Salt marsh ecosystems are maintained by the dominant macrophytes that regulate the elevation of their habitat within a narrow portion of the intertidal zone by accumulating organic matter and trapping inorganic sediment. The long-term stability of these ecosystems is explained by interactions among sea level, land elevation, primary production, and sediment accretion that regulate the elevation of the sediment surface toward an equilibrium with mean sea level. We show here in a salt marsh that this equilibrium is adjusted upward by increased production of the salt marsh macrophyte Spartina alterniflora and downward by an increasing rate of relative sea-level rise (RSLR). Adjustments in marsh surface elevation are slow in comparison to interannual anomalies and long-period cycles of sea level, and this lag in sediment elevation results in significant variation in annual primary productivity. We describe a theoretical model that predicts that the system will be stable against changes in relative mean sea level when surface elevation is greater than what is optimal for primary production. When surface elevation is less than optimal, the system will be unstable. The model predicts that there is an optimal rate of RSLR at which the equilibrium elevation and depth of tidal flooding will be optimal for plant growth. However, the optimal rate of RSLR also represents an upper limit because at higher rates of RSLR the plant community cannot sustain an elevation that is within its range of tolerance. For estuaries with high sediment loading, such as those on the southeast coast of the United States, the limiting rate of RSLR was predicted to be at most 1.2 cm/yr, which is 3.5 times greater than the current, long-term rate of RSLR.

Salt marsh ecosystems are maintained by the dominant macrophytes that regulate the elevation of their habitat within a narrow portion of the intertidal zone by accumulating organic matter and trapping inorganic sediment. The long‐term stability of these ecosystems is explained by interactions among sea level, land elevation, primary production, and sediment accretion that regulate the elevation of the sediment surface toward an equilibrium with mean sea level. We show here in a salt marsh that this equilibrium is adjusted upward by increased production of the salt marsh macrophyte Spartina alterniflora and downward by an increasing rate of relative sea‐level rise (RSLR). Adjustments in marsh surface elevation are slow in comparison to interannual anomalies and long‐period cycles of sea level, and this lag in sediment elevation results in significant variation in annual primary productivity. We describe a theoretical model that predicts that the system will be stable against changes in relative mean sea level when surface elevation is greater than what is optimal for primary production. When surface elevation is less than optimal, the system will be unstable. The model predicts that there is an optimal rate of RSLR at which the equilibrium elevation and depth of tidal flooding will be optimal for plant growth. However, the optimal rate of RSLR also represents an upper limit because at higher rates of RSLR the plant community cannot sustain an elevation that is within its range of tolerance. For estuaries with high sediment loading, such as those on the southeast coast of the United States, the limiting rate of RSLR was predicted to be at most 1.2 cm/yr, which is 3.5 times greater than the current, long‐term rate of RSLR.

We compared 10 established and 2 new satellite reflectance algorithms 36 for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio 37 using coincident hyperspectral aircraft imagery and dense coincident surface 38 observations collected within one hour of image acquisition to develop simple 39 proxies for algal blooms in water bodies sensitive to algal blooms (especially toxic 40 or harmful algal blooms (HABs)) and to facilitate portability between multispectral 41 satellite imagers for regional algal bloom monitoring. All algorithms were 42 compared with narrow band hyperspectral aircraft images. These images were 43 subsequently upscaled spectrally and spatially to simulate 5 current and near future 44 satellite imaging systems. Established and new Chl-a algorithms were then applied 45 to the synthetic satellite images and compared to coincident surface observations of 46Chl-a collected from 44 sites within one hour of aircraft acquisition of the imagery. 47We found several promising algorithm/satellite imager combinations for routine 48Chl-a estimation in smaller inland water bodies with operational and near-future 49 satellite systems. The CI, MCI, FLH, NDCI, 2BDA and 3 BDA Chl-a algorithms 50 worked well with CASI imagery. The NDCI, 2BDA, and 3BDA Chl-a algorithms 51 worked well with simulated WorldView-2 and 3, Sentinel-2, and MERIS-like 52 imagery. NDCI was the most widely applicable Chl-a algorithm with good 53 performance for CASI, WorldView 2 and 3, Sentinel-2 and MERIS-like imagery 54 and limited performance with MODIS imagery. A new fluorescence line height 55 "greenness" algorithm yielded the best Chl-a estimates with simulated Landsat-8 56 imagery. 57 ARTICLE INFO 58 Article history: 59 Received ….. 60 Submission to Remote Sensing of Environment 3 Keywords: chorophyll-a, algal bloom, harmful algal bloom, algorithm, satellite, 61 hyperspectral, multispectral 62 63 64 65

The purpose of this investigation was to determine whether tree-core analysis could be used to delineate shallow groundwater contamination by chlorinated ethenes. Analysis of tree cores from bald cypress [Taxodium distichum (L.) Rich], tupelo (Nyssa aquatica L.), sweet gum (Liquidambar stryaciflua L.), oak (Quercus spp.), sycamore (Platanus occidentalis L.), and loblolly pine (Pinus taeda L.) growing over shallow groundwater contaminated with cis-1,2-dichloroethene (cDCE) and trichloroethene (TCE) showed that those compounds also were present in the trees. The cores were collected and analyzed by headspace gas chromatography. Bald cypress, tupelo, and loblolly pine contained the highest concentrations of TCE, with lesser amounts in nearby oak and sweet gum. The concentrations of cDCE and TCE in various trees appeared to reflect the configuration of the chlorinated-solvent groundwater contamination plume. Bald cypress cores collected along 18.6-m vertical transects of the same trunks showed that TCE concentrations decline by 30-70% with trunk height. The ability of the tested trees to take up cDCE and TCE make tree coring a potentially cost-effective and simple approach to optimizing well placement at this site.

