The present study identified the various zones vulnerable to urban flood in Cochin City, one of the biggest metro cities on the southwest coast of peninsular India. The analysis and assessment of vulnerability was done through the application of multi-criteria evaluation approach in a...

Floods are random phenomena that not only cause damage to the lives, natural resources and the environment, but also affect the health of people. The severity of flooding tends to increase with urbanization. Socio-economic impacts of floods depend on the area, duration and depth of inundation,...

This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the...

We build upon much of the accumulated knowledge of the widely used SLEUTH urban land change model and offer advances. First, we use SLEUTH’s exclusion/attraction layer to identify and test different urban land cover change drivers; second, we leverage SLEUTH’s self-modification capability to...

Land-use change models grounded in complexity theory such as agent-based models (ABMs) are increasingly being used to examine evolving urban systems. The objective of this study is to develop a spatial model that simulates land-use change under the influence of human land-use choice behavior....

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced...

In order to deal with complex water management problems, it is increasingly claimed that researchers should collaborate with authorities and other stakeholders. According to the literature, such collaboration can enhance cognitive learning about the issues at stake, but there is little empirical...

Spatial Monte Carlo Analysis (SMCA) is a newly developed Multi-Criteria Decision Making (MCDM) technique based on Spatial Compromise Programming (SCP) and Monte Carlo Simulation (MCS) technique. In contrast to other conventional MCDM techniques, SMCA has the ability to address uneven spatial...

Consecutive extreme rainfall events, especially those having unfavourable spatio-temporal patterns, always trigger large floods. This paper aims to examine, through the multivariate hydrological frequency analysis, the probability of the synchronous occurrence of rainfall extremes in the Pearl...

Geographical Information Systems (GIS) are computer programs that are able to bring large amounts of data of both the physical and the social system together in one comprehensive overview shown digitally. GIS occurred very rapidly on the Dutch policy agenda. In this paper we analyze how the fast...