Journ al of Env ir o nmental Protection, 2013, 4, 23-30
doi:10.4236/jep.2013.41b005 Published Online January 2013 (http://www.SciRP.o rg/journal/jep)
Copyright © 2013 SciRes. JEP
A Study on Water Demand Load Estimation by Using
Unit of Living Water - F ocused on Micro Water Supply
Area in Daegu Cit y
Ji-Soo Lee, Won-Hwa Hong*
Departmentof Architecture, Kyunpook National University,Daegu, Republic of Korea.
Email: *
Received 2013
Water supply capability has been significantly reduced as water demand has been increased due to changes of the
world's weather, causing the increase of drought frequency, and urbanization. In terms of water production, water can
be secured by construction a dam or procuring substitute water. However, the study approaches in terms of management
of water supply area to control the existing water efficiently. Therefore, water demand was estimated by buildings, by
which water load of micro water supply area was calculated. As a result, the deviation of water demand for 1,357 micro
water supply areas could be calculated while the alternatives to dissolve the spatial demand unbalance were suggested
by two types. From the study, firstly, we could anticip ate th e total water supply demand f rom the total sum b y filtration
plants but it was not possible to anticipate the characteristics of distribution within urban areas. For this, the study at-
tempted to anticipate the demand of each 250 thousands of buildings, comprehending the demand of micro areas. Se-
condly, based on the built results, we suggest the directions to dissolve the water demand unbalance between and
among regio ns , wh ich could be the found ation to suggest the concrete methodo logy in the future.
Keywords: Water Supp ly Area; Water Demand Estimation; Basic Unit, Water for Living; Smart Water Gr id
1. Introduction
Due to the rapid industrialization, many cities have been
larger and the recent weather changes cause the severe
drought. Therefore, the water demand increases about 6
times in 20th century while the water supply has been
unstabilized; it is expected that in 2025, about t wo thirds
of the world population encounter short supply of water.
In addition, the water dispute is getting severe between
regions, and it was found that totally 58 cases of disputes
occurred from the cases of each administration and 5
rivers' areas of Korea for 10 years(SWRRC 2008). Such
problems show that the water procurement by dams had
to be limited. As an alternative, smart water grid is sug-
gested by utilizing the latest IT technology in terms of
water demand control. The core of smart water grid is to
dissolve spatia l and temporal unbala nce through efficient
water control. However, to currently construct the smart
grid system in the territory, it is prerequisite to estimate
the water demand for a micro size, which is 5 thousands
of households or micro water area. The domestic micro
size water supply areas are su b-divided into water supply
zones of the filtration plant, so the water usage can be
calculated but it is not possible to anticipate the water
usage by buildings o wing to the classificatio n of building
use and the properties.
Therefore, the study realizes the primary purpose of
anticipating water usage by buildings in an urban area by
using the basic unit of city water . Then, based on the
calculated data, the water load of sub-divisions within an
urban area is also calculated. The study would contribute
to establishing the methodology of dissolving the unba-
lanced water supply in subdivisions and be the funda-
mental data to construct the smart water grid.
2. Setting a Unit of Living Water by
Building Use Type
Water can be roughly divided into Living water and
agricultural water. Living water is also sub-divided into
living water and industrial water ; the former(living water)
is, in turn, divided into household water and city utiliza-
tion water(Water membarane, 2006). The study limited
the subject to the living water, which occupies about
84% (Daegu Statistical Annual Report, 2011) of Daegu
city water. Before applying the basic unit, it is necessary,
*Corresponding author.
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
in case of domestic household water, to convert the basic
unit per person to the basic unit of area. Meanwhile, the
city utilization water is applied with the existing basic
unit numbers and applications..
2.1. Setting a Unit of House Hold Water
Household water consists of toilet water, washing water,
bath water and laundry water by applications. The basic
unit of the study is the basic unit by house types, which
was suggested b y Kim. According to the above study, the
house type(Detached house[141 lpcd], Apartment [155l
pcd], Multi unit dwelling[159 lpcd]) and the basic unit
were applied. The procedure and method to convert the
basic unit per person to the basic unit per area in the
study are as follows.
