Paola Passalacqua

Automatic geomorphic feature extraction from lidar in flat and engineered landscapes

[1] High-resolution topographic data derived from light detection and ranging (lidar) technology enables detailed geomorphic observations to be made on spatially extensive areas in a way that was previously not possible. Availability of this data provides new opportunities to study the spatial organization of landscapes and channel network features, increase the accuracy of environmental transport models, and inform decisions for targeting conservation practices. However, with the opportunity of increased resolution topographic data come formidable challenges in terms of automatic geomorphic feature extraction, analysis, and interpretation. Low-relief landscapes are particularly challenging because topographic gradients are low, and in many places both the landscape and the channel network have been heavily modified by humans. This is especially true for agricultural landscapes, which dominate the midwestern United States. The goal of this work is to address several issues related to feature extraction in flat lands by using GeoNet, a recently developed method based on nonlinear multiscale filtering and geodesic optimization for automatic extraction of geomorphic features (channel heads and channel networks) from high-resolution topographic data. Here we test the ability of GeoNet to extract channel networks in flat and human-impacted landscapes using 3 m lidar data for the Le Sueur River Basin, a 2880 km 2 subbasin of the Minnesota River Basin. We propose a curvature analysis to differentiate between channels and manmade structures that are not part of the river network, such as roads and bridges. We document that Laplacian curvature more effectively distinguishes channels in flat, human-impacted landscapes compared with geometric curvature. In addition, we develop a method for performing automated channel morphometric analysis including extraction of cross sections, detection of bank locations, and identification of geomorphic bankfull water surface elevation. Using the slope plotted along each channel-floodplain cross section, we demonstrate the ability to identify and measure the height of river banks and bluffs. Finally, we present an example that demonstrates how extracting such features automatically is important for modeling channel evolution, water and sediment transport, and channel-floodplain sediment exchange.

GeoNet: An open source software for the automatic and objective extraction of channel heads, channel network, and channel morphology from high resolution topography data

Abstract Extracting hydrologic and geomorphic features from high resolution topography data is a challenging and computationally demanding task. We illustrate the new capabilities and features of GeoNet, an open source software for the extraction of channel heads, channel networks, and channel morphology from high resolution topography data. The method has been further developed and includes a median filtering operation to remove roads in engineered landscapes and the calculation of hillslope lengths to inform the channel head identification procedure. The software is now available in both MATLAB and Python, allowing it to handle datasets larger than the ones previously analyzed. We present the workflow of GeoNet using three different test cases; natural high relief, engineered low relief, and urban landscapes. We analyze default and user-defined parameters, provide guidance on setting parameter values, and discuss the parameter effect on the extraction results. Metrics on computational time versus dataset size are also presented. We show the ability of GeoNet to objectively and accurately extract channel features in terrains of various characteristics.

Quantifying the patterns and dynamics of river deltas under conditions of steady forcing and relative sea level rise

Understanding deltaic channel dynamics is essential to acquiring knowledge on how deltas respond to environmental changes, as channels control the distribution of water, sediment, and nutrients. Channel-resolving morphodynamic models provide the basis for quantitative study of channel-scale dynamics, but they need to be properly assessed with a set of robust metrics able to quantitatively characterize delta patterns and dynamics before being used as predictive tools. In this work we use metrics developed in the context of delta formation, to assess the morphodynamic results of DeltaRCM, a parcel-based cellular model for delta formation and evolution. By comparing model results to theoretical predictions and field and experimental observations, we show that DeltaRCM captures the geometric growth characteristics of deltas such as fractality of channel network, spatial distribution of wet and dry surfaces, and temporal dynamics of channel-scale processes such as the decay of channel planform correlation. After evaluating the ability of DeltaRCM to produce delta patterns and dynamics at the scale of channel processes, we use the model to predict the deltaic response to relative sea level rise (RSLR). We show that uniform subsidence and absolute sea level rise have similar effects on delta evolution and cause intensified channel branching. Channel network fractality and channel mobility increase with higher-RSLR rates, while the spatial and temporal scales of avulsion events decrease, resulting in smaller sand bodies in the stratigraphy. Our modeling results provide the first set of quantitative predictions of the effects of RSLR on river deltas with a specific focus on the distributary channel network.

Identifying environmental controls on the shoreline of a natural river delta

River deltas form where sediment-laden water debouches into a basin. The spatial delineation of a delta is nontrivial and yet is fundamental to systematically evaluating fluxes across its surface. Here we study shoreline dynamics of the Wax Lake Delta (WLD), a naturally developing delta, downstream of the Atchafalaya River, USA. We demonstrate the ability to extract hydrodynamic and morphodynamic shorelines from time series of satellite imagery and topography data, respectively. The hydrodynamic shoreline corresponds to the traditional dry-wet interface, whereas we introduce the concept of a morphodynamic shoreline demarcating the topset-foreset transition of a delta to quantitatively express the degree of inundation of a delta plain. These shorelines enable us to assess environmental controls on inundation of the WLD delta plain, noting the abundance of satellite imagery, whereas time series of bathymetric data from delta plains are scarce. From the analysis of NOAA and U.S. Geological Survey environmental data, we identify the effects of river discharge, tides, wind, and vegetation on shoreline position. In particular, using Delft3D simulations and a simplified momentum balance, we highlight the nonuniform and nonlinear effect of wind on delta plain inundation. Our analyses reveal that wind, riverine discharge, and tides significantly contribute to inundation of the WLD, and hence, incorporating their interaction is essential to the accurate modeling of hydrodynamics and ecodynamics of the WLD delta plain, as well as to the dynamic shape of delta plains in general.

