Integration of Hydrological Simulations into the Design Process to Assess the Performance of Green Infrastructure Designs

With the growing threat of flooding in coastal and inland communities, it is necessary to migrate nature-based solutions such as green infrastructure. However, one of the challenges that designers face with this strategy lies in the design phase where it is difficult to quantify the performance with traditional design tools. Thus, there is an incentive to incorporate hydrological models within GIS to aid designers in quantifying performance. The goal of this research is to demonstrate that hydrological simulations can be used as a design tool for designers–such as landscape architects & architects– to analyze the feasibility of green infrastructure designs for flash flooding mitigation. The research will describe the methodology framework of the design process that includes the explanation of the process required to run the simulations on open-source software GRASS GIS’s models r.sim.water; as well as the workflow between GRASS GIS and 3D modeling software such as Rhinoceros 3D and Grasshopper. The framework includes data collection, data processing, design interventions, simulation, analysis, and how to incorporate the feedback from the simulations to optimize the green infrastructure design. The project will explain the methodology framework through a case study in the city of LaPlace, Louisiana that will focus on testing hydrologic performance of a green infrastructure design. The results of this study will provide a framework that can be replicated for any location in the world, helping communities transition more easily to green infrastructure strategies and improving their resilience to climate change.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-01
DOI
https://doi.org/10.5281/zenodo.15381439
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
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article

Integration of Hydrological Simulations into the Design Process to Assess the Performance of Green Infrastructure Designs

Zenodo (CERN European Organization for Nuclear Research)
Genetic and phenotypic traits in livestock
article

Integration of Hydrological Simulations into the Design Process to Assess the Performance of Green Infrastructure Designs

article en

Abstract

With the growing threat of flooding in coastal and inland communities, it is necessary to migrate nature-based solutions such as green infrastructure. However, one of the challenges that designers face with this strategy lies in the design phase where it is difficult to quantify the performance with traditional design tools. Thus, there is an incentive to incorporate hydrological models within GIS to aid designers in quantifying performance. The goal of this research is to demonstrate that hydrological simulations can be used as a design tool for designers–such as landscape architects & architects– to analyze the feasibility of green infrastructure designs for flash flooding mitigation. The research will describe the methodology framework of the design process that includes the explanation of the process required to run the simulations on open-source software GRASS GIS’s models r.sim.water; as well as the workflow between GRASS GIS and 3D modeling software such as Rhinoceros 3D and Grasshopper. The framework includes data collection, data processing, design interventions, simulation, analysis, and how to incorporate the feedback from the simulations to optimize the green infrastructure design. The project will explain the methodology framework through a case study in the city of LaPlace, Louisiana that will focus on testing hydrologic performance of a green infrastructure design. The results of this study will provide a framework that can be replicated for any location in the world, helping communities transition more easily to green infrastructure strategies and improving their resilience to climate change.

Zenodo (CERN European Organization for Nuclear Research)
Louisiana State University (US)
Openalex Percentile: Top 52%
Genetic and phenotypic traits in livestock
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