LID-BMPs planning for urban runoff control and the case study in China.

Watershed-scale impacts of stormwater green infrastructure on hydrology, nutrient fluxes, and combined sewer overflows in the mid-Atlantic region.

Eutrophication has threatened water resources worldwide, yet mechanistic understanding on controls of nutrient export remains elusive. This work tests the shallow and deep hypothesis: subsurface vertical chemical contrasts regulate nitrate export patterns under different land use conditions. We synthesized data from 228 watersheds and used reactive transport modeling (500 simulations) under broad land use, climate, and geology conditions. Data synthesis indicated that human perturbation has amplified chemical contrasts in shallow water (e.g., soil water) versus deep waters (e.g., groundwater), inducing primarily flushing patterns (concentrations increase with streamflow) in agriculture lands and dilution patterns (concentrations decrease with streamflow) in urban watersheds. Results revealed a quantitative relationship between export patterns and shallow-versus-deep concentration contrasts, underscoring the often-overlooked role of nutrient distribution over depth. Results challenge the commonly held perception that legacy stores in agricultural lands induce chemostasis where concentrations vary negligibly with streamflow. They suggest that nitrate concentrations from agricultural lands will escalate during large hydrological events, which can exacerbate nutrient export problems as flooding events intensify in the future climate.

The Shallow and Deep Hypothesis: Subsurface Vertical Chemical Contrasts Shape Nitrate Export Patterns from Different Land Uses.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sce.21525

Toward coherence in curriculum, instruction, and assessment: A review of learning progression literature

Learning progressions—particularly as defined and operationalized in science education—have significant potential to inform teachers’ formative assessment practices. In this overview article, I lay...

An argument for formative assessment with science learning progressions

Older, economically troubled urban neighborhoods present multiple challenges to environmental quality. Here, we present results from an initiative in Baltimore, Maryland, where water-quality improvements were rooted in a socioecological framework that highlighted the interactions between biogeophysical dynamics and social actors and institutions. This framework led to implementation of best management practices followed by assessment of changes in human perception, behavior, and education programs. Results suggest that such an initiative can improve both water quality (eg reductions in nitrogen and phosphorus runoff) and quality of life (eg increased involvement in outdoor recreation by residents and improvements in student environmental literacy and performance) in urban neighborhoods. However, proposed solutions to the water-quality problems in such neighborhoods have (1) typically emphasized the need for stormwater facilities that are difficult to build and maintain and (2) comprehensively addressed neither the issues related to aging infrastructure and hydrologic complexity nor the benefits derived from linkages between resident perception of environmental improvements and behavior and water-quality outcomes.

https://www.fs.fed.us/nrs/pubs/jrnl/2013/nrs_2013_hager_001.pdf

Socioecological revitalization of an urban watershed

While learning progressions (LPs) hold promise as instructional tools, researchers are still in the early stages of understanding how teachers use LPs in formative assessment practices. We report o...

Teachers’ use of learning progression-based formative assessment in water instruction

Using Computational Thinking and Modeling to Build Water and Watershed Literacy

https://par.nsf.gov/servlets/purl/10086729

DATA JAMS: Promoting Data Literacy and Science Engagement While Encouraging Creativity

Nearly a decade ago, the Framework for K-12 Science Education argued for the need to intertwine science and engineering practices, disciplinary core ideas, and crosscutting concepts in performance expectations. However, there are few empirical examples for how intertwining three dimensions facilitates learning. In this study, we used a learning progressions approach to examine how student engagement in computational thinking (science and engineering practice) intertwines with learning about the flow of water through environmental systems (disciplinary core ideas) and understanding of systems and system models (crosscutting concept). We developed three secondary-level curriculum units situated in current groundwater contamination and urban flooding contexts. Units included specially designed NetLogo computational models. Post-assessments measured student performances in computational thinking processes and understanding of hydrologic systems. Using item response theory in our analysis, we identified distinct levels of performance on a learning progression. At the lower end, literal model users interacted with models and manipulated model interfaces to achieve a specified goal. In the middle, Model Technicians used computational models to solve real-world problems. At the upper end, principle-based model users used computational thinking processes and principles related to systems modeling and hydrology to explain how the models worked to predict water flow. Differences between performances of literal model users, model technicians, and principle-based model users reflected shifts in how students made sense of the systems and system models crosscutting concept. These shifts in performances aligned with progress in computational thinking practices and finally with use of hydrology disciplinary core ideas. These findings contribute to understanding of how science and engineering practices, disciplinary core ideas, and crosscutting concepts intertwine during learning; how computational thinking practices develop; and how computational thinking about system models facilitates learning for environmental science literacy. 

Computational thinking for using models of water flow in environmental systems: Intertwining three dimensions in a learning progression

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