Process connectivity in a naturally prograding river delta

River deltas are lowland systems that can display high hydrological connectivity. This connectivity can be structural (morphological connections), functional (control of fluxes), and process connectivity (information flow from system drivers to sinks). In this work, we quantify hydrological process connectivity in Wax Lake Delta, coastal Louisiana, by analyzing couplings among external drivers (discharge, tides, and wind) and water levels recorded at five islands and one channel over summer 2014. We quantify process connections with information theory, a branch of mathematics concerned with the communication of information. We represent process connections as a network; variables serve as network nodes and couplings as network links describing the strength, direction, and time scale of information flow. Comparing process connections at long (105 days) and short (10 days) time scales, we show that tides exhibit daily synchronization with water level, with decreasing strength from downstream to upstream, and that tides transfer information as tides transition from spring to neap. Discharge synchronizes with water level and the time scale of its information transfer compares well to physical travel times through the system, computed with a hydrodynamic model. Information transfer and physical transport show similar spatial patterns, although information transfer time scales are larger than physical travel times. Wind events associated with water level setup lead to increased process connectivity with highly variable information transfer time scales. We discuss the information theory results in the context of the hydrologic behavior of the delta, the role of vegetation as a connector/disconnector on islands, and the applicability of process networks as tools for delta modeling results.

Automatic Channel Network Extraction From Remotely Sensed Images by Singularity Analysis

The quantitative analysis of channel networks plays an important role in river studies. To provide a quantitative representation of channel networks, we propose anew method that extracts channels from remotely sensed images and estimates their widths. Our fully automated method is based on a recently proposed multiscale singularity index that strongly responds to curvilinear structures but weakly responds to edges. The algorithm produces a channel map using a single image where water and nonwater pixels have contrast, such as a Landsat near-infrared band image or a water index defined on multiple bands. The proposed method provides a robust alternative to the procedures that are used in the remote sensing of fluvial geomorphology and makes the classification and analysis of channel networks easier. The source code of the algorithm is available at http://live.ece.utexas. edu/research/cne/.

What controls the transition from confined to unconfined flow? : Analysis of hydraulics in a river delta

AbstractRecent field work at the Wax Lake Delta (WLD) in coastal Louisiana indicates lateral outflow from channels to islands upstream of the receiving basin; in this region of the delta the flow t...

Impact of tidal currents on delta-channel deepening, stratigraphic architecture, and sediment bypass beyond the shoreline

Deltas are sensitive indicators of coastal processes (e.g., waves and tides) and show dynamic changes in shoreline morphology, distributary channel network, and stratigraphic architecture in response to coastal forcing. Numerical modeling has long been used to show delta evolution associated with a single dominant coastal process, but rarely to examine the sensitivity of deltas to mixed processes. Physics-based morphodynamic simulations (Delft3D) are used to investigate the influence of tidal currents on deltas. Tidal amplitude and the sand:mud ratio of subsurface sediment have been varied in the model. The results show that increasing tidal amplitude causes deeper and more stable distributary channels and more rugose planform shoreline patterns. A new metric for channel geometry quantifies tidal influence on the distributary channel network. Stable distributary channels act as an efficient mechanism for ebb-enhanced currents to (1) bypass sediment across the delta plain, and (2) extend channel tips seaward through mouth bar erosion. The basinward channel extension leads to sandier deposits in the tide-influenced deltas than in their river-dominated counterparts. The delta-front bathymetry also reflects sediment redistribution, changing the delta-front profile from concave to convex with compound geometries as tidal amplitude increases. These results suggest that channel overdeepening is a possible tidal signature that should be considered when interpreting ancient systems, and that sand may be bypassed much farther basinward in tide-influenced than in purely river-dominated deltas.

How much subsidence is enough to change the morphology of river deltas

Understanding the effect of subsidence on fluviodeltaic morphology is important not only to maintain sustainable coastal cities and habitats but also to interpret the information contained in the stratigraphic record. While tectonic steering in alluvial environments has been investigated, similar studies in fluviodeltaic environments are limited to physical experiments and field observations. We perform numerical experiments with a parcel-based cellular model to analyze the deltaic surface and subsurface responses to regional subsidence. We quantify model results using robust metrics and show that while sediment partitioning and shoreline pattern vary gradually with increasing subsidence rate, channel mobility and stratigraphic connectivity of channel deposits show a threshold transition. Conditions for this transition are captured with a dimensionless filling index β, defined as the ratio between the rates of accommodation creation and sediment supply. A channel-locking mechanism activates when β exceeds 0.6 and is responsible for the threshold transition.

A dynamical system model of eco-geomorphic response to landslide disturbance

Vegetated landscapes form through the interactions of ecologic and geomorphic processes. These interactions are generally slow and steady, but they are occasionally the subject of abrupt disturbance. In humid uplands, for example, landslides episodically disrupt forest growth and regolith development, suddenly mobilize soil, regolith and bedrock, and facilitate runoff-driven erosion by abruptly removing canopy protection over a wide area. Here we model such an environment as a stochastically perturbed dynamical system whose simplified low dimensionality makes its eco-geomorphic interactions easier to explore and understand. The model captures some of the spatial variability across a catchment by treating an ensemble of subcatchments: in each, aggregated biomass and regolith coevolve as a two-dimensional dynamical system subject to episodic disturbance by slope failure. This coevolution gives rise to a notional stable equilibrium between regolith and biomass, but one that is not achieved in practice where landslide disturbance is significant. Instead, a catchment-scale, ensemble-average state arises in which higher storm frequency entails thinner regolith, less biomass, and weaker canopy protection against runoff erosion. The model makes the counter-intuitive prediction that, as rainfall-triggered landslides become more frequent, their contribution to the erosion of weathered bedrock will diminish as the role from storm runoff erosion rises. In some environments apparently dominated by landsliding, the model predicts that runoff erosion may be more important in the removal of regolith and fine sediment from hillslopes than mass wasting.