GRAD COURSE

DATA PROCESSING AND ANALYSIS IN HYDROGEOLOGY (GEOSTATISTICS)

Instructor:

Miriam Rios-Sanchez

Dow 402

mriossan@mtu.edu

487-3098

Office Hours: By Appointment

Text: No text book required

Software: The following programs are going to be used in this course like:

Spreadsheet

Surfer

Arc-Gis

Geoeas

Objective

Hydrogeological variables are unique in the sense that aquifers and groundwater systems are dinamic which means they are in constant change. The geological nature of them and the interaction of groundwater with superficial water and with the rocks makes them to show variations in space (i.e variation of permeability due to changes in lithology or the change on water heads because of differential of potential) as well as in time (water level variations due to seasonal changes). Many of them are time/space dependent.

There are many ways to represent this variables and this course pretend to show the students the most common tools abd how to use them.

The objective of this class is to facilitate students:

. The learning of the tools and techniques currently available to analyze hydrogeology data

. Use these tools to provide solutions to some common problems like presenting data and mapping parameters

. The use of them to design groundwater monitoring networks

Class Attendance

Since most of the classes are designed to clarify concepts, attendance at all lectures is expected.

I am more than willing to pass on lecture notes and meet with you to make up the hands-on-exercises.

Grade Guidelines

Lab reports are worth 50%, half of them are going to be in group. The class project will be worth 30%

and the lab practical 20%. The lab practical will be conducted during the last week of classes during the lab session and will involve solving a resource management problem.

Course Prerequisites

Skills and knowledge are expected in the following areas: basic hydrogeology, basic statistics, both univariate and multivariate, word processing, spreadsheets, presentation skills, basic computer skills (moving, creating and deleting files, managing large numbers of files, basic Microsoft workstation commands). If you need help in any of these areas, please let me know ASAP.

Structure of the course

Since this course is meant to be a learning centered course a major involvement if students is expected. For each class, except for week 1, reading material is going to be provided for reading and analysis to before the class. The class is meant to explain in detail some of the most difficult concepts and to go through some examples.

For the labs a set of exercises are going to be provided so each student can choose one of them to solve. The Lab report should include a summary of the steps used to come up with the answers.

SYLLABUS

Week 1. - Introduction: why spatial analysis?

- Characteristics of hydrogeological phenomena

spatial behavior, temporal characteristics of hydrogeology phenomena and spatial/temporal phenomena.

Week 2. - Examples of analysis of hydrogeology data

- Classic statistics (Univariate, Bivariate, Multivariate)

Week 3 - Time series

Week 4 - Spatial analysis (interpolation, extrapolation, spatial description)

Week 5 - The process of interpolation and extrapolation and measurement of errors.

Week 6. - Spatial estimation using kriging

Week 7. - The use of variograms as a tool to analyze hydrogeological variables

Week 8. Analyzing hydrogeological variables

- Case I: Water quality parameters (chemistry)

. What are we looking for when analizyng chemistry data?

. Analysis of single parameters

Week 9. . Bivariate Analysis of chemical parameters

. Multivariate Analysis of chemical parameters

Week 10 . Geostatistical Analysis and Mapping of chemical parameters

Week 11. Modeling hydrogeology variables

- Case II. Analysis of water levels

. The purpose of analyzing water levels: flow calculation, flow systems, water budgets, inputs for vulnerability analysis

. Univariate statistics

Week 12. . Bivariate statistics (correlation with parameters such as topography, rainfall, etc)

. Geostatistical analysis and Mapping of water levels

Week 13. - Case III. Time series analysis

. Purpose of analyzing time series

. Tools for analyzing time series

. Basic characteristics of time series

. Modeling stationary time series

. Modeling non-stationary time series

Week 14. Applications of data analysis to groundwater monitoring

Network density for estimating Global Mean

Monitoring of diffusive pollution

Monitoring of waste disposal sites

Determination of sampling frequency for water level monitoring