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Groundwater Data Requirement and Analysis

C. P. Kumar

Scientist F

- National Institute of Hydrology
- Roorkee 247667 (India)

Outline

- Introduction
- Data Requirement for Groundwater Studies
- Groundwater Data Acquisition
- Processing of Groundwater Data
- Interpolation of Hydrological Variables
- Geostatistical Analysis using ArcGIS
- Groundwater Data Management and Analysis Tools

Introduction

- Why should we devote resources for assessing

groundwater conditions? - Groundwater is a vital natural resource for our

country - A major source of drinking water and irrigation

water supply - Groundwater baseflow sustains streamflow during

low flow periods - Dependence on groundwater is rapidly increasing
- Theres a lot of stress on groundwater resource

contamination, over-pumping

- Groundwater is an important, but often overlooked

component of the hydrologic cycle - Groundwater and surface water are in reality an

interconnected resource. - Water management decisions that ignore the

contributions of, or impacts to, groundwater are

not sustainable in the long run.

- Accurate and reliable groundwater resource

information (including quality) is critical to

planners and decision-makers. - Huge investment in the areas of ground water

exploration, development and management at state

and national levels aims to meet the groundwater

requirement for drinking and irrigation and

generates enormous amount of data. - We need to focus on improved data management,

precise analysis and effective dissemination of

data.

Data Requirement for Groundwater Studies

ALL GROUND-WATER HYDROLOGY WORK IS MODELING A

Model is a representation of a system.

Modeling begins when one formulates a concept

of a hydrologic system, continues with

application of, for example, Darcy's Law or the

Theis equation to the problem, and may culminate

in a complex numerical simulation.

- The success of any groundwater study, to a large

measure, depends upon the availability and

accuracy of measured/recorded data required for

that study. - Therefore, identifying the data needs and

collection/monitoring of required data form an

integral part of any groundwater exercise. - The first phase of any groundwater study consists

of collecting all existing geological and

hydrological data on the groundwater basin in

question. - Any groundwater balance or numerical model

requires a set of quantitative hydrogeological

data that fall into two categories - Data that define the physical framework of the

groundwater basin - Data that describe its hydrological framework

Physical Framework 1. Topography 2. Geology

3. Types of aquifers 4. Aquifer thickness

and lateral extent 5. Aquifer boundaries 6.

Lithological variations within the aquifer 7.

Aquifer characteristics

Hydrological Framework 1. Water table

elevation 2. Type and extent of recharge areas 3.

Rate of recharge 4. Type and extent of discharge

areas 5. Rate of discharge

- The data required for a groundwater flow

modelling study under physical framework are - Geologic map and cross section or fence diagram

showing the areal and vertical extent and

boundaries of the system. - Topographic map at a suitable scale showing all

surface water bodies and divides. Details of

surface drainage system, springs, wetlands and

swamps should also be available on map. - Land use maps showing agricultural areas.
- Contour maps showing the elevation of the base

of the aquifers and confining beds. - Isopach maps showing the thickness of aquifers

and confining beds. - Maps showing the extent and thickness of stream

and lake sediments. - These data are used for defining the geometry of

the groundwater domain under investigation,

including the thickness and areal extent of each

hydrostratigraphic unit.

- Under the hydrogeologic framework, the data

requirements for a groundwater flow modelling

study are - Water table and potentiometric maps for all

aquifers. - Hydrographs of groundwater head and surface

water levels. - Maps and cross sections showing the hydraulic

conductivity and/or transmissivity distribution. - Maps and cross sections showing the storage

properties of the aquifers and confining beds. - Spatial and temporal distribution of rates of

evaporation, groundwater recharge, groundwater

pumping etc.

Groundwater Data Acquisition

- Some data may be obtained from existing reports

of various agencies/departments, but in most

cases additional field work is required. - The observed raw data obtained from the field may

contain inconsistencies and errors. Before

proceeding with data processing, it is essential

to carry out data validation in order to correct

errors in recorded data and assess the

reliability of a record. - Amongst the hydrologic stresses including

groundwater pumping, evapotranspiration and

recharge, groundwater pumpage is the easiest to

estimate. - Field information for estimating

evapotranspiration is likely to be sparse and can

be estimated from information about the land use

and potential evapotranspiration values. - Recharge is one of the most difficult parameters

to estimate.