The average gross floor area was calculated by using
the no. of household(statistics) while the gross floor
area by types was calculated by using the building
spatial data of Daegu.
Meanwhile, the basic unit by types and the average
residence per house were used to estimate the water
usage per house.
Then, the spatial i nfor mation was used to esti mate the
total floor area of a specific building while the water
usage was estimated by using the average total floor
area per house and the water usage per house by types,
which were estimated in the a b ove procedure.
That can be summarized as follows.
sr Da
tDt D
(Qt: Water cons umption o f ta r ge t b ui ld i n g [ℓ/building∙day];
As: Gross aera of Target building [m2]; Ur: Water con-
sumption units by house type [ℓ/capita∙day]; .Da
P: The
average number of people per household (Daegu city);
A: Total gross area of residential buildings (Daegu
city) [m2];
: T he number of househo ld( Daegu city)
2.2. Setting a Unit of City Utilization Water
The basic unit to ap ply city utilization water was applied
by the business types and the basic units suggested by
Lee. The following table shows the business type, based
on the Korea Standard Industrial Classification and
represents the basic unit by business types.
Table 1. Unit of city utilization water.
Classification Unit Consumption
(l/m2/day) Classification Unit Consumption
1 wholesale and retail trade 15.7 23 Schools 2.9
2 Wholesale of Fer til izer s
& Agricultural Chemic als 13.5 24 Preschool 5.5
3 Gas station Operation 11.4 25 Primary schools 1.7
4 Supermarkets 6.9 26 Junior High schools 1.0
5 General retail 17.9 27 Senior High schools 1.7
6 Meat retail 2 5.3 28 Hospital Activities 7.4
7 Ret ail S ale of Textiles,
Clothing, Footwea r & Leather Goods 12.5 29 General clinics 6.8
8 Other Retai l S ale of Hardware, Wallpaper,
Heati ng Equipm ent & Construction Materials 9.2 30 Dental Hospita ls 7.8
9 Retail Sale of Pharmaceutical and Medical
Goods 19.8 31 Oriental Medical Hospitals 8.3
10 Retail of Flowers and Plants 10.4 32 Veterinary Clinic 13.7
11 Accommodation 21.19 33 Public Health Centers 3.4
12 Restaura n ts, Bars & Canteens 22.2 34 General Hospi tals 7.8
13 Restaurants 22.8 35 Service Industry 19.1
14 Drinking Places 19.8 36 Sports Facility Operation 10.8
15 Social Work Activities 6.7 37 Recreational Activities 7.4
16 Office Support Services 7.3 38 Religious Organizations 4.5
17 Post and Telecommun i cations 6.4 39 Maintenan ce & Repair Servi ces of M o tor
Vehicles 5.0
18 Financial & Insurance Institutions 2.2 40 Hairs, Nails & Skin Cares 27.3
19 Real Estate Activities 18.9 41 Saunas 42.6
20 Enterpri se Service Business 2.8 42 Washing & Dry Cleaning Services 33.4
21 Exam Preparation 8.3 43 Interurban Rail Transportation 21.9
22 Public O f f ice 8.1
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
3. Building a Data of Water Demand in
Daegu City
3.1. Status of Water Supply System in Daegu
Daegu, the subject city of the study, accommodates 2,529
thousands of population in 883.7 km of total area and
940 thousands of households. Administratively, the city
consists of 8 gu and 139 dong. In the urban area, there
are 5 filtration plants for living water and 1 filtration
plant for industrial water. T he total capacity of the facili-
ty is 1,640 thousands daily, among which about 12%,
200 thousands of water is produced in Gong- san
plant. The scope of the study, Daegu living water plant
and production can be summarized as the Table 2 bel ow.
