A Dynamic GIS–Multicriteria Technique for Siting the NASA–Clark Atlanta Urban Rain Gauge Network

Abstract

Because Atlanta, Georgia, is a model of rapid transition from forest/agriculture land use to urbanization, NASA and other agencies have initiated programs to identify and understand how urban heat islands (UHIs) impact the environment in terms of land use, air quality, health, climate, and other factors. Atlanta's UHI may also impact the regional water cycle by inadvertent forcing of precipitating cloud systems. Yet, a focused assessment of the role of urban-induced rainfall in Atlanta has not been a primary focus of past efforts. Several observational and climatological studies have theorized that UHIs can have a significant influence on mesoscale circulations and resulting convection. Using spaceborne rain radar and a limited network of irregularly spaced, ground-based rain gauges, evidence that the Atlanta and Houston, Dallas, and San Antonio, Texas, urban areas may modify cloud and precipitation development was recently found. To validate these recent satellite-based findings, it was determined that a higher density of rainfall gauges would be required for future work. The NASA-sponsored Study of Precipitation Anomalies from Widespread Urban Landuse (SPRAWL) seeks to further address the impact of urban Atlanta on precipitation variability by implementing a dense rain gauge network to validate spaceborne rainfall estimates. To optimize gauge location to a given set of criteria, a geographical information system (GIS) aided by a spatial decision support system (DSS) has been developed. A multicriteria decision analysis (MCDA) technique was developed to locate optimal sites in accordance to the guidelines defined by the World Meteorological Organization (WMO). A multicriteria analysis model for the optimization of prospective sites was applied to identify prime locations for the tipping-bucket rain gauges. The MCDA design required development of a spatial model by applying a series of linear programming methods, with the aid of spatial analytical techniques, in order to identify land sites that meet a particular set of criteria.