Monitoring of riparian vegetation response to flood disturbances using terrestrial photography

Flood disturbance is one of the major factors impacting riparian vegetation on river floodplains. In this study we use a high-resolution ground-based camera system with near-infrared sensitivity to quantify the immediate response of riparian vegetation in an Alpine, gravel bed, braided river to flood disturbance with the use of vegetation indices. Five large floods with return periods between 1.4 and 20.1 years in the period 2008–2011 in the Maggia River were analysed to evaluate patterns of vegetation response in three distinct floodplain units (main bar, secondary bar, transitional zone) and to compare the sensitivity of seven broadband vegetation indices. The results show both a negative (damage) and positive (enhancement) response of vegetation within 1 week following the floods, with a selective impact determined by pre-flood vegetation vigour, geomorphological setting and intensity of the flood forcing. The spatial distribution of vegetation damage provides a coherent picture of floodplain response in the three floodplain units. The vegetation indices tested in a riverine environment with highly variable surface wetness, high gravel reflectance, and extensive water–soil–vegetation contact zones differ in the direction of predicted change and its spatial distribution in the range 0.7–35.8%. We conclude that vegetation response to flood disturbance may be effectively monitored by terrestrial photography with near-infrared sensitivity, with potential for long-term assessment in river management and restoration projects.

[1]  F. Swanson,et al.  An Ecosystem Perspective of Riparian ZonesFocus on links between land and water , 1991 .

[2]  Steven J. Thomson,et al.  Determination of differences in crop injury from aerial application of glyphosate using vegetation indices , 2011 .

[3]  A. Viña,et al.  Comparison of different vegetation indices for the remote assessment of green leaf area index of crops , 2011 .

[4]  Chunhua Zhang,et al.  The application of small unmanned aerial systems for precision agriculture: a review , 2012, Precision Agriculture.

[5]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[6]  A. Huete,et al.  A Modified Soil Adjusted Vegetation Index , 1994 .

[7]  W. Bertoldi,et al.  The response of braided planform configuration to flow variations, bed reworking and vegetation: the case of the Tagliamento River, Italy , 2012 .

[8]  John R. Miller,et al.  Imaging chlorophyll fluorescence with an airborne narrow-band multispectral camera for vegetation stress detection , 2009 .

[9]  C. Field,et al.  Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types , 1995 .

[10]  N. Drake,et al.  The topographic signature of vegetation development along a braided river: Results of a combined analysis of airborne lidar, color air photographs, and ground measurements , 2011 .

[11]  Angela M. Gurnell,et al.  Trees as riparian engineers: the Tagliamento river, Italy , 2006 .

[12]  Robert J. Naiman,et al.  Dynamic patch mosaics and channel movement in an unconfined river valley of the Olympic Mountains , 2006 .

[13]  Hideki Kobayashi,et al.  In situ examination of the relationship between various vegetation indices and canopy phenology in an evergreen coniferous forest, Japan , 2012 .

[14]  Johannes Kollmann,et al.  The life history of Salicaceae living in the active zone of floodplains , 2002 .

[15]  R. Dunford,et al.  Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest , 2009 .

[16]  Tuqa Khalid,et al.  Monitoring Unmanned Aerial Vehicle , 2014 .

[17]  R. Jackson,et al.  Interpreting vegetation indices , 1991 .

[18]  Plant–water interactions , 1997 .

[19]  N. Drake,et al.  Interactions between river flows and colonizing vegetation on a braided river: exploring spatial and temporal dynamics in riparian vegetation cover using satellite data , 2011 .

[20]  Paolo Perona,et al.  Impact of floods on the statistical distribution of riverbed vegetation , 2013 .

[21]  Cliff R. Hupp,et al.  Hydrological and geomorphological impacts on riparian plant communities , 2000 .

[22]  R. Jacobson.  12.2 Riverine Habitat Dynamics , 2013 .

[23]  D. Lytle,et al.  Theory, methods and tools for determining environmental flows for riparian vegetation: riparian vegetation‐flow response guilds , 2010 .

[24]  E. Booth,et al.  Effects of changing channel morphology on vegetation, groundwater, and soil moisture regimes in groundwater-dependent ecosystems , 2011 .

[25]  S. G. Nelson,et al.  Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape , 2008, Sensors.

