Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams
The spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations,...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-12-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/24/4183 |
id |
doaj-4b14bc03ab4544e295eac049d1bc57ef |
---|---|
record_format |
Article |
spelling |
doaj-4b14bc03ab4544e295eac049d1bc57ef2020-12-22T00:02:42ZengMDPI AGRemote Sensing2072-42922020-12-01124183418310.3390/rs12244183Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral StreamsEmmanouil Andreadakis0Michalis Diakakis1Emmanuel Vassilakis2Georgios Deligiannakis3Antonis Antoniadis4Petros Andriopoulos5Nafsika I. Spyrou6Efthymios I. Nikolopoulos7Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimioupoli Zografou, 15784 Athens, GreeceFaculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimioupoli Zografou, 15784 Athens, GreeceFaculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimioupoli Zografou, 15784 Athens, GreeceDepartment of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 11855 Athens, GreeceFaculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimioupoli Zografou, 15784 Athens, GreeceFaculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimioupoli Zografou, 15784 Athens, GreeceFaculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimioupoli Zografou, 15784 Athens, GreeceFlorida Institute of Technology, Department of Mechanical and Civil Engineering, Melbourne, FL 32901, USAThe spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations, aiming to improve our understanding of hydrological response dynamics under extreme meteorological forcing. However, discharge estimations are associated with demanding fieldwork aiming to record in small timeframes delicate data and data prone-to-be-lost and achieve the desired accuracy in measurements to minimize various uncertainties of the process. In this work, we explore the potential of unmanned aerial systems (UAS) technology, in combination with the Structure for Motion (SfM) and optical granulometry techniques in peak discharge estimations. We compare the results of the UAS-aided discharge estimations to estimates derived from differential Global Navigation Satellite System (d-GNSS) surveys and hydrologic modelling. The application in the catchment of the Soures torrent in Greece, after a catastrophic flood, shows that the UAS-aided method determined peak discharge with accuracy, providing very similar values compared to the ones estimated by the established traditional approach. The technique proved to be particularly effective, providing flexibility in terms of resources and timing, although there are certain limitations to its applicability, related mostly to the optical granulometry as well as the condition of the channel. The application highlighted important advantages and certain weaknesses of these emerging tools in indirect discharge estimations, which we discuss in detail.https://www.mdpi.com/2072-4292/12/24/4183UASstructure-from-motionflash flooddischarge estimationmanningphotogrammetry |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Emmanouil Andreadakis Michalis Diakakis Emmanuel Vassilakis Georgios Deligiannakis Antonis Antoniadis Petros Andriopoulos Nafsika I. Spyrou Efthymios I. Nikolopoulos |
spellingShingle |
Emmanouil Andreadakis Michalis Diakakis Emmanuel Vassilakis Georgios Deligiannakis Antonis Antoniadis Petros Andriopoulos Nafsika I. Spyrou Efthymios I. Nikolopoulos Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams Remote Sensing UAS structure-from-motion flash flood discharge estimation manning photogrammetry |
author_facet |
Emmanouil Andreadakis Michalis Diakakis Emmanuel Vassilakis Georgios Deligiannakis Antonis Antoniadis Petros Andriopoulos Nafsika I. Spyrou Efthymios I. Nikolopoulos |
author_sort |
Emmanouil Andreadakis |
title |
Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams |
title_short |
Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams |
title_full |
Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams |
title_fullStr |
Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams |
title_full_unstemmed |
Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams |
title_sort |
unmanned aerial systems-aided post-flood peak discharge estimation in ephemeral streams |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-12-01 |
description |
The spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations, aiming to improve our understanding of hydrological response dynamics under extreme meteorological forcing. However, discharge estimations are associated with demanding fieldwork aiming to record in small timeframes delicate data and data prone-to-be-lost and achieve the desired accuracy in measurements to minimize various uncertainties of the process. In this work, we explore the potential of unmanned aerial systems (UAS) technology, in combination with the Structure for Motion (SfM) and optical granulometry techniques in peak discharge estimations. We compare the results of the UAS-aided discharge estimations to estimates derived from differential Global Navigation Satellite System (d-GNSS) surveys and hydrologic modelling. The application in the catchment of the Soures torrent in Greece, after a catastrophic flood, shows that the UAS-aided method determined peak discharge with accuracy, providing very similar values compared to the ones estimated by the established traditional approach. The technique proved to be particularly effective, providing flexibility in terms of resources and timing, although there are certain limitations to its applicability, related mostly to the optical granulometry as well as the condition of the channel. The application highlighted important advantages and certain weaknesses of these emerging tools in indirect discharge estimations, which we discuss in detail. |
topic |
UAS structure-from-motion flash flood discharge estimation manning photogrammetry |
url |
https://www.mdpi.com/2072-4292/12/24/4183 |
work_keys_str_mv |
AT emmanouilandreadakis unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT michalisdiakakis unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT emmanuelvassilakis unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT georgiosdeligiannakis unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT antonisantoniadis unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT petrosandriopoulos unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT nafsikaispyrou unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams AT efthymiosinikolopoulos unmannedaerialsystemsaidedpostfloodpeakdischargeestimationinephemeralstreams |
_version_ |
1724374561715126272 |