Productivity-Based Indicators for Nitrogen Use Efficiency

Nitrogen use efficiency (NUE) is often used to evaluate an agricultural system's relative ability to process nitrogen (N) inputs. However, no universal indicator has simultaneously considered both economic and environmental objectives. We develop Luenberger indicators of NUE that incorporate both economic and environmental objectives to examine spatio-temporal changes in NUE, which we apply to the Upper Mississippi River Basin (UMRB) for the period 2002-2012. We find considerable spatial-temporal variation in NUE, which could be used to inform future agri-environmental policy and conservation targeting decisions in the UMRB. Using this approach could lead to more cost-effective targeting of areas for N reduction in the UMRB

Modeling Landscape Change Effects on Stream Temperature Using the Soil and Water Assessment Tool

Stream temperature is one of the most important factors for regulating fish behavior and habitat. Therefore, models that seek to characterize stream temperatures, and predict their changes due to landscape and climatic changes, are extremely important. In this study, we extend a mechanistic stream temperature model within the Soil and Water Assessment Tool (SWAT) by explicitly incorporating radiative flux components to more realistically account for radiative heat exchange. The extended stream temperature model is particularly useful for simulating the impacts of landscape and land use change on stream temperatures using SWAT. The extended model is tested for the Marys River, a western tributary of the Willamette River in Oregon. The results are compared with observed stream temperatures, as well as previous model estimates (without radiative components), for different spatial locations within the Marys River watershed. The results show that the radiative stream temperature model is able to simulate increased stream temperatures in agricultural sub-basins compared with forested sub-basins, reflecting observed data. However, the effect is overestimated, and more noise is generated in the radiative model due to the inclusion of highly variable radiative forcing components. The model works at a daily time step, and further research should investigate modeling at hourly timesteps to further improve the temporal resolution of the model. In addition, other watersheds should be tested to improve and validate the model in different climates, landscapes, and land use regimes

The Development and Initial Evaluation of Two Promising Mental Preparatory Methods in a Sample of Female Cross Country Runners

The development of standardized mental preparation procedures specific to cross country running performance is delineated, including a preliminary assessment of the relative efficacy of these interventions in 6 Division I female cross country runners (n=6) in the USA. The interventions occur immediately prior to running, and involve: asking athletes to report current thoughts and feelings; stating motivational phrases to the athlete; and instructing athletes to focus on actions that are consistent with optimum performance. In the origination of these interventions, athletes were employed to assist in the generation of specific content. A preliminary evaluation of these interventions involved performance comparisons between 1000 m baseline trials, and 1000 m trials for each runner consequent to each of the interventions (a Latin square experimental design was utilized to counterbalance effects due to the order in which interventions were implemented, i.e., control for fatigue/practice effects). Preliminary results, including consumer satisfaction indices completed by the cross country runners who participated in this study, suggest the motivational and instructional interventions are most promising. Future recommendations are discussed in light of these results

Towards a hierarchical optimization framework for spatially targeting incentive policies to promote green infrastructure amidst multiple objectives and uncertainty

We introduce a hierarchical optimization framework for spatially targeting green infrastructure (GI) incentive policies in order to meet objectives related to cost and environmental effectiveness. The framework explicitly simulates the interaction between multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities) and is especially useful for constructing and evaluating environmental and ecological policy. Using the framework with a hypothetical urban watershed, we present trade-offs between policy cost and environmental benefits (e.g., water usage, nutrient run-off) using GI incentive policies. In addition, we introduce uncertainties related to policy budget, compliance, and GI effectiveness and show that robust policies (with respect to each uncertainty type) are possible at the expense of reductions in overall objective performance. Overall, we demonstrate the utility of hierarchical optimization as a framework for targeting incentives to promote effective GI that ensures robust policies amidst conflicting objectives and uncertainty

Urban watershed modeling in Seattle, Washington using VELMA: a spatially explicit ecohydrological watershed model

Urban watersheds are notoriously difficult to model due to their complex, small-scale combinations of landscape and land use characteristics including impervious surfaces that ultimately affect the hydrologic system. We utilized EPA’s Visualizing Ecosystem Land Management Assessments (VELMA) model, which is a spatially explicit (i.e., gridded) ecohydrological watershed model, to simulate watershed-scale hydrologic discharge and nutrient concentrations for several urban stream systems in Seattle, Washington, including Thornton Creek, Piper’s Creek, Longfellow Creek, and Taylor Creek. A 1-meter land use classification is used to distinguish four cover types, including roads, buildings, trees, and grass. After model calibration and validation, we construct scenarios of hypothetical green roof implementations and simulate their impacts on watershed-scale discharge. Results show that VELMA is capable of simulating the impacts of targeted green infrastructure management practices to reduce peak stream flow events. These results suggest that VELMA can facilitate the prioritization of urban water infrastructure to improve water quality in urban streams leading to Puget Sound

Union Catalog of Art Images (UCAI Phase 1): Final Report

This report describes the work done to build a prototype for a union catalog of art images as a proof-of-concept that it is technically possible to create such a union database

Further Development of a Shared Cataloging Resource for the Visual Resources Community: UCAI Phase Two: Final Report

This report describes efforts  to advance and stabilize the intrastructure for a shared cataloging utility for art images by developing a set of production-quality tools that operate on a large, standardized set of legacy metadata

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