Geology topics

Diana L. Karwan

Publications and source records attributed to Diana L. Karwan.

8 recordsLinked to original sources

USGS2025

Source and longevity of streambed sediment and phosphorus retention in a lake-plain tributary of the Maumee River

We described abundance and source of soft, fine-grained, streambed sediment and associated phosphorus (sed-P) during summer low flow in Little Flatrock Creek (LFR), a channelized tributary of the Maumee River and western Lake Erie. Reach-level assessments compared streambed-sediment storage to streambank erosion. Streambed sediment was fingerprinted and analyzed for sed-P and the potential for P de/sorption between the water column and streambed sediment. The ratio of two fallout radionuclides apportioned “new sediment” in streambed storage. Basin-wide streambed-sediment storage exceeded both annual streambank erosion and the annual suspended-sediment load. Streambed sediment was generally a mix of streambank and cropland sources and each equaled or exceeded abundance of new streambed sediment, indicating accumulation of sediment from both sources during the current agricultural cycle. The implication is that this mix of new and old sediment, and legacy P, takes multiple events and seasons to be transported downstream. Streambed sediment had the potential to adsorb dissolved P (DP) from the water column, with sed-P stored in the silt + clay fraction similar to the annual particulate-P (total-dissolved) load transported with suspended sediment, but with lower concentrations than cropland- and streambank-sourced sediment. This indicates supplementation of water-column DP as sediment settles to the bottom and a lag between land and channel management and in-channel P availability. Storage of fine-grained sediment and sed-P in this lake-plain/bed basin is distinct from another Maumee headwater tributary with glacial-moraine controlled geomorphology. The implication is that streambank erosion, in-channel sediment accumulation, and the resultant total-dissolved-sediment P spiral differ based on geomorphic setting and drainage history.

Indiana, Michigan, Ohio↗

USGS2024

Sediment budget of a Maumee River headwater tributary: How streambank erosion, streambed-sediment storage, and streambed-sediment source inform our understanding of legacy phosphorus

Objective We described source and phosphorus (P) retention potential of soft, fine-grained, streambed sediment and associated phosphorus (sed-P) during summer low-flow conditions. Combining in-channel, sed-P storage with relative age provided context on relevance to western Lake Erie Basin management goals. Methods In 2019, rapid geomorphic assessment (30 reaches) compared streambed-sediment storage (S) to streambank erosion (E), providing annual sediment budgets (S:E). Streambed sediment (13 reaches) was fingerprinted and analyzed for sed-P. The P saturation ratio (PSR; four reaches) quantified potential sorption/desorption of dissolved P (DP) between the water column and streambed sediment. Analyses were supplemented with data from 2017 and 2021. The ratio of two fallout radionuclides, beryllium-7 (54-day half-life) and excess lead-210 (22.3 years), apportioned “new” sediment based on time since rainfall contact. Results Streambed sediment was mostly streambank (54–96%) for contributing areas > 2.7 km 2 ; for upstream reaches, a larger percentage was apportioned as upland (cropland, pasture, forest, and road), with < 30% streambank. Streambank erosion correlated with contributing area; however, soil type (ecoregion), stream characteristics, and land use combined to drive streambed-sediment storage. Individual-reach S:E (accumulation of 0.01–35 years of streambank erosion) differentiated erosional and depositional in-channel environments. Most reaches indicated that 17–57% of sediment had recent contact with rainfall. Streambed-sediment PSR indicated a low potential for further sorption of DP from the water column; one reach was a P source when sampled. Conclusion Sed-P was higher in streambed sediment than in source samples, which varied by land use and ecoregion. This indicates homogenization resulting from in-stream sorption of DP during sediment transport that occurs over multiple events.

