Optimal Expansion Strategy for a Sewer System under Uncertainty

Abstract

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fastgrowing city in the US/Mexico borderlands-the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technologybased decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.

Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources

“…The proposed monitoring network design methodology incorporates uncertainties as random errors. However, a more rigorous analysis may be accomplished by adopting soft computing techniques such as fuzzy logic (Ning and Chang 2004) and grey system theory (Chang and Hernandez 2008).…”

Watershed-based point sources permitting strategy and dynamic permit-trading analysis

“…The spectrum of applications may include WLA for water pollution control (Chen and Chang, 1998), optimal deployment of water quality monitoring stations Chang, 2002, 2004;Ning et al, 2006), and planning, design and operation of regional sewer systems (Chang and Hernandez, 2006). A variety of functional forms for optimization analyses were derived and assessed to ensure the credibility and reliability in applications (Margeta, 1984;Vieira and Lijklema, 1989;Lee and Wen, 1996a, b;Chang et al, 1996a, b;Cardwell and Ellis, 1996;Somlyo´dy, 1997;Jolma et al, 1997;Onur et al, 1999;Chen and Chang, 1998;Schu¨tze et al, 1999;Dorn and Ranjithan, 2003).…”

A Generalized Interval Fuzzy Chance-Constrained Programming Method for Domestic Wastewater Management Under Uncertainty – A Case Study of Kunming, China

“…However, a variety of complexities exist in such domestic wastewater management systems, including the wastewater generation rate to be treated, the wastewater treatment technologies to be used, the eco-environmental water requirements to be met, and the nutrients emission permits to be offered. Also, from a long-term planning point of view, decision makers are facing problems of insufficiency in terms of available capacities of wastewater treatment plant (WTP) to satisfy the increasing wastewater disposal demands (Chang and Hernandez 2008). Thus, an in-depth cost-benefit analysis for the identification of optimal domestic wastewater management schemes is required.…”

“…Based on previous studies, wastewater management is not a trivial process and there are considerable uncertainties inherent in it, such as multiple forms of uncertainties in public policies, government incentives, and the associated capital and operating costs (Flores-Alsina et al 2008;Sin et al 2011;Tjandraatmadja et al 2013;Trinh et al 2013). In addition, many domestic wastewater system parameters such as wastewater generation rates, capacity of WTPs, lake nutrient emission permits, and eco-environmental water requirements of urban rivers, may appear uncertain in multiple forms that can be expressed as fuzzy sets, probability density functions, and intervals (Cabanillas et al 2012;Chang and Hernandez 2008). Furthermore, such multiple forms of uncertainties may be further multiplied by the site-specific features of many system components, factors, and parameters (Cai et al 2011).…”

“…Huang (1998) developed the IMP model for dealing with system optimization problems, and the results indicated that IMP is an effective tool in dealing with interval numbers in objective function coefficients and constraint parameters. As a pioneer study upon wastewater planning problem, Chang and Hernandez (2008) used a mixed-integer IMP method to reflect the systematic concerns about integrative uncertainties, which could help decision makers to make all-inclusive decisions for WTP expansion in an economically growing region. On the other hand, in fuzzy possibility theory (Zadeh 1978), the membership function of a fuzzy set can be used to encode a possibilistic distribution.…”