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

Transcription

1 2013 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies Budget Allocation Assessment for Water Resources Project in Thailand Using GIS-based Water Poverty Index Supet Jirakajohnkool a*, Uruya Weesakul a and Sarintip Tantanee b a Department of Civil Engineering, Faculty of Engineering, Thammasat University, THAILAND b Department of Civil Engineering, Faculty of Engineering, Naresuan University, THAILAND A R T I C L E I N F O 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; A B S T R A C T 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 INT TRANS J ENG MANAG SCI TECH.. *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 283

2 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 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

3 2. GIS Preparation Process for Budget Allocation Monitoring 2.1 Studying water budget allocation during the years 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 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 ) 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, *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 285

4 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. WPI N i= 1 = N i= 1 w X i w i i (1), 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 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 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

5 N i= 1 w 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. wr R + wa A + wcc + wuu + we E WPI = (3), w + w + w + w + w r a c u e By using w r, w a, w c, w u and w e 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. *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 287

6 Table 1: Data Selected As WPI Component Variables for 25 River Basins Assessment (Modified from Sullivan (2002)). WPI Components* Data Used Sources of data Resources (R) Quantitative evaluation of measurable values of surface water in each basin 1. Runoff per year (million cubic meters) 2. Retention water per year (million cubic meters) 3. Potential ground water (million cubic meters / year) 4. Average rainfall (mm 3 / year). -Royal Irrigation Department -Department of Groundwater Resources -Meteorological Department Access (A) Assessment of water access and effective use in each basin 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 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 / m 3 ) 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 -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 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

7 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 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 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 ( ), 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 *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 289

8 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. Water Budget (million baht) 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2, , , , Water Budget ( ) of 5 Deparments (million baht) Department of Royal 10, , , , , , , , Figure 1: Water Budget Allocation in ( ) 5 years by 5 Departments. 15, , , Irrigation Department of Local Administration Department of Land Development Department of Water Resource Department of National Parks, Wildlife and Plant Conservation 290 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

9 Figure 2: Water Budget Allocation per basin area in ( ) 5 years. Figure 3: Water Budget Allocation per capita in 5 years ( ) 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 *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 291

10 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 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

11 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. *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 293

12 Water Budget Allocation, sorting by WPI Water Budget (Baht/Sq.Km.) 1,000, , , , , , , , , , MAE NAM MUN MAE NAM PATTANI MAE NAM KOK PENINSULA - WEST COAST MAE NAM PASAK MAE NAM CHI MAE NAM SALAWIN TONLE SAP THALE SAP SONGKHLA MAE NAM KHONG (Northeast) PENINSULA - EAST COAST EAST COAST GULF MAE NAM PRACHINBURI MAE NAM KHONG (North) PRACHUAPKHIRI - KHAN COAST MAE NAM TAPI MAE NAM WANG MAE NAM YOM MAE NAM BANG PAKONG MAE NAM PHETCHABURI MAE NAM THA CHIN MAE NAM PING MAE NAM SAKAE KRANG MAE NAM MAE KLONG MAE NAM NAN MAE NAM CHAO PHRAYA Water Poverty Index Score (WPI) Water Budget (Baht/Sq.Km.) WPI Score Figure 4: Water Budget Allocation, compared with basin area, sorting by WPI. Water Budget per capita (Baht : Person) 12,000 10,000 8,000 6,000 4,000 2, MAE NAM MUN MAE NAM PATTANI MAE NAM KOK PENINSULA - WEST MAE NAM PASAK MAE NAM CHI Water Budget Allocation, sorting by WPI MAE NAM SALAWIN TONLE SAP THALE SAP SONGKHLA MAE NAM KHONG PENINSULA - EAST COAST EAST COAST GULF MAE NAM PRACHINBURI MAE NAM KHONG (North) PRACHUAPKHIRI - KHAN MAE NAM TAPI MAE NAM WANG MAE NAM YOM MAE NAM BANG PAKONG MAE NAM PHETCHABURI MAE NAM THA CHIN MAE NAM PING MAE NAM SAKAE KRANG MAE NAM MAE KLONG MAE NAM NAN MAE NAM CHAO PHRAYA Water Poverty Index Score (WPI) Water Budget per capita (Baht : Person) 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 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

13 Basin Basin Name ID 01 MAE NAM SALAWIN 02N MAE NAM KHONG (North) 02NE MAE NAM KHONG (Northeast) 03 MAE NAM KOK 04 MAE NAM CHI 05 MAE NAM MUN 06 MAE NAM PING 07 MAE NAM WANG 08 MAE NAM YOM 09 MAE NAM NAN 10 MAE NAM CHAO PHRAYA 11 MAE NAM SAKAE KRANG 12 MAE NAM PASAK 13 MAE NAM THA CHIN 14 MAE NAM MAE KLONG 15 MAE NAM PRACHINBURI 16 MAE NAM BANG PAKONG 17 TONLE SAP 18 EAST COAST GULF 19 MAE NAM PHETCHABURI 20 PRACHUAPKHIRI - KHAN COAST 21 PENINSULA - EAST COAST 22 MAE NAM TAPI 23 THALE SAP SONGKHLA 24 MAE NAM PATTANI 25 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 Budget Allocation per Basin area Ranking (Baht/Sq.Km.) Water Poverty Index Ranking (Quartile #1) (Quartile #2) (Quartile #3) (Quartile #4) 47, , (Quartile #1) MAE NAM SALAWIN MAE NAM CHI MAE NAM KHONG (Northeast) TONLE SAP MAE NAM PING MAE NAM SAKAE KRANG MAE NAM MAE KLONG 131, , (Quartile #2) MAE NAM KOK MAE NAM MUN MAE NAM PRACHINBURI MAE NAM WANG MAE NAM TAPI 167, , (Quartile #3) MAE NAM PASAK MAE NAM PATTANI PENINSULA - WEST COAST MAE NAM KHONG (North) PRACHUAPKHIRI - KHAN COAST 225, , (Quartile #4) PENINSULA - EAST COAST EAST COAST GULF THALE SAP SONGKHLA MAE NAM YOM MAE NAM BANG PAKONG MAE NAM THA CHIN MAE NAM PHETCHABURI 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 *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 295

14 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 (Quartile #1) (Quartile #2) (Quartile #3) (Quartile #4) , (Quartile #1) MAE NAM KOK MAE NAM CHI MAE NAM MUN TONLE SAP 1, , (Quartile #2) MAE NAM PASAK MAE NAM PATTANI MAE NAM KHONG (Northeast) THALE SAP SONGKHLA 1, , (Quartile #3) PENINSULA - WEST COAST MAE NAM PRACHINBURI EAST COAST GULF 3, , (Quartile #4) MAE NAM SALAWIN PENINSULA - EAST COAST MAE NAM TAPI MAE NAM WANG MAE NAM KHONG (North) MAE NAM YOM MAE NAM BANG PAKONG PRACHUAPKHIRI - KHAN COAST MAE NAM CHAO PHRAYA MAE NAM THA CHIN MAE NAM PING MAE NAM MAE KLONG MAE NAM SAKAE KRANG MAE NAM PHETCHABURI MAE NAM NAN 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 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee

15 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. 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, Octerber 2002: *Corresponding author (S.Jirakajohnkool). Tel/Fax: Ext address: supetgis2me@gmail.com International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 4 No.4 ISSN eissn Online Available at 297

16 Sullivan, C.A. (2002). Calculating a Water Poverty Index. 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): 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: 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 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 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. 298 Supet Jirakajohnkool, Uruya Weesakul, and Sarintip Tantanee