# Presentation: 240486

## Characterizing the Landscape for Water-Quality Analysis

**Methods and implementation**
**2006 National Monitoring Conference, **
**San Jose, CA**

**Notes:**
Curtis Price, cprice@usgs.gov, Rapid City, SD
Gail P. Thelin,  gpthelin@usgs.gov, Sacramento, CA
Naomi Nakagaki, nakagaki@usgs.gov, Sacramento, CA
Kerie J. Hitt, kjhitt@usgs.gov, Reston, VA
Sharon Qi, slqi@usgs.gov, Vancouver, WA

## Authors

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

## Overview

**About NAWQA**
**Using GIS to describe the landscape**
**Area-weighted transfer techniques**
**Summary**

## NAWQA Study Units (“Cycle 1”)

## NAWQA Cycle II

## Slide 6

## Slide 7

## Slide 8

## Slide 9

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

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

## Ancillary data

**Summarizes the landscape **** **
**Used to**
**Put water quality data in context**
**Develop statistical models**

## 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

## 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

## GIS data representations 

**Points**
**Point sources**
**Surfaces**
**Precipitation**** **
**Tabular data by geography**
**	****(for example, by county)**
**Population**
**Water Use**
**Agricultural statistics**

## One theme (land cover), different representations

**categories**
**(areas)**

**percentages**
** ****(grid cells)**

## Area characterization

**Well buffers, well recharge areas**
**Aquifer areas **
**Drainage basins**

## Characterizing a surface (ground-water conductivity)

## Characterizing thematic data (land cover)

## 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**

## Census Block Group and drainage basin

## Attribute transfer methods

**Simple Area-weighted transfer**
**Transfer of data values weighted by area**
**Assumes values evenly distributed**** **

## Simple area-weighting

**Simple area-weighting**

- Area-weighted mean(1.0*50%) + (10.0*25%) + (16.0*25%) = 7.0

## Census Block Group and drainage basin

## Problems with simple area-weighting

- Urban area

- Basin boundary

- Census polygon

## 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)**

## 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)**