Budget Allocation Assessment for Water Resources Project in Thailand Using GIS-based Water Poverty Index

2013 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies.

International Transaction Journal of Engineering,
Management, & Applied Sciences & Technologies
http://TuEngr.com

Budget Allocation Assessment for Water Resources Project
in Thailand Using GIS-based Water Poverty Index
Supet Jirakajohnkool
a
b

a*

a

, Uruya Weesakul and Sarintip Tantanee

b

Department of Civil Engineering, Faculty of Engineering, Thammasat University, THAILAND
Department of Civil Engineering, Faculty of Engineering, Naresuan University, THAILAND

ARTICLEINFO

ABSTRACT

Article history:
Received 24 October 2012
Received in revised form
02 September 2013
Accepted 05 September 2013
Available online
09 September 2013
Keywords:
Geographic Information
Systems;
Water Management;
GIS-Based Index;
water budget allocation;

During the last 5 years, Thailand has allocated water budget to
mitigate water resources problems totally THB 100,460 million
(US$31264 million). However, it is found no study to assess whether
such allocation corresponds to the problems or to water demand.
This study, therefore, assesses appropriateness of the budget
allocation to 25 major basins in Thailand by applying the concept of
Water Poverty Index (WPI). WPI is developed by Sullivan (2002)
consisting of five main factors of Resources (R), Access (A), Capacity
(C), Use (U) and Environment (E). Sub-factors of 22 variables have
also been selected based on the physical and geographical
characteristics of 25 major river basins. Data are scored for priority.
GIS is cooperated the results of water shortage area according to
priority on basin basis.
It is found that WPI scores of Mae Nam Pattani, Mae Nam
Kok, Peninsula - West Coast, Mae Nam Mun, Mae Nam Chi, Mae
Nam Salawin and Mae Nam Khong (Northeast) were low, which
reflected a higher level of water shortage than other basins. By
considering water budget allocation per capita, it was found that Mae
Nam Kok, Mae Nam Chi, Mae Nam Mun, were allocated less budget
compared to other basins. Thus, water budget allocation is
inconsistent with the water poverty index. However, the WPI scoring
system is based only on water poverty. Future study should integration
of disaster index into the scoring system, to improve the efficiency of
budget allocation system.
2013 INT TRANS J ENG MANAG SCI TECH.

.

*Corresponding author (S.Jirakajohnkool). Tel/Fax: +66-2-5644440 Ext.2300. E-mail address:
supetgis2me@gmail.com.
2013 International Transaction Journal of Engineering,
Management, & Applied Sciences & Technologies. Volume 4 No.4
ISSN 2228-9860
eISSN 1906-9642. Online Available at http://TuEngr.com/V04/283-298.pdf

283

1. Introduction
Currently, many countries in the world have the problem of scarcity and confront with
inadequate water issue. Therefore, the need for more efficient water management is urgently
needed (Mlote et al., 2002). In the past 50 years, water resources management in Thailand has
focused on increasing water storage, by developing small, medium and large–scaled water
resources projects. At present, a situation of environmental changes cause the restrictions on
water resources development, while water demands for domestic and agricultural use in
Thailand have been rising continuously. Therefore, the Government has an initiative to use
integrated water management for implementation of river basin development. Under this
approach, the government has tried to achieve equity in national water resources development
and management (ICID, 2012). Water crisis in Thailand began to become more severe (HAII,
2008). Water accessibility at different levels has become gradually more significant (Sen,
1999). The most critical decision of water management is resource allocation, which related to
water policy.

Science and interdisciplinary approaches have been adopted to support

decision-making for determination of more effective water policies.

Accordingly, WPI

methodology has been developed to identify the areas and assess shortage of the existing water
resources (Sullivan, 2002). Although the use of WPI at major basin or sub basin levels is a
beneficial study to integrated water management, there is a doubt that the database without
correlation among such physical, hydrological and socio-economic information is still an issue
to be resolved in the future researches (Sullivan and Meigh, 2006).
WPI mapping becomes an increasingly important tool for identifying inaccessible target
areas to water. Integration of information on both social and physical sciences, comprising
Resources (R), Access (A), Capacity (C), Use (U) and Environmental (E). All these five main
factors have been used to analyze and presented in more systematic way.

