Land Use Change Prediction and Hydrological Response Assessment of Watershed Based on FLUS Model

TANG Jia; HU Xi-jun; WEI Bao-jing; LUO Zi-wei; ZHAO Si-wen; WANG Ye-zi

doi:10.11988/ckyyb.20210182

PDF(8135 KB)

Journal of Changjiang River Scientific Research Institute ›› 2022, Vol. 39 ›› Issue (4) : 63-69. DOI: 10.11988/ckyyb.20210182

WATER SOIL CONSERVATION AND ECOLOGICAL RESTORATION

Land Use Change Prediction and Hydrological Response Assessment of Watershed Based on FLUS Model

TANG Jia^1,2,3, HU Xi-jun^1,2,3, WEI Bao-jing^1,2,3, LUO Zi-wei^1,2,3, ZHAO Si-wen^1,2,3, WANG Ye-zi^1,2,3

Author information +

History +

Abstract

Simulating land use change under different future development scenarios and evaluating its impact on hydrology play an important role in guiding land use optimization and water security in the watershed. The trend of land use change in the Miluo River Basin from 2000 to 2018 was analyzed, and the land use in 2035 was predicted using FLUS model under two scenarios: the baseline scenario with no control area, and the restricted scenario with development restriction area. Moreover, the change of hydrological response caused by land use change in different scenarios was evaluated by SWAT model. Results showed that: 1) The six land use types in the Miluo River Basin showed obvious change trends from 2000 to 2018, among which the main trend was the transformation from woodland and cultivated land to construction land. 2) Compared with the baseline scenario, the restricted scenario saw increments in forestland and unused land by 0.14 km² and 0.04 km², and reduction in cultivated land and grassland by 0.13 km² and 0.06 km², respectively. The proportion of total area of various land use types remained unchanged. 3) The annual runoff of the basin under the restricted scenario is 383 500 m³ less than that under the baseline scenario.

Key words

land use prediction / hydrologic response / FLUS model / SWAT model / Miluo River Basin

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

TANG Jia, HU Xi-jun, WEI Bao-jing, LUO Zi-wei, ZHAO Si-wen, WANG Ye-zi. Land Use Change Prediction and Hydrological Response Assessment of Watershed Based on FLUS Model[J]. Journal of Changjiang River Scientific Research Institute. 2022, 39(4): 63-69 https://doi.org/10.11988/ckyyb.20210182

