Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity of water system

doi:10.1007/s11783-019-1200-x

Front. Environ. Sci. Eng.

2020, Vol. 14

Issue (2) : 21 https://doi.org/10.1007/s11783-019-1200-x

RESEARCH ARTICLE

Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity of water system

Yilei Lu¹, Yunqing Huang¹, Siyu Zeng^1,²(

), Can Wang^1,²

¹. School of Environment, Tsinghua University, Beijing 100084, China
². Environmental Simulation and Pollution Control State Key Joint Laboratory, School of Environment, Tsinghua University, Beijing 100084, China

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Abstract

• Impact of urban development on water system is assessed with carrying capacity.

• Impacts on both water resource quantity and environmental quality are involved.

• Multi-objective optimization revealing system trade-off facilitate the regulation.

• Efficiency, scale and structure of urban development are regulated in two stages.

• A roadmap approaching more sustainable development is provided for the case city.

Environmental impact assessments and subsequent regulation measures of urban development plans are critical to human progress toward sustainability, since these plans set the scale and structure targets of future socioeconomic development. A three-step methodology for assessing and optimizing an urban development plan focusing on its impacts on the water system was developed. The methodology first predicted the pressure on the water system caused by implementation of the plan under distinct scenarios, then compared the pressure with the carrying capacity threshold to verify the system status; finally, a multi-objective optimization method was used to propose regulation solutions. The methodology enabled evaluation of the water system carrying state, taking socioeconomic development uncertainties into account, and multiple sets of improvement measures under different decisionmaker preferences were generated. The methodology was applied in the case of Zhoushan city in South-east China. The assessment results showed that overloading problems occurred in 11 out of the 13 zones in Zhoushan, with the potential pressure varying from 1.1 to 18.3 times the carrying capacity. As a basic regulation measure, an environmental efficiency upgrade could relieve the overloading in 4 zones and reduce 9%‒63% of the pressure. The optimization of industrial development showed that the pressure could be controlled under the carrying capacity threshold if the planned scale was reduced by 24% and the industrial structure was transformed. Various regulation schemes including a more suitable scale and structure with necessary efficiency standards are provided for decisionmakers that can help the case city approach a more sustainable development pattern.

Keywords Urban development plan Urban water system Carrying capacity Scenario analysis Multi-objective optimization

Corresponding Author(s): Siyu Zeng

Issue Date: 19 December 2019

Cite this article:

Yilei Lu,Yunqing Huang,Siyu Zeng, et al. Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity of water system[J]. Front. Environ. Sci. Eng., 2020, 14(2): 21.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-019-1200-x
https://academic.hep.com.cn/fese/EN/Y2020/V14/I2/21

Fig.1 Methodological flow chart.

Domestic	Scale of socioeconomic activities in 2020		Efficiencies						Prediction
Domestic	P (10000 persons)	$θ$	DU (L/capita /d)	RU (L/capita/d)	$β$	$γ$	$S C e$ (mg/L)	$S N e$ (mg/L)	WU (10000 m³)	DC (t)	DN (t)
BAU scenario	70	0.75	179	97	0.74	0.07	100	25	4050	5039	881
BAE scenario	70	0.75	195	120	0.95	0.1	60	8	4500	2265	297

Tab.1 Pressure prediction of the domestic sector of Dinghai District in two scenarios

Tab.2 Pressure prediction of the industrial sector of Dinghai District in two scenarios

Tab.3 Pressure prediction of the agricultural sector of Dinghai District in two scenarios

Fig.2 Overloading index values of the 13 zones in 2020.

Fig.3 Optimization results of the four objective functions in Dinghai District.

Fig.4 Optimal industrial scales for Dinghai District based on different decision preferences.

Fig.5 The planned and optimal industrial scale and structure of the 13 zones in Zhoushan.

Fig.6 Industrial overloading index values of the 13 zones in 2020 after the multi-objective optimization.

