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Summer Synthesis Institute

Summer Synthesis Institute. Vancouver, British Columbia June 22 – August 5. Overview of Synthesis Project Synthesis Project Descriptions Summer Institute Logistics. Water Cycle Dynamics in a Changing Environment: Advancing Hydrologic Science through Synthesis.

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Summer Synthesis Institute

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  1. Summer Synthesis Institute Vancouver, British Columbia June 22 – August 5 Overview of Synthesis Project Synthesis Project Descriptions Summer Institute Logistics

  2. Water Cycle Dynamics in a Changing Environment: Advancing Hydrologic Science through Synthesis Murugesu SivapalanPraveen Kumar, Bruce Rhoads, Don Wuebbles University of Illinois Urbana, Illinois

  3. Session 2 Contaminant Dynamics across Scales: Temporal and Spatial Patterns Nandita Basu University of Iowa Suresh Rao Purdue University Aaron Packman Northwestern University

  4. Conceptual Model Cascading Controls • Non linear filters create emergent patterns/signatures across scales • Signatures integrate ecosystem structure and function • Relationship of water flow and water quality to stream ecosystems • Examining signatures using data analysis and models

  5. Overall Hypothesis Despite process complexity at the local scale, non-linear interactions in the cascade of filters and buffers generate emergent spatio-temporal patterns or signatures that can be expressed as simple functions of the hydrologic and biogeochemical drivers of the system. 5

  6. Emergent Patterns: Runoff Coefficient (RC) and Flow Duration Curve • Budyko Curve describes the mean annual streamflow across the climatic gradient • Botter et al. (2009) showed that FDC can be predicted as a simple analytical function of λ/k • - λ (runoff frequency) • - k (catchment mean residence time) • Runoff frequency can be expressed in terms of underlying soil vegetation and rainfall properties • Catchment mean residence time estimated from hydrograph recession curve analysis • Able to describe pdfs of streamflows across several catchments in US Inter-annual Slope = RC Intra-annual 6

  7. Example 1: Emergent Pattern: LAPU and Load Duration Curve (LDC) Inter-annual LAPU: Load as a Percent Used (analogous to RC) Slope = LAPU • Formulate Hypotheses • LDC is a function of • FDC since water carries the chemical • Chemical Properties (sorption, degradation, etc.) • Chemical input functions (atmospheric deposition vs. fertilizer application) • Landscape Biogeochemical Filter Intra-annual 7

  8. Emergent Pattern: Load Duration Curve (LDC) 2. Run Model to explore dominant controls on LDC Two available transient hillslope-network coupled models - Model A (Reggiani et al.) Sheng Ye and Hongyi Li - Model B (Rinaldo et al.) Stefano Zanardo 3. Analyze data to explore dominant controls on LDC 4. Develop simple analytical approaches 5. Response to change

  9. Hydrologic and Biogeochemical Filters Two Functions of Filters: Decrease in mass - Hydrologic Filter: runoff coefficient - Biogeochemical Filter: load as a percent used 2. Alteration of the distribution: - relationship between flow distribution curve and rainfall duration curve (Hydrologic Filter) - relationship between load distribution curve and flow duration curve (Biogeochemical Filter)

  10. Example 2: Biogeochemical Filter:Dual Duration Curve (DDC) What does the DDC depend on?

  11. Biogeochemical Filter:Dual Duration Curve (DDC) A – nitrate B – atrazine Why is nitrate so different from atrazine? How can we classify chemicals or watersheds based on such signatures?

  12. Mean Annual Patterns: Flow vs. Load Intra-annual patterns observed in DDC persists in the mean annual behavior…

  13. Network Models: Spatial Patterns Nitrogen Yield kg/km2

  14. Objectives/Tasks Identify relevant hydrologic, biogeochemical and ecological signatures (2) Understand the functioning of the hydrologic and biogeochemical filters that modify the forcing functions (rainfall and chemical application) - Formulate hypotheses - Run model - Analyze Data (3) Develop simple analytical approaches to predict the signatures as a function of the key parameters of the filters and forcings (4) Identify how land use or climate change would alter the attributes of the filters, and thus change the signatures.

  15. Data based Signatures • Humid: Little Vermilion Watershed in Illinois: • tile-drained agricultural watershed, approximately 480 km2 • Arid: Avon River Basin in Western Australia: • agricultural watershed of size 120,000 km2 • We are searching for other catchments with water quality data --- suggest your favorite catchment • Chemicals of interest: Dissolved (Nitrate, pesticides etc)

  16. Key preparation work required • Read the papers and familiarize yourself with the primary assumptions in the two models • Question the assumptions and think what they would mean in terms of the observed signatures • Start thinking about the signatures and filters --- other interesting signatures or questions that you may want to explore • Read the questions/hypotheses in the framework and think about additional ones that you want to explore. • Contact me if you have or know of contrasting watersheds with water quality data • More thinking than doing….

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