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International Journal of Scientific Research

http://journalijsr.com/ Vol. II, Issue 1, 2017

APPLYING THE STRUCTURAL EQUATION MODELING IN THE DETERMINATION OF RISK GROUPS CAUSING WATER RESOURCE

INSECURITY Nguyen Truc Lea,*, Nguyen ManhCuonga, Nguyen Viet Loca, Nguyen Tat Tuanb,

Nguyen Ngoc Mienc aUniversity of Economics and Business, Vietnam National University,

144, XuanThuy, Hanoi, Vietnam bCenter for Water Resources Monitoring and Forecast, Ministry of Natural Resources and

Environment, 10 Ton That Thuyet, Hanoi, Vietnam cCentral for Rural Water Supply and Sanitation, Lai Chau, Vietnam

Abstract The research aims at considering the risk groups causing water resource insecurity in Vietnam. The research is conducted based on the survey data from the residents and the managers in Vietnam's Northwestern provinces including HoaBinh, Dien Bien, Son La and Lai Chau. Three groups of measuring scales are applied in the research including demand scale, policy mechanism scale and natural elements scale. Based on the survey data, the structural equation modeling is applied to analyze the risk groups causing water in security including three steps: (i) testing the reliability coefficient of the scales; (ii) exploratory factor analysis (EFA); (iii) confirmatory factor analysis (CFA). The analysis results indicate that the groups of natural elements and policy mechanism affect water security, whereas the group of demand has no impact on water security. Key words: Structural equation modeling; Water security; Vietnam Introduction For over a decade, water securityhas been warned about the worldwide shortage of water by the scientists and international organizations. According to World Water Development Report, the world will encounter a shortage of water supply by 40% in the next 15 years (UNESCO, 2015). This indicatesthat the security ensurance of water becomes an urgent issue of many countries. Although Vietnam owns the abundant water reserves, the country is facing to the significant challenge on water security due to the unequal distribution of water resources, environmental pollution, decline in water resource in terms of water quantity and quality and strong dependence on the water of the rivers with 63% of total flow of Vietnam rivers from the neighboring countries. In addition, due to the impact of the industrialization and modernization process, the pressure of population growth, the urbanization process, the rise in food demand, the complex shrinking of agricultural land and watershed forests,water security in some areas has been seriously threatened. The dumping of industrial waste, domestic waste without treatment, use of chemicals and pesticides in agriculture seriously pollute the water resources both surface water and groundwater. The

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construction of hydropower plants in the upstream areas of the major rivers has severely changed the water flow, reduced the sediment to the downstream delta and destroyed the biodiversity and implications which can not predicted tothe security and safety for the residents in the area of river basin.The unreasonable exploitation and use of water resources, even over-exploitation that has not accompanied with management of the exploitation and protection, cause the water resources decline and more serious pollution affecting the lives and production. The deployment of the coordinating mechanism and the supervision of coordination activities of the ministries, industries, businesses, communities and residents to address the common issues across the river basin have been inefficient. The consequences of waterinsecurityare very serious to humans, water resources, increasing the risk of unsustainable economic- social growth and development. The decline in water resources becomesthe big challenge in ensuring water security for sustainable development.

Many researchers and international organizations have conducted the studies on the various issues related to water security (Jiang, 2015; Bindra et al, 2014; Pahl-Wost et al, 2013; Bogardi et al, 2012; Brown and Matlock, 2011; David and Claudia, 2007). These studies focus on solving one of the following contents: (i) clarifying the definition of water security; (ii) identifying the groups of factor affecting water security; (iii) providing the solutions that contribute to improve the efficiency of water use and management. However, in Vietnam, the number of studies related to water securityis limited, especially the studies on risks of water insecurity in the river basin.

Therefore, the purpose of the study is to consider the risks ofwaterinsecurity at Da River basin - the largest tributary of the Red River. The data of study is collected through a survey of residents and managers in Vietnam's Northwestern provincesincludingHoa Binh, Dien Bien, Son La, and Lai Chau.

