Drainage network detection and assessment of network storage capacity in agrarian landscape
Version of Record online: 19 MAR 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Volume 27, Issue 4, pages 541–553, 15 February 2013
How to Cite
Cazorzi, F., Fontana, G. D., Luca, A. D., Sofia, G. and Tarolli, P. (2013), Drainage network detection and assessment of network storage capacity in agrarian landscape. Hydrol. Process., 27: 541–553. doi: 10.1002/hyp.9224
- Issue online: 23 JAN 2013
- Version of Record online: 19 MAR 2012
- Accepted manuscript online: 27 JAN 2012 01:36PM EST
- Manuscript Accepted: 13 JAN 2012
- Manuscript Received: 5 AUG 2011
- artificial drainage network;
- agrarian landscape;
- high resolution topography;
Drainage networks in agrarian landscape within floodplains constitute surface's discontinuities that are expected to affect hydrological response during floods. Drainage network recognition and quantification of water storage capacity within channels are, therefore, crucial for watershed planning and management. These evaluations require accurate spatial information for the area of interest and in most cases, when studying large catchments, broad datasets of ditches locations and descriptions are not available. In order to characterize drainage networks for large areas, the availability of high resolution topography derived by airborne laser scanner (LiDAR) represents a new and effective tool. Nowadays LiDAR DTMs covering large areas are readily available for public authorities, and there is a greater and more widespread interest in the application of such information for the development of automated methods aimed at solving geomorphological and hydrological problems. While LiDAR DTMs reliability in steep landscape has been proven by several recent studies, only few researches have been conducted to take into account the effectiveness of these data in agrarian low relief landscapes. The goal of this research is to propose a semi-automatic approach based on a LiDAR DTM to (1) detect drainage networks in agrarian/floodplain contexts, and (2) to estimate some of the network summary statistics (network length, width, drainage density and storage capacity). The procedure is applied in two typical alluvial-plain areas in the North East of Italy, and tested comparing automatically derived network with surveyed ones. The results underline the capability of high resolution DTMs for drainage network detection and characterization in the context of agrarian landscapes within floodplains, opening at the same time new challenges to evaluate some hydrological processes in these areas. Copyright © 2012 John Wiley & Sons, Ltd.