[26]  N. Polunin.  Aquatic ecosystems: trends and global prospects. , 2008 .

[27]  Andrew D. Richardson,et al.  Monitoring vegetation phenology using an infrared-enabled security camera , 2014 .

[28]  L. Ridolfi,et al.  Modelling river and riparian vegetation interactions and related importance for sustainable ecosystem management , 2009, Aquatic Sciences.

[29]  Mauricio Sánchez-Silva,et al.  Calibration of floodplain roughness and estimation of flood discharge based on tree-ring evidence and hydraulic modelling , 2011 .

[30]  F. Hauer,et al.  Strong effect of coarse surface layer on moisture within gravel bars: Results from an outdoor experiment , 2010 .

[31]  G. Birth,et al.  Measuring the Color of Growing Turf with a Reflectance Spectrophotometer1 , 1968 .

[32]  Alireza Sharifi,et al.  Comparison the accuracies of different spectral indices for estimation of vegetation cover fraction in sparse vegetated areas , 2011 .

[33]  P. Burlando,et al.  Effects of streamflow variability on the vertical root density distribution of willow cutting experiments , 2012 .

[34]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .

[35]  Nicholas C. Coops,et al.  Aerial Photography: A Rapidly Evolving Tool for Ecological Management , 2010 .

[36]  D. Beegle,et al.  Evaluating Multiple Indices from a Canopy Reflectance Sensor to Estimate Corn N Requirements , 2008 .

[37]  P. Burlando,et al.  Mechanisms of vegetation uprooting by flow in alluvial non-cohesive sediment , 2011 .

[38]  D. Mulla.  Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps , 2013 .

[39]  M. Vincini,et al.  A broad-band leaf chlorophyll vegetation index at the canopy scale , 2008, Precision Agriculture.

[40]  F. Baret,et al.  TSAVI: A Vegetation Index Which Minimizes Soil Brightness Effects On LAI And APAR Estimation , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.

[41]  I. Iorgulescu,et al.  Flooding tolerance of Central European tree and shrub species , 2006 .

[42]  T. T. Kozlowski,et al.  Acclimation and adaptive responses of woody plants to environmental stresses , 2002, The Botanical Review.

[43]  J. Webster,et al.  Patch Dynamics in Lotic Systems: The Stream as a Mosaic , 1988, Journal of the North American Benthological Society.

[44]  A. Gitelson,et al.  Use of a green channel in remote sensing of global vegetation from EOS- MODIS , 1996 .

[45]  B. Caruso,et al.  Invasive riparian vegetation response to flow regimes and flood pulses in a braided river floodplain. , 2013, Journal of environmental management.

[46]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[47]  O. Mutanga,et al.  Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review , 2010, Wetlands Ecology and Management.

[48]  G. Petts,et al.  Hydrology and ecology of river systems , 2011 .

[49]  Gregor T. Auble,et al.  Relating Riparian Vegetation to Present and Future Streamflows , 1994 .

[50]  Peter Molnar,et al.  Floodplain forest dynamics in a hydrologically altered mountain river , 2006 .

[51]  Michael A. Crimmins,et al.  Monitoring Plant Phenology Using Digital Repeat Photography , 2008, Environmental management.

[52]  H. Lichtenthaler.  Vegetation stress : an introduction to the stress concept in plants , 1996 .

[53]  H. Jones,et al.  Remote Sensing of Vegetation: Principles, Techniques, and Applications , 2010 .

[54]  K. Tockner,et al.  Riverine flood plains: present state and future trends , 2002, Environmental Conservation.

[55]  Mark A. Friedl,et al.  Digital repeat photography for phenological research in forest ecosystems , 2012 .

[56]  J. Friedman,et al.  Mortality of riparian box elder from sediment mobilization and extended inundation , 1999 .

[57]  S. Dufour,et al.  Image Utilisation for the Study and Management of Riparian Vegetation: Overview and Applications , 2012 .

[58]  C. Corona,et al.  Mass movements and tree rings: A guide to dendrogeomorphic field sampling and dating , 2013 .

[59]  A. Gillespie,et al.  Fluvial Remote Sensing for Science and Management: Carbonneau/Fluvial Remote Sensing for Science and Management , 2012 .