2. Research procedure and methods

Based on the literature review, the measuring scales are adopted in this study including: natural elements scale, demand scale and policy mechanism scale. Specifically, the risk groups related to natural elements include: geohazard (measured by six variables from TBDC 1 to TBDC 6), climate change (measured by three variables from BDKH 1 to BDKH 3), land covering (measured by two variables TP1-2), topography, geomorphology (measured by four variables from DHDM 1 to DHDM 4), groundwater (measured by six variables from NNgam1 to NNgam6) and surface water (measured by six variables from NMat1 to NMat6). The risk groups related to the water demand include: environmental flow (measured by three variables from DCMT1 to DCMT3), tourism and services (measured by four variables from DLDV1 to DLDV4), industry (measured by three variables from CN1 to CN3), agriculture (measured by three variables from NN1 to NN3) and living (measured by three variables from SH1 to SH3), hydropower (measured by six variables from TD1 to TD6). The risk groups related to policy mechanisms includes: crime and terrorism (measured by three variables from TPKB1 to TPKB3), policies and legislation (measured by seven variables from CCCS1 to CCCS7), education and communication (measured by six variables from GDTT1 to GGTT6), politics and diplomacy (measured by five variables from Ctri1 to Ctri5.

In this study, the method of sociology investigation using questionnaire survey is

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applied to collect primary data. The samples are selected according to the convenient method, one of the non-probability sampling models. According to the convenient sampling method, the selected respondents are able to be accessed. After being completed, the questionnaire is sent to 560 respondents (including the residents and managers of HoaBinh, Dien Bien, Son La and Lai Chau province), and the number of valid responses received is 500 votes (accounting for 89.3%). According to Hair et al. (1998), to achieve EFA, the applied sample size of the study is at least 5 folds of the total number of observed variables. The model has 92 observation variables, so the minimum number of samples is 92*5 = 460; for multivariate regression analysis: the minimum sample size needed to be achieved by the formula is 50 + 8 * m (where m is the number of independent variables) (Tabachnick and Fidell, 1996). The research has 8 independent variables, so the minimum sample size is 50 + 8*8 = 114 observations. Thus, the total sample of 500 is entirely consistent with the requirements, ensuring the overall representation.

The measuring scales are preliminarily evaluated through two main tools including reliability coefficient - Cronbach alpha and Exploratory Factor Analysis (EFA). Cronbach Alpha was used in advance to remove the unsuitable variables. The variables have the item-total correlation which is less than 0.30 will be removed, so the criteria for selecting the scale will have the Cronbach alpha from 0.60 (Nunnallly and Berntein, 1994). Next, EFA is applied. In this section, the variable has factor loading which is less than 0.40 in EFA will continue to be removed. The scale is accepted if the total average variance extracted is equal or greater than 50% (Gerbing and Anderson, 1988). Finally, the scale is evaluated by CFA through the AMOS21 software.

3. The analysis result in the mainstream of Da River 3.1. Background of Da River

Da River is the largest tributary of the Red River, originating from Van Nam Province - China, and flowing into Vietnam in MuongTe (Lai Chau), making the confluence with the Red River in PhuTho. Da River valley is 52,500 km2 with the length of 910 km. The section in the territory of Vietnam covers an area of 26,800 km2 and 540 km in length.

The river flows across the north-western provinces of Vietnam including Lai Chau, Dien Bien, Son La, HoaBinh and PhuTho. The rivers and streams in the Da Riverbasin have narrow valley and the river beds are being seriously dug up, with many rapids. The average altitude of the river valley is 1,130 metres; particularly the section in the territory of Vietnam is 965 meters. Beside the mainstream, Da River hassix river branches including Nam Po, Nam Na, Nam Muc, Nam Mu, Nam Sap, and Nam Bu.

