JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
APRIL
AMERICAN WATER RESOURCES ASSOCIATION
2004
DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER
RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL IN TAIWAN1
Chen Wuing Liu2
ABSTRACT: Ground water is a vital water resource in the
Choushui River alluvial fan in Taiwan. A significantly increased
demand for water, resulting from rapid economic development, has
led to large scale ground water extraction. Overdraft of ground
water has considerably lowered the ground water level, and caused
seawater intrusion, land subsidence, and other environmental damage. Sound ground water management thus is essential. This study
presents a decision support system (DSS) for managing ground
water resources in the Choushui River alluvial fan. This DSS integrates geographic information, ground water simulation, and
expert systems. The geographic information system effectively analyzes and displays the spatially varied data and interfaces with the
ground water simulation system to compute the dynamic behavior
of ground water flow and solute transport in the aquifer. Meanwhile, a ground water model, MODFLOW-96, is used to determine
the permissible yield in the Choushui River alluvial fan. Additionally, an expert system of DSS employs the determined aquifer permissible yield to assist local government agencies in issuing water
rights permits and managing ground water resources in the
Choushui River alluvial fan.
(KEY TERMS: decision support system; expert system; ground
water management; geographic information system; permissible
yield.)
the Peikang River to the south. The alluvial fan has
an area of around 1,800 km2 and is partitioned primarily into proximal-fan, mid-fan, and distal-fan
areas. The unconsolidated sediment underlying the
alluvial fan contains abundant ground water and is of
the late Quaternary age.
Liu, Chen Wuing, 2004. Decision Support System for Managing Ground Water
Resources in the Choushui River Alluvial Fan in Taiwan. Journal of the American Water Resources Association (JAWRA) 40(2):431-442.
INTRODUCTION
The Choushui River alluvial fan is located on the
western coast of Taiwan, and covers the plain containing Chang-Hwa, Yun-Lin, and northern Chia-Yi
Counties (Figure 1). The alluvial fan is enclosed by
the Taiwan Strait to the west, the Wu River to the
north, Dulliu Hill and Baguah Mount to the east, and
Figure 1. Location of the Choushui River Alluvial Fan in Taiwan.
1Paper No. 02116 of the Journal of the American Water Resources Association (JAWRA) (Copyright © 2004). Discussions are open until
October 1, 2004.
2Professor, Department of Bioenvironmental Systems Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan 10617, R.O.C. (E-Mail: lcw@gwater.agec.ntu.edu.tw).
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
431
JAWRA
LIU
Between 1992 and 1998, the government implemented a seven-year comprehensive ground water
monitoring network plan to investigate the hydrogeological characteristics of the major ground water systems in Taiwan. The new ground water monitoring
network in the Choushui River alluvial fan was established as part of this plan. The network includes 77
hydrogeological investigation stations and 188 ground
water monitoring wells in different aquifers (Taiwan
Sugar Company, 1997).
Subsurface hydrogeological analysis to a depth of
approximately 300 m can be divided into six interlayering sequences, including three marine sequences
and three nonmarine sequences, in the distal-fan
and the mid-fan areas. Generally, the nonmarine
sequences, with coarse sediment sizes, ranging from
medium sand to highly permeable gravel, can be considered as aquifers, while the marine sequences with
fine sediment sizes, ranging from clay to low permeability fine sand, can be considered as aquitards (Figure 2). Meanwhile, the hydrogeological formation of
the proximal fan, which is composed entirely of gravel
and sand, is regarded as an unconfined aquifer. The
proximal fan is a major region for aquifer recharging.
exceeding the safe yield for the aquifer. Ground water
overdraft has caused serious environmental problems,
including seawater intrusion, ground water salinization and land subsidence (Water Resources Bureau,
2001; Gau and Liu, 2002). Figure 3 displays measured
ground water head contours in Aquifers 1, 2, and 3 in
1999, indicating that the ground water heads of the
three aquifers on the southwestern coast of the
Choushui River alluvial fan are all below sea level.
The southwestern coast corresponds to the most serious seawater intrusion and land subsidence area in
the Choushui River alluvial fan.
The ground water monitoring network provides
valuable hydrogeological information concerning the
Choushui River alluvial fan. Detailed hydrogeological
data are useful for setting up accurate models for simulating dynamic aquifer system behavior. The established ground water flow model combined with
geographic information and expert systems can be
integrated to establish a decision support system
(DSS) for effectively managing ground water
resources and preventing further environmental deterioration in the Choushui River alluvial fan.
