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Reproducible environmental modelling often relies on spatial datasets as inputs, typically manually subset for specific areas. Yet, models can benefit from a data distribution approach facilitated by online repositories, and automating processes to foster reproducibility. This study introduces a method leveraging diverse state-scale spatial datasets to create cohesive packages for GIS-based environmental modelling. These datasets were generated and shared via GeoServer and THREDDS Data Server Connected to HydroShare, contrasting with conventional distribution methods. Using the Regional Hydro-Ecologic Simulation System (RHESSys) across three U.S. catchment-scale watersheds, we demonstrate minimal errors in spatial inputs and model streamflow outputs compared to traditional approaches. This spatial data-sharing method facilitates consistent model creation, fostering reproducibility. Its broader impact allows scientists to tailor the method to various use cases, such as exploring different scales beyond state-scale or applying it to other online repositories using existing data distribution systems, eliminating the need to develop their own. 

The relationship between (a) the structure and composition of the landscape around an individual's home and (b) environmental perceptions and health outcomes has been well demonstrated (eg the value of vegetation cover to well‐being). Few studies, however, have examined how multiple landscape features (eg vegetation and water cover) relate to perceptions of multiple environmental problems (eg air or water quality) and whether those relationships hold over time. We utilized a long‐term dataset of geolocated telephone surveys in Baltimore, Maryland, to identify relationships between residents’ perceptions of environmental problems and nearby landcover. Residents of neighborhoods with more vegetation or located closer to water were less likely to perceive environmental problems. Water quality was one exception to this trend, in that people were more likely to perceive water‐quality problems when nearby water cover was greater. These trends endured over time, suggesting that these relationships are stable and therefore useful for informing policy aimed at minimizing perceived environmental problems. 

Abstract. Spatially distributed hydrological models are commonly employed to optimize the locations of engineering control measures across a watershed. Yet, parameter screening exercises that aim to reduce the dimensionality of the calibration search space are typically completed only for gauged locations, like the watershed outlet, and use screening metrics that are relevant to calibration instead of explicitly describing the engineering decision objectives. Identifying parameters that describe physical processes in ungauged locations that affect decision objectives should lead to a better understanding of control measure effectiveness. This paper provides guidance on evaluating model parameter uncertainty at the spatial scales and flow magnitudes of interest for such decision-making problems. We use global sensitivity analysis to screen parameters for model calibration, and to subsequently evaluate the appropriateness of using multipliers to adjust the values of spatially distributed parameters to further reduce dimensionality. We evaluate six sensitivity metrics, four of which align with decision objectives and two of which consider model residual error that would be considered in spatial optimizations of engineering designs. We compare the resulting parameter selection for the basin outlet and each hillslope. We also compare basin outlet results for four calibration-relevant metrics. These methods were applied to a RHESSys ecohydrological model of an exurban forested watershed near Baltimore, MD, USA. Results show that (1) the set of parameters selected by calibration-relevant metrics does not include parameters that control decision-relevant high and low streamflows, (2) evaluating sensitivity metrics at the basin outlet misses many parameters that control streamflows in hillslopes, and (3) for some multipliers, calibrating all parameters in the set being adjusted may be preferable to using the multiplier if parameter sensitivities are significantly different, while for others, calibrating a subset of the parameters may be preferable if they are not all influential. Thus, we recommend that parameter screening exercises use decision-relevant metrics that are evaluated at the spatial scales appropriate to decision making. While including more parameters in calibration will exacerbate equifinality, the resulting parametric uncertainty should be important to consider in discovering control measures that are robust to it. 

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. 

Abstract Urbanization increases stormwater runoff into streams, resulting in channel erosion, and increases in sediment and nutrient delivery to receiving water bodies. Stream restoration is widely used as a Best Management Practice to stabilize banks and reduce sediment and nutrient loads. While most instream nutrient retention measurements are often limited to low flow conditions, most of the nutrient load is mobilized at high stream flows in urban settings. We, therefore, use a process‐based stream ecosystem model in conjunction with measurements at low flows and focus on estimation of stream nitrogen retention over the full streamflow distribution. The model provides a theoretical framework to evaluate the geomorphic, hydrologic, and ecological factors that are manipulated by stream restoration, and drive nitrogen retention. We set a model for a pool‐riffle sequence restored stream (190 m) in Baltimore County, Maryland and calibrated the model to thein situmeasured primary production (Nash–Sutcliffe model efficiency coefficient [NSE] NSE = 0.89), respiration (NSE = 0.74), and nitrate uptake lengths (R² = 0.88). At the daily scale, simulations showed low nitrogen retention during high flows due to high transport rates, mobilization of stored hyporheic nitrogen, and scouring of periphyton biomass. This result underscores the need to reduce contributing watershed runoff flashiness to promote aquatic nutrient cycling and retention. At monthly and yearly time scale, model predicted a higher percent reduction in summer than in winter and estimated 5.7%–9.5% of annual nitrate reductions. While the model was tested in a pool‐riffle sequence restoration design, the approach can be adapted to evaluate a range of channel restoration design characteristics, and the effects of upland watershed restoration to mitigate stormwater loading through both restored and unrestored streams. 

Abstract Forest canopy water use and carbon cycling traits (WCT) can vary substantially and in spatially organized patterns, with significant impacts on watershed ecohydrology. In many watersheds, WCT may vary systematically along and between hydrologic flowpaths as an adaptation to available soil water, nutrients, and microclimate‐mediated atmospheric water demand. We hypothesize that the emerging patterns of WCT at the hillslope to catchment scale provide a more resistant ecohydrological system, particularly with respect to drought stress, and the maintenance of high levels of productivity. Rather than attempting to address this hypothesis with species‐specific patterns, we outline broader functional WCT groups and explore the sensitivity of water and carbon balances to the representation of canopy WCT functional organization through a modelling approach. We use a well‐studied experimental watershed in North Carolina where detailed mapping of forest community patterns are sufficient to describe WCT functional organization. Ecohydrological models typically use broad‐scale characterizations of forest canopy composition based on remotely sensed information (e.g., evergreen vs. deciduous), which may not adequately represent the range or spatial pattern of functional group WCT at hillslope to watershed scales. We use three different representations of WCT functional organizations: (1) restricting WCT to deciduous/conifer differentiation, (2) utilizing more detailed, but aspatial, information on local forest community composition, and (3) spatially distributed representation of local forest WCT. Accounting for WCT functional organization information improves model performance not only in terms of capturing observed flow regimes (especially watershed‐scale seasonal flow dynamics) but also in terms of representing more detailed canopy ecohydrologic behaviour (e.g., root zone soil moisture, evapotranspiration, and net canopy photosynthesis), especially under dry condition. Results suggest that the well‐known zonation of forest communities over hydrologic gradients is not just a local adaptation but also provides a property that regulates hillslope to catchment‐scale behaviour of water use and drought resistance.