- Values of transmissivity and storage coefficient

are usually obtained from data generated during

pumping tests and subsequent data processing. - For modelling at a local scale, values of

hydraulic conductivity may be determined by

pumping tests if volume-averaged values are

required. - In the field, in-situ hydraulic conductivity may

be measured by Guelph Permeameter. - For unconsolidated sand-size sediment, hydraulic

conductivity may be obtained from laboratory

permeability tests using permeameters. - Laboratory analyses of core samples tend to give

lower values of hydraulic conductivity than are

measured in the field.

- Monitoring of Groundwater Levels
- A network of observation wells and/or piezometers

are established to obtain data on the - - Depth and configuration of the water table
- Direction of groundwater movement
- Location of recharge and discharge areas
- In any drainage investigation, the highest and

the lowest water table positions, as well as the

mean water table during a hydrological year are

important. - For this reason, water level measurements should

be made at frequent intervals. The interval

between readings should preferably not exceed one

month. - All measurements in a study area should, as far

as possible, be made on the same day because this

gives a complete picture of the water table.

- Monitoring of Groundwater Quality
- The objectives of the water quality monitoring

network are to - Detect water quality changes with time
- Identify potential areas that show rising trend
- Detect potential pollution sources
- Study the impact of land use and

industrialization on groundwater quality - Substantial costs are incurred to obtain and

analyze samples. Field costs for drilling,

installing, and sampling monitoring wells and

laboratory costs for analyzing samples are not

trivial. - Comprehensive data analysis and evaluation by a

knowledgeable professional should be the final

quality assurance step .

- The frequency of sampling required in a

ground-water-quality monitoring program is

dictated by the expected rate of change in the

concentrations of chemical constituents. - For monitoring concentrations of major ions and

nutrients, and values of physical properties of

ground water, twice yearly sampling should be

sufficient. - More frequent sampling should be considered if

the types and conditions of any upgradient

sources of these compounds are changing. - Monitoring of ground-water quality should be a

long-term activity.

Processing of Groundwater Data

Processing of Groundwater Data

- Before any conclusions can be drawn about the

cause, extent, and severity of an areas

groundwater related problems, the raw groundwater

data on water levels and water quality have to be

processed. - This data then have to be related to the geology

and hydrogeology of the area. The results,

presented in graphs, maps, and cross-sections,

will enable a diagnosis of the problems. - The following graphs and maps have to be prepared

that are discussed hereunder - Groundwater hydrographs
- Water table-contour map
- Depth-to-water table map
- Water table-fluctuation map
- Head-differences map
- Groundwater-quality map
- A proper interpretation of groundwater data,

hydrographs, and maps requires a coordinate study

of a regions geology, soils, topography,

climate, hydrology, land use, and vegetation.

Groundwater Hydrographs

- When the amount of groundwater in storage

increases, the water table rises when it

decreases, the water table falls. This response

of the water table to changes in storage can be

plotted in a hydrograph. - Groundwater hydrographs show the water-level

readings, converted to water levels below ground

surface, against their corresponding time. - A hydrograph should be plotted for each

observation well or piezometer. It is important

to know the rate of rise of the water table, and

even more important, that of its fall.

July Aug Sept Oct Nov Dec Jan

Feb Mar Apr May June

- Groundwater hydrographs also offer a means of

estimating the annual groundwater recharge from

rainfall. This, however, requires several years

of records on rainfall and water tables. - An average relationship between the two can be

established by plotting the annual rise in water

table against the annual rainfall. - Extending the straight line until it intersects

the abscissa gives the amount of rainfall below

which there is no recharge of the groundwater.

Any quantity less then this amount is lost by

surface runoff and evapotranspiration.

Water Table Contour Map

- A water table - contour map shows the elevation

and configuration of the water table on a certain

date. - To draw the water table-contour lines, we have to

interpolate the water levels between the

observation points, using the linear

interpolation method. - A proper contour interval should be chosen,

depending on the slope of the water table. For a

flat water table, 0.25 to 0.50 m may suit in

steep water table areas, intervals of 1 to 5 m or

even more may be needed to avoid overcrowding the

map with contour lines. - A water table-contour map is an important tool in

groundwater investigations because, from it, one

can derive the gradient of the water table

(dh/dx) and the direction of groundwater flow,

which is perpendicular to the water table-contour

lines.

