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  1. Free, publicly-accessible full text available August 1, 2024
  2. Whalen, Joann (Ed.)
    Abstract

    Residential landscapes are essential to the sustainability of large areas of the United States. However, spatial and temporal variation across multiple domains complicates developing policies to balance these systems’ environmental, economic, and equity dimensions. We conducted multidisciplinary studies in the Baltimore, MD, USA, metropolitan area to identify locations (hotspots) or times (hot moments) with a disproportionate influence on nitrogen export, a widespread environmental concern. Results showed high variation in the inherent vulnerability/sensitivity of individual parcels to cause environmental damage and in the knowledge and practices of individual managers. To the extent that hotspots are the result of management choices by homeowners, there are straightforward approaches to improve outcomes, e.g. fertilizer restrictions and incentives to reduce fertilizer use. If, however, hotspots arise from the configuration and inherent characteristics of parcels and neighborhoods, efforts to improve outcomes may involve more intensive and complex interventions, such as conversion to alternative ecosystem types.

     
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    Free, publicly-accessible full text available September 29, 2024
  3. Abstract

    Stream restoration is widely used to mitigate the degradation of urban stream channels, protect infrastructure, and reduce sediment and nutrient loadings to receiving waterbodies. Stabilizing and revegetating riparian areas can also provide recreational opportunities and amenities, and improve quality of life for nearby residents. In this project, we developed indices of an environmental benefit (potential nitrate load reduction, a priority in the Chesapeake Bay watershed) and economic benefit (household willingness to pay, WTP) of stream restoration for all low order stream reaches in three main watersheds in the Baltimore metro region. We found spatial asynchrony of these benefits such that their spatial patterns were negatively correlated. Stream restoration in denser urban, less wealthy neighborhoods have high WTP, but low potential nitrate load reduction, while suburban and exurban, wealthy neighborhoods have the reverse trend. The spatial asynchrony raises challenges for decision makers to balance economic efficiency, social equity, and specific environmental goals of stream restoration programs.

     
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  4. null (Ed.)
  5. Abstract

    Synoptic sampling of streams is an inexpensive way to gain insight into the spatial distribution of dissolved constituents in the subsurface critical zone. Few spatial synoptics have focused on urban watersheds although this approach is useful in urban areas where monitoring wells are uncommon. Baseflow stream sampling was used to quantify spatial variability of water chemistry in a highly developed Piedmont watershed in suburban Baltimore, MD having no permitted point discharges. Six synoptic surveys were conducted from 2014 to 2016 after an average of 10 days of no rain, when stream discharge was composed of baseflow from groundwater. Samples collected every 50 m over 5 km were analyzed for nitrate, sulfate, chloride, fluoride, and water stable isotopes. Longitudinal spatial patterns differed across constituents for each survey, but the pattern for each constituent varied little across synoptics. Results suggest a spatially heterogeneous, three‐dimensional pattern of localized groundwater contaminant zones steadily contributing solutes to the stream network, where high concentrations result from current and legacy land use practices. By contrast, observations from 35 point piezometers indicate that sparse groundwater measurements are not a good predictor of baseflow stream chemistry in this geologic setting. Cross‐covariance analysis of stream solute concentrations with groundwater model/backward particle tracking results suggest that spatial changes in base‐flow solute concentrations are associated with urban features such as impervious surface area, fill, and leaking potable water and sanitary sewer pipes. Predicted subsurface residence times suggest that legacy solute sources drive baseflow stream chemistry in the urban critical zone.

     
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  6. Abstract

    Nonpoint source urban nutrient loading into streams and receiving water bodies is widely recognized as a major environmental management challenge. A dominant research and management paradigm assumes that loading primarily derives from elevated stormwater. However, baseflow can account for a large portion of total loading, especially for low development intensity watersheds which comprise the largest urban areas. We investigated the sources and drivers of nonpoint source baseflow nitrogen loading across 27 headwater catchments in the urbanized Piedmont region of North Carolina, USA. Nitrate isotopes, predictors of concentration‐discharge (CQ) slopes, and predictors of mean annual total dissolved nitrogen (TDN) loading suggest that wastewater was a major baseflow nonpoint source of nitrogen across developed catchments likely contributing 61% of nitrate loading from septic served catchments and 49% from sewer served catchments. Our findings suggest that subsurface TDN was abundant, loading was largely transport limited, and the hydrogeomorphic position of sanitary infrastructure strongly influences transport. We developed an empirical model showing catchment loading increased with the topographic wetness index of sanitary sewer location, convergent sloping land area, parcel density, and residual agricultural landcover (R2 = 0.78). We extended this model to the study region's 1,436 developed small (0.3–20.8 sq km) catchments. We estimated up to 92.7% of nonpoint source baseflow TDN loading comes from low and medium development intensity catchments, and sanitary infrastructure in wet areas of the landscape accounts for 39% of regional baseflow loading. Our research indicates that managing baseflow loading will require addressing lower development intensity catchments and sanitary infrastructure.

     
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  7. Abstract

    The spatial variation of soil moisture over very small areas (<100 m2) can have nonlinear impacts on cycling and flux rates resulting in bias if it is not considered, but measuring this variation is difficult over extensive temporal and spatial scales. Most studies examining spatial variation of soil moisture were conducted at hillslope (0.01 km2) to multi‐catchment spatial scales (1000 km2). They found the greatest variation at mid wetness levels and the smallest variation at wet and dry wetness levels forming a concave down relationship. There is growing evidence that concave down relationships formed between spatial variation of soil moisture and average soil moisture are consistent across spatial scales spanning several orders of magnitude, but more research is needed at very small, plot scales (<100 m2). The goal of this study was to characterise spatial variation in shallow soil moisture at the plot scale by relating the mean of measurements collected in a plot to the standard deviation (SD). We combined data from a previous study with thousands of new soil moisture measurements from 212 plots in eight catchments distributed across the US Mid‐Atlantic Region to (1) test for a generalisable mean–SD relationship at plot scales, (2) characterise how landcover, land use, season, and hillslope position contribute to differences in mean–SD relationships, and (3) use these generalised mean–SD relationships to quantify their impacts on catchment scale nitrification and denitrification potential. Our study found that 98% of all measurements formed a generalised mean–SD relationship like those observed at hillslope and catchment spatial scales. The remaining 2% of data comprised a mean–SD relationship with greater spatial variation that originated from two riparian plots reported in a previous study. Incorporating the generalised mean–SD relationship into estimates of nitrification and denitrification potential revealed strong bias that was even greater when incorporating mean–SD observations from the two riparian plots with significantly greater spatial variation.

     
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