The river has ahigh discharge, providing 31% of the water for the Red River and the river is the great hydropower resource for Vietnam’s power industry. Along Da River, a

lot of reservoirs have been built to serve the power generation, downstream flood control and enhancing the downstream flow during the dry season for irrigation and water supply.These hydroelectric power plants includeHoaBinh, Son La, and Lai Chau. The river basin has the great resource potential with various types of rare minerals, tupical ecosystems including biological sources with high biodiversity level. 3.2. Analysis result

In this section, to assess the risk group causing of water resource insecurity in the

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mainstream area of Da River, the study is conducted via 03 steps: (i) testing the reliability of the scale; (ii) analyzing the exploratory factor (EFA); (iii) analyzing the confirmatory factor (CFA). 3.2.1. Testing the reliability of the scale

The results from testing the reliability of the scale show that most of the variables in the three scales have the Cronbach’s Alpha> 0.6 and item -total correlation coefficients> 0.4. The variables which are not suitable are excluded from the model including: Nngam3, Nmat3, and TBDC2

3.2.2. EFA a) The measuring scale of policy mechanism

The analysis result of EFA for the policy mechanism group indicates that KMO, Bartlett's test and Cumulative of variance satisfy the requirements. However, the observed variables of GDTT1, CSPL7, Ctri1, Ctri2, and Ctri3 do not satisfy the factor loading. Thus, these variables need to be excluded from the model.

Table 1.Rotation matrix -measuring scale of policy mechanism

Factors 1 2 3 4 5

GDTT2 .932 GDTT3 .612 GDTT4 .858 GDTT5 .660 GDTT6 .616 TPKB1 .758 TPKB2 .920 TPKB3 .904 CSPL1 .681 CSPL2 .906 CSPL3 .751 CSPL4 .647 CSPL5 .835 CSPL6 .665 Ctri4 .734 Ctri5 .897 CCCS1 .728 CCCS2 .851 CCCS3 .645 Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.874 Bartlett's Test of Sphericity Approx. Chi-Square 6368.753

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df 171 Sig. .000

Cumulative of Variance 62.919 b) The measuring scale of demand

The analysis results of EFA for the group of demand in Table 2show that KMO, Bartlett's test and Cumulative of variance fulfill the requirements. However, the factor loading of the variables TD4, TD5, and TD6areless than 0.5, so these variables should be excluded from the model.

Table 2.Rotation matrix - measuring scale of demand

Factor 1 2 3 4 5 6 7 NCSD2 .849 NCSD4 .819 NCSD3 .781 NCSD1 .756 NCSD5 .708 NCSD6 .664 DLDV3 .869 DLDV4 .862 DLDV2 .677 DLDV1 .618 NN2 .889 NN1 .640 NN3 .601 SH2 .842 SH1 .691 SH3 .676 CN2 .920 CN1 .676 CN3 .567 DCMT2 .883 DCMT1 .676 DCMT3 .630 TD1 .827 TD2 .612 TD3 .534 Kaiser-Meyer-Olkin Measure of Sampling Adequacy. (KMO) 0.886

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Bartlett's Test of Sphericity Approx. Chi-Square 7182.686 df 300 Sig. .000

Cumulative of Variance (%) 58.203 c) The measuring scale of natural elements

The analysis results of EFA for the group of natural elements (in Table 3) show that KMO, Bartlett's test and Cumulative of variance fulfill the requirements. However, the factor loading of the variable DHDM1 is less than 0.5. Thus, this variable is excluded from the model.

Table 3.Rotation matrix - measuring scale of natural elements

Factor 1 2 3 4 5 6 7 YTTN2 .802 YTTN5 .764 YTTN4 .713 YTTN1 .684 YTTN3 .584 TBDC4 .870 TBDC5 .703 TBDC3 .678 TBDC6 .614 TBDC1 .561 NMat5 .711 NMat4 .708 NMat6 .665 NMat1 .657 NMat2 .618 NNgam6 .812 NNgam5 .682 NNgam1 .632 NNgam2 .569 NNgam4 .562 TPhu2 .913 TPhu1 .859 DHDM4 .772 DHDM2 .654

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DHDM3 .614 BDKH3 .769 BDKH2 .647 BDKH1 .556 Kaiser-Meyer-Olkin Measure of Sampling Adequacy. (KMO) 0.728

Bartlett's Test of Sphericity Approx. Chi-Square 5945.018 df 378 Sig. .000

Cumulative of Variance (%) 50.853 3.2.3. Confirmatory factor analysis a) Scale of policy mechanism

After competing EFA, the author conducts the confirmatory factor analysis, the result is obtained in terms of model as follows (Figure 1): CMIN/df = 3.978 < 5 (acceptable level); CFI, TLI, GFI coefficients are greater than 0.9; RMSEA = 0.071 <0.08. So, the model is entirely appropriate for the data.