Geographic

Information Systems (GIS) demonstrates all statistical data of physical and socio-economic in
form of map. The results of WPI analysis will reflect water shortage areas according to main
those factors. Thus, the purpose of this study is to apply WPI to Thailand’s 25 major basins
comparing with water budget allocation among 25 river basins of Thailand by using the water
budget data collected during the years 2004–2008.

284

Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

2. GIS Preparation Process for Budget Allocation Monitoring
2.1 Studying water budget allocation during the years 2004-2008 to 25
major basins in Thailand
This study collected the statistics on the budget used for water management of five major
departments, i.e. Royal Irrigation Department, Department of National Parks, Wildlife and
Plant Conservation, Department of Water Resources, Land Development Department and
Department of Local Government. The budget information collected during the fiscal years
2004–2008 were used to study the spatial budget allocation on basin basis.

The study

processes are as follows.
1) Collecting and processing statistics related to water budget of the five agencies as
allocated to the 25 basins in each year during the fiscal years of 2004 - 2008.
2) Developing a processing program to characterize water budget statistics compared to
basin areas and water budget to per capita, and then classifying the statistics in quartile
form into 4 important levels. Any basin allotted less budget will be ranked into Quartile
1, with 1 score, while the basins allotted more budget will be ranked into Quartile 4,
with 4 scores.
3) Coding a Spreadsheet program to facilitate database preparation storing the results
processed in Step 2 in form of attribute data that will be linked to spatial data in GIS in
order to determine data visualization of entire 25 major basins in Thailand.

2.2 Key components of WPI and mathematical model of Thailand’s 25
major basins
WPI analysis aims to develop a tool for water shortage assessment due to water resources
limitation (Sullivan, 2003). WPI is designed to lead to water issues and water scarcity
management. Guidelines for local water management are the main objectives in development
of WPI, a tool used to monitor progress and identify the areas with high water demand. WPI
has provided water prioritization prospects. The advantages of WPI are i.e. convenient for
policy makers to understand the factors used, with transparent process, able to explain water
poverty extent of the community and with adjustable variables in line with the situation and the
different area levels. As holistic approach, WPI will take into account a number of factors to
effective water management, the index has focused on effective water access at basin level.

WPI is an integrated tool developed based on consultation of scientists, practitioners and
policymakers (Sullivan and Meigh, 2006). The issues on available resources, access, capacity,
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285

use and environment are considered as key components of WPI, which will display an overview
and prospects of more efficient water management (Sullivan and Meigh, 2003, Sullivan et al.,
2003):
•

Resources (R) – available water resources e.g. surface water, runoff

•

Access (A) – access to water resources, water use in agriculture

•

Capacity (C) – capacity improvement of water management

•

Use (U) – use of water including agricultural economy

•

Environment (E) – environmental impact of water management

WPI is the main tool for water managers to assess water situation in different areas in
holistic manner that will make it easier to compare the 25 main river basins in Thailand, with
the factors helping decision-making based on physical and socio-economic data. In addition, if
operation for several years, it will be a tool used to monitor progress or changes continually.

WPI methodology is originated from combination of the relevant variables that can explain
covering water shortage in that situation. WPI is the results of the five key components
integration (resources, access, capacity, utilization and environment), stressing on water for
agriculture. All data will be collected and processed as WPI statistics by means of weight rating
of primary and secondary factors. Also, quartile ranges are to be found for purpose of water
scarcity classification of each element. Mathematical equations as used demonstrate WPI
components, as shown in the equation below.
N

WPI =

∑w X
i =1
N

i

i

∑w
i =1

(1),

i

Whereas WPI shows water poverty index in major river basins by using the sum of the
weighted scores of major 5 factors as in Equation (3), i.e. resource (R), access (A), capacity (C),
use (U) and environment (E), with each factor to be scored in the weight range of 0 -100 points.
Wi is the weight of each of the factors, (X), a component of WPI, is the score of each element,
which has 22 sub factors used in the WPI study, while a number of sub factors are represented
by n. The value Wi is the weight of each main factor, with the sum equal to 1 as in Equation (2)
(Mlote, Sullivan and Meigh, 2002).
286


N

∑w
i =1

i

=1

(2),

WPI will adjust the scores in the range of 0 to 100; the lowest score is 0, representing high
water scarcity or more shortage than other areas in the river basin. Meanwhile, the score of
100 means less water scarcity than other areas or more adequate than other basins. The total
scores will be divided by Quartile into 4 scarcity orders. The equation is shown as follows.