As seen in the above, Mae-gok plant accupies about
57% of the total living water production capacity, fol-
lowed by Mun-san, Go-san, Ga-chang and Gong-san.
Looking at the production rates to facility capacity of
individual plants, it was about 51% on average but the
production rate to the total facility capacity was just
about 53%.
3.2. Building a Foundation Database for
Calculating of Living Water Demand
To estimate the living water usage of all buildings in
Daegu, the fundamental data can be divided to 3 types.
1) Buildingsspatial data classified by residence types
and business types of Daegu
2) Properties data to estimate household water and cit y
utilization water(basic unit and gro ss floo r area)
3) Diagram data of Daegus small water supply areas
Table 2. St atus of living wa ter supply in Daegu city.
Division Tota l Water for living
Mae-gok Mubn-san Go-san Ga -chan g Gong-san
Cap acit ies of Facilities
(thousand /day) 1,440 800 200 350 50 40
Production moun t 769 441 187 96 30 15
Household number of
Watersupply(thousand) 892 490 242 85 42 33
People nu mber o f wa ter
supply (thousand) 2,506 1,345 684 268 115 94
Water supply area 7(gu), 1(gun), 134(dong),
3(eup), 6(myun) 4(gu),1(gun), 54(d ong),
3(eup), 5(myun) 3(gu),
36(dong) 1(gu ),
1(gun) 1(gu), 1(gun),
1(myun) 6(dong) 1(gu),
Table 3. Classificatio ns of building uses.
Classification Numbers Gross Area
n % %
Detached house 171,386 91.84 29,583,612 31.60
Apartment house 6,531 3.50 58,905,510 62.93
Multi-unit dwelling 8,702 4.66 5,116,537 5.47
total 186,619 100.00 93,605,659 100.00
None Residential
1 111 0.16 116,522 0.30
2 127 0.19 59,607 0.15
3 793 1.17 229,939 0.59
4 406 0.60 635,782 1.64
5 27,447 40.53 8,996,840 23.25
6 3 0.00 23,710 0.06
7 4 0.01 1,891 0.00
8 1,085 1.60 278,908 0.72
9 38 0.06 13,475 0.03
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
10 154 0.23 37,757 0.10
11 1,073 1.58 1,306,720 3.38
12 9,490 14.01 3,647,336 9.42
13 4,142 6.12 1,236,032 3.19
14 95 0.14 45,797 0.12
15 451 0.67 309,589 0.80
16 4,476 6.61 4,651,426 12.02
17 124 0.18 374,115 0.97
18 247 0.36 363,106 0.94
19 133 0.20 29,333 0.08
20 5,932 8.76 3,134,859 8.10
21 601 0.89 373,167 0.96
22 1,330 1.96 2,463,479 6.37
23 439 0.65 244,740 0.63
24 683 1.01 1,812,522 4.68
25 371 0.55 970,557 2.51
26 424 0.63 1,450,371 3.75
27 198 0.29 483,178 1.25
28 458 0.68 631,923 1.63
29 28 0.04 51,932 0.13
30 103 0.15 42,958 0.11
31 2,098 3.10 464,384 1.20
32 22 0.03 20,362 0.05
33 52 0.08 489,380 1.26
34 140 0.21 126,045 0.33
35 169 0.25 550,995 1.42
36 473 0.70 508,878 1.31
37 2,659 3.93 1,695,946 4.38
38 698 1.03 379,764 0.98
39 184 0.27 49,296 0.13
40 128 0.19 150,687 0.39
41 54 0.08 10,498 0.03
42 42 0.06 230,730 0.60
43 39 0.06 5,598 0.01
total 67,724 100.00 38,700,1 34 100.00
For the programs to integrate the above data and create
the fundamental data, Arc GIS 9.3 was used. The spatial
data created in the data is shp file for mat, so the attr ibute
data is exported as the format of dbf file. To construct the
data of 1), the usage of every building in Daegu except
for factories from Daegu buildingsspatia l data was clas-
sified. The d ata contain 0.2 5 millio n of data and they are
divided into 3 residence types and 43 business types. The
following figure shows the mapped c la ssification data.