A DSS builds a decision model using the analytical
method, and is optimized with an interactive computer program. The model helps decision makers assess
the feasibility, impact, and selection of alternative
solutions and make appropriate decisions. A DSS provides a range of tools to allow user defined evaluation
of scenario results, as well as explanations and supporting information for elucidating ecological modeling. Alternative solutions are based on information,
data, and expert knowledge. Such alternative solutions are required for solving large and nonstructural
problems (Andriole, 1989). Water resource management using a DSS has grown rapidly following recent
advances in computer processors, operational systems, and user friendly interfaces (Loucks, 1991;
Adelman, 1992; Fedra, 1993; Endreny and Jenning,
1999; Young et al., 2000; Koutsoyiannis et al., 2002).
However, successful application of a DSS in the field
remains limited.
Andreu et al. (1991) integrated simulation and
optimization models to assess the conjunctive use of
the Segura River in Spain. The DSS model, which
includes an interactive and automatic graphical display system, allows decision makers to analyze a set
of alternative solutions. Stansbury et al. (1991) combined a ground water/surface water simulation model,
response analytical model using a geographic information system (GIS), and multiobjective decision
model to formulate a DSS to evaluate water transfer.
The DSS was applied to evaluate the social, economic
and environmental impact of water transfer in
Nebraska in the United States.
Figure 2. Conceptual Hydrogeologic Profile
of the Choushui River Alluvial Fan.
Long term average amounts of pumped and
recharged ground water from 1970 to 1990 were 1.326
and 1.024 billion m3/yr, respectively. This statistic
indicates substantial ground water overdrafting from
the aquifers (Central Geological Survey, 1999).
Ground water levels fell significantly from 1970 to
1995 and rebounded slightly after 1996. Ground
water overdraft is caused mainly by illegal fishpond
wells, densely located in the coastal area, and
the over issuing of ground water rights permits,
JAWRA
432
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL FAN IN TAIWAN
Figure 3. Ground Water Head Contours (m) of the Choushui River Alluvial Fan
in 1999: (1) Aquifer 1, (b) Aquifer 2, and (3) Aquifer 3.
Endreny and Jennings (1999) described a DSS that
was designed to efficiently perform data combination
and evaluate the potential benefits of reducing standard error in surface water quality estimates. By
quantifying how data augmentation changes the spatial coarseness of the monitoring network and accuracy estimates, a DSS generates information required
by decision makers. Young et al. (2000) developed a
DSS for river flow ecology assessment in the MurrayJOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
Darling Basin in Australia. The DSS used the
RAISON shell (Lam et al., 1994) and integrated various simple riverine ecology models that can qualitatively and quantitatively represent the response of
different aspects of instream and flood plain ecology
depending on river flow regime. Koutosyiannis et al.
(2002) described a DSS for water resources management focused on multipurpose reservoir systems. This
DSS was applied to two of the most complicated
433
JAWRA
LIU
yield valuable decision making information. The
developed DSS comprises three modules: the GIS
module, the ground water simulation module, and the
expert system module. Figure 4 illustrates the structure of the DSS for managing ground water resources.
The functions of the three modules are described
below.
hydrosystems in Greece, demonstrating that a suitable system configuration could accomplish various
and contradictory objectives and assure sustainable
development of sensitive river and estuary ecosystems.
This study presents a DSS for managing ground
water resources in the Choushui River alluvial fan in
Taiwan. The DSS developed here integrates GIS, the
simulation model, and an expert system, and helps
local governmental agencies manage ground water
resources effectively. The MODFLOW-96 (Harbaugh
and McDonald, 1996) ground water simulation model
is used to determine the permissible yield in the
Choushui River alluvial fan. Issuance of water rights
permits by local governmental officers is used as an
example to illustrate the effectiveness of the DSS.
GIS Module
The system adopts the GIS as the kernel of the
user interface. GIS is superior to conventional data
management software in that it links spatial and
attribute data and includes query and display capabilities. The GIS has powerful display and analysis
functions. The open structure allows users easily to
integrate the module with other modules. Additionally, the spatial data structure links with other data
banks to extend the analytical capability including
graphical displays and statistical analysis of hydrographs, contour plots, descriptive statistics, and geostatistics. GIS not only offers two-dimensional display
but also provides three-dimensional versatile analysis
and display.
SYSTEM DEVELOPMENT
The DSS developed here mainly focuses on supporting decision makers in managing ground water
resources. The system includes a complete data bank
and employs the advanced tools of GIS, the ground
water simulation model, and the expert system to
Figure 4. Structure of the Decision Support System.
