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

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.

Graphical abstract

Keywords

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

References

[1] Chang J X, Bai T, Huang Q, Yang D W (2013). Optimization of Water Resources Utilization by PSO-GA. Water Resources Management, 27(10): 3525–3540

[2] Daniels P L, Lenzen M, Kenway S J (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

[3] Feng K S, Siu Y L, Guan D B, Hubacek K (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

[4] Feng L H, Zhang X C, Luo G Y (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

[5] Gong L, Jin C L (2009). Fuzzy comprehensive evaluation for carrying capacity of regional water resources. Water Resources Management, 23(12): 2505–2513

[6] Graymore M L M, Sipe N G, Rickson R E (2010). Sustaining human carrying capacity: A tool for regional sustainability assessment. Ecological Economics, 69(3): 459–468

[7] Herstein L M, Filion Y R, Hall K R (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

[8] Huang Y, Dong X, Zeng S Y, Chen J N (2015). An integrated model for structure optimization and technology screening of urban wastewater systems. Frontiers of Environmental Science & Engineering, 9(6): 1036–1048

[9] Li N, Yang H, Wang L C, Huang X J, Zeng C F, Wu H, Ma X X, Song X T, Wei Y N (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

[10] Li P, Zeng S Y, Chen J N (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] Lin Y H, Chen Y P, Yang M D, Su T C (2016). Multiobjective optimal design of sewerage rehabilitation by using the nondominated sorting genetic algorithm-II. Water Resources Management, 30(2): 487–503

[12] Liu R Z, Borthwick A G L (2011). Measurement and assessment of carrying capacity of the environment in Ningbo, China. Journal of Environmental Management, 92(8): 2047–2053

[13] Liu Y, Chen J, He W, Tong Q, Li W (2010). Application of an uncertainty analysis approach to strategic environmental assessment for urban planning. Environmental Science & Technology, 44(8): 3136–3141

[14] Long H L, Liu Y Q, Hou X G, Li T T, Li Y R (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

[15] Marques J, Cunha M, Savic D A (2015). Multi-objective optimization of water distribution systems based on a real options approach. Environmental Modelling & Software, 63: 1–13

[16] Penn R, Friedler E, Ostfeld A (2013). Multi-objective evolutionary optimization for greywater reuse in municipal sewer systems. Water Research, 47(15): 5911–5920

[17] Ren C, Guo P, Li M, Li R (2016). An innovative method for water resources carrying capacity research: Metabolic theory of regional water resources. Journal of Environmental Management, 167: 139–146

[18] Ridoutt B G, Pfister S (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

[19] Ruggiero G, Verdiani G, Dal Sasso S (2012). Evaluation of carrying capacity and territorial environmental sustainability. Journal of Agricultural Engineering, 43(2): 65–71

[20] Song X M, Kong F Z, Zhan C S (2011). Assessment of water resources carrying capacity in Tianjin City of China. Water Resources Management, 25(3): 857–873

[21] Tarebari H, Javid A H, Mirbagheri S A, Fahmi H (2018). Multi-objective surface water resource management considering conflict resolution and utility function optimization. Water Resources Management, 32(14): 4487–4509

[22] Ullmer C, Kunde N, Lassahn A, Gruhn G, Schulz K (2005). WADO™: Water design optimization—methodology and software for the synthesis of process water systems. Journal of Cleaner Production, 13(5): 485–494

[23] Vieira J, Cunha M C, Nunes L, Monteiro J P, Ribeiro L, Stigter T, Nascimento J, Lucas H (2011). Optimization of the operation of large-scale multisource water-supply systems. Journal of Water Resources Planning and Management, 137(2): 150–161

[24] Wang C H, Hou Y L, Xue Y J (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

[25] Wang S, Yang F L, Xu L, Du J (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

[26] Wang T X, Xu S G (2015). Dynamic successive assessment method of water environment carrying capacity and its application. Ecological Indicators, 52: 134–146

[27] Wang Y, Zhou X, Engel B (2018). Water environment carrying capacity in Bosten Lake basin. Journal of Cleaner Production, 199: 574–583

[28] Wang Z Y, Huang K, Yang S S, Yu Y J (2013b). An input-output approach to evaluate the water footprint and virtual water trade of Beijing, China. Journal of Cleaner Production, 42: 172–179

[29] Cao X C, Wu M Y, Guo X P, Zheng Y L, Gong Y, Wu N, Wang W G (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

[30] Xu T, Jia H F, Wang Z, Mao X H, Xu C Q (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

[31] Yang J F, Lei K, Khu S, Meng W, Qiao F (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

[32] Zeng W H, Wu B, Chai Y (2016). Dynamic simulation of urban water metabolism under water environmental carrying capacity restrictions. Frontiers of Environmental Science & Engineering, 10(1): 114–128

[33] Zhao X, Yang H, Yang Z, Chen B, Qin Y (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

[34] Zheng F F, Zecchin A (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

[35] Zhou X Y, Zheng B, Khu S T (2019). Validation of the hypothesis on carrying capacity limits using the water environment carrying capacity. Science of the Total Environment, 665: 774–784

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature