The effectiveness of lowimpactdevelopment (LID) measures depends on the geology, topography, climate, and land use patterns in a watershed. Therefore, the planning, design, and implementation of LIDs must be perform...
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The effectiveness of lowimpactdevelopment (LID) measures depends on the geology, topography, climate, and land use patterns in a watershed. Therefore, the planning, design, and implementation of LIDs must be performed optimally by accounting for all the relevant characteristics of the watershed through adequate physical processbased modeling. This study integrates the Genetic Algorithm (GA) with a physics-based process modeling of LIDs using the Multi-Layer Green-Ampt infiltration (MLGA) method as a new attempt for determining optimal LID measures at river basin scales. The study also proposes a methodology for LID planning at large spatial scales that involves clustering sub-basins into hydrologically similar groups based on their physical characteristics. The results from the simulation-optimization framework indicated that the LID implementation percentages within hydrologically similar sub-basin groups fall in identical ranges. Thus, the optimal combination of LID measures obtained for a sub-basin could be applied over other hydrologically similar sub-basins in the same group, reducing the computational expenses required for river basin scale analyses and implementation planning. The impact of optimal LID combinations was demonstrated in the study for the river basins of Chennai in India for a 10-year design storm, and a maximum flood volume reduction of 38-82% and a peak reduction of 37-75% were obtained in the impervious areas of the basin. This study provides insight into the efficiency of LID measures at the river basin scale, which is essential for planning and implementing a sustainable urban drainage system.
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