JAWRA
434
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL FAN IN TAIWAN
GIS uses the Internet to gather data from other
agencies and to search and display required user
information. The DSS described here uses the GIS
module to illustrate an interface that interacts with
simulation and expert system modules for data transmission. The GIS module calls other modules to perform analysis or simulation, and then transfers the
analytical results in a binary format to update the
data bank.
namely – knowledge base, inference engine, and user
interface. The inference engine is adopted from the
commercial software Visual Rule Studio (Durkin,
1994), and performs forward, backward, and hybrid
chaining inference. Moreover, the knowledge base is
built using the opinions of experts in the field with
the Rule Adjuster being used to summarize system
knowledge.
Ground Water Simulation Module
The DSS not only offers appropriate suggestions
based on the analytical results, but also conducts
ground water flow and transport simulations to
determine how various ground water resources management schemes affect the analysis of the expert
system. The ground water simulation module used
in this study is the Processing Modflow version 5.3
(Chiang and Kinzelbach, 1998), and includes the
ground water flow model, MODFLOW-96 (Harbaugh
and McDonald, 1996); contaminant transport model,
MT3D-96 (Zheng, 1996); and land subsidence model,
INTERBED (Leake and Prudic, 1991) a module of
MODFLOW. The ground water simulation model simulates the dynamic flow of ground water, solute transport, and land subsidence caused by overpumping of
ground water. Users can input the in situ boundary
and initial conditions, including pumping rate, precipitation, ground water level, and evapotranspiration,
to simulate changes in ground water level, drawdown
head, permissible yield, solute movement, and land
subsidence. The model results are useful for assessing
how individual factors influence ground water systems. The spatial data used in the simulation and the
computed result can be transferred back to the GIS
module for post processing and visual display. The
computed flow field also can serve as input data for
the MT3D-96 solute transport and the INTERBED
land subsidence models.
Figure 5. General Layout of the Expert System.
SYSTEM APPLICATIONS
When users log on to the DSS, the system provides
detailed ground water hydrogeological data, a simulated analysis, a comprehensive graphic display, and
expert decision support. The DSS effectively accelerates decision processing and facilitates decision
making. The DSS presented here incorporates the following features:
• Five coordinate input options for positioning the
geographic window.
• Attribute querying using spatial data.
• Graphical display of temporal variation of hydrological parameters.
• Descriptive statistical analysis of observed data.
• Construction of contour lines using statistical
interpretation.
• User friendly interface with the simulation
model.
• Linking the simplified version of the simulation
model via the interface of the GIS module.
Expert System
The GIS and simulation modules only provide casespecific analytical results without comprehensive
expert advice. The expert system fills this gap. Based
on user needs, the expert system, with a knowledge
base and an inference engine, offers integrated expert
opinions regarding water resource management. Decision makers use this information to establish a sound
ground water resource management plan.
Figure 5 presents the general layout of an expert
system. The system comprises three main parts,
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
435
JAWRA
LIU
• Linking the professional version of the Processing Modflow simulation system with the interface of
the GIS module.
• Offering expert advice and suggestions regarding issuing water rights permits and helping local
government agencies to effectively manage ground
water resources.
than in dry years. This study classifies wet, average
and dry years based on annual precipitation data
from 1990 to 1999 (Central Weather Bureau, 19901999). Using Weibull’s method, the exceedence probability curves of precipitation at 75 percent, 50 percent
and 25 percent, denote the precipitation corresponding to wet, average, and dry years, respectively. The
identified wet, average and dry years are 1994, with
precipitation of 2,052 mm; 1997, with precipitation of
1,805 mm; and 1991, with precipitation of 1,307 mm.
These data provide the initial conditions for the
MODFLOW-96 simulation.
