Skip to main content
Log in

The Impact of Uncertainty Factors on Optimal Sizing and Costs of Low-Impact Development: a Case Study from Beijing, China

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

The facility allocation optimization of Low-impact development (LID) optimization has been used widely to prevent and tackle urban storm water pollution. However, uncertainties existing in nature and human society would influence the size and total cost of LID. To study the influence of the uncertainties on LID optimization allocation, the research develops the model of LID optimization allocation under uncertainty. The principle of the model is establishing primarily the LID optimization model based on certain numbers and identifying the uncertainties. Hence, the model integrates the uncertainty programming, including interval programming, fuzzy programming, stochastic programming, chance constraint programming (CCP) and scenario programming. The model of LID optimization allocation under uncertainty is established with the conditions. The developed uncertainty model tackles multiple types of uncertainties, and the results of the model are in the interval form in multiple scenarios. The model analyses the effects of uncertainties on the size and total cost of LID in this way. The study shows that the uncertainties in rainfall, infiltration rate, release coefficient, funds and unit price all have a significant influence on the size and total cost of LID when these uncertainty factors overlay. A higher violation probability of CCP corresponding to LID sizing results to a wider interval number of the corresponding uncertainty. The developed method of the study is universal, and the method could be extended to other cases of LID optimization allocation to speculate the influence of uncertainties.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Amorocho J (1973) Nonlinear hydrologic analysis. Adv Hydrosci 9:203–251

    Article  Google Scholar 

  • Charnes A, Cooper WW (1983) Response to "decision problems under risk and chance constrained programming: dilemmas in the transition". Manag Sci 29:750–753

    Article  Google Scholar 

  • Chen L, Wei G, Shen Z (2016) Incorporating water quality responses into the framework of best management practices optimization. J Hydrol 541:1363–1374

    Article  Google Scholar 

  • Coutts AM, Tapper NJ, Beringer J, Loughnan M, Demuzere M (2013) Watering our cities: the capacity for water sensitive Urban Design to support urban cooling and improve human thermal comfort in the Australian context. Prog Phys Geogr 37:2–28

    Article  Google Scholar 

  • Damodaram C, Zechman EM (2013) Simulation-optimization approach to design low impact development for managing peak flow alterations in urbanizing watersheds. J Water Res Plan Man 139:290–298

    Article  Google Scholar 

  • Debo TN, Reese AJ (2003) Municipal storm water management

  • Faucette LB, Scholl B, Beighley RE, Governo J (2009) Large-scale performance and design for construction activity erosion control best management practices. J Environ Qual 38:1248

    Article  Google Scholar 

  • Gabellani S, Boni G, Ferraris L, Hardenberg JV, Provenzale A (2007) Propagation of uncertainty from rainfall to runoff: a case study with a stochastic rainfall generator. Adv Water Resour 30:2061–2071

    Article  Google Scholar 

  • Gu JJ, Guo P, Huang GH, Shen N (2013) Optimization of the industrial structure facing sustainable development in resource-based city subjected to water resources under uncertainty. Stoch Env Res Risk A 27:659–673

    Article  Google Scholar 

  • Gu JJ, Li M, Guo P, Huang G (2016a) Risk assessment for ecological planning of arid Inland River basins under hydrological and management uncertainties. Water Resour Manag 30:1415–1431

    Article  Google Scholar 

  • Gu JJ, Guo P, Huang GH (2016b) Achieving the objective of ecological planning for arid inland river basin under uncertainty based on ecological risk assessment. Stoch Env Res Risk A 30:1485–1501

    Article  Google Scholar 

  • Guo P, Huang GH (2011) Inexact fuzzy-stochastic quadratic programming approach for waste management under multiple uncertainties. Eng Optim 43:525–539

    Article  Google Scholar 

  • He L, Huang G, Lu H, Zeng G (2008) Optimization of surfactant-enhanced aquifer remediation for a laboratory BTEX system under parameter uncertainty. Environ Sci Technol 42:2009–2014

    Article  Google Scholar 

  • Herendeen N, Glazier N, Makarewicz J, Bosch I, Waiser M (2009) Agricultural best management practices for Conesus Lake: the role of extension and soil/water conservation districts. J Great Lakes Res 35:15–22

    Article  Google Scholar 

  • Huang GH, Loucks DP (2000) An inexact two-stage stochastic programming model for water resources management under uncertainty. Civ Eng Environ Syst 17:95–118