- The topographic base map should contain contour

lines of the land surface and should show all

natural drainage channels and open water bodies. - For the given date, the water levels of these

surface waters should also be plotted on the map.

Only with these data and data on the land surface

elevation can water table contour lines be drawn

correctly.

- For a proper interpretation of a water

table-contour map, one has to consider not only

the topography, natural drainage pattern, and

local recharge and discharge patterns, but also

the subsurface geology. - More specifically, one should know the spatial

distribution of permeable and less permeable

layers below the water table. - For instance, a clay lens impedes the downward

flow of excess irrigation water or, if the area

is not irrigated, the downward flow of excess

rainfall. A groundwater mound will form above

such a horizontal barrier.

Depth-to-Water Table Map

- A depth-to-water table map shows the spatial

distribution of the depth of the water table

below the land surface. A suitable contour

interval may be 50 cm. - The regions of map where the groundwater level is

between 0-2 m depicts the area having drainage

problems. - Based on measurement results for a year, the map

drawn using the lowest water table levels

indicates to which extent the groundwater falls

in a year. - The section where the water table level is

between 0-1 m determines the areas in which

groundwater exists in the root-zone throughout a

year. - The depth and shape of the first impermeable

layer below the water table strongly affect the

height of the water table.

Water Table - Fluctuation Map

- A water table - fluctuation map is a map that

shows the magnitude and spatial distribution of

the change in water table over a period (e.g. a

season or a whole hydrological year). - A water table-fluctuation map is a useful tool in

the interpretation of drainage problems in areas

with large water table fluctuations. - The change in water table in fine-textured soils

will differ from that in coarse-textured soils,

for the same recharge or discharge.

Head - Differences Map

- A head-differences map is a map that shows the

magnitude and spatial distribution of the

differences in hydraulic head between two

different soil layers. - We calculate the difference in water level

between the two piezometers, and plot the result

on a map. After choosing a proper contour

interval (e.g. 0.10 or 0.20 m), we draw lines of

equal head difference. - The map is a useful tool in estimating upward or

downward seepage.

Groundwater - Quality Maps

- A groundwater-quality map (for example,

electrical-conductivity map) is a map that shows

the magnitude and spatial variation in the

salinity of the groundwater. - The EC values of all representative wells (or

piezometers) are used for this purpose. - Groundwater salinity varies not only horizontally

but also vertically. It is therefore advisable to

prepare an electrical-conductivity map not only

for the shallow groundwater but also for the deep

groundwater. - In electrical conductivity maps, critical

groundwater salinity is taken as 5000

micromhos/cm, although it changes according to

species of the crop to be grown.

- By plotting all the EC values on a map, lines of

equal electrical conductivity (equal salinity)

can be drawn. Preferably the following limits

should be taken less than 100 micromhos/cm, 100

to 250 250-750 750 to 2500 2500 to 5000 and

more than 5000. Other limits may, of course, be

chosen, depending on the salinity found in the

waters. - Other types of groundwater-quality maps can be

prepared by plotting different quality parameters

(e.g. Sodium Adsorption Ratio (SAR) values). - The groundwater in the lower portions of coastal

and delta plains may be brackish to extremely

salty, because of sea-water encroachment. - In the arid and semi-arid zones, shallow water

table areas may contain very salty groundwater

because of high rates of evaporation. Irrigation

in such areas may contribute to the salinity of

the shallow groundwater through the dissolution

of salts accumulated in the soil layers.

Interpretation of Hydraulic Head and Groundwater

Conditions

Measurements of hydraulic head, normally achieved

by the installation of a piezometer or well

point, are useful for determining the directions

of groundwater flow in an aquifer system.

In the above figure, three piezometers installed

to the same depth enable the determination of the

direction of groundwater flow and, with the

application of Darcys law, the calculation of

the horizontal component of flow.

