Watershed analysis of urban stormwater contaminant 6PPD-Quinone hotspots and stream concentrations using a process-based ecohydrological model.

Coho salmon (Oncorhynchus kisutch) are highly sensitive to 6PPD-Quinone (6PPD-Q). Details of the hydrological and biogeochemical processes controlling spatial and temporal dynamics of 6PPD-Q fate and transport from points of deposition to receiving waters (e.g., streams, estuaries) are poorly understood. To understand the fate and transport of 6PPD and mechanisms leading to salmon mortality Visualizing Ecosystem Land Management Assessments (VELMA), an ecohydrological model developed by US Environmental Protection Agency (EPA), was enhanced to better understand and inform stormwater management planning by municipal, state, and federal partners seeking to reduce stormwater contaminant loads in urban streams draining to the Puget Sound National Estuary. This work focuses on the 5.5 km2 Longfellow Creek upper watershed (Seattle, Washington, United States), which has long exhibited high rates of acute urban runoff mortality syndrome in coho salmon. We present VELMA model results to elucidate these processes for the Longfellow Creek watershed across multiple scales-from 5-m grid cells to the entire watershed. Our results highlight hydrological and biogeochemical controls on 6PPD-Q flow paths, and hotspots within the watershed and its stormwater infrastructure, that ultimately impact contaminant transport to Longfellow Creek and Puget Sound. Simulated daily average 6PPD-Q and available observed 6PPD-Q peak in-stream grab sample concentrations (ng/L) corresponds within plus or minus 10 ng/L. Most importantly, VELMA's high-resolution spatial and temporal analysis of 6PPD-Q hotspots provides a tool for prioritizing the locations, amounts, and types of green infrastructure that can most effectively reduce 6PPD-Q stream concentrations to levels protective of coho salmon and other aquatic species.

Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model.

Modeling large-scale hydrological impacts brought about by site-level green and gray stormwater remediation actions is difficult because urbanized areas are extremely complex dynamic landscapes that include engineered features that, by design, expedite urban runoff to streams, creeks, and other water bodies to reduce urban flooding during storm events. Many urban communities use heavily engineered gray infrastructure to achieve that goal, along with more recent additions of green infrastructure such as rain gardens, bioswales, and riparian corridors. Therefore, successfully characterizing those design details and associated management practices, interactions, and impacts requires a detailed understanding of how fine and course-scale hydrologic processes and routing are altered and managed in urban watersheds. To enhance hydrologic modeling capabilities of urban watersheds, we implemented a number of improvements to an existing ecohydrology model called VELMA-Visualizing Ecosystem Land Management Assessments-including the addition of spatially explicit engineered features that impact urban hydrology (e.g., impervious surfaces, curbed roadways, stormwater routing) and refinement to the computational representations of evapotranspiration by adding impervious surface evaporation. We demonstrate improved capabilities for modeling within complex urbanized watersheds by simulating stream runoff within the Longfellow Creek watershed, City of Seattle, Washington (WA), United States (US) with and without these added urban watershed characteristics. The results demonstrate that the newly improved VELMA model allows for more accurate modeling of hydrology within urban watersheds. Being a fate and transport ecohydrology model, the improved hydrologic flow enhances VELMA's current capacity for modeling nutrient, contaminant, and thermal loadings.

Tough places and safe spaces: Can refuges save salmon from a warming climate?

The importance of thermal refuges in a rapidly warming world is particularly evident for migratory species, where individuals encounter a wide range of conditions throughout their lives. In this study, we used a spatially explicit, individual-based simulation model to evaluate the buffering potential of cold-water thermal refuges for anadromous salmon and trout (Oncorhynchus spp.) migrating upstream through a warm river corridor that can expose individuals to physiologically stressful temperatures. We considered upstream migration in relation to migratory phenotypes that were defined in terms of migration timing, spawn timing, swim speed, and use of cold-water thermal refuges. Individuals with different migratory phenotypes migrated upstream through riverine corridors with variable availability of cold-water thermal refuges and mainstem temperatures. Use of cold-water refuges (CWRs) decreased accumulated sublethal exposures to physiologically stressful temperatures when measured in degree-days above 20, 21, and 22°C. The availability of CWRs was an order of magnitude more effective in lowering accumulated sublethal exposures under current and future mainstem temperatures for summer steelhead than fall Chinook Salmon. We considered two emergent model outcomes, survival and percent of available energy used, in relation to thermal heterogeneity and migratory phenotype. Mean percent energy loss attributed to future warmer mainstem temperatures was at least two times larger than the difference in energy used in simulations without CWRs for steelhead and salmon. We also found that loss of CWRs reduced the diversity of energy-conserving migratory phenotypes when we examined the variability in entry timing and travel time outside of CWRs in relation to energy loss. Energy-conserving phenotypic space contracted by 7%-23% when CWRs were unavailable under the current thermal regime. Our simulations suggest that, while CWRs do not entirely mitigate for stressful thermal exposures in mainstem rivers, these features are important for maintaining a diversity of migration phenotypes. Our study suggests that the maintenance of diverse portfolios of migratory phenotypes and cool- and cold-water refuges might be added to the suite of policies and management actions presently being deployed to improve the likelihood of Pacific salmonid persistence into a future characterized by climate change.

