Vegetation characteristics control local sediment and nutrient retention on but not underneath vegetation in floodplain meadows

Sediment and nutrient retention are essential ecosystem functions that floodplains provide and that improve river water quality. During floods, the floodplain vegetation retains sediment, which settles on plant surfaces and the soil underneath plants. Both sedimentation processes require that flow velocity is reduced, which may be caused by the topographic features and the vegetation structure of the floodplain. However, the relative importance of these two drivers and their key components have rarely been both quantified. In addition to topographic factors, we expect vegetation height and density, mean leaf size and pubescence, as well as species diversity of the floodplain vegetation to increase the floodplain’s capacity for sedimentation. To test this, we measured sediment and nutrients (carbon, nitrogen and phosphorus) both on the vegetation itself and on sediment traps underneath the vegetation after a flood at 24 sites along the River Mulde (Germany). Additionally, we measured biotic and topographic predictor variables. Sedimentation on the vegetation surface was positively driven by plant biomass and the height variation of the vegetation, and decreased with the hydrological distance (total R2 = 0.56). Sedimentation underneath the vegetation was not driven by any vegetation characteristics but decreased with hydrological distance (total R2 = 0.42). Carbon, nitrogen and phosphorus content in the sediment on the traps increased with the total amount of sediment (total R2 = 0.64, 0.62 and 0.84, respectively), while C, N and P on the vegetation additionally increased with hydrological distance (total R2 = 0.80, 0.79 and 0.92, respectively). This offers the potential to promote sediment and especially nutrient retention via vegetation management, such as adapted mowing. The pronounced signal of the hydrological distance to the river emphasises the importance of a laterally connected floodplain with abandoned meanders and morphological depressions. Our study improves our understanding of the locations where floodplain management has its most significant impact on sediment and nutrient retention to increase water purification processes.

Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning

Riverscapes are complex ecosystems consisting of dynamic processes influenced by spatially heterogeneous physical features. A critical component of riverscapes is vegetation in the stream channel and floodplain, which influences flooding and provides habitat. Riverscape vegetation can be highly variable in size and structure, including wetland plants, grasses, shrubs, and trees. This vegetation variability is difficult to precisely measure over large extents with traditional surveying tools. Drone laser scanning (DLS), or UAV-based lidar, has shown potential for measuring topography and vegetation over large extents at a high resolution but has yet to be used to quantify both the temporal and spatial variability of riverscape vegetation. Scans were performed on a reach of Stroubles Creek in Blacksburg, VA, USA six times between 2017 and 2019. Change was calculated both annually and seasonally over the two-year period. Metrics were derived from the lidar scans to represent different aspects of riverscape vegetation: height, roughness, and density. Vegetation was classified as scrub or tree based on the height above ground and 604 trees were manually identified in the riverscape, which grew on average by 0.74 m annually. Trees had greater annual growth and scrub had greater seasonal variability. Height and roughness were better measures of annual growth and density was a better measure of seasonal variability. The results demonstrate the advantage of repeat surveys with high-resolution DLS for detecting seasonal variability in the riverscape environment, including the growth and decay of floodplain vegetation, which is critical information for various hydraulic and ecological applications.

Using MODIS-NDVI Time Series to Quantify the Vegetation Responses to River Hydro-Geomorphology in the Wandering River Floodplain in an Arid Region

Vegetation, hydrology and geomorphology are three major elements of the floodplain ecosystem on Earth. Although the normalized difference vegetation index (NDVI) has been used extensively to characterize floodplain vegetation growth, vigour and biomass, methods for quantifying the various distinct responses of floodplain vegetation to hydro-geomorphological changes in different lateral belts in arid regions are still needed. In this study, the Linhe reach was divided into four lateral belts based on their hydro-geomorphological characteristics, and the Moderate Resolution Imaging Spectroradiometer (MODIS)-NDVI time series statistical indicators were used to characterise the distinct changing the patterns of vegetation growth in different belts. The response of floodplain vegetation to river hydro-geomorphology in each belt was analysed. The result showed that the average maximum NDVI value in the regular inundation area was 0.23 and higher than that in the other lateral belts. The correlation between the water persistence time and peak NDVI value in the regular water inundation area was significant (ρ = 0.84), indicating that in contrast to highly frequent or extremely rare water inundation, regular water inundation provides significant benefits to floodplains. Continuous or highly frequent inundation may cause decreased vegetation productivity. Overall, our results suggest that the vegetation greenness response to the river hydro-geomorphology is different from the river to the edge of the floodplain. Thus, a better understanding of the interactions between the floodplain vegetation and river hydro-morphology and river water resource management in arid-region floodplains.