Indiana, Ohio↗

USGS2023

Importance of dense aquatic vegetation in seasonal phosphate and particle transport in an agricultural headwater stream

Agricultural headwater streams and ditches commonly host dense stands of aquatic vegetation that grow and decay over seasons and exert physical and biological controls on the transport of nutrients from cropland to larger rivers. This study examined changes in the transport of phosphorus (P) in an agricultural drainage ditch in the Maumee River Basin (Ohio, USA) by conducting constant rate injections of a novel tracer mixture (conservative salt [Cl as NaCl], dissolved P [KH 2 PO 4 ], and a fluorescent fine particle) in spring, summer, and fall. We quantified transport behavior for solutes and particles using a traditional transient storage modeling framework consisting of mobile and immobile storage zones connected by a first-order exchange rate constant. Transient storage was greatest during the spring, when thicker vegetation caused more pooling and flow stagnation, and decreased through fall, as vegetation thinned. Soluble P uptake lengths were 8.7 times longer in fall than spring, likely due to declines in biological uptake rates with colder temperatures and immobile zone storage with thinning vegetation. Particle capture lengths also decreased by a factor of 4.3 from fall to spring. With the increasing eutrophication of Lake Erie and waterbodies around the world that lie downstream from agricultural landscapes, it is beneficial to understand nutrient transport across watersheds, including small agricultural streams. This study highlights the physical and biological roles that aquatic vegetation plays in small agricultural streams by creating seasonally variable immobile zones that slow the flow of nutrients, providing surface area for biofilms, and capturing particles that bind nutrients.

Water Resources Research↗

USGS2023

How machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota

Understanding fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. However, fluvial sediment transport is difficult to understand because of the multitude of factors controlling the potential sources, delivery, mechanics, and storage of sediment in aquatic systems. While physical fluvial sediment samples are an integral part of developing solutions for these environmental concerns, samples cannot be collected at every river and time of interest. Therefore, accurate and cost-effective estimates of sediment loading are needed to manage riverine sediment transport at a multitude of scales (Ellison et al. 2016); also needed are methods to estimate sediment transport at sites where little or no physical samples have been collected (Gray & Simes 2008). The application of machine learning (ML) approaches to estimate sediment transport has grown over the past two decades (Afan et al. 2016). ML used in sediment transport research has shown multiple benefits over traditional approaches, such as increased prediction accuracy, the ability to learn complex linear and non-linear relations amongst the dataset and providing the ability to interpret these complex relations with important features used in the model (Cisty et al. 2021; Francke et al. 2008; Khan et al. 2021; Zounemat-Kermani et al. 2020; Cutler et al. 2007).

Minnesota↗

USGS2022

Using machine learning to improve predictions and provide insight into fluvial sediment transport

A thorough understanding of fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. Fluvial sediment samples are integral for addressing these environmental concerns but cannot be collected at every river and time of interest. Therefore, to gain a better understanding for rivers where direct measurements have not been made, extreme gradient boosting machine learning (ML) models were developed and trained to predict suspended sediment and bedload from sampling data collected in Minnesota, United States (U.S.), by the U.S. Geological Survey. Approximately 400 watershed (full upstream area), catchment (nearby landscape), near-channel, channel, and streamflow features were retrieved or developed from multiple sources, reduced to approximately 30 uncorrelated features, and used in the final ML models. The results indicate suspended sediment and bedload ML models explain approximately 70% of the variance in the datasets. Important features used in the models were interpreted with Shapley additive explanation (SHAP) plots, which provided insight into sediment transport processes. The most important features in the models were developed to normalize streamflow by the 2-year recurrence interval and quantify the rate of change in streamflow (slope), which helped account for sediment hysteresis. Generally, this study also showed a combination of mostly watershed and catchment geospatial features were important in ML models that predict sediment transport from physical samples. This study is a promising step forward in making fluvial sediment transport predictions using machine learning models trained by physically collected samples. The approach developed here can be used wherever similar datasets exists and will be useful for landscape and water management.

Minnesota↗

USGS2019

Tracking phosphorus and sediment sources and transport from fields and channels in Great Lakes Restoration Initiative priority watersheds