Modeling the hydrologic effects of watershed-scale green roof implementation in the Pacific Northwest, United States.

Green roofs are among the most popular type of green infrastructure implemented in highly urbanized watersheds due to their low cost and efficient utilization of unused or under-used space. In this study, we examined the effectiveness of green roofs to attenuate stormwater runoff across a large metropolitan area in the Pacific Northwest, United States. We utilized a spatially explicit ecohydrological watershed model called Visualizing Ecosystem Land Management Assessments (VELMA) to simulate the resulting stormwater hydrology of implementing green roofs over 25%, 50%, 75%, and 100% of existing buildings within four urban watersheds in Seattle, Washington, United States. We simulated the effects of two types of green roofs: extensive green roofs, which are characterized by shallow soil profiles and short vegetative cover, and intensive green roofs, which are characterized by deeper soil profiles and can support larger vegetation. While buildings only comprise approximately 10% of the total area within each of the four watersheds, our simulations showed that 100% implementation of green roofs on these buildings can achieve approximately 10-15% and 20-25% mean annual runoff reductions for extensive and intensive green roofs, respectively, over a 28-year simulation. These results provide an upper limit for volume reductions achievable by green roofs in these urban watersheds. We also showed that stormwater runoff reductions are proportionately smaller during higher flow regimes caused by increased precipitation, likely due to the limited storage capacity of saturated green roofs. In general, green roofs can be effective at reducing stormwater runoff, and their effectiveness is limited by both their areal extent and storage capacity. Our results showed that green roof implementation can be an effective stormwater management tool in highly urban areas, and we demonstrated that our modeling approach can be used to assess the watershed-scale hydrologic impacts of the widespread adoption of green roofs across large metropolitan areas.

Active travel and social justice: Addressing disparities and promoting health equity through a novel approach to Regional Transportation Planning.

Public health impacts of transportation policies and infrastructure investment are becoming better understood, particularly for those associated with physical activity. Yet health impacts are not routinely evaluated within the context of the development of a Regional Transportation Plan (RTP) and subsequent programming and investment processes. This is particularly concerning because the spatial distribution of planned transportation infrastructure potentially has significant health equity implications for vulnerable populations at greater risk of chronic disease. This study discusses the application of the National Public Health Assessment Model (NPHAM) - a new approach that expands several scenario planning tools to include health - for the San Joaquin Council of Governments 2018 RTP. It demonstrates how quantifying health impacts at a finer spatial scale (census block groups) helps assess the extent to which RTP strategies are likely to benefit or harm health. It further enables a spatial form of health equity analysis that can help planners understand where infrastructure is most needed to meet social equity goals. To the knowledge of the authors, this is the first example of a quantified, health equity analysis of transport physical activity and a health outcome - body mass index - associated with an RTP; it demonstrates significant advancement in transportation planning practice and policy.

Assessing contributions of cold-water refuges to reproductive migration corridor conditions for adult Chinook Salmon and steelhead trout in the Columbia River, USA.

Diadromous fish populations face multiple challenges along their migratory routes. These challenges include suboptimal water quality, harvest, and barriers to longitudinal and lateral connectivity. Interactions among factors influencing migration success make it challenging to assess management options for improving migratory fish conditions along riverine migration corridors. We describe a spatially explicit simulation model that integrates complex individual behaviors of fall-run Chinook Salmon (Oncorhynchus tshawytscha) and summer-run steelhead trout (O. mykiss) during migration, responds to variable habitat conditions over a large extent of the Columbia River, and links migration corridor conditions to fish condition outcomes. The model is built around a mechanistic behavioral decision tree that drives individual interactions of fish within their simulated environments. By simulating several thermalscapes with alternative scenarios of thermal refuge availability, we examined how behavioral thermoregulation in cold-water refuges influenced migrating fish conditions. Outcomes of the migration corridor simulation model show that cold-water refuges can provide relief from exposure to high water temperatures, but do not substantially contribute to energy conservation by migrating adults. Simulated cooling of the Columbia River decreased reliance on cold-water refuges and there were slight reductions in migratory energy expenditure. This modeling of simulated thermalscapes provides a framework for assessing the contribution of cold-water refuges to the success of migrating fishes, but any final determination will depend on analyzing fish survival and health for their entire migration, water temperature management goals and species recovery targets.

