1. Statistics in WR: Lecture 22
Key Themes
Review of concepts from Lecture 1
Patterns in space and time from class exercises
Principles for thinking about spatial and temporal variation

2. Data Cube – What, Where, When
Space, L
Time, T
Variable, V D
“When”
A data value
“Where”
“What”

3. Continuous Space-Time Data Model -- NetCDF
Time, T
Coordinate
dimensions
{X} D
Space, L
Variable dimensions
{Y}
Variables, V

4. Discrete Space-Time Data Model
Time, TSDateTime
TSValue
Space, FeatureID
Variables, TSTypeID

5. Hydrologic Statistics
Time Series Analysis
Geostatistics
Multivariate analysis
How do we understand space-time correlation fields
of many variables?

6. Ex 3: Patterns of Discharge, Sediment Concentration and Load

7. Ex 4: Correlation in space and time

8. Ex 5: Trends through Time

9. Ex 6: Diurnal and Seasonal Patterns

10. Ex 7: SPARROW Modeling of Nitrogen Transport
Mean annual load of Total N

11. 288 USGS sites with flow and Nitrogen data
These sites are ones that were used for the Sparrow model that continue to be operational to 2008

12. Ex 8: Flood frequency analysis
100 year flood discharge
p = 0.01

13. USGS Peak-Flow Regression Equations for 100-year discharge
100 mile2
10 mile2
110 mile2
What happens to design flood discharge when a 10 square mile tributary joins a 100 square mile river?

14. Ex 9: Time Evolution of Spatial Patterns

15. Texas Water Data Services 10 services 15,870 sites 81,625 series
8,549,857 records

16. Salinity Layer for Texas