PDF Download HTML

]" id="html" rel="external">HTML

[1]XU Quanli,WANG Qing,HONG Liang,et al.Dynamic Simulation of Impervious Surface Expansion and Its Risk Assessment on Non-point Source Pollution in Dianchi Lake Basin[J].Research of Soil and Water Conservation,2021,28(04):186-192.

Copy

Dynamic Simulation of Impervious Surface Expansion and Its Risk Assessment on Non-point Source Pollution in Dianchi Lake Basin

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 28 Number of periods: 2021 04 Page number: 186-192 Column: Public date: 2021-08-10

Title:: Dynamic Simulation of Impervious Surface Expansion and Its Risk Assessment on Non-point Source Pollution in Dianchi Lake Basin

Author(s):: XU Quanli^1,2,3,4, WANG Qing^1,2,3,4, HONG Liang^1,2,3,4, YANG Kun^1,2,3,4, PENG Shuangyun^1,2,3,4, ZHANG Shaohua^1,2,3,4; (1.Department of Geography, Yunnan Normal University, Kunming 650500,China;2.GIS Technology Engineering Research Centre for West-China Resources and Environment, Ministry of Education,Yunnan Normal University, Kunming 650500,China;3.Yunnan Geospatial Information Technology Engineering Research Center, Kunming 650500,China;4.University Key Laboratory of Resources and Environment Remote Sensing in Yunnan, Kunming 650500,China)

Keywords:: Dianchi Basin; impervious surface; partitioned cellular automata; hydrological response unit; non-point source pollution risk

CLC:: X2

DOI:: -

Abstract:: The rapid urbanization of lakeside cities not only results a massive expansion of impervious surface, but also makes a significant influence on water environment. It is an effective way to quantitatively explore the sustainable development of lakeside cities to simulate the spatiotemporal evolution pattern of impervious surface and its water environment effect by using hybrid models. Therefore, taking the Dianchi Lake Basin as the study area, we used remote sensing and GIS technology to analyze the temporal-spatial expansion characteristics of impervious surface from 2000 to 2016 caused by urbanization, and simulated and predicted the distribution of impervious surface in the future of 2021 and 2031 by using the partitioned cellular automata model. Then, the coverage of the impervious surface(ISC)from 2000 to 2031 was calculated on the sub-basin scale and the hydrological response units scale, as well as their temporal-spatial characteristics were analyzed. Finally, the historical and future non-point source pollution risk of Dianchi Lake Basin water environment was evaluated based on the relationship between ISC and water quality. The results show that:(1)the expansion of the impervious surface of the Dianchi Lake Basin is characterized by outward radiation from the Dianchi Lake; the impervious surface area has increased by 286.28 km², the annual growth rate is 17.9 km², and the fastest annual growth rate in 2006—2009 is 38.8 km², its coverage increased from 10.16% in 2000 to 20.64% in 2016;(2)compared to non-partitioned CA model, the partitioned CA model can significantly improve the accuracy of land use changes simulation(where Kappa increases over 16%, and total accuracy increases over 26%), which can be used to simulate the expansion of the impervious surface in the future;(3)the impervious surface coverage both in sub-basins and hydrological response unit has been increasing year by year, and the risk of urban non-point source pollution also increases year by year; if attention does no be paid to the risk, the risk will be more severe in future. These research results can provide the scientific bases for adjusting land use structure and coordinating urban construction as well as water environment protection.

