This study tested a focused strategy for reducing phosphorus (P) and sediment loads in agricultural streams. The strategy involved selecting small watersheds identified as likely to respond relatively quickly, and then focusing conservation practices on high-contributing fields within those watersheds. Two 5,000 ha (12,360 ac) watersheds in the Driftless Area of south central Wisconsin, previously ranked in the top 6% of similarly sized Wisconsin watersheds for expected responsiveness to conservation efforts to reduce high P and sediment loads, were chosen for the study. The stream outlets from both watersheds were monitored from October of 2006 through September of 2016 for streamflow and concentrations of sediment, total P, and, beginning in October of 2009, total dissolved P. Fields and pastures having the highest potential P delivery to the streams in each watershed were identified using the Wisconsin P Index (Good et al. 2012). After three years of baseline monitoring (2006 to 2009), farmers implemented both field-and farm-based conservation practices in one watershed (treatment) as a means to reduce sediment and P inputs to the stream from the highest contributing areas, whereas there were no out-of-the-ordinary conservation efforts in the second watershed (control). Implementation occurred primarily in 2011 and 2012. In the four years following implementation of conservation practices (2013 through 2016), there was a statistically significant reduction in storm-event suspended sediment loads in the treatment watershed compared to the control watershed when the ground was not frozen (p = 0.047). While there was an apparent reduction in year-round suspended sediment event loads, it was not statistically significant at the 95% confidence level (p = 0.15). Total P loads were significantly reduced for runoff events (p < 0.01) with a median reduction of 50%. Total P and total dissolved P concentrations for low-flow conditions were also significantly reduced (p < 0.01) compared to the control watershed. This study demonstrated that a strategy that first identifies watersheds likely to respond to conservation efforts and then focuses implementation on relatively high-contributing fields within those watersheds can be successful in reducing stream P concentrations and loads.
This paper presents results from a randomized experimental design replicated over four semesters that compared students' performance in understanding landform evolution processes as measured by the pretest to posttest score growth between two treatment methods: an online interactive simulation tool and a paper-based exercise. While both methods were shown to be effective at enhancing students' learning of the landform concepts and processes, there was no statistically significant difference in score growth between the two instructional methods. However, the attitudinal survey indicated that students consistently favored the simulation approach over the paper-based exercise. With the simulation method, female students showed greater score growth than males, especially for test items requiring higher level thinking. This indicates that the visually rich interactive simulation tool may be integrated to better support female students' learning in geoscience. Science major students generally outperformed non-science major students in terms of score growth, which suggests that background knowledge played an important role in realizing the potential of computer modeling in enhancing students' learning. Sufficient scaffolding is necessary to maximize the effect of interactive earth surface modeling in geoscience education.Earth surface modeling for education 1463 RQ4: Are the findings from the preliminary study upheld with a larger sample collected over repeated experiments, and across multiple semesters?
Description of WILSIM-GCWILSIM-GC is an accessible, interactive environment for students to engage in scientific inquiry and to enhance students' understanding of the processes involved in landform evolution through meaningful manipulation of parameters for different scenarios (Luo et al., 2016). A screenshot of the model is shown in Figure 1. More details about the model can be found at the project website: https://serc.carleton.edu/landform/.
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