Model to estimate urban public services demand, by zone, using geographic information systems

Authors

DOI:

https://doi.org/10.24850/j-tyca-2024-04-10

Keywords:

Urban population, resident population, floating population, GIS models, municipal planning, urban planning, land use planning plans, public service demand

Abstract

For the design and operation of any public service, a basic element is to determine the number of people to whom the service would be provided, regardless of whether it is drinking water, drainage, transportation or electricity. However, when urban clusters are large or have dormitory cities, estimating the population to serve becomes complex, especially since population censuses usually only consider the resident population in a territory. Thus a commercial or financial district, may have a relatively small resident population, but a considerable floating population that, although only working, studying or visiting the area, requires basic services (water, drainage, etc.). Traffic measurements give an overall value of how many people enter a municipality or territory, but hardly determine how they are distributed in urban areas. The proposed model takes advantage of Geographic Information Systems (GIS), to locate the demand, calculating an estimate of the population to be served, based on the square meters built and type of use. This allows not only to determine the resident and floating population of a region, but also to select and delimit specific areas, to obtain the population data to be served in a sector, defining volumes of water, networks, water treatment plants, size of drains and sanitary discharges, as well as sizing wastewater treatment plants (WWTP) or transport and electric service needs. The model was applied in the urban area of the Guatemala Municipality, Guatemala, located in Central America, obtaining the resident and floating population for each of the zones. The model allows defining the floating population, to estimate it in the future based on the projections of built area and adjusting it as changes occur.

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Published

2023-04-04

How to Cite

Cobos, C. R., Anta, J., Teijeiro, M. T., & Basterrechea, M. (2023). Model to estimate urban public services demand, by zone, using geographic information systems. Tecnología Y Ciencias Del Agua, 15(4), 405–437. https://doi.org/10.24850/j-tyca-2024-04-10