Daily Monitoring of Shallow and Fine-Grained Water Patterns in Wet Grasslands Combining Aerial LiDAR Data and In Situ Piezometric Measurements

Abstract

The real-time monitoring of hydrodynamics in wetlands at fine spatial and temporal scales is crucial for understanding ecological and hydrological processes. The key interest of light detection and ranging (LiDAR) data is its ability to accurately detect microtopography. However, how such data may account for subtle wetland flooding changes in both space and time still needs to be tested, even though the degree to which these changes impact biodiversity patterns is of upmost importance. This study assesses the use of 1 m × 1 m resolution aerial LiDAR data in combination with in situ piezometric measurements in order to predict the flooded areas at a daily scale along a one-year hydrological period. The simulation was applied over 663 ha of wet grasslands distributed on six sites across the Marais Poitevin (France). A set of seven remote sensing images was used as the reference data in order to validate the simulation and provide a high overall accuracy (76-94%). The best results were observed in areas where the ditch density was low, whereas the highly drained sites showed a discrepancy with the predicted flooded areas. The landscape proportion index was calculated for the daily steps. The results highlighted the spatiotemporal dynamics of the shallow flooded areas. We showed that the differences in the flooding durations among the years were mainly related to a narrow contrast in topography (40 cm), and occurred over a short period of time (two months).Sustainability 2018, 10, 708 2 of 16 address these challenges, data with both spatial fine-scale and intensive temporal resolutions for the flooding proxies are required.There have been recent advances in Earth observation technology, including improved spatial, temporal, spectral, and radiometric resolutions [7]; however, the monitoring of shallow and fine-grained water pattern dynamics is still limited by the trade-off between either high-resolution images or images with intensive repetition over time [8]. As an example, some studies have shown an interest in SAR (Synthetic Aperture Radar) time series for monitoring flooded areas in wetlands at a regional scale [9,10], while other studies have underlined an interest in single-date light detection and ranging (LiDAR) intensity [11] or multispectral data [12] for detecting fine-scale spatial patterns in the flooding of shallow waters.Earth observation data can be used to calibrate and develop flood models [13]. Topographic data are crucial for hydraulic modeling, particularly in wetlands where the topography affects water runoff [1]. Topographic data are also the most significant source of uncertainty [14]; consequently, the broad digital elevation model (DEM) derived from SAR data such as SRTM (Shuttle Radar Topography Mission), or, more recently, TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) are only appropriate for large-scale flood studies [8]. Conversely, LiDAR-based digital terrain models (DTM) provide high-resolution spatial information, and have been found to be suitable for the characteri...

Mapping grassland plant communities using a fuzzy approach to address floristic and spectral uncertainty

“…Specifically, the contribution of LiDAR DTM (+5% in overall accuracy) corroborates previous studies highlighting the strong relationship between plant community distribution and microtopography in wetlands (Alexander et al., ; Moeslund et al., ). It should be kept in mind, however, that this relationship can be biased locally by water management such as intensive drainage for agriculture or, conversely, water retention for conservation (Rapinel et al., ). Beyond 2‐D LiDAR variables, many studies (Zlinszky et al., , ) have also highlighted the contribution of 3‐D variables such as echo width, intensity response and surface roughness to accurately map grassland habitats (overall accuracy 62–68%, kappa index 0.57–0.64).…”

SAR analysis of wetland ecosystems: Effects of band frequency, polarization mode and acquisition dates

“…(Lanoé, 2008), (d) field photograph of a hygrophilic grassland with Cardamine pratensis plant species (white flowers) and (e) field photograph of a pond surrounded by Eleocharis palustris plant species (long-flooded grassland). SAR analysis of wetland ecosystems is particularly challenging given (i) the highly hydrodynamic nature of wetlands, with a flooded area that can change by several ha in a few days (Gallant 2015;Rapinel et al 2018), and (ii) the strong impact of water on the SAR impulse response of wetland vegetation (Cazals et al 2016;Mahdianpari, Salehi, Mohammadimanesh, and Brian Brisco 2017). Unfortunately, multi-sensor SAR data studies rarely considered the high spatiotemporal dynamics of wetland ecosystems.…”

Do highly anthropized hydrological conditions in marshes influence fish communities according to their life‐history strategies?

“…Two additional hydrological variables were calculated at the hydrological unit scale to describe the rate of water depth changes at the pivotal period in early spring, namely the coefficients of variation of water depth in March and in April. We also assessed the amount of temporary fish‐accessible aquatic habitats as expressed by the flooding duration (days) of at least 5% (a maximum water depth ranging from 6 to 21 cm depending on the hydrological unit) and at least 20% (a maximum water depth ranging from 14 to 44 cm) of the meadows in the whole hydrological unit (see Rapinel et al, 2018; Crabot et al, 2022 for a complete description of the calculation). We calculated these metrics at the hydrological unit scale because they better reflected the conditions experienced by fish before refuging in the largest canals in late spring.…”