Geology topics

Matthew J. Cashman

Publications and source records attributed to Matthew J. Cashman.

28 records · Page 2Linked to original sources

USGS2022

Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States

Excessive sediment runoff as a result of anthropogenic activities is a major concern for watershed ecologic health. This study sought to determine the sources, storage, and delivery of sediment using a sediment budget approach for the predominantly pasture and forested Smith Creek watershed, Virginia United States, a tributary to the Chesapeake Bay. Utilizing a novel combination of the Universal Soil Loss Equation (USLE) model and an index of connectivity along with field surveys of channels, this study indicated that streambanks and pastures were major sources of sediment. Overestimation of fine-grained sediment flux exported from the watershed according to this study's models (3811 Mg/year) compared to export measured at the outlet (2918 Mg/year) most likely indicates underestimation of storage in the watershed from unaccounted for geomorphic features (ponds, toe slopes, and colluvial slopes). Sediment budget results indicating that streambanks are a major source of sediment in the watershed support previous sediment fingerprinting results and provide a framework for managers to address the sediment problem in Smith Creek and similar tributaries to the Chesapeake Bay.

Chesapeake Bay Watershed↗

USGS2022

Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA

Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healthy watersheds. To achieve these goals, resource managers need to better understand which stressors are most likely driving biological impairment. Our study addressed this knowledge gap through two approaches: 1) reviewing and synthesizing published multi-stressor studies, and 2) examining 303(d) listed impairments linked to biological impairment as identified by jurisdiction regulatory agencies (the states within the watershed and the District of Columbia). Results identified geomorphology (i.e., physical habitat), salinity, and toxic contaminants as important for explaining variability in benthic community metrics in the literature review. Geomorphology (i.e., physical habitat and sediment), salinity, and nutrients were the most reported stressors in the jurisdictional impairment analysis. Salinity is likely a major stressor in urban and mining settings, whereas geomorphology was commonly reported in agricultural settings. Toxic contaminants, such as pesticides, were rarely measured; more research is needed to quantify the extent of their effects in the region. Flow alteration was also highlighted as an important urban stressor in the literature review but was rarely measured in the literature or reported by jurisdictions as a cause of impairment. These results can be used to prioritize stressor monitoring by managers, and to improve stressor identification methods for identifying causes of biological impairment.

Chesapeake Bay Watershed↗

USGS2022

Using fish community and population indicators to assess the biological condition of streams and rivers of the Chesapeake Bay watershed, USA

The development of indicators to assess relative freshwater condition is critical for management and conservation. Predictive modeling can enhance the utility of indicators by providing estimates of condition for unsurveyed locations. Such approaches grant understanding of where “good” and “poor” conditions occur and provide insight into landscape contexts supporting such conditions. However, as assessments are conducted at large extents crossing jurisdictional boundaries, combined datasets are likely not suited for traditional assessment approaches which rely on jurisdictionally-specific reference sites. Here, we used a large dataset compiled from multiple providers to assess the condition of fish habitat for non-tidal streams and rivers in the Chesapeake Bay watershed (CBW), USA. We concurrently used community and species-level analyses to provide a more holistic view of habitat conditions by using random forest models to predict selected metrics and species occurrence with landscape data for inland CBW stream reaches. Community analyses included metrics describing composition, tolerances, habitat preferences, and functional traits of fish communities whereas species-level analyses consisted of distribution models for key sensitive and gamefish species. For community analyses, a final index was calculated as the average of selected metric deciles with higher scores inferring less biologically altered (i.e., better) conditions, providing an alternative to using reference sites. For species analyses, species occurrence was predicted for stream reaches, with presence indicating suitable habitat. Uncertainty was calculated for both approaches using model prediction intervals. Results indicated different numbers of suitable metrics for each region, with most in the Northern Appalachian (15) and least in the Southern Appalachian Piedmont (3). Four species (three sensitive) were suitable for modeling. At the CBW scale, predictions did not vary greatly among deciles for the community or species analyses for 2001, 2006, 2011, and 2016. Most stream reaches did not vary in mean decile rank or in species occurrence between 2001 and 2016; however, the largest community changes occurred in large rivers in the Coastal Plains ecoregion and the largest species occurrence changes occurred in Torrent Suckers in medium-sized rivers. When compared, results from community analyses agreed for one sensitive species (Brook Trout) but not the other three, potentially due to regionally inappropriate tolerance assignment. Comparisons also demonstrated substantial variation among approaches suggesting a lack of redundancy. While each approach traditionally has its targeted audience and respective strengths and weaknesses, concurrent use of these approaches permits direct comparisons and may assuage shortcomings of each approach when considered separately.

