,2018,38(12):4373-4382. YIN B C, HE S Y, LI Y, et al. Development and application of an ecological network model for a coastal megalopolis based on land-sea integration[J].Acta Ecologica Sinica,2018,38(12):4373-4382.

TAN L M, ARBABI H, LI Q, et al. Ecological network analysis on intra-city metabolism of functional urban areas in England and Wales[J].Resources, Conservation and Recycling, 2018,138:172-182.

BODIN Ö, TENGÖ M. Disentangling intangible social-ecological systems[J].Global Environmental Change,2012,22(2):430-439.

RATHWELL K J, PETERSON G D. Connecting social networks with ecosystem services for watershed governance: A social-ecological network perspective highlights the critical role of bridging organizations[J].Ecology and Society,2012,17(2):21-45.

MU H W, LI X C, MA H J, et al. Evaluation of the policy-driven ecological network in the Three-North Shelterbelt region of China[J].Landscape and Urban Planning,2022,218:104305-104316.

邹磊,刘慧媛,王飞宇,等.长江中游城市群绿色发展水平的地区差异及其影响因素[J].中国科学:地球科学,2022,52(8):1462-1475. ZOU L, LIU H Y, WANG F Y, et al. Regional difference and influencing factors of the green development level in the urban agglomeration in the middle reaches of the Yangtze River[J].Scientia Sinica(Terrae),2022,52(8):1462-1475.

何利杰,杜梦晴,韦晶,等.长江中游城市群土地利用变化对PM

2.5

污染的影响及空间溢出效应[J].长江流域资源与环境,2023,32(5):1018-1029. HE L J, DU M Q, WEI J, et al. Impact of land use change on PM

2.5

pollution and its spatial spillover effect in urban agglomerations in the middle reaches of the Yangtze River[J].Resources and Environment in the Yangtze Basin,2023,32(5):1018-1029.

曾晨,程轶皎,吕天宇.基于生态系统健康的国土空间生态修复分区:以长江中游城市群为例[J].自然资源学报,2022,37(12):3118-3135. ZENG C, CHENG Y J, LÜ T Y. Research on land-space ecological restoration zoning based on ecosystem health:A case study of the urban aggloeration in the middle reaches along the Yangtze River[J].Journal of Natural Resources,2022,37(12):3118-3135.

长江中游城市群发展规划[Z].国务院,2015. Development Plan for City Clusters in the Middle Reaches of the Yangtze River[Z].State Council,2015.

姚采云,安睿,窦超,等.基于MSPA与MCR模型的三峡库区林地生态网络构建与评价研究[J].长江流域资源与环境,2022,31(9):1953-1962. YAO C Y, AN R, DOU C, et al. Research on construction and evaluation of forest land ecological network in three gorges reservoir area based on MSPA and MCR model[J].Resources and Environment in the Yangtze Basin, 2022,31(9):1953-1962.

黄木易,岳文泽,冯少茹,等.基于MCR模型的大别山核心区生态安全格局异质性及优化[J].自然资源学报, 2019, 34(4):771-784. HUANG M Y, YUE W Z, FENG S R, et al. Analysis of spatial heterogeneity of ecological security based on MCR model and ecological pattern optimization in the Yuexi county of the Dabie Mountain Area[J].Journal of Natural Resources, 2019,34(4):771-784.

俞孔坚.生物保护的景观生态安全格局[J].生态学报,1999,19(1):8-15. YU K J. Landscape ecological security patterns in biological conservation[J].Acta Ecologica Sinica,1999,19(1):8-15.

JIANG B, HUANG J. A new approach to detecting and designing living structure of urban environments[J].Computers, Environment and Urban Systems,2021,88:e101646.

国家统计局.2021年中国城市统计年鉴[M].北京:中国统计出版社,2021. National Bureau of Statistics. China urban statistics yearbook 2021[M].Beijing:China Statistics Press,2021.

陈小平,陈文波.鄱阳湖生态经济区生态网络构建与评价[J].应用生态学报,2016,27(5):1611-1618. CHEN X P, CHEN W B. Construction and evaluation of ecological network in Poyang Lake Eco-economic Zone,China[J].Chinese Journal of Applied Ecology,2016,27(5):1611-1618.

谢辉,巴可伟.长江中游城市群湖北区域综合交通布局规划研究[J].综合运输,2020,42(4):19-24. XIE H, BA K W. On the comprehensive transportation planning of Hubei urban agglomeration in the Middle of the Yangtze River[J].China Transportation Review,2020,42(4):19-24.

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