Geostatistical Analysis of Hydrologic Parameters

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Geostatistical Analysis of Hydrologic Parameters

• Nishesh Mehta
• Hydrology - CE394K
• 26th April 07

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Outline of the problem

• An interesting study to investigate geospatial
  correlationship between hydrologic parameters.
• Industrial Water Use
• Public Supply Water Use
• Irrigation Water Use
• Slope ( flatlands)
• Geologic Texture ( sand)
• Bedrock Permeability
• Climate (Precipitation-PET)

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Data Sources

• Water Use data for the US
• http//water.usgs.gov/watuse/data/2000/index.html
• contains Industrial Water Use
• Public Supply Water Use
• Agricultural Water Use
• Hydrologic landscape regions of the United States
• http//water.usgs.gov/GIS/metadata/usgswrd/XML/hlr
  us.xml
• Contains

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How to do it?

• Semivariograms-

• Geostatistical Analyst

• The semivariogram captures the spatial
  dependence between samples by plotting
  semivariance against separation distance
• h
• 0.5 avg (value i value j)2

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Semivariogram
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Preliminary Results

• Correlation lengths calculated on county basis
• Data used was raw (not treated to have a normal
  distribution)
• Semivariance calculated between each set of
  counties within the continental US

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Surface generated using the semivariogram
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Synthesis of Analysis

• base unit of analysis -
• Counties 3077
• HUCs 2158 (grouped on similar hydrologic
  properties)
• Spatial Join A tool that helps to associate and
  interpolate values spatially. Ex- convert
  parameter classified by county basis to HUC basis
• Random Sampling
• Basis of all statistical processes
• Enables sampling out of a large number of
  points

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Randomization Tool
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CUAHSI test bed sites as pilot test

• Random sampling of HUCs from the site
• comprised of HUC units
• Use any parameter from the attribute table

Sierra Nevada
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Results

• Scaling length Industrial water for the entire
  Sierra Nevada 110 kms
• Scaling length Industrial water for a random
  sample of Sierra Nevada- 110 kms

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Statistical Significance

• Treatment of Data to attain normality
• logIndustrialWaterUselog10(0.1
  IndustrialWaterUse)
• A quick fix method to check results
• Morans index - A test for spatial
  autocorrelation Positive spatial autocorrelation
  indicates spatial clustering

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What to take back ?!

• The cool randomizing tool ( in royalty)
• The intellectual framework of how Geospatial
  correlation may be computed
• ArcGIS has powerful geostatistic tools

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Questions?
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