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<OL> <LI>Landscape Characterization - Coarse and Fine Resolution GIS Analyses Objective: To determine at what spatial scale (coarse ,30 m vs. fine, < 1m remote data resolution; reach vs. subwatershed) the performance of BMPs can be assessed and subsequently aggregated on a watershed basis. <LI>Hydrologic and Landscape Modeling of BMP Performance Objective: To quantify the relative importance of agricultural uplands, riparian zones, and streams channels as sediment sources, and to quantify the relative benefits of upland, riparian, and in-stream BMPs on stream sediment loads. <LI>Ground-based Monitoring and Ecological Analyses Objectives: a) To determine if reach-level measures of abiotic (substrate composition) and biotic (macroinvertebrates and fish) variables are useful surrogate measures of water quality to describe effects of BMPs on stream ecosystems. b) To determine if reach-level abiotic and biotic variables vary spatially with regard to the number of BMPs implemented upstream of study reaches. c) To assess the time required to measure stream responses to BMPs over a range of 1 to 12 years. <LI>Socio-Economic and Outreach Objectives: a) To explore the factors that affect effective farmer adoption of BMPs and citizen perception of water quality. b) To develop methods for integrating and communicating the complexity of water quality measures derived from multiple measures and multiple sites to stakeholders by watershed.
Non-Technical Summary: Assessing the performance of conservation Best Management Practices (BMPs) in agricultural watersheds across the U.S. is difficult because of the array of BMPs used, the variety of hydrogeomorphic settings in which they are implemented, and the breadth of geographic regions involved. One approach is to organize information such that the effectiveness of the BMPs for improving water quality can be assessed consistently and at a scale - the small watershed - that makes ecological and management sense. We will organize data collected by a variety of methods for the streams, fish, macroinvertebrates, and landscapes to assess BMP performance in a systematic manner on a well-studied watershed, Spring Creek, in central Pennsylvania, which drains into the Susquehanna. Impacts from agricultural activities are documented in this watershed. To evaluate BMPs, one must be able to distinguish among landscape settings. For example, one BMP might improve water quality to nearly unaltered conditions, whereas another BMP might maintain water quality of a stream at a constant level in the face of degrading land use. We will assess the performance of a BMP relative to the measured (or expected) stream condition without the BMP. Our study will focus on conservation buffers and nutrient management. Building on recent surveys in Spring Creek, new focus groups, interviews, and surveys will be conducted to gain more understanding about the motivations to participate in BMP implementation, maintenance, and monitoring. <P> Approach: We will use an approach for evaluating BMPs on agricultural lands that is be flexible, adaptable, and efficient, and one that will recognize and distinguish the physical environment from the actual performance of the BMP. The foundation of our analyses will focus on pre-construction and post-construction data collected from the experimental reaches and data collected from an ambient water quality monitoring program throughout the watershed, to answer multiple questions about the temporal and spatial responses of aquatic ecosystems (substrate, fish, macroinvertebrates) to BMPs. By combining ground-based measurements with fine-resolution LIDAR data, we will be able to more precisely map topographically and hydrologically distinct reaches (e.g., hydrogeomorphic settings) that vary in their response to BMPs. We have long-term datasets from Spring Creek Watershed, Centre Co., Pennsylvania, that will demonstrate how the performance of selected BMPs addressing several stressors, can be evaluated with regard to both spatial and temporal factors. Based on empirical findings, we will develop a conceptual model of how the implemented BMPs are expected to function in distinct hydrogeomorphic reaches. Using a combination of these field data, landscape analyses, and hydrologic modeling from the experimental reaches and other watershed segments, we will determine if evaluations at the reach scale can be compiled predictively to characterize the condition of watersheds. We will base our landscape level analyses on both the currently available coarse resolution GIS data, and newly collected fine resolution (LIDAR based) GIS data. A necessary criterion for BMPs to be effective is that they are adopted and implemented well by landowners/farmers/agriculturists. Therefore, we will examine the factors that have affected BMP implementation, performance, and maintenance throughout the watershed. Our team has pioneered ways to integrate ecological and socio-economic data in assessing the condition of watersheds. Based on recent surveys in Spring Creek, new focus groups, interviews, and surveys will be conducted to gain more understanding about the motivations. These will target both participating landowners and citizens in the watershed that benefit from implemented BMPs. This latter step will show how a watershed level assessment and compilation of BMP performances can improve definition of project goals, thereby increasing the efficiency of expending public and private funds.