1. CVEN 675 Stochastic Hydrology Professor Anthony Cahill

2. What is Stochastic Hydrology (and why would want to take it)? We often have measurements of system behavior, but not enough knowledge of physics Model our lack of knowledge as a random (stochastic) element Allows us to make predictions of system behavior (within some confidence limits)

3. Examples – Streamflow time series USGS has gauging stations throughout US We’d like to predict streamflow – estimate flooding, recession, water availability, etc.

4. Streamflow time series, cont. Difference between streamflow time series and rolling dice – dependence of sequential observations Can we model the time series (for understanding)?

5. Streamflow time series, cont. Can we predict the streamflow in future based on past behavior (forecasting)?

6. Example – Rainfall time series Different than river time series – intermittant in time, but still dependence

7. Rainfall time series cont. Use a different method than streamflow time series for modeling and prediction

8. Frequency analysis – flood frequency, storm frequency and extreme values Change the time period of interest so that events are independent – usually annual maximum event

9. Frequency analysis, cont. Used extensively for planning, runoff estimation, etc. We are working with rare extreme events Need to treat tails carefully

10. Spatial statistical methods Spatial data sets ubiquitous in hydrology –Rain gauge data –Hydraulic conductivity –Soil moisture

11. Spatial statistics cont. Optimal interpolation of point data – “kriging” This is both modeling and prediction Very useful in GIS – built into ArcGIS (I think)

12. If time permits… Fractals in hydrology Stochastic groundwater models

13. Housekeeping Books –Brockwell and Davis, Introduction to Time Series and Forecasting, 2 nd ed. –Isaaks and Srivastava, Applied Geostatistics Software –In Brockwell and Davis –I will provide some –You will write some

14. Class Web Page http://ceprofs.tamu.edu/cahill/teaching675.html I’ll put stuff up there Including syllabus

15. Grading Homework – 30% Two tests – 20% each –First test in in-class –Second test is a takehome due the day of the final (i.e. no in class final), which is Monday, December 15, 8AM. Project – 30%

16. Project Explore some question of interest to you in stochastic hydrology Required: a paper – can be analysis or review Start thinking – due dates –Topic – October 1 –1 st draft – November 19 –Final version – December 15 You can talk to me about project anytime

17. Classroom This course is TTVN to Corpus Christi We will meet in WERC 049 Get used to disembodied interruptions I will not be using Power Point usually I will be using software