    Article  Google Scholar 

  • Huang GH, Sae-Lim N, Liu L, Chen Z (2001) An interval-parameter fuzzy-stochastic programming approach for municipal solid waste management and planning. Environ Model Assess 6:271–283

    Article  Google Scholar 

  • Huang GH, Niu YT, Lin QG, Zhang XX, Yang YP (2011) An interval-parameter chance-constraint mixed-integer programming for energy systems planning under uncertainty. Energ Source Part B 6:192–205

    Article  Google Scholar 

  • Iskander MG (2005) A suggested approach for possibility and necessity dominance indices in stochastic fuzzy linear programming. Appl Math Lett 18:395–399

    Article  Google Scholar 

  • Jia H, Ma H, Sun Z, Yu S, Ding Y, Liang Y (2014) A closed urban scenic river system using stormwater treated with LID-BMP technology in a revitalized historical district in China. Ecol Eng 71:448–457

    Article  Google Scholar 

  • Kapelan, Z., D. Savic, and G. A. Walters. 2003. Robust least cost design of water distribution systems using GAS. Pages 147-155 in Advances In Water Supply Management

  • Li M, Guo P, Singh VP (2016a) Biobjective optimization for efficient irrigation under fuzzy uncertainty. J Irrig Drain Eng 142:05016003

    Article  Google Scholar 

  • Li M, Guo P, Singh VP, Yang G (2016b) An uncertainty-based framework for agricultural water-land resources allocation and risk evaluation. Agric Water Manag 177:10–23

    Article  Google Scholar 

  • Loaiciga HA, Church RLC (2010) Linear programs for nonliear hydrologic Eestmation 1. J Am Water Resour Assoc 26:645–656

    Article  Google Scholar 

  • Loáiciga HA, Sadeghi KM, Shivers S, Kharaghani S (2015) Stormwater control measures: optimization methods for sizing and selection. J Water Resour Plan Manag 141:04015006

    Article  Google Scholar 

  • Mao X, Jia H, Yu SL (2016) Assessing the ecological benefits of aggregate LID-BMPs through modelling. Ecol Model

  • Martin-Mikle CJ, Beurs KMD, Julian JP, Mayer PM (2015) Identifying priority sites for low impact development (LID) in a mixed-use watershed. Landsc Urban Plan 140:29–41

    Article  Google Scholar 

  • Mishra S, Parker JC, Singhal N (1989) Estimation of soil hydraulic properties and their uncertainty from particle size distribution data. J Hydrol 108:1–18

    Article  Google Scholar 

  • Ren C, Guo P, Tan Q, Zhang L (2017) A multi-objective fuzzy programming model for optimal use of irrigation water and land resources under uncertainty in Gansu Province, China. J Clean Prod 164

  • Tan Y, Dur F (2010) Developing a sustainability assessment model: the sustainable infrastructure, land-use. Environment and transport model. Sustainability 2:321–340

    Article  Google Scholar 

  • U.S. Corps of Engineers (2000) Hydrologic modeling system: technical reference manual. Hydrologic Engineering Center, Davis

    Google Scholar 

  • Wu CB, Huang GH, Li W, Xie YL, Xu Y (2015) Multistage stochastic inexact chance-constraint programming for an integrated biomass-municipal solid waste power supply management under uncertainty. Renew Sustain Energy Rev 41:1244–1254

    Article  Google Scholar 

  • Zhou Q (2014) A review of sustainable urban drainage systems considering the climate change and urbanization impacts. Water 6:976–992

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge financial supports for this research from projects of National Natural Science Foundation of China (Grant No. 41601581) and Science Technology Plan Project for Construction Industry of Anhui Province (Grant No. 2011YF-32) and Beijing Natural Science Foundation (Grant No. 8172015).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dazhi Gu.

Ethics declarations

Conflict of Interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled “The Impact of Uncertainty Factors on the Optimization Allocation of Best Management Practices and Low-impact Development”.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gu, J., Zhang, Q., Gu, D. et al. The Impact of Uncertainty Factors on Optimal Sizing and Costs of Low-Impact Development: a Case Study from Beijing, China. Water Resour Manage 32, 4217–4238 (2018). https://doi.org/10.1007/s11269-018-2040-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-018-2040-3

Keywords

Navigation