1 / 26

Characterizing the Landscape for Water-Quality Analysis

Characterizing the Landscape for Water-Quality Analysis. Methods and implementation 2006 National Monitoring Conference, San Jose, CA. Authors. NAWQA National Synthesis Curtis Price (cprice@usgs.gov) Naomi Nakagaki Kerie Hitt Gail Thelin High Plains Ground Water Study Sharon Qi.

lspell
Download Presentation

Characterizing the Landscape for Water-Quality Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Characterizing the Landscape for Water-Quality Analysis Methods and implementation 2006 National Monitoring Conference, San Jose, CA

  2. Authors • NAWQA National Synthesis Curtis Price (cprice@usgs.gov) Naomi Nakagaki Kerie Hitt Gail Thelin • High Plains Ground Water Study Sharon Qi

  3. Overview • About NAWQA • Using GIS to describe the landscape • Area-weighted transfer techniques • Summary

  4. NAWQA Study Units (“Cycle 1”)

  5. NAWQA Cycle II

  6. http://water.usgs.gov/nawqa/data

  7. Ancillary data • Summarizes the landscape • Used to • Put water quality data in context • Develop statistical models

  8. Using results of area characterization Example: Population density for areas around wells less than 100 persons per square kilometer 100 to 1000 persons per square kilometer greater than 1000 persons per square kilometer

  9. Using results of area characterization • VOC predictors from NAWQA national study: • Septic systems • Urban land • RCRA hazardous-waste facilities • Regulated underground storage tanks • Climatic conditions • Depth to top of well screen • Hydric (anoxic) soils • Oxic ground water (dissolved-oxygen concentration greater than or equal to 0.5 milligram per liter) • Type of well Source: USGS Circular 1292

  10. GIS data representations • Points • Point sources • Surfaces • Precipitation • Tabular data by geography (for example, by county) • Population • Water Use • Agricultural statistics

  11. One theme (land cover), different representations categories (areas) percentages (grid cells)

  12. Area characterization • Well buffers, well recharge areas • Aquifer areas • Drainage basins

  13. Characterizing a surface (ground-water conductivity)

  14. Characterizing thematic data (land cover)

  15. Geocoded data: Census • Data linked to polygons from block to national level • Census data values required for different polygons (drainage basins) that do not coincide with Census polygons

  16. Census Block Group and drainage basin

  17. Attribute transfer methods • Simple Area-weighted transfer • Transfer of data values weighted by area • Assumes values evenly distributed

  18. 1.0 1.0 50 % 10.0 16.0 25 % 25 % 10.0 16.0 Simple area-weighting Area-weighted mean(1.0*50%) + (10.0*25%) + (16.0*25%) = 7.0

  19. Census Block Group and drainage basin

  20. Problems with simple area-weighting Urban area Census polygon Basin boundary

  21. Attribute transfer methods • Area-weighted transfer • Transfer of data values weighted by area • Assumes values evenly distributed • Spatial disaggregation • Refine georeferenced data (for example, data reported by county) using other data sets (such as land cover)

  22. Summary • Land characterization using GIS has played a key role in NAWQA design, site selection, and analysis of sampling results • Carefully selecting which data sets to use and how to represent them in the GIS is important • Simple area-weighted transfer methods work well, but assume that values are constant in space within a polygon (in this example, Census Block Group)

More Related