Individual Based Modelling of Fish Migration in a 2-D River System: Model Description and Case Study.

CONTEXT: Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. These stressors complicate the prioritization of proposed management actions intended to improve conditions for migratory fishes including anadromous salmon and trout. OBJECTIVES: We describe a multi-scale hybrid mechanistic-probabilistic simulation model linking migration corridor conditions to fish fitness outcomes. We demonstrate the model's utility using a case study of salmon and steelhead adults in the Columbia River migration corridor exposed to spatially- and temporally-varying stressors. METHODS: The migration corridor simulation model is based on a behavioral decision tree that governs individual interactions with the environment, and an energetic submodel that estimates the hourly costs of migration. Emergent properties of the migration corridor simulation model include passage time, energy use, and survival. RESULTS: We observed that the simulated fishes' initial energy density, the migration corridor temperatures they experienced, and their history of behavioral thermoregulation were the primary determinants of their fitness outcomes. Insights gained from use of the model might be exploited to identify management interventions that increase successful migration outcomes. CONCLUSIONS: This paper describes new methods that extend the suite of tools available to aquatic biologists and conservation practitioners. We have developed a 2-dimensional spatially-explicit behavioral and physiological model and illustrated how it can be used to simulate fish migration within a river system. Our model can be used to evaluate trade-offs between behavioral thermoregulation and fish fitness at population scales.

Penumbra: A spatially distributed, mechanistic model for simulating ground-level incident solar energy across heterogeneous landscapes.

Landscape solar energy is a significant environmental driver, yet it remains complicated to model well. Several solar radiation models simplify the complexity of light by estimating it at discrete point locations or by averaging values over larger areas. These modeling approaches may be useful in certain cases, but they are unable to provide spatially distributed and temporally dynamic representations of solar energy across entire landscapes. We created a landscape-scale ground-level shade and solar energy model called Penumbra to address this deficiency. Penumbra simulates spatially distributed ground-level shade and incident solar energy at user-defined timescales by modeling local and distant topographic shading and vegetative shading. Spatially resolved inputs of a digital elevation model, a normalized digital surface model, and landscape object transmittance are used to estimate spatial variations in solar energy at user-defined temporal timesteps. The research goals for Penumbra included: 1) simulations of spatiotemporal variations of shade and solar energy caused by both objects and topographic features, 2) minimal user burden and parameterization, 3) flexible user defined temporal parameters, and 4) flexible external model coupling. We test Penumbra's predictive skill by comparing the model's predictions with monitored open and forested sites, and achieve calibrated mean errors ranging from -17.3 to 148.1 µmoles/m2/s. Penumbra is a dynamic model that can produce spatial and temporal representations of shade percentage and ground-level solar energy. Outputs from Penumbra can be used with other ecological models to better understand the health and resilience of aquatic, near stream terrestrial, and upland ecosystems.

Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers.

Modeling the spatial and temporal dynamics of soil temperature is deterministically complex due to the wide variability of several influential environmental variables, including soil column composition, soil moisture, air temperature, and solar energy. Landscape incident solar radiation is a significant environmental driver that affects both air temperature and ground-level soil energy loading; therefore, inclusion of solar energy is important for generating accurate representations of soil temperature. We used the U.S. Environmental Protection Agency's Oregon Crest-to-Coast (O'CCMoN) Environmental Monitoring Transect dataset to develop and test the inclusion of ground-level solar energy driver data within an existing soil temperature model currently utilized within an ecohydrology model called Visualizing Ecosystem Land Management Assessments (VELMA). The O'CCMoN site data elucidate how localized ground-level solar energy between open and forested landscapes greatly influence the resulting soil temperature. We demonstrate how the inclusion of local ground-level solar energy significantly improves the ability to deterministically model soil temperature at two depths. These results suggest that landscape and watershed-scale models should incorporate spatially distributed solar energy to improve spatial and temporal simulations of soil temperature.

HexSim: a modeling environment for ecology and conservation.