1	J X Chang, T Bai, Q Huang, D W Yang (2013). Optimization of Water Resources Utilization by PSO-GA. Water Resources Management, 27(10): 3525–3540 https://doi.org/10.1007/s11269-013-0362-8
2	P L Daniels, M Lenzen, S J Kenway (2011). The ins and outs of water use: A review of multi-region input-output analysis and water footprints for regional sustainability analysis and policy. Economic Systems Research, 23(4): 353–370 https://doi.org/10.1080/09535314.2011.633500
3	K S Feng, Y L Siu, D B Guan, K Hubacek (2012). Assessing regional virtual water flows and water footprints in the Yellow River Basin, China: A consumption based approach. Applied Geography (Sevenoaks, England), 32(2): 691–701 https://doi.org/10.1016/j.apgeog.2011.08.004
4	L H Feng, X C Zhang, G Y Luo (2008). Application of system dynamics in analyzing the carrying capacity of water resources in Yiwu City, China. Mathematics and Computers in Simulation, 79(3): 269–278 https://doi.org/10.1016/j.matcom.2007.11.018
5	L Gong, C L Jin (2009). Fuzzy comprehensive evaluation for carrying capacity of regional water resources. Water Resources Management, 23(12): 2505–2513 https://doi.org/10.1007/s11269-008-9393-y
6	M L M Graymore, N G Sipe, R E Rickson (2010). Sustaining human carrying capacity: A tool for regional sustainability assessment. Ecological Economics, 69(3): 459–468 https://doi.org/10.1016/j.ecolecon.2009.08.016
7	L M Herstein, Y R Filion, K R Hall (2011). Evaluating the environmental impacts of water distribution systems by using EIO-LCA-Based multiobjective optimization. Journal of Water Resources Planning and Management, 137(2): 162–172 https://doi.org/10.1061/(ASCE)WR.1943-5452.0000101
8	Y Huang, X Dong, S Y Zeng, J N Chen (2015). An integrated model for structure optimization and technology screening of urban wastewater systems. Frontiers of Environmental Science & Engineering, 9(6): 1036–1048 https://doi.org/10.1007/s11783-015-0792-z
9	N Li, H Yang, L C Wang, X J Huang, C F Zeng, H Wu, X X Ma, X T Song, Y N Wei (2016). Optimization of industry structure based on water environmental carrying capacity under uncertainty of the Huai River Basin within Shandong Province, China. Journal of Cleaner Production, 112: 4594–4604 https://doi.org/10.1016/j.jclepro.2015.08.074
10	P Li, S Y Zeng, J N Chen (2010). A New method for regional water environmental capacity estimation based on natural-social water cycle analysis. In: Proceedings of 2010 National Biomaterials Conference, Chengdu, China
11	Y H Lin, Y P Chen, M D Yang, T C Su (2016). Multiobjective optimal design of sewerage rehabilitation by using the nondominated sorting genetic algorithm-II. Water Resources Management, 30(2): 487–503 https://doi.org/10.1007/s11269-015-1173-x
12	R Z Liu, A G L Borthwick (2011). Measurement and assessment of carrying capacity of the environment in Ningbo, China. Journal of Environmental Management, 92(8): 2047–2053 https://doi.org/10.1016/j.jenvman.2011.03.033 pmid: 21507560
13	Y Liu, J Chen, W He, Q Tong, W Li (2010). Application of an uncertainty analysis approach to strategic environmental assessment for urban planning. Environmental Science & Technology, 44(8): 3136–3141 https://doi.org/10.1021/es902850q pmid: 20199065
14	H L Long, Y Q Liu, X G Hou, T T Li, Y R Li (2014). Effects of land use transitions due to rapid urbanization on ecosystem services: Implications for urban planning in the new developing area of China. Habitat International, 44: 536–544 https://doi.org/10.1016/j.habitatint.2014.10.011
15	J Marques, M Cunha, D A Savic (2015). Multi-objective optimization of water distribution systems based on a real options approach. Environmental Modelling & Software, 63: 1–13 https://doi.org/10.1016/j.envsoft.2014.09.014
16	R Penn, E Friedler, A Ostfeld (2013). Multi-objective evolutionary optimization for greywater reuse in municipal sewer systems. Water Research, 47(15): 5911–5920 https://doi.org/10.1016/j.watres.2013.07.012 pmid: 23932104
17	C Ren, P Guo, M Li, R Li (2016). An innovative method for water resources carrying capacity research: Metabolic theory of regional water resources. Journal of Environmental Management, 167: 139–146 https://doi.org/10.1016/j.jenvman.2015.11.033 pmid: 26683766
18	B G Ridoutt, S Pfister (2013). A new water footprint calculation method integrating consumptive and degradative water use into a single stand-alone weighted indicator. International Journal of Life Cycle Assessment, 18(1): 204–207 https://doi.org/10.1007/s11367-012-0458-z
19	G Ruggiero, G Verdiani, S Dal Sasso (2012). Evaluation of carrying capacity and territorial environmental sustainability. Journal of Agricultural Engineering, 43(2): 65–71 https://doi.org/10.4081/jae.2012.16
20	X M Song, F Z Kong, C S Zhan (2011). Assessment of water resources carrying capacity in Tianjin City of China. Water Resources Management, 25(3): 857–873 https://doi.org/10.1007/s11269-010-9730-9
21	H Tarebari, A H Javid, S A Mirbagheri, H Fahmi (2018). Multi-objective surface water resource management considering conflict resolution and utility function optimization. Water Resources Management, 32(14): 4487–4509 https://doi.org/10.1007/s11269-018-2051-0
22	C Ullmer, N Kunde, A Lassahn, G Gruhn, K Schulz (2005). WADO™: Water design optimization—methodology and software for the synthesis of process water systems. Journal of Cleaner Production, 13(5): 485–494 https://doi.org/10.1016/j.jclepro.2003.09.009
23	J Vieira, M C Cunha, L Nunes, J P Monteiro, L Ribeiro, T Stigter, J Nascimento, H Lucas (2011). Optimization of the operation of large-scale multisource water-supply systems. Journal of Water Resources Planning and Management, 137(2): 150–161 https://doi.org/10.1061/(ASCE)WR.1943-5452.0000102
24	C H Wang, Y L Hou, Y J Xue (2017). Water resources carrying capacity of wetlands in Beijing: Analysis of policy optimization for urban wetland water resources management. Journal of Cleaner Production, 161: 1180–1191 https://doi.org/10.1016/j.jclepro.2017.03.204
25	S Wang, F L Yang, L Xu, J Du (2013a). Multi-scale analysis of the water resources carrying capacity of the Liaohe Basin based on ecological footprints. Journal of Cleaner Production, 53: 158–166 https://doi.org/10.1016/j.jclepro.2013.03.052
26	T X Wang, S G Xu (2015). Dynamic successive assessment method of water environment carrying capacity and its application. Ecological Indicators, 52: 134–146 https://doi.org/10.1016/j.ecolind.2014.12.002
27	Y Wang, X Zhou, B Engel (2018). Water environment carrying capacity in Bosten Lake basin. Journal of Cleaner Production, 199: 574–583 https://doi.org/10.1016/j.jclepro.2018.07.202
28	Z Y Wang, K Huang, S S Yang, Y J Yu (2013b). An input-output approach to evaluate the water footprint and virtual water trade of Beijing, China. Journal of Cleaner Production, 42: 172–179 https://doi.org/10.1016/j.jclepro.2012.11.007
29	X C Cao, M Y Wu, X P Guo, Y L Zheng, Y Gong, N Wu, W G Wang (2017). Assessing water scarcity in agricultural production system based on the generalized water resources and water footprint framework. Science of the Total Environment, 609: 587–597 https://doi.org/10.1016/j.scitotenv.2017.07.191 pmid: 28763656
30	T Xu, H F Jia, Z Wang, X H Mao, C Q Xu (2017). SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization: A case study in Tianjin. Frontiers of Environmental Science & Engineering, 11(4): 1–12 https://doi.org/10.1007/s11783-017-0934-6
31	J F Yang, K Lei, S Khu, W Meng, F Qiao (2015). Assessment of water environmental carrying capacity for sustainable development using a coupled system dynamics approach applied to the Tieling of the Liao River Basin, China. Environmental Earth Sciences, 73(9): 5173–5183 https://doi.org/10.1007/s12665-015-4230-0
32	W H Zeng, B Wu, Y Chai (2016). Dynamic simulation of urban water metabolism under water environmental carrying capacity restrictions. Frontiers of Environmental Science & Engineering, 10(1): 114–128 https://doi.org/10.1007/s11783-014-0669-6
33	X Zhao, H Yang, Z Yang, B Chen, Y Qin (2010). Applying the input-output method to account for water footprint and virtual water trade in the Haihe River basin in China. Environmental Science & Technology, 44(23): 9150–9156 https://doi.org/10.1021/es100886r pmid: 20945890
34	F F Zheng, A Zecchin (2014). An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources. Environmental Modelling & Software, 55: 143–155 https://doi.org/10.1016/j.envsoft.2014.01.028
35	X Y Zhou, B Zheng, S T Khu (2019). Validation of the hypothesis on carrying capacity limits using the water environment carrying capacity. Science of the Total Environment, 665: 774–784 https://doi.org/10.1016/j.scitotenv.2019.02.146 pmid: 30790750

