Infrastructure projects are being planned and implemented around the world. These projects lead to economic growth and social development, but often unexpected side effects emerge. The problem is that financial analyses for infrastructure projects do not incorporate quantified economic assessments of social and environmental impacts. Equally, social and environmental assessments for infrastructure projects rarely qualify or quantify socioeconomic outcomes for investments in mitigation practices. Our analysis builds on a review of existing methodologies and tools to propose a method for jointly applying three modeling approaches for integrated economic and spatial planning. The results of case study of the Mekong Flooded Forest landscape shows the capability of the models to anticipate desired and undesired outcomes across social, economic and environmental indicators. This shows promising potential for better informing decision making for sustainability.
Top1. Introduction
Infrastructure projects are being planned and implemented around the world. They include large undertakings, such as airports and highways, as well as smaller ones, like irrigation projects; but all share the same goal: to support economic development and increase human well-being (Korytárová & Hromádka, 2014). These investment projects are driven both by the private sector - primarily for economic gains (Kateja, 2012) - and the public sector looking for social outcomes through reduced poverty, increased access to services and improvements in quality of life (Zhang & Chen, 2013). The returns for society and economies –local, national and regional– on infrastructure investment are analyzed by governments and investors, but mostly focus on financial returns and desired economic outcomes, whatever these may be (Jones, Moura, & Domingos, 2014). Yet, there are unintended and unforeseen consequences of physical design and construction of infrastructure projects that impede the attainment of development goals. These are harder to measure in financial terms and therefore not considered deeply upfront in (Arce & Gullòn, 2000).
One critical example in the developing regions of the world is the relationship between infrastructure development and natural capital. Integrity of biodiversity, land and water all support a flow of inputs to our economies and societies at different scales. The complex natural systems that the world relies on for food, water, and energy are increasingly strained by climate change and the demands of a growing human population (MEA, 2005; Helm, 2014). The top pressures on “stores” of this natural capital are natural resource extraction (Behrens, Giljum, Kovanda, & Niza, 2007), infrastructure projects for transport and energy (Meunier, 2012) and expanding agricultural production and human settlements (McDonald, et al., 2014; Schäffler & Swilling, 2013). Under pressure, natural systems become less stable and resilient. This is a problem of global significance that entail risks for sectors reliant on natural inputs and impacts on the world’s most vulnerable people who typically rely most directly on nature’s “free” benefits.
The problem is essentially that financial analyses for infrastructure projects do not incorporate quantified economic assessments of social and environmental impacts. Equally, social and environmental assessments for infrastructure projects rarely qualify or quantify socioeconomic outcomes for investments in mitigation practices. How would land use change if the economy develops as desired? And what would be the consequences on natural resource use and on ecosystem services –particularly those related to food-energy-water? How large might the resulting cost implications be for vulnerable households? How best to plan roads, railways, power, waste management or irrigation infrastructure in a context of climate change? These are questions to which current methodologies for infrastructure assessments give unsatisfactory answers (for more information, see http://www.ruom.net/portfolio-item/inside-969-movement/).
Many tools are being put forward to inform decision-making by estimating the short, medium and longer-term outcomes of investments across social, economic and environmental dimensions (Bassi, Bečić, & Lombardi, 2014). There are a number of successful case studies of holistic infrastructure and land use planning, but far many more examples that have not found the mark. The results being produced by these tools are not all that useful for the end-users they aim to support (Rozema & Bond, In press).