The MODFLOW-96 model is first calibrated using
the metrological and ground water level data of 1997
and adjusting local pumping rates to match ground
water levels to the field measurements. The calibrated model then performs a simulation to obtain the
relationship of pumping rate to drawdown for wet,
average, and dry hydrological years. The Hill method,
which plots simulated pumping rate against drawdown, is employed to determine the permissible yield
of each aquifer, which is defined as the determined
annual ground water pumping rates with zero drawdown of the corresponding aquifer. Figure 6 illustrates the determined wet year permissible yield,
181 x 106 m3/yr, of the first aquifer in Yun-Lin by the
Hill method. The estimated permissible yields of
other aquifers in the Yun-Lin and Chang-Hwa Counties can be obtained by the same procedures. Figure 7
summarizes the procedures used to determine the
permissible yield. Moreover, the permissible yields
determined for the Choushui River alluvial fan in dry,
average, and wet years are given in Table 1. The
determined permissible yields in the dry, average, and
wet years are 0.86 x 109, 0.96 x 109, and 1.20 x 109
m3/years, respectively, for the Choushui River alluvial
fan. The safe yield of 1.1 x 109 m3/years estimated by
Shen (1991) corresponds to the wet year permissible
yield, whereas the safe yield of 0.90 x 109 m3/years
determined by Yeh and Yang (1998) falls within the
permissible yields of dry and average years. The permissible yields in Yun-Lin County are generally much
higher than those in Chang-Hwa County. Aquifers 1,
2-1, 2-2, and 3 evenly supply the ground water for
Yun-Lin County, whereas Aquifer 1 is the primary
source of ground water supply for Chang-Hwa County. Finally, Table 2 lists the permissible yields for typical wet hydrological years determined for 20
townships in Yun-Lin County. The Townships of 1, 8,
and 20, which are all located in the coastal area, have
high permissible yields, indicating the southwestern
distal fan area contains abundant ground water. However, this coastal zone also corresponds to the most
serious seawater intrusion and land subsidence area,
mainly caused by the overdraft of ground water.
Proper management of the ground water resources
The application of the ground water simulation
model and expert system of the DSS are described
below.
Groundwater Simulation Model for Determining
Permissible Yield
The ground water simulation model is used as a
kernel of the simulation module. The simulation
model interactively exchanges with GIS data banks.
The GIS module utilizes the data and converts them
into a binary or specific format as input parameters in
the simulation model, and vice versa.
By inputting different initial and boundary conditions, the models can perform scenario analysis on
ground water level and drawdown. This study applies
the ground water simulation model of MODFLOW-96
to determine the permissible yield of the Choushui
River alluvial fan. The Choushui River alluvial fan
has suffered from excessive ground water extraction
from 1970 to 1995. The large extraction has created
serious adverse impacts and damaged the surrounding environment. Determination of the permissible
pumping yield for the ground water aquifer thus
becomes imperative.
The permissible ground water pumping yield is
taken to be the maximum possible extraction compatible with maintaining stable supply in an area. Lee
(1915) defined safe yield as the quantity of water that
can be regularly extracted over the long term without
dangerously depleting storage reserves. The general
definition of safe yield is the amount of water that can
be withdrawn from an aquifer without lowering average ground water levels. According to this definition,
various constant safe yields have been proposed for
the Choushui River alluvial fan. Shen (1991) used the
water balance method to estimate a safe yield of 1.1 x
10 9 m 3 /year. Similarly, Yeh and Yang (1998) used
MODFLOW to simulate variation in ground water
levels and estimated a safe yield of 0.9 x 109 m3/year.
However, the safe yield for a given area may not be
constant (Domenico and Schwartz, 1990), and may
vary with ground water recharge, which itself is closely related to precipitation. Rainwater recharge into a
ground water aquifer is greater in a wet year than in
a dry year. The safe yield thus is higher in wet years
JAWRA
436
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL FAN IN TAIWAN
using the DSS is essential to the Choushui River alluvial fan.
The determined permissible yields of different
townships in the Choushui River alluvial fan for wet,
average, and dry hydrological years are stored in the
GIS data bank and can be easily retrieved for subsequent use to issue water rights permits.
Figure 6. Estimated Wet Year Permissible Yield
of the First Aquifer in Yun-Lin.
Figure 7. Procedure for Determining the Permissible Yield.
Expert System for Issuing Water Rights Permits
The engineering factors considered are: permissible
yield, ground water level and drawdown, land subsidence, seawater intrusion, and ground water quality.
A questionnaire dealing with granting or declining
an application for a water rights permit was prepared
and mailed to local experts. A knowledge based rule
was established in the expert system based on the
answers and opinions by the local experts. Permits
granted are classified into regular and temporary permits. Unless applicants specifically request a temporary permit (for example, for dewatering during
engineering excavations), they are assumed to be
applying for a regular permit. Furthermore, only temporary permits are granted to applicants seeking to
Water rights permit issuing is a complex task
involving engineering, economic, political, social,
legal, and environmental considerations. Except for
the legal and engineering aspects, these aspects are
subject to the interests of various groups and are very
difficult to assess. As such, the expert system for issuing water rights considers only engineering and legal
aspects. An expert suggestion based on system analysis is rational and objective.
