Friday 09 Feb 2018Dynamic scenarios and water demand simulations: a spatial analysis approach for an ill-planned urban area

Professor Iana Rufino - Federal University of Campina Grande, Brazil

Harrison 170 14:30-15:30

Abstract: This study aims to reproduce water demand scenarios using Geographic Information Systems and cellular automata as a methodological approach for spatial patterns simulations of urban growth (dynamic scenarios). Urban Growing increases pressures for water (water supply problems). Brazilian semi-arid region is facing the longest drought ever (over 6 years). In consequence, thousands of urban inhabitants are dealing with water scarcity. Water consumption simulations can use future land use trends (dynamic modelling). Aggregated models tend to "soften" the inherent dynamism of urban space. On the other hand, some "cell" modelling approaches (such as agent-based modelling) have become popular for phenomena such as disease propagation, crime, and land use applications [1]. This type of modelling is also capable of simulating the dynamics of land use and human activities. Interactions between human activities and the land use are modelled and reached, providing a much more realistic urban pattern of scenario representation [2]. Cellular automata are formal systems based on grids, in which change processes are represented cell by cell, as a simple mapping of the current state of a cell and its neighbors to the state of the next cell at the next time point [3]. Campina Grande county is located in the north-eastern region of Brazil and is the second largest city in the semiarid region which makes a significant pressure on natural resources. Last six years, the county has been facing the most severe water shortage in its human supply. All the water supply depends on the unique surface reservoir (Epitacio Pessoa Dam). There is no river or groundwater available for water supply, which makes the city a good lab for resilience and adaptation studies and practices. Past, present and future land use scenarios area acquired from RS data combined with data from Census, historical and field data. In cities, land use changes too dynamically and fast. Field data is essential for a good quality of present scenarios and helps to explain better some land use transitions from past to present in the dynamic simulations (future). For past and present scenarios, the water consumption is calculated based on land use type (for each land use there are different consumption patterns); the number of floors and unities (sometimes estimated); based on the herein methodologies used in Brazil [4]. So, for future scenarios, there is a spatial analysis by pixel (land use consumption by pixel) establishing "a water consumption rate by pixel by LU" based on past and present scenarios [5]. Urban planners and water resources managers should promote better strategies and practices of water conservation in urban environments. This research expects to support interdisciplinary approach for urban planning teams making the water issues and urban planning issues closer and essential for the resilience of present and future cities.

For the full abstract, please see here:

Biography: Dr Iana Rufino has joined to Natural Resources Center of UFCG in 2006 where now she is a Full Professor. She held a Ph.D. in Natural Resources at UFCG in 2004, a M.Sc. degree in Architecture and Urbanism at USP in 1996, and a Bachelor’s degree in Civil Engineering at UFPB in 1994. She developed her post-doctoral studies at the Center for Geospatial Technology/Texas Tech University in Lubbock, TX (USA) from 2012 to 2013. Nowadays, she teaches classes for undergraduate courses (Civil Engineering and Architecture and Urbanism) and Graduate courses (Environmental and Civil Engineering; Natural Resources). Since 2016 she is the coordinator of the Graduate program in Civil and Environmental Engineering at UFCG (PPGECA). She is also an advisor (Master and Doctorate degrees) and researcher collaborating with many national and international projects. Her main interests are Geospatial Technologies applied to Environmental Studies in Urban and Regional Areas; Remote Sensing supporting Land Use/Land Cover Changes studies in semi-arid regions.

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