A pinboard by
Hadi Ganjidoost

Research Assistant, University of Waterloo


A decision support tool enables water utilities to develop long-term financially sustainable plans.

Water distribution and wastewater collection networks have been in service for more than a century in the majority of the cities in Canada. Although “out of sight” infrastructure might often be “out of mind”, the functionality of these city arteries greatly influences public health. Lack of effective maintenance and proactive renewal plans may increase the incurred costs of water infrastructure systems drastically until they cannot be covered by water fees. Management of aging water infrastructure systems with limited financial resources requires comprehensive asset management plans that help decision-makers minimize the total life-cycle cost of their assets while enhancing levels of service. A viable asset management plan should incorporate a Strategic plan (10+year), to set the policies and strategies; Tactical plan (2-10 years), to develop renewal programs; and Operational plan (1-2 years), to establish renewal projects. An effective dynamic communication among planning levels is critical to share and exchange information, and, thus promote alignment of their respective objectives. This research will develop an Integrated Water Infrastructure Asset Management (IWAIM) model comprised of strategic, tactical and operational plans to (1) align corresponding objectives; (2) share and exchange their information; and (3) optimize the allocation of financial resources. The proposed research will make several noteworthy contributions to the body of knowledge for water distribution and wastewater collection networks: (1) The development of an integrated strategic-tactical asset management planning model to build R&R programs with aligned objectives; (2) The development of an integrated strategic-tactical-operational asset management planning model to build R&R programs and establish R&R projects with aligned objectives; (3) The development of an optimization model to select, group, and schedule optimal R&R activities; (4) The novel integrated infrastructure asset management decision-support tool that enables water infrastructure system stakeholders to make optimal decisions in compliance with various regulatory and legal mandates.


System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts.

Abstract: Accurate prediction of municipal water demand is critically important to water utilities in fast-growing urban regions for drinking water system planning, design, and water utility asset management. Achieving the desired prediction accuracy is challenging, however, because the forecasting model must simultaneously consider a variety of factors associated with climate changes, economic development, population growth and migration, and even consumer behavioral patterns. Traditional forecasting models such as multivariate regression and time series analysis, as well as advanced modeling techniques (e.g., expert systems and artificial neural networks), are often applied for either short- or long-term water demand projections, yet few can adequately manage the dynamics of a water supply system because of the limitations in modeling structures. Potential challenges also arise from a lack of long and continuous historical records of water demand and its dependent variables. The objectives of this study were to (1) thoroughly review water demand forecasting models over the past five decades, and (2) propose a new system dynamics model to reflect the intrinsic relationship between water demand and macroeconomic environment using out-of-sample estimation for long-term municipal water demand forecasts in a fast-growing urban region. This system dynamics model is based on a coupled modeling structure that takes into account the interactions among economic and social dimensions, offering a realistic platform for practical use. Practical implementation of this water demand forecasting tool was assessed by using a case study under the most recent alternate fluctuations of economic boom and downturn environments.

Pub.: 18 Feb '11, Pinned: 17 Aug '17