Vegetation characteristics control sediment and nutrient retention on but not underneath vegetation in floodplain meadows

Sediment and nutrient retention are essential ecosystem functions that floodplains provide and that improve river water quality. During floods, the floodplain vegetation retains sediment, which settles on plant surfaces and the soil underneath plants. Both sedimentation processes require that flow velocity is reduced, which may be caused by the topographic features and the vegetation structure of the floodplain. However, the relative importance of these two drivers and their key components have rarely been both quantified. In addition to topographic factors, we expect vegetation height and density, mean leaf size and pubescence, as well as species diversity of the floodplain vegetation to increase the floodplain's capacity for sedimentation. To test this, we measured sediment and nutrients (carbon, nitrogen and phosphorus) both on the vegetation itself and on sediment traps underneath the vegetation after a flood at 24 sites along the River Mulde (Germany). Additionally, we measured biotic and topographic predictor variables. Sedimentation on the vegetation surface was positively driven by plant biomass and the height variation of the vegetation, and decreased with the hydrological distance (total R2=0.56). Sedimentation underneath the vegetation was not driven by any vegetation characteristics but decreased with hydrological distance (total R2=0.42). Carbon, nitrogen and phosphorus content in the sediment on the traps increased with the total amount of sediment (total R2=0.64, 0.62 and 0.84, respectively), while C, N and P on the vegetation additionally increased with hydrological distance (total R2=0.80, 0.79 and 0.92, respectively). This offers the potential to promote sediment and especially nutrient retention via vegetation management, such as adapted mowing. The pronounced signal of the hydrological distance to the river emphasises the importance of a laterally connected floodplain with abandoned meanders and morphological depressions. Our study improves our understanding of the locations where floodplain management has its most significant impact on sediment and nutrient retention to increase water purification processes.

High-resolution mapping of floodplain vegetation changes in large tropical rivers

<p>Tropical floodplain forests are among the most complex ecosystem on earth, featured by vegetation adapted to survive in seasonal flood environments. Although their ability to resist the periodic water level oscillations, recent studies have shown that riparian forests are extremely sensitive to long-term hydrological changes caused by both anthropogenic and natural disturbances. During the recent decades fragmentation and regulation of rivers induced severe alterations of natural “flood pulse” and sediment supply along the whole watercourse, causing massive tree mortality and compromising seeds spreading. The hydroclimatic anomalies of El Nino/Southern Oscillation (ENSO) and climate change impact on riparian environments, aggravating forest stress and vulnerability to fires, in cases of prolonged drought, while inducing tree mortality for anoxia, when a multi-year uninterrupted flood occurred.</p><p>In order to develop future solutions to mitigate the consequences of these disturbances and to enable a sustainable and effective management of riparian forests in the aquatic-terrestrial transitional zone (ATTZ), large-scale monitoring of these areas is necessary. Mapping and monitoring of floodplain vegetation are extremely important not only to assess vegetation status but also because vegetation represents an indicator for early signs of any physical or chemical environmental degradation. Remote sensing offers practical and efficient techniques to estimate biochemical and biophysical parameters and analyse their evolution over time even for very remote and poor accessible areas such as tropical floodplains. Nevertheless, as the main vegetation dynamics are in the narrow area at the interface terrestrial and aquatic systems, a high spatial and temporal resolution of the data is needed for their analysis. Furthermore, the extreme cloudiness of tropical regions contaminates the land surface observation causing gap in the data.</p><p>In the present study, we combine Landsat (30m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500m spatial resolution and daily revisit cycle), using HISTARFM algorithm, to reduce noise and produce monthly gap-free high-resolution (30 m) observations over land and the associated estimation of uncertainties. Subsequently, high resolution maps of normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were derived from the high-resolution gap free reflectance data. Furthermore, estimation of NDVI and EVI uncertainties was calculated through an error propagation analyses from uncertainties of reflectance estimates.</p><p>The framework we developed has been used to derive high resolution mapping of floodplain vegetation in the large tropical rivers that during the last decades experimented a hydrological regime transition. In a first-phase, vegetation dynamic analysis focused of the tropical large rivers in Amazonia and preliminary results of the temporal series will be presented.</p><p>The coupling of hydro-geomorphological and vegetation data enables the monitoring of riparian vegetation dynamics and a better understanding of the impact that the human footprint and climate change have on them.</p>