Int J Environ Res Public Health
June 2022
The study aimed to examine how changing land use conditions are related to the occurrence of heat waves. The employed methods were (1) the Urban Expansion Intensity Index (UEII) and the Green Expansion Intensity (GEII) for 49 cities in the U.S.
View Article and Find Full Text PDFThe amount and distribution of impervious surfaces are important input parameters of hydrological models, especially in highly urbanized basins. This study tests three different methods to input impervious surface area information to a semi-distributed hydrological model in order to examine their effects on storm flow. The three methods being evaluated include: (1) a constant value for impervious surfaces in the entire urban area, (2) constant values of imperviousness for commercial and residential land uses, respectively, and (3) different imperviousness for the residential land use in each subbasin.
View Article and Find Full Text PDFWe connected a cellular, dynamic, spatial urban growth model and a semi-distributed continuous hydrology model to quantitatively predict streamflow in response to possible future urban growth at a basin scale. The main goal was to demonstrate the utility of the approach for informing public planning policy and investment choices. The Hydrological Simulation Program-Fortran (HSPF) was set up and calibrated for the Kishwaukee River basin in the Midwestern USA and was repeatedly run with various land use scenarios generated either by the urban growth model (LEAMluc) or hypothetically.
View Article and Find Full Text PDFA land-use-change simulation model (LEAM) and a non-point-source (NPS) water quality model (L-THIA) were closely coupled as LEAMwq in order to determine the long-term implications of various degree of urbanization on NPS total nitrogen (TN), total suspended particles (TSP), and total phosphorus (TP) loads. A future land-use projection in the St. Louis metropolitan area from 2005 to 2030 using three economic growth scenarios (base, low, and high) and a long-term precipitation dataset were used to predict the mean annual surface runoff and mean annual NPS pollutant loads in the region.
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