WPI =

wr R + wa A + wc C + wuU + we E

(3),

wr + wa + wc + wu + we

By using wr, wa, wc, wu and we to represent the weights of the following five key
components: Resources (R), Access (A), Capacity (C), Use (U) and Environment (E),
respectively.

2.3 Database for WPI analysis of Thailand’s 25 major river basins
In water poverty assessment at basin level by using all five key aspects, which are standard
framework of WPI application to Thailand’s 25 major basins analysis, database preparation
according to Table 1 is required. Basic principles are to calculate WPI score on comparison of
statistics of quartile classification of each basin based on the five main components and
sub-factor variables as extended from the Sullivan’s research by adapting 22 sub-elements in
compatible with the physical and geographical conditions of Thailand’s 25 major basins as
shown in Table 1.
The comparison in this manner will encourage the policymakers to use acceptable element
data by comparing the statistics collected for assessment of more reliable scores of WPI
(Sullivan and Meigh, 2006). This study has applied the analysis to the 25 major river basins,
with more acceptable results.

2.4 GIS database development to support water poverty index for 25 major
river basins
Statistical data were collected from multiple agencies and recorded in form of GIS
database representing water poverty index in respect of hydrological factors and other physical
properties of all 22 variables.
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Table 1: Data Selected As WPI Component Variables for 25 River Basins Assessment
(Modified from Sullivan (2002)).
WPI Components*
Resources (R) –
Quantitative evaluation of
measurable values of
surface water in each basin

1.
2.
3.
4.

Access (A) – Assessment of
water access and effective
use in each basin

5. Percentage of water consumers to rural population
6. Percentage of irrigated areas to farmland (Large and
medium irrigation projects)
7. Percentage of beneficial area to farmland
(Small irrigation projects, electricity water
pumping projects)
8. Percentage of farmland to basin area
9. Provincial Gross Domestic Product per population
10. Total revenue per capita (Baht / person / year)
11. Ratio of working age population to basin
population
12. In-season rice yield to water use (kg / m3)
13. In-season rice yield to Rai (Kg / Rai)
14 Off-season rice yield to Rai (Kg / Rai)
15. Sugarcane yield per Rai (Kg / Rai)
16. Corn yield per Rai (Kg / Rai)
17. Cassava yield per Rai (Kg / Rai)
18. Percentage of off-season rice field to in-season
rice field
19. Percentage of fruit-tree and perennial areas to
farmland
20. Percentage of forest area to river basins
21. Overall water quality of major rivers
22. Percentage of urban area, residential area to river
basins

Capacity (C) – Evaluation
of water demand, GDP
income and worthiness of
water use
Use (U) – Assessment of
water demand for economic
returns from economic crops
in each basin

Environment (E) –
Assessment of
environmental integrity,
population ratio per area

Sources of data

Data Used
Runoff per year (million cubic meters)
Retention water per year (million cubic meters)
Potential ground water (million cubic meters / year)
Average rainfall (mm3 / year).

-Royal Irrigation Department
-Department of Groundwater
Resources
-Meteorological Department
-Royal Irrigation Department
-Land Development Department

-National Statistics Office
-Office of Agricultural
Economics

-Office of Agricultural
Economics

-Royal Forest Department
-Office of Natural Resources and
Environmental Policy and
Planning
-Land Development Department

WPI is developed to support the policymakers to rank water scarcity orders for agriculture
in 25 major basins, with preparation process of sub-factors at basin level as follows.
1) Collecting and processing relevant statistics of all 22 sub-factors of WPI from related
agencies as shown in Table 1
2) Developing a supporting program in Spreadsheet form for WPI calculation.
3) Writing a set of equations linking formula to classify statistics of the sub-factors in
quartile form into 4 water scarcity levels. If water shortage is low, the basin will be
ranked into Quartile 4 with 4 scores, and if shortage is high, the basin will be ranked
into Quartile 1 with 1 score. Processing all 22 sub-elements
4) Processing total quartile scores of each of WPI factors of five main aspects i.e.