Then, to construct the data of 2), it should be con-
structed by dividing into household water and city utili-
zation water. Firstly, to estimate the household water
usage, the demand by each building was calculated by
substituting 2.2 formula. The data regularly entered in
the for mula (1), besides the gross floor area of a specific
building are as follows.
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
(a) (b) (c)
Figure 1. Classification of building uses in Daegu city. (a) Distribution of building uses in Daegu city; (b) Residential type
classificat ion in downt own; (c) Non-re si dential t ype clas sification in downtown.
Table 4. Data for estimation of household water demand.
house Apartment house Multi-un it
dwelli ng
Ur (ℓ) 141 159 155
PD.a(p) 2.9
AD.t() 29,583,612 58,905,510 5,116,537
HD (N) 361,447 464,960 60,435
The data of 3) were converted to shp file format by
using the data of Daegu City Water. The micro water
supply areas of Daegu was sub-divided into 1,545 zones
while the average area was about 240 thousands m2. 2,554
buildings were contained into one zone to the maximum
while 184 buildings on average are located within one
zone. The above can be constructed to shp file as follows .
4. Analysis of Water Demand Load in Daegu
Citys Micro Water Supply are
4.1. Water Demand Forecasting Within the Unit
Building of the City
The spatial distribution of water demand of Daegu was
anticipated by using Arc GIS, based on 1) Building
spatial data containing Residence types and business
types of Daegu and 2) Attributes data(basic unit and
gross floor area) to estimate the household water and city
utilization water, which wa s constructed in 3 . 2.
The figure below shows the spatial distribution of the
demands of household water, city utilization water and
livi ng wa ter by building uni t s of Daegu.
The table below shows the administrative spatial dis-
tribution of water demand while the comparison of the
estimated living water demand of Daegu and the actual
production was about 8% consistence. Looking at the
results, Daeseo-gu occupied about 30% of the total de-
mand for household water while Suseong-gu occupies
about 20% for city utilization water, which was about
20%, the highe st p rediction.
Figure 2. Constructed micro water supply area in Daegu
city ( shp file).
4.2. Building an Water Demand Data on Micro
Water Supply Area
It was calculated by integrating the water demand by
buildings and the spatial data of micro water suppl y areas,
which were anlyzed in the above, and integrating the
water usage by micro areas. To estimate them, the water
demand data by buildings were converted to point data,
which is, in turn, joined, based on micro areas' diagram
data and location data.
As a result of integrating the building information of
totally 1,545 micro areas and excepting other micro areas
with no buildings, there were 1,357 areas. The figure
shows the results o f classifying the estimated demand by
using natural break classificatio n
As a result, the average demand of micro water supply
areas was about 5,424 and the difference between the
max. and average was about 2,432,177. In addition,
standard deviation was 163,700, indicating that there
are severe unbalance between and among micro areas
and that the areas should be readjusted, based on the de-
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
(a) (b ) (c )
Figure 3. E st i mati on of livi ng water de man d by buil di ng s. (a) Residential water; (b) City utilization water; (c) Living water.
Table 4. Estimati on of wat e r diman d by administrat ive area.
Administrati v e area Li ving Water cons um ption(ℓ/day)
Household water(a) Urba n water(b) Total(a+b)
Jung-gu 2,268,025,115.9 62,353,597 .0 2,330,378,713.0
Dong-gu 7,243,507,305.6 69,132,776.6 7,312,640,082.2
Seo-gu 2,526,147,690.6 12,263,841.0 2,538,411,531.6
Nam-gu 1,842,759,505.5 42,627,634.7 1,885,387,140.2
Buk-gu 14,463,961,482.2 75,380,174.8 14,539,341,657.0
Suseong-Gu 20,064,332,667.4 87,349,282.6 20,151,681,950.0
Dalseo-gu 21,733,972,247.3 52,708,298.9 21,786 ,680,54 6.2
Dalseong-gun 3 ,042,86 7,072.1 30,878,524.3 3,073,745,596.5
Total 73,185,573,086.7 432,694,130.0 73,618,267,216.6
(a) (b) (c)
Figure 4. Esti mations of w ater de mand be micro w at er supply area usi ng over ay an aly sis. (a) B uil ding data( poi nt); (b) Micro
water supply are a (polygon); (c) Distribution of water deman d by Micro water sup ply area.
