CVEN 675 Stochastic Hydrology

Professor Anthony Cahill

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)

Examples – Streamflow time series

• USGS has gauging stations throughout US

• We’d like to predict streamflow – estimate flooding, recession, water availability, etc.

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Streamflow time series, cont.

• Difference between streamflow time series and rolling dice – dependence of sequential observations

• Can we model the time series (for understanding)?

Streamflow time series, cont.

• Can we predict the streamflow in future based on past behavior (forecasting)?

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Example – Rainfall time series

• Different than river time series – intermittant in time, but still dependence

Rainfall time series cont.

• Use a different method than streamflow time series for modeling and prediction

Frequency analysis – flood frequency, storm frequency and

extreme values• Change the time period of interest so that

events are independent – usually annual maximum event

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Frequency analysis, cont.

• Used extensively for planning, runoff estimation, etc.

• We are working with rare extreme events

• Need to treat tails carefully

Spatial statistical methods

• Spatial data sets ubiquitous in hydrology– Rain gauge data– Hydraulic conductivity– Soil moisture

Spatial statistics cont.

• Optimal interpolation of point data – “kriging”

• This is both modeling and prediction

• Very useful in GIS – built into ArcGIS (I think)

If time permits…

• Fractals in hydrology

• Stochastic groundwater models

Housekeeping

• Books– Brockwell and Davis, Introduction to Time

Series and Forecasting, 2nd ed.– Isaaks and Srivastava, Applied Geostatistics

• Software– In Brockwell and Davis– I will provide some– You will write some

Class Web Page

• http://ceprofs.tamu.edu/cahill/teaching675.html

• I’ll put stuff up there

• Including syllabus

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%

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– 1st draft – November 19– Final version – December 15

• You can talk to me about project anytime

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