Kristen L. Underwood

Evaluating Spatial Variability in Sediment and Phosphorus Concentration‐Discharge Relationships Using Bayesian Inference and Self‐Organizing Maps

Given the variable biogeochemical, physical, and hydrological processes driving fluvial sediment and nutrient export, the water science and management communities need data-driven methods to identify regions prone to production and transport under variable hydrometeorological conditions. We use Bayesian analysis to segment concentration-discharge linear regression models for total suspended solids (TSS) and particulate and dissolved phosphorus (PP, DP) using 22 years of monitoring data from 18 Lake Champlain watersheds. Bayesian inference was leveraged to estimate segmented regression model parameters and identify threshold position. The identified threshold positions demonstrated a considerable range below and above the median discharge—which has been used previously as the default breakpoint in segmented regression models to discern differences between pre and post-threshold export regimes. We then applied a Self-Organizing Map (SOM), which partitioned the watersheds into clusters of TSS, PP, and DP export regimes using watershed characteristics, as well as Bayesian regression intercepts and slopes. A SOM defined two clusters of high-flux basins, one where PP flux was predominantly episodic and hydrologically driven; and another in which the sediment and nutrient sourcing and mobilization were more bimodal, resulting from both hydrologic processes at post-threshold discharges and reactive processes (e.g., nutrient cycling or lateral/vertical exchanges of fine sediment) at prethreshold discharges. A separate DP SOM defined two high-flux clusters exhibiting a bimodal concentration-discharge response, but driven by differing land use. Our novel framework shows promise as a tool with broad management application that provides insights into landscape drivers of riverine solute and sediment export.

Minimal East Antarctic Ice Sheet retreat onto land during the past eight million years

The East Antarctic Ice Sheet (EAIS) is the largest potential contributor to sea-level rise. However, efforts to predict the future evolution of the EAIS are hindered by uncertainty in how it responded to past warm periods, for example, during the Pliocene epoch (5.3 to 2.6 million years ago), when atmospheric carbon dioxide concentrations were last higher than 400 parts per million. Geological evidence indicates that some marine-based portions of the EAIS and the West Antarctic Ice Sheet retreated during parts of the Pliocene1,2, but it remains unclear whether ice grounded above sea level also experienced retreat. This uncertainty persists because global sea-level estimates for the Pliocene have large uncertainties and cannot be used to rule out substantial terrestrial ice loss3, and also because direct geological evidence bearing on past ice retreat on land is lacking. Here we show that land-based sectors of the EAIS that drain into the Ross Sea have been stable throughout the past eight million years. We base this conclusion on the extremely low concentrations of cosmogenic 10Be and 26Al isotopes found in quartz sand extracted from a land-proximal marine sediment core. This sediment had been eroded from the continent, and its low levels of cosmogenic nuclides indicate that it experienced only minimal exposure to cosmic radiation, suggesting that the sediment source regions were covered in ice. These findings indicate that atmospheric warming during the past eight million years was insufficient to cause widespread or long-lasting meltback of the EAIS margin onto land. We suggest that variations in Antarctic ice volume in response to the range of global temperatures experienced over this period—up to 2–3 degrees Celsius above preindustrial temperatures4, corresponding to future scenarios involving carbon dioxide concentrations of between 400 and 500 parts per million—were instead driven mostly by the retreat of marine ice margins, in agreement with the latest models5,6.Analysis of cosmogenic isotopes from a marine sediment core shows that much of the land-based East Antarctic Ice Sheet has remained stable for the past eight million years, including during the warm Pliocene epoch.

Bridging the climate information gap: a framework for engaging knowledge brokers and decision makers in state climate assessments

Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now engage in assessment processes to meet information needs for local authorities. The goals of state climate assessments (SCAs) should be to provide relevant, actionable information to state and local authorities, and to generate primary sources, build networks and inform stakeholders. To communicate local climate impacts to decision makers, SCAs should express credibility, salience and legitimacy. They can provide information (e.g., case studies, data sets) and connect stakeholders to the NCA and its process. Based on our experience in the Vermont Climate Assessment (VCA), we present a framework to engage decision makers in SCAs using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis and writing. The VCA addressed economic, environmental and social impacts of climate change at local scales to increase resiliency and manage risk. Knowledge brokers communicated VCA findings through their own stakeholder networks. We include a qualitative impact evaluation, and believe our framework for interaction among scientists, knowledge brokers and stakeholders to be an effective structure for SCAs and a transformative experience for students.

A Watershed Classification System using Hierarchical Artificial Neural Networks for Diagnosing Watershed Impairment at Multiple Scales

A hierarchical system of simple, geostatistical -based, artificial neural networks (ANNs) have been developed to enhance existing geographic information system (GIS)-based watershed management tools for diagnosing geomorphic instability at a variety of sub-basin and watershed scales. Two ANNs originally developed for the classification of reach -scale vulnerability and geomorphic condition have been tested (in concert with best judgment by experts) using existing data for two Vermont watersheds. These ANNs will support future development of modules to enhance land use management at the watershed scale to better predict geomorphic insta bility and sediment transport in response to natural and anthropogenic stresses.

Heuristic assessment of bridge scour sensitivity using differential evolution: case study for linking floodplain encroachment and bridge scour

BackgroundStakeholders are often required to make judgments and decisions about the tradeoffs between multiple competing objectives inherent in any engineering design. Design optimization can provide decision support for such situations, but often prescribes that only a single design solution be selected for a given set of preferences. The purpose of this study is to frame an objective function for assessing how the sensitivity of one objective relative to another varies in space and to demonstrate the method using a real site, with spatially-dependent floodplain access and bridge scour as the objective tradeoffs. Bridge scour is a widespread and expensive infrastructure problem, and the proposed methodology provides the ability to assess how the sensitivity of bridge scour to floodplain access varies at different locations in a river reach.ResultsThe site chosen for demonstration purposes was the Lewis Creek in the vicinity of the Quinlan Covered Bridge in Charlotte, VT. Differential evolution (DE) was wrapped around an existing HEC-RAS model. The decision variables corresponded to floodplain access at locations up and downstream of the bridge; the objective function was constructed so that optimal solutions may be interpreted as relative salience of floodplain access to bridge scour. Multiple weightings of the objectives were used to verify that the rank-order of locations was robust. The optimal DE solutions for all weightings resulted in the same sensitivity ranking of locations, providing evidence that the analysis is not dependent on a particular choice of stakeholder objective weightings.ConclusionsFor systems with spatially dependent variables that impact a constraint or objective of interest to stakeholders, a tool for identifying locations where that variable has a particularly strong or weak impact (e.g. where floodplain access is more or less important for bridge scour) has obvious advantages. This study demonstrates a method for conducting such a sensitivity analysis using a numerical optimization scheme. On the real test site, the sensitivity ranking was consistent across multiple stakeholder weightings, providing evidence that the technique is robust, and one that can be used at multiple stages of design. This work demonstrates the utility of a novel interpretation of optimization results in which locations are ranked according to the relative sensitivity of competing objectives.