288


Resource (R), Access (A), Capacity (C), Use (U) and Environment (E). Combining
scores in each aspect and adjusting statistics of each major component to allow WPI
scores in the range of 0 – 100. If water shortage is high, WPI score is to be close to 0
(Thulani et al., 2006)
5) Processing total scores of 5 major factors (WPI) and adjusting statistics of WPI ratings
in the range of 0 - 100 to indicate water scarcity level. If the scores close to 100, it
indicates that water shortage is less than other basins.
6) Coding a Spreadsheet program to facilitate database preparation of the outputs
processed in steps 3), 4), 5), and 6) to be stored in attribute data form that will be
associated with spatial data in GIS. to determine data visualization of 25 major river
basins in Thailand
7) Recording 22 sub-factors in form of spatial data, then displaying the results in GIS,
water scarcity levels of 25 basins to be shown in form of WPI ratings for policy makers
to visualize geographically. Based on the statistics classified in quartiles with spatial
data, the statistics can be displayed.
8) Comparing water budget data to WPI outputs

3. Study Results and Discussion
3.1 Budget allocation to 25 basins by five agencies
In collecting water budget by major river basins from 5 agencies, as shown in Table 2, over
a period of 5 years (2004-2008), it was found that Royal Irrigation Department was the agency
with the highest allocation from the government totaling THB 60,312 million (US$1885
million (taken as THB32 = US$1)), more than the other four agencies involved in water
resources management. The budgets were allocated to the basins as follows: Mae Nam Bang
Pakong, Mae Nam Nan, Mae Nam Chao Phraya, Peninsula – East Coast, East Coast Gulf, Mae
Nam Yom and Mae Nam Mun, respectively (Table 2). According to the study, given that a lot
of dams and reservoirs in Thailand are in responsibility of the Royal Irrigation Department,
water management budgets allocated to the Department are quite more than the other agencies.
Department of Local Government was the second department that was allocated for water
budget totaling THB 29,980 million (US$937 million). The funds were distributed to Mae Nam
Mun, Mae Nam Chi and Peninsula – East Coast, respectively (Table 2). Department of Local
Government has also a role to allocate the budget for water resources management to local
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governments countrywide.
Thailand’s water scarcity and water demand have increased. According to Figure 1, it
shows that total amount of the budget allocated to the five agencies for water management in
accordance with each agency’s water-based missions tends to increase.
Table 2: Water Budget Allocation by five Departments in 25 river basins.

2,000
0

2004

2005

2006

15,739.73

Department of Royal
Irrigation

6,124.32

2007

959.79
1,372.18
189.60

4,000

818.24
833.75
193.00

6,000

1,163.31
912.06
184.13

8,000

1,115.23
497.78
78.70

5,588.00

10,000

9,333.66

12,000

10,129.53

14,000

9,467.88
8,050.53

16,000

1,034.25
1,166.02
620.00
67.65

Water Budget (million baht)

18,000

9,196.39

15,739.59

Water Budget (2004 - 2008) of 5 Deparments
(million baht)

2008

Department of Local
Administration
Department of Land
Development
Department of Water
Resource
Department of National
Parks, Wildlife and Plant
Conservation

Figure 1: Water Budget Allocation in (2004-2008) 5 years by 5 Departments.

290


Figure 2: Water Budget Allocation per
basin area in (2004-2008) 5 years.

Figure 3: Water Budget Allocation per capita
in 5 years (2004-2008) by five Departments
in 25 river basins.

Comparison of water budget allocation helps distinguish clearly the allocation to each
basin and allows ranking analysis of total water budgets sorted by the amount as shown in Table
2. In analysis of water budget allocation in accordance with the allocation orders, it was found
that the budgets were arranged in descending order to the basins as follows: Mae Nam Mun,
Mae Nam Bang Pakong, Mae Nam Nan, Mae Nam Chao Phraya, Peninsula – East Coast, Mae
Nam Chi and East Coast Gulf, respectively. Based on the total budget for each basin, statistics
were grouped in form of Quartile 4 (with more budgets allocated than other basins) in water
budget allocation as illustrated in map (Figure 2). In setting priority of budget distribution,
some basins were found obtaining the largest part of the allocation. Anyhow, if water scarcity
orders are ranked by WPI, it is made certain that accurate and more reliable information will be
achieved.
According to water budget allocation per basin area (Baht / sq. km), it was found that Mae
Nam Yom, Mae Nam Nan, Peninsula – East Coast, Thale Sap Songkhla, Mae Nam Chao
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291