References:: [1] Schueler T. The importance of imperviousness[J]. Watershed Protection Techniques, 1994,1(3):100-111. DOI:10,9774/GLEAF.978-1-909493-38-4_2.
[2] Weng Q. Remote sensing of impervious surfaces in the urban areas:Requirements, methods, and trends[J]. Remote Sensing of Environment, 2012,117(2):34-49. DOI:10,1016/j. rse.2011.02.030.
[3] 吴桂平.不同尺度转换方式对土地利用格局模拟的影响效应研究[J].水土保持研究,2010,17(5):75-79.
[4] Zhang S, Fan W, Li Y, et al. The influence of changes in land use and landscape patterns on soil erosion in a watershed[J]. Science of the Total Environment, 2017,574:34-45. DOI:10,1016/j. scitotenv.2016.09.024.
[5] 毕直磊,张妍,张鑫,等.土地利用和农业管理对丹江流域非点源氮污染的影响[J].水土保持学报,2020,34(3):135-141.
[6] Walsh C. Urban impacts on the ecology of receiving waters: A framework for assessment, conservation and restoration[J]. Hydrobiologia, 2000,431(2):107-114. DOI:10.1023/A:1004029715627.
[7] 刘珍环,李猷,彭建.城市不透水表面的水环境效应研究进展[J].地理科学进展,2011,30(3):275-281.
[8] Brabec E, Schulte S, Richards P L. Impervious Surfaces and water quality: A review of current literature and its implications for watershed planning[J]. Journal of Planning Literature: Incorporating the Cpl Bibliographies, 2002,16(4):499-514. DOI:10,1177/088541202400903563.
[9] 杨昆,潘梅娥,杨荣,等.滇池流域不透水表面的水环境影响分析及其治理措施[J].环境工程学报,2016,10(10):5407-5412.
[10] 李中杰,郑一新,张大为.滇池流域近20年社会经济发展对水环境的影响[J].湖泊科学,2012,24(6):875-882.
[11] 徐晓梅,吴雪,何佳,等.滇池流域水污染特征(1988—2014年)及防治对策[J].湖泊科学,2016,28(3):476-484.
[12] 罗毅,赵艺淞,杨昆,等.城镇化过程中滇池流域不透水表面扩张特征及其水环境效应[J].农业工程学报,2018,34(6):224-232.
[13] 黎夏,刘小平.基于案例推理的元胞自动机及大区域城市演变模拟[J].地理学报,2007,62(10):1097-1109.
[14] 吴大千,王仁卿,高甡,等.黄河三角洲农业用地动态变化模拟与情景分析[J].农业工程学报,2010,26(4):285-290.
[15] Liu X, 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 & Urban Planning, 2017,168:94-116.
[16] 柯新利,边馥苓.基于空间数据挖掘的分区异步元胞自动机模型研究[J].中国图象图形学报,2010,15(6):921-930.
[17] 柯新利,邓祥征,刘成武.基于分区异步元胞自动机模型的耕地利用布局优化:以武汉城市圈为例[J].地理科学进展,2010,29(11):1442-1450.
[18] 荣洁,曾春芬,王腊春.太湖流域LUCC对水文过程的影响[J].湖泊科学,2014,26(2):305-312.
[19] Du J, Qian L, Rui H, et al. Assessing the effects of urbanization on annual runoff and flood events using an integrated hydrological modeling system for Qinhuai River basin, China[J]. Journal of Hydrology, 2012,464/465:127-139. DOI:10.1016/j. jhydrol.2012.06.057.
[20] 董欣,杜鹏飞,李志一,等. SWMM模型在城市不透水区地表径流模拟中的参数识别与验证[J].环境科学,2008,29(6):1459-1501.
[21] 渠勇建,成向荣,虞木奎,等.基于SWAT模型的衢江流域土地利用变化径流模拟研究[J].水土保持研究,2019,26(1):130-134.
[22] 秦莉俐,陈云霞,许有鹏.城镇化对径流的长期影响研究[J].南京大学学报:自然科学版,2005,41(3):279-285.
[23] Barco J, Wong K, Stenstrom M. Automatic Calibration of the U. S. EPA SWMM Model for a Large Urban Catchment[J]. Journal of Hydraulic Engineering, 2008,134(4):466-474. DOI:10,1061/(ASCE)0733-9429(2008)134:4(466).
[24] Baker T, Miller S. Using the Soil and Water Assessment Tool(SWAT)to assess land use impact on water resources in an East African watershed[J]. Journal of Hydrology, 2013,486(8):100-111. DOI:10,1016/j. jhydrol.2013.01.041.
[25] Engel B, Ahiablame L, Leroy J. Modeling the impacts of urbanization on lake water level using L-THIA[J]. Urban Climate, 2015,14(4):578-585. DOI:10,1016/j. uclim.2015.10.001.
[26] 王龙,黄跃飞,王光谦.城市非点源污染模型研究进展[J].环境科学,2010,31(10):2532-2540.
[27] 刘珍环,李正国,杨鹏,等.城市景观组分影响水质退化的阈值研究[J].生态学报,2013,33(2):586-594.
[28] Conway T M. Impervious surface as an indicator of pH and specific conductance in the urbanizing coastal zone of New Jersey, USA[J]. Journal of Environmental Management, 2007,85(2):308-316.
[29] Wang A, Zhang S, Peng Y, et al. Impact of rapid urbanization on the threshold effect in the relationship between impervious surfaces and water quality in shanghai, China[J]. Environmental Pollution, 2020,267:115569. doi:10.1016/j.envpol.2020.115569.
[30] 马宇龙,林志垒.基于面向对象和CART决策树方法的遥感影像湿地变化检测研究:以龙祥岛地区为例[J].福建师范大学学报:自然科学版,2017,33(6):69-80.
[31] 乔伟峰,盛业华,方斌,等.基于转移矩阵的高度城市化区域土地利用演变信息挖掘:以江苏省苏州市为例[J].地理研究,2013,32(8):1497-1507.
[32] 何丹,周璟,高伟,等.基于CA-Markov模型的滇池流域土地利用变化动态模拟研究[J].北京大学学报:自然科学版,2014,50(6):1095-1105.
[33] Ke X, Qi L, Zeng C. A partitioned and asynchronous cellular automata model for urban growth simulation[J]. International Journal of Geographical Information Science, 2016,30(4):637-659. DOI:10,1080/13658816.2015.1084510.
[34] Rienow A, Goetzke R. Supporting SLEUTH-Enhancing a cellular automaton with support vector machines for urban growth modeling[J]. Computers Environment & Urban Systems, 2015,49(1):66-81. DOI:10,1016/j. compenvurbsys.2014.05.001.
[35] Shu B, Baker M, Zhang H, et al. Modeling urban expansion by using variable weights logistic cellular automata: A case study of Nanjing, China[J]. International Journal of Geographical Information Science, 2017,31(7):1314-1333. DOI:10,1080/13658816.2017.1283505.
[36] 黎夏,叶嘉安.基于神经网络的元胞自动机及模拟复杂土地利用系统[J].地理研究,2005,24(1):19-27.
[37] Li X, Liu Y, Liu X, et al. Knowledge transfer and adaptation for land-use simulation with a logistic cellular automaton[J]. International Journal of Geographical Information Science, 2013,27(10):1829-1848. doi:10,1080/13658816.2013.825264.

Similar References:

Memo

Last Update: 2021-08-20