The legal factors considered are: hydraulic law and
its implementation regulations, the Groundwater
Control Act of Taiwan, Irrigation Management Regulations of Taiwan, and the Drinking Water Act.
TABLE 1. Determined Permissible Yield of the Choushui River Alluvial Fan.
Hydrological
Year
Dry
Average
Wet
County
Aquifer 1
Yun-Lin
Chung-Hwa
Yun-Lin
Chang-Hwa
Yun-Lin
Chang-Hwa
60
171
130
207
181
281
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
Permissible Yield (in 106 m3/year)
Aquifer 2-1
Aquifer 2-2
228
21
233
25
252
41
437
150
32
158
13
173
41
Aquifer 3
∑
162
40
164
42
181
50
600
264
687
277
787
414
JAWRA
LIU
TABLE 2. Estimated Wet Year Permissible Yield of 20 Townships in Yun-Lin County (in 106 m3/year)
∑ (1)+(2-1)+2-2)+(3)
Determined
Percentage
(percent)
Township
Aquifer 1
Aquifer 2-1
Aquifer 2-2
Aquifer 3
01*
27.6
38.3
26.4
27.6
119.9
15.22
02*
6.0
8.3
5.7
6.0
26.0
3.29
03
14.2
19.7
13.6
14.2
61.7
7.83
04
8.6
12.0
8.3
8.6
37.5
4.77
05
3.2
4.4
3.0
3.2
13.6
1.74
06
1.5
2.1
1.4
1.5
6.5
0.83
07
8.2
11.4
7.9
8.2
35.7
4.53
08
18.2
25.3
17.4
18.2
79.1
10.03
09
8.2
11.4
7.8
8.2
35.6
4.51
10*
5.8
8.0
5.5
5.8
25.1
3.19
11*
4.5
6.4
4.4
4.5
19.8
2.51
12*
11.2
15.5
10.7
11.2
48.6
6.17
13*
9.9
13.8
9.5
9.9
43.1
5.48
14*
8.0
11.2
7.7
8.0
34.9
4.44
15
4.8
6.7
4.6
4.8
20.9
2.66
16
1.4
1.9
1.3
1.4
6.0
0.77
17
9.3
13.1
8.9
9.3
40.6
5.15
18*
2.7
3.8
2.6
2.7
11.8
1.50
19
7.9
11.0
7.5
7.9
34.3
4.35
20*
20.0
27.8
19.1
20.0
86.9
11.03
181.1
251.9
173.2
181.1
787.6
∑
∑ (percent)
23.00
32.00
22.00
23.00
100.00
*Located in the ground water restricted area.
drill a ground water well within ground water
restricted areas. This study uses the confidence level
approach to analyze the applied field conditions. Five
important factors are considered in the confidence
level, including: amount of water in present application, local ground water quality, permissible yield of
local ground water, average drawdown of local ground
water, and pumping interference. The permissible
yield is obtained from the previous MODFLOW-96
simulation. The specific value of each factor in the
confidence level, C, is evaluated using the following
criterion relationships:
Confidence level A, CA, is determined by


amount of water applied
CA =  1 −
 × 100%
maximum rationed water used in a sec tor 

where the maximum rationed water used for the
domestic, agricultural, and industrial sector is adopted from Yu (2000), who has developed a comprehensive set of regression equations based on the data
JAWRA
(1)
from various water-use sectors. The developed regression equations were used to estimate the amount of
maximum rationed water used.
438
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL FAN IN TAIWAN
The confidence level B, CB, is computed by
latest measured items exceed the water



quality standard of all wells in the township 
CB =  1 −
 × 100%
all measured water quality items






Although the magnitude of the exceedance could be of
equal or greater importance than the number of
exceedances, the study restricted the number of
exceedances of the water quality standard. The
impacts of the high concentration items on the environment and human health need to be evaluated by
more advanced tools such as risk assessment, which
is beyond the scope of the study.
The confidence level C, Cc, is determined as follows:
water levels (Hsafe, Hlow, and Hseriously low) are then
calculated from the relationships listed in Table 3.
The safe, low, and seriously low ground water levels
in the proximal-fan, mid-fan, and distal-fan are all set
to the mean plus one, mean minus one, and mean
minus two standard deviations of the measured
ground water level, respectively. The safe, low, and
seriously low ground water levels in the restricted
area are more strict and are set to the mean plus one
standard deviation, mean, and mean minus one standard deviation of the measured ground water level,
respectively, to prevent further land subsidence and
seawater intrusion in the coastal area.