Phraya, East Coast Gulf and Mae Nam Bang Prakong, respectively (Table 3), were ranked into
Quartile 4, with the majority budgets allocated more than other basins. Meanwhile, the basins
with less allocation were i.e. Mae Nam Salawin, Mae Nam Mae Klong, Mae Nam Ping, Mae
Nam Khong (Northeast), Mae Nam Chi, Mae Nam Sakaekrang and Tonle Sap, respectively,
categorized in Quartile 1.
According to water budget allocation per population (Baht /person), it was found that Mae
Nam Bang Pakong, Mae Nam Yom, Peninsula – East Coast, Mae Nam Nan, Mae Nam Salawin,
Mae Nam Khong (North) and Prachuapkhiri Khan Coast, respectively (Table 3) were in
Quartile 4, with more budget allocation than other basins. Meanwhile, the basins with less
allocation were i.e. Mae Nam Chao Phraya, Mae Nam Tha Chin, Mae Nam Ta Pi, Mae Nam
Kok, Tonle Sap, Mae Nam Mun and Mae Nam Chi, classified into Quartile 1.
Table 3: Water Budget Allocation in 5 year, compared with area and capita.

3.2 Water Poverty index for 25 river basins
The study demonstrated the feasibility of using statistical data available of the 25 river
basins and basin ranking according to the WPI to explain water scarcity statistics rationally.
The weight ratings of WPI involve basin ranking in respect of water scarcity based on the 22
sub-factors, with quartile ranking of each variable and the processed sum of all factors in WPI
scores.
From Table 4, WPI scores showed the ranks of water scarcity in the 25 river basins by
using statistics on resources, access, capacity development, use and environment as key
292


elements in the analysis. It was found Mae Nam Kok has high WPI scores, but having limited
access (A). On the other hand, Mae Nam Mun has limitation on access (A), capacity (C) and
environment (E). WPI scores reflect the values of the 22 sub-elements that indicate stress of
water resources in different issues. If any basin has WPI ratings under other basins, it reflects
that such basin has higher water poverty than other areas.
Score results obtained will be crucial to water poverty ranking as shown in Table 4, Figure
4 and Figure 5, which show clearly that after combining statistics scores at basin level, the
Northeast of Thailand has been identified as areas where water shortage is utmost among the 25
major river basins. The basins ranked in accordance with the WPI of 25 basins, in descending
order, which have WPI scores lower than other basins and classified into Quartile 1 were i.e.
Mae Nam Mun, Mae Nam Pattani, Peninsula –West Coast, Mae Nam Kok, Mae Nam Pa Sak,
Mae Nam Chi and Mae Nam Salawin.
Table 4: Water Poverty Index for 25 river basins.

Figure 4 is a sequence of WPI in ascending order. If any basin has WPI lower than other
basins, it represents that that basin has higher water shortage than other basins. When compared
to water budget allocation to basin areas, the water budget distributed in that basin was found
inconsistent on WPI aspect. Though in comparison with water budget allocation per capita as
shown in Figure 5, it was found that the water budget is inconsistent with WPI either.
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293

90
80
70
60
50
40
30
20
10
0

Water Poverty Index Score (WPI)

77.98
MAE NAM CHAO PHRAYA

73.33

75.12
MAE NAM NAN

MAE NAM MAE KLONG

72.62

70.36

64.23
PRACHUAPKHIRI - KHAN
COAST

MAE NAM PING

63.51
MAE NAM KHONG
(North)

MAE NAM SAKAE KRANG

63.27
MAE NAM PRACHINBURI

69.64

63.15
EAST COAST GULF

67.86

61.49
PENINSULA - EAST
COAST

MAE NAM THA CHIN

60.54
MAE NAM KHONG
(Northeast)

MAE NAM PHETCHABURI

60.42
THALE SAP SONGKHLA

65.60

59.76
TONLE SAP

64.88

59.11
MAE NAM SALAWIN

MAE NAM YOM

58.51
MAE NAM CHI

Water Budget (Baht/Sq.Km.)