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
4.3. Adjustment Measures of Water Demand
Load on Micro Water Supply Area
As analyzed above, since there is much deviation of wa-
ter demand, alternatives to reduce the unbalance should
be studied. For this, the study extracted top 10% of the
1,357 micro areas, 135 areas were extracted, establishing
the problems and suggesting the method to re-adjust the
The estimated water demand for the 10% areas occu-
pies about 76% of the estimated total water demand,
55,786,386 m3. In addition, looking at density analysis
(gross floor areap[]/micro area[]) results (figure), it
was 1 .7 1 , 1. 17 hig her than t he ave r age o f D ae gu, 0 .5 4 . In
addition, the average area of micro areas was 368,000,
which is 12,000 larger than the average area.
Meanwhile, considering the frequency of buildings, it
was analyzed that 184 buildings are located on average
for the total micro areas while 531 buildings were contained
in top 10% areas.
Based on the above results, two types of alternatives
can be suggested to reduce the deviation of loads be-
tween and among areas. Firstly, an area where the build-
ing density is high but spatial area is broad, so more
buildings are contained would be divided. The figure
below shows the representative area for the first type.
The area's density was 0.087, which is just the lowest
40% of the total areas but the no. of buildings was 1,504,
which is top 0.4%. To divide an area.
Figure 5. Top 10% of water demand area.
Figure 6. Result of density analysis.
The second type is an alternative re-adjusting the high
density area, which is frequently found in urban areas
(Figure 8). In the area of the figure below, interchange/
adjustment alternative of c r os s -areas to neighboring areas
can be suggested while the interchange unit is desirably
block, in consider a tion of structure of water pipes.
5. Conclusion
The study suggest the alternative to dissolve the water
supply unbalance by regions, the core subject of smart
grid and to r educe the d eviat ion. Fo r this , whil e anal yzin g
the load by micro water supply areas, the water demand
of all buildings except factories in Daegu was estimated
while the spatial distribution of the demand can be
comprehended. As a result of the study, the place
estimated to have the largest demand of livin g water was
Dalseo-gu, i n whic h hou se ho l d wat er usa ge was esp e c ia ll y
high. After analyzing the estimated water demand and
the existing water supply areas, the standard deviation of
1,357 areas was 163,700 m3, suggesting that the un-
balanced state should be dissolved by an alternative.
However, the alternati ve suggested in the stud y is a kind
of directions, so more effort is required to substantialize
it. Although the study suggests the types based on the
frequency of buildings and the density, the further study
Figure 7. 1stre-adjustingalternative.
Figure 8. 2nd re-adjusting alternative.
A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro
Water Supply Area in D aegu City
Copyright © 2013 SciRes. JEP
would suggest the methodology, based on the basic unit
of usages within the areas.
While it was possible according to the previous studies
to comprehend the total water demand from the total
production of filtration plants, it was not possible to
comprehend the small water demand of micro water
supply areas due to the difference of authorities. The
study was meaningful that it provides the fundamental
data to construct the smart water grid by enabling the
water demand by micro areas and estimation of water
demand by buildings while it is expected that the study
would contribute to the efficient control of water, which
is the important issue fo r the co untrie s .
6. Acknowledgements
This work was supported by the National Research
Foundation of Korea(NRF) grant funded by the Korea
government( MEST) (No. 2012-0008716).
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