Reservoirs are a globally significant source of methane (CH4), although most measurements have been made in tropical and boreal systems draining undeveloped watersheds. To assess the magnitude of CH4 emissions from reservoirs in midlatitude agricultural regions, we measured CH4 and carbon dioxide (CO2) emission rates from William H. Harsha Lake (Ohio, U.S.A.), an agricultural impacted reservoir, over a 13 month period. The reservoir was a strong source of CH4 throughout the year, emitting on average 176 ± 36 mg C m(-2) d(-1), the highest reservoir CH4 emissions profile documented in the United States to date. Contrary to our initial hypothesis, the largest CH4 emissions were during summer stratified conditions, not during fall turnover. The river-reservoir transition zone emitted CH4 at rates an order of magnitude higher than the rest of the reservoir, and total carbon emissions (i.e., CH4 + CO2) were also greater at the transition zone, indicating that the river delta supported greater carbon mineralization rates than elsewhere. Midlatitude agricultural impacted reservoirs may be a larger source of CH4 to the atmosphere than currently recognized, particularly if river deltas are consistent CH4 hot spots. We estimate that CH4 emissions from agricultural reservoirs could be a significant component of anthropogenic CH4 emissions in the U.S.A.

The objectives of this study were to elucidate spatial and temporal dynamics in source-specific Bacteroidales 16S rRNA genetic marker data across a watershed; to compare these dynamics to fecal indicator counts, general measurements of water quality, and climatic forces; and to identify geographic areas of intense exposure to specific sources of contamination. Samples were collected during a 2-year period in the Tillamook basin in Oregon at 30 sites along five river tributaries and in Tillamook Bay. We performed Bacteroidales PCR assays with general, ruminant-source-specific, and human-source-specific primers to identify fecal sources. We determined the Escherichia coli most probable number, temperature, turbidity, and 5-day precipitation. Climate and water quality data collectively supported a rainfall runoff pattern for microbial source input that mirrored the annual precipitation cycle. Fecal sources were statistically linked more closely to ruminants than to humans; there was a 40% greater probability of detecting a ruminant source marker than a human source marker across the basin. On a sample site basis, the addition of fecal source tracking data provided new information linking elevated fecal indicator bacterial loads to specific point and nonpoint sources of fecal pollution in the basin. Inconsistencies in E. coli and host-specific marker trends suggested that the factors that control the quantity of fecal indicators in the water column are different than the factors that influence the presence of Bacteroidales markers at specific times of the year. This may be important if fecal indicator counts are used as a criterion for source loading potential in receiving waters.

The storm water management model (SWMM) is a widely used tool for urban drainage design and planning. Hundreds of peerreviewed articles and conference proceedings have been written describing applications of SWMM. This review focuses on collecting information on model performance with respect to calibration and validation in the peer-reviewed literature. The major developmental history and applications of the model are also presented. The results provide utility to others looking for a quick reference to gauge the integrity of their own unique SWMM application. A gap analysis assesses the model's ability to perform water-quality simulations considering green infrastructure (GI)/low impact development (LID) designs and effectiveness. It is concluded that the level of detail underlying the conceptual model of SWMM versus its overall computational parsimony is well balanced-making it an adequate model for large and medium-scale hydrologic applications. However, embedding a new mechanistic algorithm or providing user guidance for coupling with other models will be necessary to realistically simulate diffuse pollutant sources, their fate and transport, and the effectiveness of GI/LID implementation scenarios.

Aquatic ecosystems are a globally significant source of nitrous oxide (N 2 O), a potent greenhouse gas, but estimates are largely based on studies conducted in streams and rivers with relatively less known about N 2 O dynamics in reservoirs. Due to long water residence times and high nitrogen (N) loading rates, reservoirs support substantial N processing and therefore may be particularly important sites of N 2 O production. Predicting N 2 O emissions from reservoirs is difficult due to complex interactions between microbial N processing in the oxygen-poor hypolimnion and oxygen-rich epilimnion. Here we present the results of a survey of N 2 O depth profiles in 20 reservoirs draining a broad range of land use conditions in four states in the U.S. Nitrous oxide was supersaturated in the epilimnion of 80% of the reservoirs and was undersaturated in only one, indicating that reservoirs in this region are generally a source of N 2 O to the atmosphere. Nitrous oxide was undersaturated in the hypolimnion of 10 reservoirs, supersaturated in 9, and transitioned from supersaturation to undersaturation in 1 reservoir that was monitored periodically from midsummer to fall. All reservoirs with a mean hypolimnion nitrate concentration less than 50 μg N L À1 showed evidence of net N 2 O consumption in the hypolimnion. All reservoirs sampled during lake turnover supported N 2 O production throughout the water column. These results indicate that N 2 O dynamics in reservoirs differ widely both among systems and through time but can be predicted based on N and oxygen availability and degree of thermal stratification.