[60]  Andrew E. Suyker,et al.  An alternative method using digital cameras for continuous monitoring of crop status , 2012 .

[61]  Peter Molnar,et al.  An observation‐based stochastic model for sediment and vegetation dynamics in the floodplain of an Alpine braided river , 2009 .

[62]  Cyril Zipfel,et al.  Transgeneration memory of stress in plants , 2006, Nature.

[63]  Yuji Toda,et al.  Effects of Flood Flow on Flood Plain Soil and Riparian Vegetation in a Gravel River , 2005 .

[64]  D. Hollinger,et al.  Use of digital webcam images to track spring green-up in a deciduous broadleaf forest , 2007, Oecologia.

[65]  G. Bornette,et al.  Connectivity and biocomplexity in waterbodies of riverine floodplains , 2002 .

[66]  N. Coops,et al.  Monitoring plant condition and phenology using infrared sensitive consumer grade digital cameras , 2014 .

[67]  S. Eckert,et al.  Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data , 2013 .

[68]  Johnathan A. Napier,et al.  Stressful 'memories' of plants: evidence and possible mechanisms , 2007 .

[69]  Andrew D Richardson,et al.  Near-surface remote sensing of spatial and temporal variation in canopy phenology. , 2009, Ecological applications : a publication of the Ecological Society of America.

[70]  K. Walker,et al.  Tolerance of riverine plants to flooding and exposure indicated by water regime , 1999 .

[71]  M. Parsons,et al.  Patterns of vegetation greenness during flood, rain and dry resource states in a large, unconfined floodplain landscape , 2013 .

[72]  J. A. Schell,et al.  Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor] , 1973 .

[73]  Hella Ellen Ahrends,et al.  Quantitative phenological observations of a mixed beech forest in northern Switzerland with digital photography , 2008 .

[74]  Hervé Piégay,et al.  Fluvial remote sensing for science and management. , 2012 .

[75]  Klement Tockner,et al.  Aquatic Ecosystems: Flood plains: critically threatened ecosystems , 2008 .

[76]  Yeqiao Wang,et al.  Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects , 2009 .

[77]  Frederick J. Swanson,et al.  An Ecosystem Perspective of Riparian Zones , 2007 .

[78]  H. Décamps.  The renewal of floodplain forests along rivers: a landscape perspective , 1996 .

[79]  Kenlo Nishida Nasahara,et al.  The comparison of several colour indices for the photographic recording of canopy phenology of Fagus crenata Blume in eastern Japan , 2011 .

[80]  E. Tabacchi,et al.  Reciprocal interactions and adjustments between fluvial landforms and vegetation dynamics in river corridors: A review of complementary approaches , 2007 .

[81]  D. Lu,et al.  Change detection techniques , 2004 .

[82]  Glen L. Ritchie,et al.  Sensitivities of Normalized Difference Vegetation Index and a Green/Red Ratio Index to Cotton Ground Cover Fraction , 2010 .

[83]  D. Sims,et al.  Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features , 2003 .

[84]  Andreas Wombacher,et al.  Hydrodynamic model calibration from pattern recognition of non-orthorectified terrestrial photographs , 2014, Comput. Geosci..

[85]  Stuart R. Phinn,et al.  Mapping of riparian zone attributes using discrete return LiDAR, QuickBird and SPOT-5 imagery: Assessing accuracy and costs , 2010 .

[86]  D. Corenblit,et al.  Changing river channels: the roles of hydrological processes, plants and pioneer fluvial landforms in humid temperate, mixed load, gravel bed rivers. , 2012 .

[87]  C. Paola,et al.  Effects of vegetation on channel morphodynamics: results and insights from laboratory experiments , 2010 .

[88]  Laurent Barillé,et al.  Seasonal spectral variation of Zostera noltii and its influence on pigment-based Vegetation Indices , 2013 .

[89]  M. Schaepman,et al.  Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data , 2008 .

[90]  J. Bendix,et al.  Stream power influence on southern Californian riparian vegetation , 1999 .

[91]  P. Molnar,et al.  Biomass selection by floods and related timescales: Part 1. Experimental observations , 2012 .

[92]  C. Nilsson,et al.  Alterations of Riparian Ecosystems Caused by River Regulation , 2000 .