In the above figure, two examples of piezometer

nests are shown that allow the measurement of

hydraulic head and the direction of groundwater

flow in the vertical direction to be determined

either at different levels in the same aquifer

formation or in different formations.

Interpolation of Hydrological Variables

- A fundamental problem of Hydrology is that our

models of hydrological variables assume

continuity in space (and time), while

observations are done at points. - The elementary task is to estimate a value at a

given location, using the existing observations.

- Hydrological data have variability in space and

time. - Spatial variability is observed by a sufficient

number of stations - Time variability is observed by recording time

series - Spatial variability can be in different range of

values or in different temporal behaviour - A continuous field v v(x,y,z,t) is to be

estimated from discrete values vi v(xi,yi,zi,ti)

- Global estimation characteristic value for area
- Point estimation estimation at a point P

P(x,y) - We need data AND a conceptual model, how these

data are related, (i.e. a conceptual model of the

process) - If the process is well defined, only few data are

needed to construct the model

Example

- A groundwater table in a confined, homogeneous,

isotropic aquifer under steady state discharge

from a well is described by the Thiem well

formula. - Theoretically, the observation of two groundwater

heads at different distances from the well is

sufficient to reconstruct the complete

groundwater surface.

- Hydrological variables are random and uncertain ?

Geostatistical Methods - Mostly 2D consideration ? v v(x,y,t)

Regionalisation and Interpolation

- Regionalisation Identification of the spatial

distribution of a function g, depending on local

information as well as by transfer of information

from other regions by transfer functions. - Regionalisation therefore means to describe

spatial variability (or homogeneity) of - Model parameters
- Input variables
- Boundary conditions and coefficients

- Regionalisation includes the following tasks
- Representation of fields of hydrological

parameters and data (contour maps) - Smoothing spatial fields
- Identification of homogeneous zones
- Interpolation from point data
- Transfer of point information from one region to

others - Adaptation of model parameters for the transfer

from point to area

Interpolation

- Given z z(x,y) at some points we want to

estimate z0 at (x0, y0)

- Weighted linear combination -
- The methods differ in the way how they establish

the weights.

Global and Local Interpolation

- An interpolation method is working globally, if

all data points are evaluated in the

interpolation. - Local interpolation techniques use only data

points in a certain neighbourhood of the

estimated point.

Deterministic or Statistical Interpolation

- Deterministic methods attempt to fit a surface of

given or assumed type to the given data points - Exact
- Smoothing
- Statistical (stochastic) methods

Choice of Interpolation Method

- Depends primarily on the nature of the variable

and its spatial variation. - Examples Rainfall, groundwater, soil physical

properties, topography

Example Groundwater Data

- Groundwater tables have smooth surface, but

trend! - Hydrogeological information is highly random, has

faults, few points with good data

Deterministic Interpolation Methods

- Polynomials
- Spatial join (point in polygon)
- Thiessen polygons
- TIN and linear interpolation
- Spline
- Inverse Distance Weighting (IDW)

Polynomials

- General
- Plane
- Second Order
- Number of coefficients
- Over- and undershoots

Spatial Join (point in polygon)

- Assign spatial properties by spatial join

Thiessen Polygons

- Thiessen polygons
- A point in the domain receives the value of the

closest data point - Step-wise function

Interpolation of elevation surface using Thiessen

Polygons

TIN and Linear Interpolation

- Surface is approximated by facets of plane

triangles - Continuous surface, but discontinuous 1st

derivative

Splines

- Spline estimates values using a mathematical

function that minimizes overall surface

curvature, resulting in a smooth surface that

passes exactly through the input points. - Conceptually, it is like bending a sheet of

rubber to pass through the points while

minimizing the total curvature of the surface.

Inverse Distance Weighting (IDW)

- Default method in many software packages b 2
- Controlled by exponent b

Stochastic (Geostatistical) Interpolation

- Analysis of the spatial correlation in the random

component of a variable - Optimum determination of weights for interpolation

Semi-variance

- Regionalized variable theory uses a related

property called the semi-variance to express the

degree of relationship between points on a

surface. - The semi-variance is simply half the variance of

the differences between all possible points

spaced a constant distance apart.