MAE NAM BANG PAKONG

58.21
MAE NAM PASAK

64.82

55.89

64.58

55.89
MAE NAM KOK

PENINSULA - WEST
COAST

MAE NAM TAPI

54.64

MAE NAM WANG

52.20
MAE NAM MUN

1,000,000
900,000
800,000
700,000
600,000
500,000
400,000
300,000
200,000
100,000
-

MAE NAM PATTANI

Water Budget (Baht/Sq.Km.)

Water Budget Allocation, sorting by WPI

WPI Score

69.64

70.36

72.62

73.33

75.12

77.98

MAE NAM THA CHIN

MAE NAM PING

MAE NAM SAKAE KRANG

MAE NAM MAE KLONG

MAE NAM NAN

MAE NAM CHAO PHRAYA

65.60
MAE NAM BANG PAKONG

67.86

64.88
MAE NAM YOM

MAE NAM PHETCHABURI

64.82
MAE NAM WANG

64.23
PRACHUAPKHIRI - KHAN…

64.58

63.51

MAE NAM TAPI

63.27
MAE NAM PRACHINBURI

MAE NAM KHONG (North)

60.42
THALE SAP SONGKHLA

63.15

59.76
TONLE SAP

61.49

59.11
MAE NAM SALAWIN

EAST COAST GULF

58.51
MAE NAM CHI

PENINSULA - EAST COAST

58.21
MAE NAM PASAK

60.54

55.89

55.89
MAE NAM KOK

PENINSULA - WEST…

54.64

8,000

MAE NAM PATTANI

10,000

52.20

12,000

MAE NAM MUN

6,000
4,000
2,000
-

MAE NAM KHONG…

Water Budget per capita (Baht : Person)

Water Budget Allocation, sorting by WPI

Water Budget per capita (Baht : Person)

90
80
70
60
50
40
30
20
10
0

Water Poverty Index Score (WPI)

Figure 4: Water Budget Allocation, compared with basin area, sorting by WPI.

WPI Score

Figure 5: Water Budget Allocation, compared with capita, sorting by WPI.
Based on the study results of water budget allocation per basin area and of compared WPI,
as shown in Table 5, the basins with WPI scores and ranking in Quartile 1, with high water
scarcity and water budget still in Quartile 1 Group, which received less funding than other
areas, were i.e. Mae Nam Salawin and Mae Nam Chi
According to the study results of water budget allocation per capita compared to WPI, as
shown in Table 6, the basins with WPI scores in Quartile 1 Group, which received less funding
than other areas, were i.e. Mae Nam Kok, Mae Nam Chi and Mae Nam Mun. The study through
comparison of two approaches will be an alternative for the five agencies involved in water
resources to use the WPI statistics and maps in addition to policy planning of water budget
allocation to manage water resources more effectively.
294


Basin
ID
01
02N
02NE
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25

Basin Name
MAE NAM SALAWIN
MAE NAM KHONG (Northeast)
MAE NAM KOK
MAE NAM CHI
MAE NAM MUN
MAE NAM PING
MAE NAM WANG
MAE NAM YOM
MAE NAM NAN
MAE NAM CHAO PHRAYA
MAE NAM SAKAE KRANG
MAE NAM PASAK
MAE NAM THA CHIN
MAE NAM MAE KLONG
MAE NAM PRACHINBURI
MAE NAM BANG PAKONG
TONLE SAP
EAST COAST GULF
MAE NAM PHETCHABURI
PRACHUAPKHIRI - KHAN COAST
MAE NAM TAPI
THALE SAP SONGKHLA
MAE NAM PATTANI
PENINSULA - WEST COAST

Figure 6: Water Poverty Index Ranking, in 25 river basins, Thailand
Table 5: Comparison of Water Budget Allocation per basin area and WPI

Water Poverty Index Ranking

Water Budget Allocation per Basin area Ranking (Baht/Sq.Km.)