[1]	Te Xu, Haifeng Jia, Zheng Wang, Xuhui Mao, Changqing Xu. SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization: a case study in Tianjin[J]. Front. Environ. Sci. Eng., 2017, 11(4): 1-.
[2]	Nanqi Ren, Qian Wang, Qiuru Wang, Hong Huang, Xiuheng Wang. Upgrading to urban water system 3.0 through sponge city construction[J]. Front. Environ. Sci. Eng., 2017, 11(4): 9-.
[3]	Weihua ZENG,Bo WU,Ying CHAI. Dynamic simulation of urban water metabolism under water environmental carrying capacity restrictions[J]. Front. Environ. Sci. Eng., 2016, 10(1): 114-128.
[4]	Yue HUANG,Xin DONG,Siyu ZENG,Jining CHEN. An integrated model for structure optimization and technology screening of urban wastewater systems[J]. Front. Environ. Sci. Eng., 2015, 9(6): 1036-1048.
[5]	Fangfang ZHANG, Huiquan LI, Bo CHEN, Xue GUAN, Yi ZHANG. Vanadium metabolism investigation using substance flow and scenario analysis[J]. Front Envir Sci Eng, 2014, 8(2): 256-266.
[6]	Junying CHU, Hao WANG, Can WANG. Exploring price effects on the residential water conservation technology diffusion process: a case study of Tianjin city[J]. Front Envir Sci Eng, 2013, 7(5): 688-698.
[7]	Xiong NING, Yi LIU, Jining CHEN, Xin DONG, Wangfeng LI, Bin LIANG. Sustainability of urban drainage management: a perspective on infrastructure resilience and thresholds[J]. Front Envir Sci Eng, 2013, 7(5): 658-668.
[8]	Haifeng JIA, Shuo WANG, Mingjie WEI, Yansong ZHANG. Scenario analysis of water pollution control in the typical peri-urban river using a coupled hydrodynamic-water quality model[J]. Front Envir Sci Eng Chin, 2011, 5(2): 255-265.

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