CONTEXT: Simulation models are increasingly used in both theoretical and applied studies to explore system responses to natural and anthropogenic forcing functions, develop defensible predictions of future conditions, challenge simplifying assumptions that facilitated past research, and to train students in scientific concepts and technology. Researcher's increased use of simulation models has created a demand for new platforms that balance performance, utility, and flexibility. OBJECTIVES: We describe HexSim, a powerful new spatially-explicit, individual-based modeling framework that will have applications spanning diverse landscape settings, species, stressors, and disciplines (e.g. ecology, conservation, genetics, epidemiology). We begin with a model overview and follow-up with a discussion of key formative studies that influenced HexSim's development. We then describe specific model applications of relevance to readers of Landscape Ecology. Our goal is to introduce readers to this new modeling platform, and to provide examples characterizing its novelty and utility. CONCLUSIONS: With this publication, we conclude a >10 year development effort, and assert that our HexSim model is mature, robust, extremely well tested, and ready for adoption by the research community. The HexSim model, documentation, worked examples, and other materials can be freely obtained from the website www.hexsim.net.

Cumulative Effects of Low Impact Development on Watershed Hydrology in a Mixed Land-Cover System.

Low Impact Development (LID) is an alternative to conventional urban stormwater management practices, which aims at mitigating the impacts of urbanization on water quantity and quality. Plot and local scale studies provide evidence of LID effectiveness; however, little is known about the overall watershed scale influence of LID practices. This is particularly true in watersheds with a land cover that is more diverse than that of urban or suburban classifications alone. We address this watershed-scale gap by assessing the effects of three common LID practices (rain gardens, permeable pavement, and riparian buffers) on the hydrology of a 0.94 km2 mixed land cover watershed. We used a spatially-explicit ecohydrological model, called Visualizing Ecosystems for Land Management Assessments (VELMA), to compare changes in watershed hydrologic responses before and after the implementation of LID practices. For the LID scenarios, we examined different spatial configurations, using 25%, 50%, 75% and 100% implementation extents, to convert sidewalks into rain gardens, and parking lots and driveways into permeable pavement. We further applied 20 m and 40 m riparian buffers along streams that were adjacent to agricultural land cover. The results showed overall increases in shallow subsurface runoff and infiltration, as well as evapotranspiration, and decreases in peak flows and surface runoff across all types and configurations of LID. Among individual LID practices, rain gardens had the greatest influence on each component of the overall watershed water balance. As anticipated, the combination of LID practices at the highest implementation level resulted in the most substantial changes to the overall watershed hydrology. It is notable that all hydrological changes from the LID implementation, ranging from 0.01 to 0.06 km2 across the study watershed, were modest, which suggests a potentially limited efficacy of LID practices in mixed land cover watersheds.

Bringing health into transportation and land use scenario planning: Creating a National Public Health Assessment Model (N-PHAM).

There is mounting evidence linking land development and transportation investments to physical activity with resulting implications for chronic disease prevention. Links between the physical environment and health have traditionally focused on harmful exposures such as air pollution, noise, and traffic injury. Given limited funds and competition for how and where investments are made, there is a need to prioritize and target resources to maximize health benefits that can include activity related chronic disease prevention. The ability to apply this evidence to decision making has been limited by the complexity and inconsistency of research methods, and lack of a direct connection with the planning contexts in which decisions are made. Scenario planning tools provide a method to apply evidence with spatial planning decisions at a range of geographic scales. The US Environmental Protection Agency commissioned the development of a National Public Health Assessment Model (N-PHAM). This project utilized built and natural environment data at the block-group level and large population surveys to model the relationships of the environment with several health outcomes for a range of age and income groups. N-PHAM is the first health assessment tool that can connect to multiple existing scenario planning platforms utilizing nationally available data and can be consistently applied nationally. Such tools can empower communities to choose investments that have the greatest potential to improve public health and quality of life, reduce health care costs, and address environmental justice related disparities.

Modular and Spatially Explicit: A Novel Approach to System Dynamics.

The Open Modeling Environment (OME) is an open-source System Dynamics (SD) simulation engine which has been created as a joint project between Oregon State University and the US Environmental Protection Agency. It is designed around a modular implementation, and provides a standardized interface for interacting with spatially explicit data while still supporting the standard SD model components. OME can be run as a standalone simulation or as a plugin to a larger simulation framework, and is capable of importing Models from several SD model formats, including Simile model files, Vensim model files, and the XMILE interchange format. While it has been released, OME is still under development, and a number of potential future improvements are discussed. To help illustrate the utility of OME, an example model design process is provided as an Appendix.

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America.

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.