52.2 - 59.27
(Quartile #1)
59.27 - 63.39
(Quartile #2)

47,267.07 - 131,221.78
(Quartile #1)
MAE NAM SALAWIN
MAE NAM CHI

131,221.78 - 167,653.28
(Quartile #2)
MAE NAM KOK
MAE NAM MUN

TONLE SAP

MAE NAM PRACHINBURI

MAE NAM WANG
MAE NAM TAPI

63.39 - 67.29
(Quartile #3)
67.29 - 77.98
(Quartile #4)

MAE NAM PING
MAE NAM SAKAE KRANG
MAE NAM MAE KLONG

MAE NAM THA CHIN

167,653.28 - 225,937.64
(Quartile #3)
MAE NAM PASAK
MAE NAM PATTANI

PRACHUAPKHIRI - KHAN
COAST
MAE NAM PHETCHABURI

225,937.64 - 945,230.96
(Quartile #4)

EAST COAST GULF
THALE SAP SONGKHLA
MAE NAM YOM
MAE NAM BANG PAKONG
MAE NAM NAN
MAE NAM CHAO PHRAYA

Based on the study results of budget allocation compared to basin area and budget
allocation compared to population (Table 3), the basins classified into Quartile 1 were i.e. Mae
Nam Chi and Tonle Sap. However, if compared by using WPI scores to analyze as well, it was
found that Mae Nam Chi would be classified into Quartile 1 in both respects of less water and
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295

low WPI, which represented shortage of both water and budget. While Tonle Sap had WPI
scores in Quartile 2, that is, having fewer budgets but with fair WPI ratings.
Table 6: Comparison of Water Budget Allocation per capita and WPI
Water Budget Allocation per Captita Ranking (Baht/person)

Water Poverty Index Ranking

738.48 - 1,072.79
(Quartile #1)

1,072.79 - 1,840.43
(Quartile #2)

1,840.43 - 3,264.02
(Quartile #3)

3,264.02 - 11,346.16
(Quartile #4)

MAE NAM KOK
MAE NAM CHI
MAE NAM MUN

MAE NAM PASAK
MAE NAM PATTANI


MAE NAM SALAWIN

TONLE SAP

52.2 - 59.27
(Quartile #1)

THALE SAP SONGKHLA

MAE NAM PRACHINBURI
EAST COAST GULF


MAE NAM WANG

MAE NAM YOM
MAE NAM BANG PAKONG
PRACHUAPKHIRI - KHAN COAST

MAE NAM SAKAE KRANG
MAE NAM PHETCHABURI

MAE NAM NAN

59.27 - 63.39
(Quartile #2)
MAE NAM TAPI
63.39 - 67.29
(Quartile #3)

67.29 - 77.98
(Quartile #4)

MAE NAM CHAO PHRAYA
MAE NAM THA CHIN

MAE NAM PING
MAE NAM MAE KLONG

According to Table 4, Mae Nam Chi had restrictions on capacity (C) and environment (E),
ranked in Quartile 1, with low WPI scores, requiring updated guidelines for development to
increase capacity. There are also restrictions on utilization (U), found in Quartile 2, which can
improve more efficient water use. Therefore, the five government agencies may have policies
to develop water sources to improve water use so as to increase agricultural productivity and
fairly distribute water resources later.

4. Conclusion
A comparison of the historical water budget allocations among the basins and water
poverty level are the important information for policymakers to decide on the budget allocation
for water project over the country. Water Poverty Index (WPI) is an index developed by
Sullivan (2002), consisting of 5 main factors of Resources (R), Access (A), Capacity (C), Use
(U) and Environment (E). In this study, WPI scoring system has been developed with 22
sub-factors in order to analyze the priorities of basins that required water allocation according
to water scarcity ranking.
WPI application related to water resources consists of 5 main factors, resources (R), access
(A), capacity (C), use (U) and environment (E). The water budget information from five
government agencies of: Department of Royal Irrigation; Department of National Parks;
Wildlife and Plant Conservation; Department of Water Resource; Department of Land
Development; and, Department of Local Administration have been collected to use in this
296


study. The 22 sub-factors, which developed from water resources characteristics of each basin
and the historical budget allocations over Thailand, were categorized into these 5 main factors.
It was found that WPI score of 25 basins were neither consistent with the allocated budget to the
basin nor corresponded to the water budget per capita.
The Quartile system has been applied to arrange the group of WPI score in order to clarify
the significant level of water/budget needs. High water shortage with less budget allocation per
capita and budget allocation per area, was set as the first Quartile group of the basin. Mae Nam
Chi is the basin of the highest level of water problem whereas the least allocated water budget,
as shown in the GIS map. Statistics of WPI scores reflect the areas vulnerable to water
shortages.
The spreadsheet program has been developed in this study in order to implement the
scoring system easily. This program contains all 22 sub-factors of 5 main factors. However, the
WPI scoring system is based only on water poverty. There should be further study on
integration of disaster index into the scoring system. Moreover, the benefit of economic crop
over the basins should be taken into account to the priority consideration.

