Modeling of urban growth dynamics and its impact on surface runoff characteristics |
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| Affiliation: | 1. Department of Civil Engineering, NIT, Calicut 673 601, India;2. Department of Hydrology, IIT, Roorkee 247 667, India;3. HIKM, UNESCO-IHE, Delft, The Netherlands;1. Federal Institute for Forest, Snow and Landscape Research (WSL), Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland;2. Institute for Environmental Studies, Vrije Universiteit Amsterdam, de Boelelaan 1087, 1081HV Amsterdam, The Netherlands;3. School of GeoSciences, University of Edinburgh, Drummond Street, Edinburgh, UK;4. Global Academy of Agriculture and Food Security, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK;5. School of Geography and Development, University of Arizona, United States;6. Department of Geography, University of Alabama, Tuscaloosa, AL, United States;7. Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Garmisch-Partenkirchen, Germany;1. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;2. Huairou Eco-Environmental Observatory, Chinese Academy of Sciences, Beijing 101408, China;1. University of Florence, DISEI Dep. of Economics and Management, Italy;2. University of Basilicata, School of Engineering, Italy;3. University of California – Santa Barbara, USA;1. Environmental Geography Group, VU University Amsterdam, Amsterdam, The Netherlands;2. Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, the Netherlands;3. School of Natural Resources and Environment, University of Michigan, Ann Arbor, MI, USA;4. Research Institute for Knowledge Systems bv, Maastricht, The Netherlands;5. School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, Australia |
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| Abstract: | Modeling urban growth and generating scenarios are essential for studying the impact and sustainability of an urban hydrologic system. Urban systems are regarded as complex self-organizing systems, where the dynamic transitions from one form of landuse to another occur over a period of time. Therefore, a modeling framework that captures and simulates this complex behavior is essential for generating urban growth scenarios. Cellular Automata (CA)-based models have the potential to model such discrete dynamic systems. In this study, a constraint-based binary CA model was used to predict the future urban growth scenario of the city of Roorkee (India). A hydrologic model was applied on the simulated urban catchment to study its hydrologic response. The Natural Resources Conservation Service Curve Number (NRCS-CN) method, which is suitable for ungauged urban watersheds, was adopted to determine the impact of urban growth on the quantity of storm water runoff over a period of time. The results indicate that urban growth has a linear relationship with peak discharge and time to peak for the catchment under investigation. |
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| Keywords: | Urban growth Cellular automata NRCS-CN method Ungauged watersheds |
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