Chesapeake Bay watershed↗

USGS2022

Explainable machine learning improves interpretability in the predictive modeling of biological stream conditions in the Chesapeake Bay Watershed, USA

Anthropogenic alterations have resulted in widespread degradation of stream conditions. To aid in stream restoration and management, baseline estimates of conditions and improved explanation of factors driving their degradation are needed. We used random forests to model biological conditions using a benthic macroinvertebrate index of biotic integrity for small, non-tidal streams (upstream area ≤200 km 2 ) in the Chesapeake Bay watershed (CBW) of the mid-Atlantic coast of North America. We utilized several global and local model interpretation tools to improve average and site-specific model inferences, respectively. The model was used to predict condition for 95,867 individual catchments for eight periods (2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019). Predicted conditions were classified as Poor, FairGood, or Uncertain to align with management needs and individual reach lengths and catchment areas were summed by condition class for the CBW for each period. Global permutation and local Shapley importance values indicated percent of forest, development, and agriculture in upstream catchments had strong impacts on predictions. Development and agriculture negatively influenced stream condition for model average (partial dependence [PD] and accumulated local effect [ALE] plots) and local (individual condition expectation and Shapley value plots) levels. Friedman's H-statistic indicated large overall interactions for these three land covers, and bivariate global plots (PD and ALE) supported interactions among agriculture and development. Total stream length and catchment area predicted in FairGood conditions decreased then increased over the 19-years (length/area: 66.6/65.4% in 2001, 66.3/65.2% in 2011, and 66.6/65.4% in 2019). Examination of individual catchment predictions between 2001 and 2019 showed those predicted to have the largest decreases in condition had large increases in development; whereas catchments predicted to exhibit the largest increases in condition showed moderate increases in forest cover. Use of global and local interpretative methods together with watershed-wide and individual catchment predictions support conservation practitioners that need to identify widespread and localized patterns, especially acknowledging that management actions typically take place at individual-reach scales.

Chesapeake Bay Watershed↗

USGS2021

Channel response to a dam‐removal sediment pulse captured at high‐temporal resolution using routine gage data

In this study, we captured how a river channel responds to a sediment pulse originating from a dam removal using multiple lines of evidence derived from streamflow gages along the Patapsco River, Maryland, USA. Gages captured characteristics of the sediment pulse, including travel times of its leading edge (~7.8 km yr −1 ) and peak (~2.6 km yr −1 ) and suggest both translation and increasing dispersion. The pulse also changed local hydraulics and energy conditions, increasing flow velocities and Froude number, due to bed fining, homogenization and/or slope adjustment. Immediately downstream of the dam, recovery to pre‐pulse conditions occurred within the year, but farther downstream recovery was slower, with the tail of the sediment pulse working through the lower river by the end of the study 7 years later. The patterns and timing of channel change associated with the sediment pulse were not driven by large flow or suspended sediment‐transporting events, with change mostly occurring during lower flows. This suggests pulse mobility was controlled by process‐factors largely independent of high flow. In contrast, persistent changes occurred to out‐of‐channel flooding dynamics. Stage associated with flooding increased during the arrival of the sediment pulse, 1 to 2 years after dam removal, suggesting persistent sediment deposition at the channel margins and nearby floodplain. This resulted in National Weather Service‐indicated flood stages being attained by 3–43% smaller discharges compared to earlier in the study period. This study captured a two‐signal response from the sediment pulse: (1) short‐ to medium‐term (weeks to months) translation and dispersion within the channel, resulting in aggradation and recovery of bed elevations and changing local hydraulics; and (2) dispersion and persistent longer‐term (years) effects of sediment deposition on overbank surfaces. This study further demonstrated the utility of US Geological Survey gage data to quantify geomorphic change, increase temporal resolution, and provide insights into trajectories of change over varying spatial and temporal scales.

Maryland↗

USGS2021

Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed

Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km 2 . Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.