(Semi-variance is a measure of the degree of

spatial dependence between samples(

- Semi-variance The magnitude of the semi-variance

between points depends on the distance between

the points. A smaller distance yields a smaller

semi-variance and a larger distance results in a

larger semi-variance.

Calculating the Semi-variance (Regularly Spaced

Points(

- Consider regularly spaced points distance (d)

apart, the semi-variance can be estimated for

distances that are multiple of (d) (Simple form)

Semi-variance

- Zi is the measurement of a regionalized variable

taken at location i , - Zih is another measurement taken h intervals

away - Nh is number of points

Semi-variogram

- The plot of the semi-variances as a function of

distance from a point is referred to as a

semi-variogram or variogram.

- Sill The point at which the semi-variance

approaches a flat region. Sill defines the level

of maximum variability. - Range The range or span defines a neighborhood

within which all data points are related to one

another.

Semi-variogram

- The semi-variance at a distance d 0 should be

zero, because there are no differences between

points that are compared to themselves. - However, as points are compared to increasingly

distant points, the semi-variance increases.

Semi-variogram

- The range is the greatest distance over which the

value at a point on the surface is related to the

value at another point. - The range defines the maximum neighborhood over

which control points should be selected to

estimate a grid node.

Characteristics of the Semi-variogram (and

therefore of the data)

Nugget variance at zero distance which should

be zero but isnt Range Distance at which max.

variance is reached (data considered

decorrelated) Sill Level of max.

variability Anisotropy might thus be manifested

by varying range with direction (constant sill

so-called geometric anisotropy). This is observed

with the elevation data.

- Experimental semi-variogram
- Things nearby tend to be more similar than things

that are farther apart

- Theoretical semi-variogram fit function through

empirical semi-variogram

Variogram - Spherical

- It is a model semi-variogram and is usually

called the spherical model. - a is called the range of influence of a sample.
- C is called the sill of the semi-variogram.

Variogram - Exponential

Spherical and Exponential with the same range and

sill

Spherical and Exponential with the same sill and

the same initial slope

Semi-variogram from ArcGIS

Interpolation by Kriging

- Kriging is named after the South African

engineer, D. G. Krige, who first developed the

method. - Kriging uses the semi-variogram, in calculating

estimates of the surface at the grid nodes.

Interpolation by Kriging

- Kriging goes through a two-step process
- Variograms and covariance functions are created

to estimate the statistical dependence (called

spatial autocorrelation) values, which depends on

the model of auto-correlation (fitting a model), - Prediction of unknown values

- Kriging yields the estimated value AND the

estimation variance

Standard deviation of estimated conductivity

Estimated conductivity

Interpolation of elevation surface using Kriging

Geostatistical Analysis using ArcGIS

- A linkage between GIS and spatial data analysis

is considered to be an important aspect

to explore and analyze spatial relationships. The

GIS methodology for the spatial analysis of

the groundwater levels involves the following

steps - (a) Exploratory spatial data analysis (ESDA)

using ArcGIS software for the data (e.g.

groundwater level) to study the following - Data distribution
- Global and local outliers
- Trend analysis
- (b) Spatial interpolation for data using ArcGIS

software, while kriging is applied by involving

the following procedures - Semivariogram and covariance modelling
- Model validation using cross validation
- Surfaces generation of the groundwater level data

Flow Chart of the Geostatistical Analysis Steps

Groundwater Data Management and Analysis Tools

Following are some of the software packages used

for groundwater data management and

analysis. AquaChem AquaChem is an integrated

software package developed specifically for

graphical and numerical analysis of geochemical

data sets. AquaChem also includes a direct link

to the popular PHREEQC program for geochemical

modeling. AquiferTest Pro Graphical analysis and

reporting of pumping test and slug test

data. EnviroInsite EnviroInsite is a desktop,

groundwater visualization package for analysis

and communication of spatial and temporal trends

in multi-analyte, environmental groundwater data.

GW Contour Data interpolation and contouring

program for groundwater professionals that also

incorporates mapping velocity vectors and

particle tracks. HydroGeo Analyst Groundwater

and borehole data management and visualization

technology. RockWorks Geological data

management, analysis visualization.

Thank You !!!

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