Characterization of Deltaic Channel Morphodynamics From Imagery Time Series Using the Channelized Response Variance

Abstract

River deltas are complex, dynamic systems whose channel networks evolve in response to internal and external forcings. To capture these changes, methods to extract and analyze deltaic morphodynamics automatically using available remotely sensed imagery and experimental observations are needed. Here, we apply a promising method for the automatic extraction of channel presence called RivaMap, on both synthetic and experimental data sets, to investigate the changes experienced by the system in response to five changes in forcings. RivaMap is an automated method to extract nonbinarized channel locations from imagery based on a singularity index that combines the multiscale first and second derivatives of the image intensity to favor the identification of curvilinear features and suppress edges. We quantify how the channelization varies by computing the channelized response variance (CRV), which we define as the variance of each pixel's singularity index response through time. We find that increasing magnitudes of sediment inflow (Qs) and water inflow (Qw) result in corresponding increases in the maximum CRV. We find that increasing the ratio of Qs to Qw results in increased number of channelized areas. We see that adding cohesion to the exposed sediment surface of the experimental delta results in decreased magnitude and decreased number of channelized areas in the CRV. Finally, by observing changes to the CRV over time, we are able to quantify the timescale of internal channel reorganization events as the experimental delta evolves under constant forcings.

Dominant process zones in a mixed fluvial–tidal delta are morphologically distinct

“…Other metrics such as the number of outlet channels have been affected by human modifications in a visible way but have not yet modified the PDF of the metric such that it is distinguishable from the PDF of the natural islands. The formation of new khas land and the siltation of channels in the inland tidal zone (Wilson et al, 2017;Jarriel et al, 2020) are thought to be related to poldering and thus human-induced modification of the tidal prism, but our cluster analysis also shows how infill of the channel network and amalgamation of young islands over time is an ongoing morphological change with maturation of the delta plain. Repeating this analysis on time series imagery of the GBMD with tools capable of quantifying change (Jarriel et al, 2019) provides additional information and points to the polder region as an area of change over the last 3 decades (Jarriel et al, 2020).…”

“…The formation of new khas land and the siltation of channels in the inland tidal zone (Wilson et al, 2017;Jarriel et al, 2020) are thought to be related to poldering and thus human-induced modification of the tidal prism, but our cluster analysis also shows how infill of the channel network and amalgamation of young islands over time is an ongoing morphological change with maturation of the delta plain. Repeating this analysis on time series imagery of the GBMD with tools capable of quantifying change (Jarriel et al, 2019) provides additional information and points to the polder region as an area of change over the last 3 decades (Jarriel et al, 2020). These changes may have not yet impacted the overall classification presented in this work; the question of what disturbance size affects the system as a whole is an important one which is yet to be addressed.…”

“…Because of the difficulty in extracting delta networks and the manual labor involved, studies up to now have analyzed metrics only in small systems or have focused on bulk metrics that do not capture how the characteristics of the delta may vary spatially and temporally. We expect that further development in automatic approaches for delta network extraction (Isikdogan et al, 2017b(Isikdogan et al, , 2018 and for the analysis of network change over time (Jarriel et al, 2019) will enable similar analyses at the global scale and over time. Hierarchical clustering of delta islands according to their common characteristics can also allow the identification of areas of the landscape that would be affected by different forecasted scenarios of future environmental conditions.…”

System wide channel network analysis reveals hotspots of morphological change in anthropogenically modified regions of the Ganges Delta

“…We then compute the Channelized Response Variance (CRV) on both the RivaMap imagery set of 30 images and the DeepWaterMap set of 30 images 35 . The CRV is a method that has been shown to quickly and accurately quantify temporal and spatial trends in channel variation from imagery by tracking changes to the channelized response through time 35 . To compute the CRV image, the RivaMap and DeepWaterMap images for each year are arranged in a time-ordered 3-D array and the variance is calculated for each pixel in the time dimension.…”

“…The extracted RivaMap and DeepWaterMap channel systems are then used to compute two Channelized Response Variance (CRV) maps. The CRV is a metric we developed to track channel morphodynamics and quantify the spatial and temporal distribution of channel change in delta systems through time 35 .…”