Geology topics

Research about Chesapeake Bay Watershed

Source-linked reports with geographic coverage including Chesapeake Bay Watershed.

24 records · Page 2Linked to original sources

USGS2012

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2010

Chesapeake bay watershed land cover data series

To better understand how the land is changing and to relate those changes to water quality trends, the USGS EGSC funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. EGSC will publish land change forecasts based on observed trends in the CBLCD over the coming year. They are in the process of interpreting and publishing statistics on the extent, type and patterns of land cover change for 1984-2006 in the Bay watershed, major tributaries and counties.

Chesapeake Bay Watershed↗

USGS2010

Expanded USGS science in the Chesapeake Bay restoration

In May 2009, the President issued Executive Order (EO) 13508 for Chesapeake Bay Protection and Restoration. For the first time since the creation of the Chesapeake Bay Program (CBP) in 1983, the full weight of the Federal Government will be used to address the challenges facing the Chesapeake Bay. The EO directs the U.S. Department of the Interior (DOI), represented by the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), and the U.S. Geological Survey (USGS), to expand its efforts and increase leadership to restore the Bay and its watershed. A Federal Leadership Committee (FLC) was established to ensure coordination of Federal activities and consult with states and stakeholders to align restoration efforts.

Chesapeake Bay Watershed↗

USGS2009

Sources, transport, and storage of sediment at selected sites in the Chesapeake Bay Watershed

The Chesapeake Bay Watershed covers 165,800 square kilometers and is supplied with water and sediment from five major physiographic provinces: Appalachian Plateau, Blue Ridge, Coastal Plain, Piedmont, and the Valley and Ridge. Suspended-sediment loads measured in the Chesapeake Bay Watershed showed that the Piedmont Physiographic Province has the highest rates of modern (20th Century) sediment yields, measured at U.S. Geological Survey streamflow-gaging stations, and the lowest rates of background or geologic rates of erosion (~10,000 years) measured with in situ beryllium-10. In the agricultural and urbanizing Little Conestoga Creek Watershed, a Piedmont watershed, sources of sediment using the 'sediment-fingerprinting' approach showed that streambanks were the most important source (63 percent), followed by cropland (37 percent). Cesium-137 inventories, which quantify erosion rates over a 40-year period, showed average cropland erosion of 19.39 megagrams per hectare per year in the Little Conestoga Creek Watershed. If this erosion rate is extrapolated to the 13 percent of the watershed that is in cropland, then cropland could contribute almost four times the measured suspended-sediment load transported out of the watershed (27,600 megagrams per hectare per year), indicating that much of the eroded sediment is being deposited in channel and upland storage. The Piedmont has had centuries of land-use change, from forest to agriculture, to suburban and urban areas, and in some areas, back to forest. These land-use changes mobilized a large percentage of sediment that was deposited in upland and channel storage, and behind thousands of mill dams. The effects of these land-use changes on erosion and sediment transport are still being observed today as stored sediment in streambanks is a source of sediment. Cropland is also an important source of sediment. The Coastal Plain Physiographic Province has had the lowest sediment yields in the 20th Century and with sandy soils, contributes little fine-grained sediment. In the agricultural Pocomoke River Watershed, a Coastal Plain watershed, cesium-137 mass-balance results indicate that erosion and deposition are both occurring on cropland fields. Sources of sediment using the sediment-fingerprinting approach for the Pocomoke River were distributed as follows: cropland (46 percent), ditch beds (34 percent), ditch banks and streambanks (7 percent), and forest (13 percent). Cropland was a source of sediment for the two largest peak flow events, which occurred during harvesting when the ground may have been bare. The Pocomoke River Watershed is heavily ditched and channelized, conditions that are favorable for ditch bed and bank erosion. In the mixed land use (forested, agricultural, and urbanizing) Mattawoman Creek Watershed, a Coastal Plain watershed, sources of sediment using the sediment-fingerprinting approach were distributed as follows: streambanks (30 percent), forest (29 percent), construction (25 percent), and cropland (17 percent). Mattawoman Creek Watershed drains a rapidly developing region with 182 hectares (approximately 1.26 percent of the watershed) under construction. Sediment from construction sites was also determined as a source of sediment in the Mattawoman Creek Watershed. The sediment-fingerprinting source results for the three watersheds analyzed, show that in all watersheds, both the stream corridor and agriculture were significant sources of sediment. Forest as a source of sediment in the Mattawoman Creek Watershed may indicate that these forests are being disturbed and forest soils are eroding. Bare ground can be an important sediment source. Spatial analysis of bare ground in the Little Conestoga Creek Watershed using satellite imagery between 2000 and 2005 showed that the majority of bare ground was classified as pasture. Bare ground was correlated to the growing season with the highest percentages occurring in the early spring (April, 34 percent) and a

