Effects of Using Different Sources of Remote Sensing and Geographic Information System Data on Urban Stormwater 2D–1D Modeling

Yi Hong,Ghassan Chebbo,Bahman Soheilian,Céline Bonhomme

doi:10.3390/app7090904

Abstract

Remote sensing (RS) and geographic information system (GIS) data is increasingly used in urban stormwater modeling. The undirected use of such data may waste economic and human resources. In order to provide guidance for practitioners to efficiently use different data collection resources, as well as give a reference for future works, this paper aims to assess the effects of using free access GIS data and ad hoc RS data on urban 2D–1D stormwater modeling. The 2D-surface Two-dimensional Runoff, Erosion, and Export model (TREX) model was published in Science of the Total Environment in 2008. The 1D-sewer CANOE (Logiciel integre de conception et de diagnostic des reseaux d’assainissement) model was published in Journal of Hydrology in 2004. The two models are integrated in the TRENOE (TREX-CANOE) platform. The modeling approach is applied to a small urban catchment near Paris (Le Perreux sur Marne, 0.12 km2). Simulation results reveal that the detailed land-use information derived from multiple data sources is a crucial factor for accurate simulations. Nevertheless, using the very high resolution LiDAR (light detection and ranging) data is not equally significant for the water flow simulations at sewage outlets. Finally, we suggest that using the free access GIS data accompanying the urban sewer network design might be an acceptable low-cost solution for accurate urban 2D–1D stormwater modeling during moderate rainfall events. Further studies of urban stormwater modeling could focus on the development of “suitable” models with “enough” input data, depending on the management/research objectives.

Highlights

Over the past 10 years, the increasing availability of distributed remote sensing data has led to a sudden shift of hydrological modeling from data-sparse to data-rich research [1,2]
Four different types of remote sensing (RS) and geographic information system (GIS) data are applied to the modeling platform: (i) high resolution topographic data derived from lightdetection detection and ranging (LiDAR); (ii) low-resolution digital terrain model (DTM) data obtained from the free access database; (iii) detailed land-use data proceeded from multiple data sources; (iv) coarse land-use information extracted from the free access database
1D-Sewer TRENOE model was applied to a small urban catchment near Paris (Le Perreux sur Marne, 0.12 km2 )

Summary

Introduction

Over the past 10 years, the increasing availability of distributed remote sensing data has led to a sudden shift of hydrological modeling from data-sparse to data-rich research [1,2]. High-resolution topographic data and high resolution multi-view aerial images are accessible by using airborne laser altimetry of LiDAR (light detection and ranging), flood extent maps are achievable by using satellites’ synthetic aperture radar (SAR), accurate information on land-use is available by analyzing digital orthophotos. Such data sources allowed a significant breakthrough in urban spatially distributed modeling [3,4,5]. As for the operational modeling applications, the acquisition of such

Objectives

Methods

Results

Conclusion