A multi-agency, integrated series of studies were initiated in 2017 under the Great Lakes Restoration Initiative (GLRI) by the U.S. Geological Survey, U.S. Forest Service, and the University of Minnesota to quantify the source, downstream travel time, and storage of particulate-bound phosphorus and sediment in agricultural tributaries to the Great Lakes. Of particular interest are contributions at the edge of field, channels, and riparian corridors. Results will be used to help identify upland and stream conservation practices that may reduce phosphorus and sediment inputs to the Great Lakes. The two study watersheds are the 50 km2 Black Creek in the Maumee River basin (Lake Erie) and the 90 km2 Plum Creek in the Lower Fox River basin (Lake Michigan). As part of other GLRI work, Black Creek and Plum Creek have existing, nested, edge-of-field studies in addition to phosphorus and sediment monitoring stations along their mainstems. Sediment-source tracking provides a direct method to quantify suspended sediment, and consequently phosphorus, sources by identifying a minimal set of properties (or fingerprint) that uniquely defines each source of sediment in the basin. This fingerprint can then be used to apportion sources of sediment from agricultural fields as well as other uplands including developed areas, forests, and pastures. These methods can also help distinguish sediment from ditches, ravines and eroding slopes, and streambanks. Multiple tracking methods are being used and adapted for best results in these watersheds, including a suite of trace elements for overall source apportionment in addition to short-term fallout radionuclides beryllium-7 (7Be) and lead-210 (210Pb) for high-flow event-based transport on fields and in stream channels. Tile drain connectivity to the surface is also of interest, especially in the Black Creek watershed. Preliminary results from the overall source apportionment from analyses of streambed sediment and monthly suspended sediment in Plum Creek indicate that the proportion attributed to different land cover varied by season and events. Further data analyses are being conducted for examining event-based pathways on individual fields, while most basin-wide sampling was monthly. Results from both watersheds will help describe the variations in transport of particulate-bound phosphorus across both steep and gentle landscapes representative of the Great Lakes basin. (this is from IP-101450)

Great Lakes↗

USGS2018

Before the storm: Antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events

While the influence of antecedent conditions on watershed function is widely recognized under typical hydrologic regimes, gaps remain in the context of extreme climate events (ECEs). ECEs are those events that far exceed seasonal norms of intensity, duration, or impact upon the physical environment or ecosystem. In this synthesis, we discuss the role of source availability and hydrologic connectivity on antecedent conditions and propose a conceptual framework to characterize system response to ECEs at the watershed scale. We present four case studies in detail that span a range of types of antecedent conditions and type of ECE to highlight important controls and feedbacks. Because ECEs have the potential to export large amounts of water and materials, their occurrence in sequence can disproportionately amplify the response. In fact, multiple events may not be considered extreme in isolation, but when they occur in close sequence they may lead to extreme responses in terms of both supply and transport capacity. Therefore, to advance our understanding of these complexities, we need continued development of a mechanistic understanding of how antecedent conditions set the stage for ECE response across multiple regions and climates, particularly since monitoring of these rare events is costly and difficult to obtain. Through focused monitoring of critical ecosystems during rare events we will also be able to extend and validate modeling studies. Cross-regional comparisons are also needed to define characteristics of resilient systems. These monitoring, modeling, and synthesis efforts are more critical than ever in light of changing climate regimes, intensification of human modifications of the landscape, and the disproportionate impact of ECEs in highly populated regions.

Biogeochemistry↗

USGS2014

Characteristic length scales and time-averaged transport velocities of suspended sediment in the mid-Atlantic Region, USA

Watershed Best Management Practices (BMPs) are often designed to reduce loading from particle-borne contaminants, but the temporal lag between BMP implementation and improvement in receiving water quality is difficult to assess because particles are only moved downstream episodically, resting for long periods in storage between transport events. A theory is developed that describes the downstream movement of suspended sediment particles accounting for the time particles spend in storage given sediment budget data (by grain size fraction) and information on particle transit times through storage reservoirs. The theory is used to define a suspended sediment transport length scale that describes how far particles are carried during transport events, and to estimate a downstream particle velocity that includes time spent in storage. At 5 upland watersheds of the mid-Atlantic region, transport length scales for silt-clay range from 4 to 60 km, while those for sand range from 0.4 to 113 km. Mean sediment velocities for silt-clay range from 0.0072 km/yr to 0.12 km/yr, while those for sand range from 0.0008 km/yr to 0.20 km/yr, 4–6 orders of magnitude slower than the velocity of water in the channel. These results suggest lag times of 100–1000 years between BMP implementation and effectiveness in receiving waters such as the Chesapeake Bay (where BMPs are located upstream of the characteristic transport length scale). Many particles likely travel much faster than these average values, so further research is needed to determine the complete distribution of suspended sediment velocities in real watersheds.

Maryland, Pennsylvania, Virginia↗