Chesapeake Bay Watershed↗

USGS2007

Development of relations of stream stage to channel geometry and discharge for stream segments simulated with Hydrologic Simulation Program-Fortran (HSPF), Chesapeake Bay Watershed and adjacent parts of Virginia, Maryland, and Delaware

The U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), Chesapeake Bay Program (CBP), Interstate Commission for the Potomac River Basin (ICPRB), Maryland Department of the Environment (MDE), Virginia Department of Conservation and Recreation (VADCR), and University of Maryland (UMD) are collaborating to improve the resolution of the Chesapeake Bay Regional Watershed Model (CBRWM). This watershed model uses the Hydrologic Simulation Program-Fortran (HSPF) to simulate the fate and transport of nutrients and sediment throughout the Chesapeake Bay watershed and extended areas of Virginia, Maryland, and Delaware. Information from the CBRWM is used by the CBP and other watershed managers to assess the effectiveness of water-quality improvement efforts as well as guide future management activities. A critical step in the improvement of the CBRWM framework was the development of an HSPF function table (FTABLE) for each represented stream channel. The FTABLE is used to relate stage (water depth) in a particular stream channel to associated channel surface area, channel volume, and discharge (streamflow). The primary tool used to generate an FTABLE for each stream channel is the XSECT program, a computer program that requires nine input variables used to represent channel morphology. These input variables are reach length, upstream and downstream elevation, channel bottom width, channel bankfull width, channel bankfull stage, slope of the floodplain, and Manning's roughness coefficient for the channel and floodplain. For the purpose of this study, the nine input variables were grouped into three categories: channel geometry, Manning's roughness coefficient, and channel and floodplain slope. Values of channel geometry for every stream segment represented in CBRWM were obtained by first developing regional regression models that relate basin drainage area to observed values of bankfull width, bankfull depth, and bottom width at each of the 290 USGS streamflow-gaging stations included in the areal extent of the model. These regression models were developed on the basis of data from stations in four physiographic provinces (Appalachian Plateaus, Valley and Ridge, Piedmont, and Coastal Plain) and were used to predict channel geometry for all 738 stream segments in the modeled area from associated basin drainage area. Manning's roughness coefficient for the channel and floodplain was represented in the XSECT program in two forms. First, all available field-estimated values of roughness were compiled for gaging stations in each physiographic province. The median of field-estimated values of channel and floodplain roughness for each physiographic province was applied to all respective stream segments. The second representation of Manning's roughness coefficient was to allow roughness to vary with channel depth. Roughness was estimated at each gaging station for each 1-foot depth interval. Median values of roughness were calculated for each 1-foot depth interval for all stations in each physiographic province. Channel and floodplain slope were determined for every stream segment in CBRWM using the USGS National Elevation Dataset. Function tables were generated by the XSECT program using values of channel geometry, channel and floodplain roughness, and channel and floodplain slope. The FTABLEs for each of the 290 USGS streamflow-gaging stations were evaluated by comparing observed discharge to the XSECT-derived discharge. Function table stream discharge derived using depth-varying roughness was found to be more representative of and statistically indistinguishable from values of observed stream discharge. Additionally, results of regression analysis showed that XSECT-derived discharge accounted for approximately 90 percent of the variability associated with observed discharge in each of the four physiographic provinces. The results of this study indicate that the methodology developed to generate FTABLEs for every s

Chesapeake Bay Watershed↗

USGS2000

Effects of climate variability and human activities on Chesapeake Bay and the implications for ecosystem restoration

Chesapeake Bay, the Nation’s largest and most productive estuary (fig. 1), faces complex environmental issues related to nutrients and oxygen, turbidity and sedimentation, toxic dinoflagellates, sea-level rise, and coastal erosion. The Chesapeake Bay Program (CBP) is a partnership among the Chesapeake Bay Commission, the Federal Government, the District of Columbia, and the States of Maryland, Virginia, and Pennsylvania. The CBP is working to preserve, restore, and protect the bay’s living resources, vital habitats, and water quality, to protect human health, and to promote sound land-use policies in the watershed. The CBP began to set restoration goals for the ecosystem in the mid-1980’s and is now refining current goals and setting new ones as part of a new bay agreement— Chesapeake 2000. As the CBP sets restoration goals for the next 10–20 years, it will be critical to understand the long-term changes of the bay ecosystem due to climate variability and the influence of past and future human activities. For the past 4 years, the U.S. Geological Survey (USGS) has been engaged in research designed to provide objective scientific answers to questions about long-term changes in the bay ecosystem: What paleoecological and geochemical methods are best for documenting trends in the bay ecosystem? How does climate variability, including drought, affect the bay? What are historical trends in dissolved oxygen? What is the relationship between sedimentation and water clarity, and what is the effect of turbidity on living resources? How have past land-use changes affected bay habitats and living resources?

Chesapeake Bay Watershed↗