Cc = 100 percent, if θc < θd ;
Cc = 70 percent, if θd < θ < θa;
Cc = 40 percent, if θa < θ < θw; and
Cc = 0 percent, if θw < θ
TABLE 3. Defined Safe, Low, and Seriously Low Ground
Water Levels in the Proximal-Fan, Mid-Fan,
Distal-Fan, and Restricted Areas.
(3)
where θ denotes the amount of annual pumping in the
township, and θ d , θ a , and θ w are the permissible
yields in dry, average, and wet years, respectively.
The confidence level D, CD is determined based on
the safe ground water level and is calculated as follows:
CD = 100%
N
P
∑ (5 × iN )
Area
Hsafe
Hlow
Hseriously low
Proximal-Fan
Mid-Fan and Distal-Fan
Restricted
µ+σ
µ+σ
µ+σ
µ-σ
µ-σ
µ
µ - 2σ
µ - 2σ
µ-σ
µ: Average measured ground water level from 1995 to 1999.
σ: Standard deviation of µ.
(4)
i
The confidence level E, CE, is determined by first
calculating
where
α=
P = 5 if Hmeasured > Hsafe,
P = 4 if Hsafe > Hmeasured > Hlow,
t1
S + t1
(5)
where
P = 2 if Hlow > Hmeasured > Hseriously low,
S=
P = 0 if Hseriously low > Hmeasured, and
N = the number of monitoring wells in the township.
( )
Q2 log R r
,
2.72 Kb
Q1 log  R R 

1
t1 =
,
2.72 Kb
The average ground water level (µ) and its standard
deviation (σ) are computed using the measured
ground water level data in the monitoring well from
1995 to 1999. The safe, low, and seriously low ground
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2)
α is the ratio of drawdown caused by pumping from a
new well to the adjacent well; S is the adjacent well
439
JAWRA
LIU
Figure 8. Main Structure of the Decision Tree in the First and Second Layers
for Issuing Ground Water Rights Permits.
Figure 9. Main Structure of the Decision Tree in the Second and Third Layers
for Issuing Ground Water Rights Permits.
JAWRA
440
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
DECISION SUPPORT SYSTEM FOR MANAGING GROUND WATER RESOURCES IN THE CHOUSHUI RIVER ALLUVIAL FAN IN TAIWAN
100 percent, CD (safe ground water level) is 58 percent, and CE (well interference) is 100 percent. A temporary water rights permit is issued because the
confidence level C B (water quality) is 33 percent,
which is less than 50 percent.
drawdown head (m); t1 is the drawdown caused by
pumping from a new well to an adjacent well (m); R is
the radius of influence of the pumping well (default =
1,000 m); r is the radius of adjacent well (m); R1 is the
distance between the new well and the adjacent well
(m); Q1 is the pumping rate of the new well (m3/day);
Q2 is the pumping rate of the adjacent well (m3/day);
K is the hydraulic conductivity (m/day); and b is the
aquifer thickness (m). If α < 0.2, then CE = 100 percent; otherwise CE = 0 percent.
If confidence is below the threshold of 50 percent,
the system downgrades applications for full permits
to temporary permits and rejects applications for
temporary permits. Figures 8 and 9 present a threelayered flowchart representing the decision tree for
issuing water rights permits. Notably, if the applied
wells are located in the restricted area, only a temporary permit can be issued. The following two examples, including domestic water used and the
industrial water used, illustrate the use of the DSS to
assist a local government officer in issuing water
rights permits.
Case II: Industrial Water Use
For this case, the basic water rights application
data include: the county (Yun Lin), the township (No.
7), the aquifer location (Aquifer 3), the water use sector (Industrial), the type of industry (basic chemical
industry), the plant area (12 hectares), the number of
employees (50), the annual expenses (30,000,000
NT$), the annual water use days (300), the pumping
type (automatic and mechanical), the type of application (regular permit), and the amount of water for
which a permit is sought (350,000 m3/yr). The adjacent well data include: the number of adjacent wells
(0), the radius of influence (NA), the distance between
new well and adjacent well (NA), and the radius of
adjacent well (NA).