References

[1] 于元赫,李子君,林锦阔,等.沂河流域土地利用时空变化图谱特征分析[J].自然资源学报,2019,34(5):975-988.
[2] 齐师杰,张行南,夏达忠,等.嘉陵江流域土地利用/覆被变化特征及其驱动力分析[J].长江科学院院报,2013,30(1):1-7.
[3] 郭强,叶许春,刘佳,等.土地利用变化对流域水文过程时空分异的影响:以赣江流域为例[J].长江流域资源与环境,2020,29(12):2747-2759.
[4] 俞孔坚,王春连,李迪华,等.水生态空间红线概念、划定方法及实证研究[J].生态学报,2019,39(16):5911-5921.
[5] 赵方圆,杨宇翔,张华堂,等.土地利用及景观格局动态变化分析:以甘肃省党河流域为例[J].水土保持研究,2021,28(3):1-7.
[6] 于辉,毋兆鹏.情景模拟的精河流域绿洲土地利用变化及预测[J].测绘科学,2019,44(12):86-94.
[7] 李晓蕾,魏建新,徐丽萍,等.基于CLUE-S模型的博斯腾湖流域土地利用变化情景模拟[J].石河子大学学报(自然科学版),2019,37(3):345-352.
[8] 岳东霞,杨超,江宝骅,等.基于CA-Markov模型的石羊河流域生态承载力时空格局预测[J].生态学报,2019,39(6):1993-2003.
[9] 于淼,廉丽姝,李宝富,等.基于CLUE-S模型的南四湖流域土地利用及其生态效应评估[J].水土保持通报,2018,38(6):231-239.
[10] 张晨星,徐晶晶,温静,等.基于CA-Markov模型和MCE约束的白洋淀流域景观动态研究[J].农业资源与环境学报,2021,38(4):655-664.
[11] 田晶,郭生练,刘德地,等.气候与土地利用变化对汉江流域径流的影响[J].地理学报,2020,75(11):2307-2318.
[12] 刘芳,熊伟,王彦辉,等.基于LUCC的泾河流域景观格局与径流的响应关系[J].干旱区资源与环境,2019,33(1):137-142.
[13] 沈振涛,赵强,高倩,等.大汶河流域土地利用变化特征及预测[J].济南大学学报(自然科学版),2021(4):1-9.
[14] 成超男,胡杨,赵鸣.城市绿色空间格局时空演变及其生态系统服务评价的研究进展与展望[J].地理科学进展,2020,39(10):1770-1782.
[15] LI X, CHEN G, LIU X, et al. A New Global Land-Use and Land-Cover Change Product at a 1-km Resolution for 2010 to 2100 Based on Human-Environment Interactions[J]. Annals of the American Association of Geographers, 2017, 107(5): 1040-1059.
[16] 欧阳晓,贺清云,朱翔.多情景下模拟城市群土地利用变化对生态系统服务价值的影响:以长株潭城市群为例[J].经济地理,2020,40(1):93-102.
[17] 张世伟,魏璐瑶,金星星, 等.基于FLUS-UGB的县域土地利用模拟及城镇开发边界划定研究[J].地球信息科学学报,2020,22(9):1848-1859.
[18] 王旭,马伯文,李丹, 等.基于FLUS模型的湖北省生态空间多情景模拟预测[J].自然资源学报,2020,35(1):230-242.
[19] 李胜鹏,柳建玲,林津,等.基于土地利用情景的福建省生态经济系统协调度时空演变模拟[J].水土保持研究,2021,28(1):234-241.
[20] 张韶月,刘小平,闫士忠,等.基于“双评价”与FLUS-UGB的城镇开发边界划定:以长春市为例[J]. 热带地理,2019,39(3):377-386.
[21] 王保盛,廖江福,祝薇,等.基于历史情景的FLUS模型邻域权重设置:以闽三角城市群2030年土地利用模拟为例[J].生态学报,2019,39(12):4284-4298.
[22] 徐新良,刘纪远,张树文,等.中国多时期土地利用土地覆被遥感监测数据集(CNLUCC)[DB/OL].中国科学院资源环境科学数据中心数据注册与出版系统(http://www.resdc.cn/DOI),2018. [2021-03-03].doi:10.12078/2018070201.
[23] 徐新良.中国人口空间分布公里网格数据集[DB/OL].中国科学院资源环境科学数据中心数据注册与出版系统(http://www.resdc.cn/DOI),2017. doi:10.12078/2017121101.
[24] 徐新良.中国GDP空间分布公里网格数据集[DB/OL].中国科学院资源环境科学数据中心数据注册与出版系统(http://www.resdc.cn/DOI),2017.doi:10.12078/2017121102.
[25] 魏怀斌,张占庞,杨金鹏.SWAT模型土壤数据库建立方法[J].水利水电技术,2007,38(6):15-18.
[26] 孟现勇,王浩.SWAT模型中国大气同化驱动数据集(CMADS V1.1)(2008—2016)[DB/OL].国家青藏高原科学数据中心,(2016-04-15)[2021-03-03]. doi:10.3972/westdc.002.2016.db.
[27] 白根川,夏建国,王昌全, 等.基于地类空间转化趋势模型的眉山市东坡区土地利用转化分析[J].资源科学,2009,31(10):1793-1799.
[28] 丛佃敏,赵书河,于涛,等.综合生态安全格局构建与城市扩张模拟的城市增长边界划定:以天水市规划区(2015—2030年)为例[J].自然资源学报,2018,33(1):14-26.
[29] 田扬,肖桂荣. 基于CMADS驱动下SWAT模型的敖江流域径流模拟[J].长江科学院院报,2020,37(11):27-32.