Chesapeake Bay watershed↗

USGS2021

Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape ( e.g ., elevation, longitude, latitude, geology) and land use ( i.e ., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality ( e.g ., total nitrogen and conductivity) and habitat ( e.g ., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species ( e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

Maryland↗

USGS2020

Sediment dynamics and implications for management: State of the science from long‐term research in the Chesapeake Bay watershed, USA

This review aims to synthesize the current knowledge of sediment dynamics using insights from long‐term research conducted in the watershed draining to the Chesapeake Bay, the largest estuary in the U.S., to inform management actions to restore the estuary and its watershed. The sediment dynamics of the Chesapeake are typical of many impaired watersheds and estuaries around the world, and this synthesis is intended to be relevant and transferable to other sediment‐impaired systems. The watershed's sediment sources, transport, delivery, and impacts are discussed with implications for effectively implementing best management practices (BMPs) to mitigate sediment issues. This synthesis revealed three key issues to consider when planning actions to reduce sediment loading: Scale, time, and land use. Geology and historical land use generated a template that current land use and climate, in addition to management, are acting upon to control sediment delivery. Important sediment sources in the Chesapeake include the Piedmont physiographic region, urban, and agricultural land use, and streambank erosion of headwater streams, whereas floodplain trapping is important along larger streams and rivers. Implementation of BMPs is widespread and is predicted to lead to decreased sediment loading; however, reworking of legacy sediment stored in stream valleys, with potentially long residence times in storage, can delay and complicate detection of the effects of BMPs on sediment loads. In conclusion, the improved understanding of sediment sources, storage areas, and transport lag times reviewed here can help target choices of BMP types and locations to better manage sediment problems—for both local streams and receiving waters.

New York, Pennsylvania, Maryland, Delaware, Virgin↗

USGS2018

Sediment source assessment using sediment fingerprints

Problem Sediment is one of the most common causes of loss of stream-biologic integrity, whether in suspension in the water column, or as deposition on a stream or lake bottom. Fine-grained silts and clays are of particular concern because they can degrade habitat and often carry phosphorus and (or) other contaminants harmful to humans and aquatic life. Sediment-impaired water bodies, usually identified by fair to poor macroinvertebrate index scores, are placed on the 303(d) list of impaired waters, where a sediment Total Maximum Daily Load (TMDL) is developed under the Clean Water Act ( https://www.epa.gov/tmdl ). In order to effectively manage sediment, it is necessary to identify the sediment sources and locations of “hot spots” of erosion and deposition.

Fact Sheet↗

USGS2018

Bank‐derived material dominates fluvial sediment in a suburban Chesapeake Bay watershed

Excess fine sediment is a leading cause of ecological degradation within the Chesapeake Bay watershed. To effectively target sediment mitigation measures, it is necessary to identify and quantify the delivery of sediment sources to local waterbodies. This study examines the contributions of sediment sources within Upper Difficult Run, a suburbanized watershed in Fairfax County, Virginia. A source sediment library was constructed from stream banks, forest soils, and road dust. Target sediments were collected from fine channel deposits and suspended sediment during 16 storm events from 2008 to 2012. Apportionment of targets to sources was performed using Sed_SAT, a publicly available toolkit for sediment fingerprinting. Bed sediment was dominated by stream bank material (mean: 98%), with minor contributions from forests (2%). Suspended fine sediments were also dominated by stream banks (suspended sediment concentration‐weighted mean: 91%), with minor contributions from roads (8%) and forests (<1%). Stream banks dominated at all discharges, and on the rising limb and at peak flow, sediment concentrations increased due to bank material rather than surface erosion. Sediment budget data indicated that direct bank erosion was insufficient to account for the suspended load derived from stream banks. However, bank‐derived sediment re‐mobilized from in‐channel storage could account for this difference and, combined, resulted in a sediment delivery ratio of 0.847 for all bank‐derived sediments. Results demonstrate that stream bank erosion is responsible for the majority of fine sediment in this suburban watershed of the Chesapeake Bay drainage area. Thus, management actions to control upland sources of sediment may have limited effect on the sediment conditions of Upper Difficult Run, whereas efforts focusing on bank stabilization, channel restoration, and/or stormwater management to reduce bank erosion may improve the ecological condition of these waterbodies.

Virginia↗