The advice from applying the expert system are:
the permitted maximum rationed water (QI) for basic
chemical industrial use is determined by the regressive equation, QI = 130.63 x plant area (hectare) +
54.36 x floor area (hectare) + 3.18 x number of
employees + 0.174 x annual expense (107 NT$/yr) =
715,000 m3/yr; the annual pumping in township No. 7
(6.8 x 106 m3/yr); the permissible yields in dry, average, and wet years (7.3, 7.5, and 8.2 x 10 6 m 3 /yr,
respectively) (see Table 2 for wet year); and the summary of confidence levels (C A (amount of rationed
water used) = 52 percent, CB (water quality) = 100
percent, CC (permissible yield) = 100 percent, CD (safe
ground water level) = 62 percent, CE (well interference) =100 percent). A regular water right permit is
issued because the confidence levels CA to CE are all
greater than 50 percent
In the Case I, only 33 percent of the local ground
water quality meets the domestic water quality standard. As the confidence level (33 percent) is below the
threshold value (50 percent), the DSS downgrades the
application from a regular permit to a temporary permit. In Case II, the five confidence level factors are all
above the 50 percent threshold value, thus the DSS
issues a regular water rights permit to the applicant.
The two examples successfully demonstrate the use of
the expert system in issuing the water rights permit.
Case I: Domestic Water Use
For this case, the basic water rights application
data include: the county (Yun Lin), the township
(No.3), the aquifer location (Aquifer 2-1), the water
use sector (domestic), the number of people (12), the
annual water use days (365), the pumping type (automatic and mechanical), the type of application (regular permit), and the amount of water for which a
permit is sought (1,000 m3/yr). The adjacent well data
include: the number of adjacent wells (1), the radius
of influence (1,000 m), the distance between the new
well and the adjacent well (500 m), the radius of the
adjacent well (0.15 m), and the pumping rate (2,000
m3/yr).
The advice from applying the expert system are:
the permitted maximum rationed water (Q I ) for
domestic use is determined by the regression equation, QI = 0.544 m3/man/day x number of people x
annual water used days = 2,383 m3/yr; the annual
pumping in township No. 3 (13.2 x 106 m3/yr); the permissible yields in dry, average, and wet years (17.8,
18.3, and 19.7 x 106 m3/yr, respectively) (see Table 2
for wet year); the daily pumping rate of new well (2.74
m3/day); the daily pumping rate of adjacent well (5.48
m 3 /day); the thickness of 2-1 aquifer (50 m); the
hydraulic conductivity of 2-1 aquifer (8.64 m/day); and
the computed α (0.05 < 0.2). The confidence levels are:
CA (amount of rationed water used) is 58 percent, CB
(water quality) is 33 percent, CC (permissible yield) is
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
441
JAWRA
LIU
CONCLUSION
Domenico, P.A. and F.W. Schwartz, 1990. Physical and Chemical
Hydrogeology. John Wiley and Sons, Inc., New York, New York,
824 pp.
Durkin, J., 1994. Expert Systems: Designing and Development.
Macmillan Publishing Co.
Endreny, T.E. and G.D. Jennings, 1999. A Decision Support System
for Water Quality Data Augmentation: A Case Study. Journal of
the American Water Resources Association (JAWRA) 35(2):363377.
Fedra, K., 1993. Models, GIS, and Expert Systems: Integrated
Water Resources Models. In: Application of Geographic Information Systems in Hydrology and Water Resources Management,
K. Kovar and H.P. Nachtnebel (Editors). IAHS Publ. No. 211,
pp. 297-308.
Gau, H.S. and C.W. Liu, 2002. Estimation of the Optimum Yield in
Yun-Lin Area of Taiwan Using Loss Function Analysis. Journal
of Hydrology 263:177-187.
Harbaugh, A.W., and M.G. McDonald, 1996. User Documentation
for MODFLOW-96: An Update to the U.S. Geological Survey
Modular Finite-Difference Groundwater Flow Model. USGS
Open File Report 90-485.
Koutsoyiannis, D., A. Efstratiadis, and G. Karavvokiros, 2002. A
Decision Support Tool for the Management of Multi-Reservoir
Systems. Journal of the American Water Resources Association
(JAWRA) 38(4):945-958.
Lam, D.C.L., C.I. Mayfield, D.A. Swayne and K. Hopkins, 1994. A
Prototype Information System for Watershed Management and
Planning. Journal of Biological Systems 2(4):499-517.
Leake, S.A. and D.E. Prudic, 1991. Documentation of a Computer
Program to Simulate Aquifer-System Compaction Using the
Modular Finite-Difference Groundwater Flow Model. U.S. Geological Survey, Techniques of Water-Resources Investigations,
Book 6, Chapter A2, 68 pp.