5. Acknowledgements
This study was accomplished with the aid of data from Department of Local Government,
Land Development Department, Department of Water Resources, Department of National
Parks, Wildlife and Plant Conservation, and courtesy of the Senate Committee on Agriculture
as well as those involved in this study. Therefore, the researcher would like to thank herein for
this opportunity

6. References
HAII (Hydro and Agro Informatics Institute), (2008). Study of the National Water Policy
Framework, Parliament House, Thailand.
International Commission on Irrigation and Drainage (ICID), (2012). General Information
about Thailand. http://www.icid.org/v_thailand.pdf.
Sen, A.K. (1999). Development as Freedom, Oxford: Clarendon Press.
Mlote, S.D.M., Caroline Sullivan and Jeremy Meigh. (2002). Water Poverty Index: a Tool for
Integrated Water Management. 3rd WaterNet/Warfsa Symposium ‘Water demand
Management for Sustainable Development’, Dar es Salaam, 30-31 Octerber 2002: 1-20.
ISSN 2228-9860

297

Sullivan, C.A. (2002). Calculating a Water Poverty Index.
1195-1210.

World Development, 30,

Sullivan, C.A., Meith, J.R. (2003). Access to water as a dimension of poverty: The need to
develop a Water Poverty Index as a tool for poverty reduction. In: Aseygul, K., Olcay
Unver, I.H and Gupta, R.K. (Eds). Quantitative measurement of poverty reduction
through water provision, Elseriver, UK.
Sullivan, C.A., Meith, J.R. (2006). Application of the Water Poverty Index at Different
Scales: A Cautionary Tale. International Water Resources Association, Water
International, Volume 31(3): 412-426.
Sullivan, C.A., Meith, J.R., Fediw, T. (2002). Developing and Testing the Water Poverty
Index: Phase 1, Final Report. Report to Df1D, CEH: Wallingfor, UK.
Sullivan, C.A., Meith, J.R., Giacomello, A.M., et al. (2003). The Water Poverty Index:
Development and application at the community scale. Natural Resource Forum, 27,3:
189-199.
Thulani F. Magagula, Barbara van Koppen and Hilmy Sally, (2006) Water Access and Poverty
in the Olifants Basin: A Spatial Analysis Of Population Distribution, Poverty
Prevalence And Trends, WaterNet/WARFSA/GWP Annual Symposium, 1-3
November 2006, Lilongwe, Malawi: Theme 5: Water for People.

Supet Jirakajohnkool is an Associate Professor of Department of Rural Technology Faculty of Science and
Technology, Thammasat University. He received his B.Sc. (Rural Technology) from Thammasat University,
with 2nd Honors in 1997. He continued his M.Sc. (Remote Sensing and GIS) study at Asian Institute of
Technology, Thailand. He works in the area of rural technology, with emphasis on Geo-Informatics of rural
development. He focuses on GIS (Geographic Information Systems), Remote Sensing, geomatics.
Dr.Uruya Weesakul earned her Ph.D. in Mechanical and Civil Engineering from the University of Montpellie
II (France) in 1992. She is currently Associate Professor, Thammasat University. She works in the area of civil
engineering, with emphasis on Water Resources Engineering.

Dr.Sarintip Tantanee is an Associate Professor of Department of Civil Engineering, Faculty of Engineering,
Naresuan University. She earned her Ph.D. in Water Resources Engineering from Khon Kaen University. She is
currently Associate Professor, Khon Kaen University. She works on the water resources research, with
emphasizes on hydro-meteorology, space information application and water resources policy.

Peer Review: This article has been internationally peer-reviewed and accepted for publication
according to the guidelines given at the journal’s website.

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Budget Allocation Assessment for Water Resources Project in Thailand Using GIS-based Water Poverty Index

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Budget Allocation Assessment for Water Resources Project in Thailand Using GIS-based Water Poverty Index