Correlation of ERTS multispectral imagery with suspended matter and chlorophyll in lower Chesapeake Bay
ERTS multispectral imagery for suspensate surveying in Chesapeake Bay estuarine waters
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ERTS multispectral imagery for suspensate surveying in Chesapeake Bay estuarine waters
Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.
The author has identified the following significant results. An effort to relate water parameters of the lower Chesapeake Bay area to multispectral scanner images of LANDSAT 1 has shown that some spectral bands can be correlated to water parameters, and has demonstrated the feasibility of synoptic mapping of estuaries by satellite. Bands 5 and 6 were shown to be useful for monitoring total particles. Band 5 showed high correlation with suspended sediment concentration. Attenuation coefficients monitored continuously by ship along three baselines were cross correlated with radiance values on three days. Improved correlations resulted when tidal conditions were taken into consideration. A contouring program was developed to display sediment variation in the lower Chesapeake Bay from the MSS bands.
An experimental water penetration film and black and white near infrared film were used to study the distribution of submerged aquatic vegetation in the lower Chesapeake Bay. Detailed description of the grass beds was obtained by flying at an altitude of 5,000 feet, at low tide when wind conditions were minimal. Results show that there was a 36% reduction in the amount of submerged aquatic vegetation in the lower Chesapeake Bay from 1971 to 1974, the greatest losses occurring in the York, Piankatank and Rappahannock rivers (tabulated data is given). Recovery of some grass beds occurs primarily through seedling recruitment and subsequent vegetative growth. Cownose rays are suspected as a main factor for the decimation of some of the grass beds. Maps and photographs of the areas studied are given.
We combined detailed bio-optical measurements and radiative transfer (RT) modeling to perform an optical closure experiment for optically complex and biologically productive Chesapeake Bay waters. We used this experiment to evaluate certain assumptions commonly used when modeling bio-optical processes, and to investigate the relative importance of several optical characteristics needed to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater RT simulations. We found that the ratio of backscattering to total scattering in the mid-mesohaline Chesapeake Bay varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530 nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the RT model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between RT calculations and measured radiometric quantities. In situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near infrared wavelengths is zero.
The application of remote sensing in the Chesapeake Bay region has been a central concern of three project activities of the U.S. Geological Survey: two are developmental, and one is operational. The two developmental activities were experiments in land-use and land-cover inventory and change detection using remotely sensed data from aircraft and from the LANDSAT and Skylab satellites. One of these is CARETS (Central Atlantic Regional Ecological Test Site). The other developmental task is the Census Cities Experiment in Urban Change Detection. The present major concern is an operational land-use and land-cover data-analysis program, including a supporting geographical information system.
The results of the Chesapeake Bay plume study are reported. The role of remote sensing in monitoring and assessing the effects of pollution of marine resources is delineated.
For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover, impervious cover, winter cover) are being produced using well-established decision tree and regression tree algorithms. The goal of this session is to present the data products that we have been developing to the Bay science community and to discuss potential avenues for improvements and usage of the products for decision support.
The Chesapeake Bay plume was identified and plotted in relation to the presence and high concentrations of phytoplankton assemblages. Seasonal differences occurred within the plume during the collection period, with Skeletonema costatum and an ultraplankton component the dominant forms. Patchiness was found along the transects, with variations in composition and concentrations common on consecutive day sampling within the plume in its movement along the shelf. The presence of 236 species is noted, with their presence indicated for plume and shelf stations during the March, June, and October 1980 collections.
This study investigated the dynamic influence of the Chesapeake Bay (CB) on local ozone (O3) concentration and distribution using a weather forecasting model. The Weather Research and Forecasting model coupled with Chemistry (WRF–Chem) was employed to simulate O3 production and transportation near the CB. Baseline (water) as well as sensitivity (nowater) model experiments of bay circulation were carried out with and without bay water by changing the water surface from water to land (loam). First, the model performance simulating O3 was evaluated using the baseline experiment results and AirNow surface wind and O3 observations. The results showed that the model overestimates surface O3 by up to 20–30%. Further, the comparisons of the baseline and sensitivity experiments revealed higher O3 mixing ratios, primarily due to the resulting bay breeze circulation. These increases, after considering model overestimation, represent a mean bay dynamics circulation-induced contribution of up to 10% at night and 5% during the day. Furthermore, the boundary layer over northern CB, where it is at its narrowest width, was higher (by 1.2 km on average) during daytime due to higher surface temperatures observed. The boundary layer depth difference between the northern, central, and southern regions of the bay leads to a differential in the role of bay circulation dynamics in the observed O3 increase. The relatively wider swath of water surface over southern CB resulted in a lower boundary layer depth and stronger breeze circulation and this circulation contributed to O3 concentrations. Moreover, since the case selected has a minimal bay breeze circulation, the associated surface ozone enhancements represent what is expected at least at a minimum.
Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.
Proceedings of conference on remote sensing of resources contained in Chesapeake Bay to determine effects of environmental pollution
The Chesapeake Bay impact structure is the focus of an ongoing federal-state-local research program. Recent core drilling and geophysical surveys address the formative processes and hydrogeologic properties of this major "wet-target" impact. Additional information is contained in the original extended abstract.
In this study, the influence of sea-level rise (SLR) on seasonal hypoxia and phytoplankton production in Chesapeake Bay is investigated using a 3D unstructured grid model. Three SLR scenarios (0.17, 0.5, and 1.0 m) were conducted from 1991 to 1995. Results show that the summer hypoxic volume (HV) increases about 2%, 8%, and 16%, respectively, for these three scenarios, compared with Base Scenario. The contributions of physical and biological processes on the increase in the HV were analyzed. With the projected SLR, enhanced gravitational circulation transports more oxygen-rich water in the bottom layer from the mouth. However, the pycnocline moves upwards along with increasing water depth, which largely prolongs the time for dissolved oxygen (DO) to be transported to the bottom. The altered physical processes contribute greatly to a larger HV bay-wide. Besides, SLR increases the whole Bay phytoplankton production, with a larger increase in shallow areas (e.g., 53% in areas with depth <1 m under SLR of 0.5 m). Enhanced light availability is suggested to be the major driver of blooming phytoplankton under SLR in shallow areas. While increased DO production over the euphotic zone is mostly released to the atmosphere and transported downstream, the increase in settled organic matter greatly promotes DO consumption in the water column. The increased respiration is another major cause of the HV increase besides the physical contributions.
Water samples collected during the ERTS overpasses of the lower Chesapeake Bay area have been analyzed for chlorophyll, particles, and sediment. Five ERTS images were sufficiently cloud free that a correlation analysis of radiance values from the MSS bands with the water parameters could be performed. A low correlation was established for chlorophyll, except during algal blooms, when band 6 was responsive. There was a fair to good correlation with particles for combinations of band 5, particularly bands (5 minus 6). Sediment correlations were excellent for band 5 or combinations of band 5 with bands 4 and 6. It was evident that such factors as the atmosphere, tide, and different water masses were tending to confuse the data.
Use of remote sensing technology provided through the NASA/Wallops Chesapeake Bay Ecological Program was investigated by means of extensive interviews with users. Since the inception of the Program four years ago, the technology has been used in 136 different managerial projects. Sixty-five regional managerial agencies took part in projects that the authors categorized as socioeconomic, political/managerial, monetary, legal, and other. Remote sensing technology was considered successful in 88.6 percent of the completed projects and unsuccessful in 2.8 percent.
This paper examines in situ water quality datameasured during2020-2021in the Chesapeake Bay for comparison with optical satellite data. Thiscollection was performed as part of a NASA project aiming to develop new methods for water quality monitoring from satellite remote sensingusing artificial intelligence. Our objective is to use insitu data as ground-truth to provide water quality classifications, or labels,to their overlapping (in time and location)satellite imagery. Having such labeled data, can help us achieve our project’s longer-termgoal:to train artificial intelligencemodelsto recognize features in spectral informationfor monitoringwater qualityfrom satellites. Because routine monitoring by state agencies is conducted at discrete locations, we obtained a flow-through system operated from small boats to measure waterquality parameters along transects for comparison with two-dimensional maps collected from space, with an initial focus on low oxygenevents, due to their large spatial extent and regular occurrence each summer.We also evaluated similar in situ data collected during 1984-2021by the Chesapeake Program.
Natural and manmade gamma-ray emitting radionuclides were measured in Chesapeake Bay sediments taken near the Calvert Cliffs Nuclear Power Plant site. Samples represented several water depths, at six locations, for five dates encompassing a complete seasonal cycle. Radionuclide contents of dry sediments ranged as follows: Tl-208, 40 to 400 pCi/kg; Bi-214, 200 to 800 pCi/kg; K, 0.04 to 2.1 percent; Cs-137 5 to 1900 pCi/kg; Ru106, 40 to 1000 pCikg Co60, 1 to 27 pCi/kg. In general, radionuclide contents were positively correlated with each other and negatively correlated with sediment grain size.