Lee, C.H., 1915. The Determination of Safe Yield of Underground
Reservoirs of the Closed Basin Type. Trans. Amer. Soc. Civil
Engrs. 78:148-151.
Loucks, D.P., 1991. Computer Aided Support for Water Resources
Research and Planning. In: Decision Support Systems: Water
Resources Planning, D.P. Loucks and J.R. da Costa (Editors).
NATO ASI Series, Springer Verlag, Berlin, Germany, pp. 173188.
Shen, S.B., 1991. Investigation on the Ground Water Resources in
the Choushui River Alluvial Fan. Chia-Yi Institute of Agriculture, Chia-Yi, Taiwan, R.O.C.
Stansbury, J., W. Woldt, I Bogardi, and A. Bleed, 1991. Decision
Support System for Water Transfer Evaluation. Water
Resources Research 27(4):443-451.
Taiwan Sugar Company, 1997. Establishment and Operational
Management of Groundwater Monitoring Network, Water
Resources Bureau, Taiwan, R.O.C.
Water Resources Bureau, 2001. The Integrated Study of Ground
Water Investigation and Land Subsidence Prevention. Minister
of Economical Affairs, Taiwan, R.O.C.
Yeh, W.W.G. and S.L. Yang, 1998. Formulation and Evaluation of
Alternatives for Mitigating Ground Water Overdraft in Taiwan’s
Coastal Area (II). Department of Civil and Environmental Engineering, University of California, Los Angeles, California.
Young, W.J., D.C.L., Lam, V. Ressel, and I.W. Wong, 2000. Development of an Environmental Flows Decision Support System.
Environmental Modeling and Software 15:257-265.
Yu, K.S., 2000. Amount of Rational Water-Used for Various WaterUsed Sectors. Water Resources Bureau, MOEA, Taiwan, R.O.C.
Zheng, C., 1996. MT3D-96 Version DoD-1.5: A Modular ThreeDimensional Transport Model. Hydrogeology Group, University
of Alabama.
The DSS depends on recent advances in computer
and water resource technology. The DSS presented
here is applied to manage ground water resources in
the Choushui River alluvial fan. Comprehensive
hydrogeological data are gathered to provide the user
with access to the most up-to-date information on the
Choushui River alluvial fan. The simulation module
uses these data to determine the hydrogeological
response to various scenarios. The simulated results
are inputted to the expert system to perform an
expert diagnosis for assessing the impact of developing various ground water resources on conservation
and offers expert advice to help decision makers. The
DSS has been applied to determine the permissible
yield of aquifers and issue water rights permits. The
MODFLOW-96 model performs a simulation to obtain
the relationship of pumping rate to drawdown for
wet, average, and dry hydrological years. The Hill
method, which plots simulated pumping rate against
drawdown, is employed to determine the permissible
yield. An expert system of the DSS then applies the
determined aquifer permissible yield to assist local
government agencies in issuing water rights permits.
The DSS described here provides a useful tool for
assisting decision makers in managing ground water
resources.
ACKNOWLEDGEMENTS
The author would like to thank the Water Resources Bureau of
the Ministry of Economic Affairs and the National Science Council
of the Republic of China for financially supporting this research
under Contract Nos. 89B6028 and NSC 90-2313-B-002-054.
LITERATURE CITED
Adelman, L., 1992. Evaluating Decision Support and Expert Systems, John Wiley and Sons, New York, New York.
Andreu, J., J. Capilla, and E. Sanch, 1991. AQUATOOL: A Computer Assisted Support System for Water Resources Research Management Including Conjunctive Use. In: Decision Support
Systems: Water Resources Planning, D.P. Loucks and J.R. da
Costa (Editors). NATO ASI Series, Springer Verlag, Berlin, Germany, pp. 333-356.
Andriole, S.J., 1989. Handbook of Decision Support Systems. Tab
Publishers, Blue Ridge Summit, Pennsylvania.
Central Geological Survey, 1999. Project of Groundwater Monitoring Network in Taiwan During First Stage Research Report of
Choushui River Alluvial Fan. Water Resources Bureau, Taiwan,
R.O.C.
Central Weather Bureau, 1990-1999. Year Book of Climate. Central
Weather Bureau, Taiwan, R.O.C.
Chiang, W.H. and W. Kinzelbach, 1998. Processing MODFLOW: A
Simulation System for Modeling Groundwater Flow and Pollution – User’s Manual. Scientific Software Group, Washington,
D.C.
JAWRA
442
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION