Technical Note: Advances in flash flood monitoring using UAVs

UAVs have the potential to capture information about the earth's surface in dangerous and previously inaccessible locations. Through image acquisition of flash flood events and subsequent object-based analysis, highly dynamic and oft- immeasurable hydraulic phenomenon may be quantified at previously unattainable spatial and temporal resolutions. The potential for this approach to provide valuable information about the hydraulic conditions present during dynamic, high-energy flash floods has until now not been explored. In this paper we adopt a novel approach, utilising the Kande-Lucas-Tomasi 10 (KLT) algorithm to track features present on the water surface which are related to the free-surface velocity. Following the successful tracking of features, a method analogous to the vector correction method has enabled accurate geometric rectification of velocity vectors. Uncertainties associated with the rectification process induced by unsteady camera movements are subsequently explored. Geo-registration errors are relatively stable and occur as a result of persistent residual distortion effects following image correction. The apparent ground movement of immobile control points between measurement intervals 15 ranges from 0.05 - 0.13m. The application of this approach to assess the hydraulic conditions present in Alyth Burn, Scotland during a 1:200 year flash flood resulted in the generation of an average 4.2 measurements m -2 at a rate of 508 measurements s -1 . Analysis of these vectors provide a rare insight into the complexity of channel-overbank interactions during flash floods. The uncertainty attached to the calculated velocities is relatively low with a spatial average across the area of ± 0.15m s -1 . Little difference is observed in the uncertainty attached to out-of-bank velocities (± 0.15m s -1 ), and within-channel velocities 20 (± 0.16m s -1 ), illustrating the consistency of the approach.

[1]  Mike Kirkby,et al.  Reconstructing flash flood magnitudes using ‘Structure-from-Motion’: A rapid assessment tool , 2014 .

[2]  Lee E. Brown,et al.  Major flood disturbance alters river ecosystem evolution , 2013 .

[3]  Louise J. Bracken,et al.  The concept of hydrological connectivity and its contribution to understanding runoff‐dominated geomorphic systems , 2007 .

[4]  B. Boudevillain,et al.  Multi-scale hydrometeorological observation and modelling for flash flood understanding , 2014 .

[5]  Jérôme Le Coz,et al.  Advantages of a mobile LSPIV method for measuring flood discharges and improving stage–discharge curves , 2011 .

[6]  Julian Simeonov,et al.  Calibrating discharge, bed friction, and datum bias in hydraulic models using water level and surface current observations , 2013 .

[7]  Steve Chien,et al.  Flood detection and monitoring with the Autonomous Sciencecraft Experiment onboard EO-1 , 2006 .

[8]  J. Ryan,et al.  UAV photogrammetry and structure from motion to assess calving dynamics at Store Glacier, a large outlet draining the Greenland ice sheet , 2015 .

[9]  Paul D. Bates,et al.  Floodplain friction parameterization in two‐dimensional river flood models using vegetation heights derived from airborne scanning laser altimetry , 2003 .

[10]  Chris Kilsby,et al.  Monitoring a flood event in a densely instrumented catchment, the Upper Eden, Cumbria, UK , 2006 .

[11]  Anton Kruger,et al.  Large-scale particle image velocimetry for flow analysis in hydraulic engineering applications , 1998 .

[12]  Wei Chen,et al.  River velocities from sequential multispectral remote sensing images , 2013 .

[13]  J. Travelletti,et al.  UAV-based remote sensing of the Super-Sauze landslide : evaluation and results. , 2012 .

[14]  Marian Muste,et al.  Large‐scale particle image velocimetry for measurements in riverine environments , 2008 .

[15]  Keith Beven,et al.  Spatial and temporal predictions of soil moisture dynamics, runoff, variable source areas and evapotranspiration for plynlimon, mid-wales. , 1993 .

[16]  Martin Beniston,et al.  Trends in joint quantiles of temperature and precipitation in Europe since 1901 and projected for 2100 , 2009 .

[17]  Aslak Grinsted,et al.  Image georectification and feature tracking toolbox: ImGRAFT , 2014 .

[18]  Matthew D. Wilson,et al.  Case Study of the Use of Remotely Sensed Data for Modeling Flood Inundation on the River Severn, U.K. , 2008 .

[19]  Witold F. Krajewski,et al.  Stream discharge using mobile large‐scale particle image velocimetry: A proof of concept , 2008 .

[20]  Luc Feyen,et al.  Correction to “Assessment of future flood hazard in Europe using a large ensemble of bias‐corrected regional climate simulations” , 2012 .

[21]  Michalis Zervakis,et al.  Feature analysis on river flow video data for floating tracers detection , 2014, 2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings.

[22]  A. Kääb,et al.  Motion detection using near-simultaneous satellite acquisitions , 2014 .

[23]  Koji Shiono,et al.  Discharge estimation in small irregular river using LSPIV , 2010 .

[24]  S. Doocy,et al.  The Human Impact of Tsunamis: a Historical Review of Events 1900-2009 and Systematic Literature Review , 2013, PLoS currents.

[25]  Eric Gaume,et al.  Post‐flood field investigations in upland catchments after major flash floods: proposal of a methodology and illustrations , 2008 .

[26]  Guillaume Dramais,et al.  Performance of image-based velocimetry (LSPIV) applied to flash-flood discharge measurements in Mediterranean rivers. , 2010 .

[27]  Ralf Ludwig,et al.  Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change. , 2012, The Science of the total environment.

[28]  Ichiro Fujita,et al.  Application of aerial LSPIV to the 2002 flood of the Yodo River using a helicopter mounted high density video camera , 2011 .

[29]  Eric Gaume,et al.  Hydrological analysis of a flash flood across a climatic and geologic gradient: The September 18, 2007 event in Western Slovenia , 2010 .

[30]  Alan Jenkins,et al.  Isotope hydrology of the Allt a' Mharcaidh catchment, Cairngorms, Scotland : implications for hydrological pathways and residence times , 2000 .

[31]  Richard D. Robarts,et al.  Time for in situ renaissance , 2015, Science.

[32]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[33]  R. Bechini,et al.  Influence of rainfall and soil properties spatial aggregation on extreme flash flood response modelling: An evaluation based on the Sesia river basin, North Western Italy , 2009 .

[34]  André Paquier,et al.  Application and evaluation of LS-PIV technique for the monitoring of river surface velocities in high flow conditions , 2008 .

[35]  Maurizio Porfiri,et al.  Development and Testing of an Unmanned Aerial Vehicle for Large Scale Particle Image Velocimetry , 2014, HRI 2014.

[36]  R. Fletcher A modified Marquardt subroutine for non-linear least squares , 1971 .

[37]  Hélène Roux,et al.  Analysis of flash flood-triggering rainfall for a process-oriented hydrological model , 2014 .

[38]  Anton Schleiss,et al.  Flow field investigation in a rectangular shallow reservoir using UVP, LSPIV and numerical modelling , 2008 .

[39]  Volker Weitbrecht,et al.  A low-cost airborne velocimetry system: proof of concept , 2015 .

[40]  Florian Pappenberger,et al.  Deriving distributed roughness values from satellite radar data for flood inundation modelling , 2007 .

[41]  Maurizio Porfiri,et al.  Large-Scale Particle Image Velocimetry From an Unmanned Aerial Vehicle , 2015, IEEE/ASME Transactions on Mechatronics.

[42]  Alberto Refice,et al.  SAR and InSAR for Flood Monitoring: Examples With COSMO-SkyMed Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[43]  Jérôme Le Coz,et al.  Gauging extreme floods on YouTube: application of LSPIV to home movies for the post‐event determination of stream discharges , 2016 .

[44]  L. Feyen,et al.  Assessment of future flood hazard in Europe using a large ensemble of bias-corrected regional climat , 2012 .

[45]  Eric Gaume,et al.  Surveying flash floods: gauging the ungauged extremes , 2008 .

[46]  S. Doocy,et al.  The Human Impact of Floods: a Historical Review of Events 1980-2009 and Systematic Literature Review , 2013, PLoS currents.

[47]  F. Schwartz,et al.  Discharge and water‐depth estimates for ungauged rivers: Combining hydrologic, hydraulic, and inverse modeling with stage and water‐area measurements from satellites , 2015 .

[48]  Doerthe Tetzlaff,et al.  Catchment data for process conceptualization: simply not enough? , 2008 .

[49]  Sandro Martinis,et al.  Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data , 2009 .

[50]  David M. Admiraal,et al.  Case Study: Particle Velocimetry in a Model of Lake Ogallala , 2004 .

[51]  Andrea Petroselli,et al.  Assessment of drone-based surface flow observations , 2016 .

[52]  Witold F. Krajewski,et al.  Experimental System for Real-Time Discharge Estimation Using an Image-Based Method , 2008 .

[53]  Joseph Calantoni,et al.  Quantifying riverine surface currents from time sequences of thermal infrared imagery , 2012 .

[54]  Bruce L. Rhoads,et al.  Resolving two‐dimensional flow structure in rivers using large‐scale particle image velocimetry: An example from a stream confluence , 2015 .