Figure 1.The analysis result of measuring scale of policy mechanism

The result from Figure 1 also shows that the variables in the model have the weight > 0.5, so the scales achieve the convergence value. From Table 4, we see that with the significance level (10%), the factors policy and legislation, education and communication factors affecting the scale of policy mechanism; while the factors crime and terrorism, politics and diplomacy have no impact on the scale of policy mechanism.

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Table 4.Covariance value of policy mechanism scale

Estimate S.E. C.R. P CSPL <--> CCCS -.055 .031 -1.762 .078 GDTT <--> CCCS -.062 .033 -1.891 .059 TPKB <--> CCCS -.006 .031 -.185 .854 CCCS <--> Ctri -.031 .025 -1.245 .213 b) Scale of demand

Figure 2 shows that the model is appropriate for the data: CMIN/df<5 (acceptable level); CFI, TLI, GFI coefficients are greater than 0.9 and RMSEA = 0.056 < 0.08

Figure 2. The analysis result of measuring scale of demand

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Table 5 indicates that with the significance level 1%, the factors TD, DLDV, CN, SH, and NN affecting the scale of NCSD, while the factor DCMT has no impact on the scale of NCSD.

Table 5. Covariance value of demand scale

Estimate S.E. C.R. P NCSD <--> DLDV .206 .027 7.737 *** NCSD <--> NN .133 .023 5.748 *** NCSD <--> SH .216 .028 7.593 *** NCSD <--> CN .161 .028 5.833 *** NCSD <--> DCMT .013 .033 .403 .687 NCSD <--> TD .143 .027 5.363 *** c) Scale of natural elements

The results from CFA show that the scales of variables NNgam2 and NNgam4 do not achieve the convergence value (because their weights are less than 0.5), so these variables should be excluded from the model. The results obtained after removing these variables indicate that the model is appropriate for the data: CMIN/df = 2.527 <3;CFI, TLI, GFI coefficients are greater than 0.9; RMSEA =0.05 <0.08.

Figure 3.The analysis result of measuring scale of natural elements

Table 6 shows that with the significance level (1%), the factors NNgam, Nmat, and TP affecting the scale of YTTN, while the factors DHDM, TBDC, BDKH have no impact on

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the scale of YTTN. Table 6. Covariance value of natural elements scale

Estimate S.E. C.R. P YTTN <--> TBDC -.047 .030 -1.584 .113 YTTN <--> NMat .061 .022 2.727 .006 YTTN <--> NNgam .092 .030 3.071 .002 YTTN <--> TPhu .126 .042 3.002 .003 YTTN <--> DHDM -.041 .031 -1.335 .182 YTTN <--> BDKH .058 .039 1.496 .135 3.3. SEM model analysis for water security scales

From Figure 4, we have: CMIN/df<5 (acceptable level); CFI, TLI, GFI coefficients are greater than 0.9 and RMSEA = 0.051 < 0.08. So, the model is appropriate for the data. Figure 4.The results of SEM analysis for water security scales

From Table 7, we can find that with the significance level (5%), the factors YTTN and CCCS affecting the scale of ANNN, while the factor NCSD has no impact on the scale of YTTN. Table 7.Covariance value of water security scales

Estimate S.E. C.R. P ANNN <--- NCSD -.362 .237 -1.524 .128 ANNN <--- YTTN .419 .191 2.191 .028 ANNN <--- CCCS 4.827 1.710 2.823 .005

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4. Discussion and conclusion Table 8 summarizes the results of hypothesis test in the section 3. The results

show the conformity of theoretical models with market information as well as the acceptance of the hypotheses: H1, H3-H5, H7, H10-H14, H17, H18 and the reject of hypotheses: H2, H6, H8, H9, H15, H16, H19 mentioned in this study offer some practical meanings for the agencies of water resource management as a basis for making the appropriate policies in the water security protection in Da River Table8.The hypothesises of the study

No Interpretation of the hypotheses Analysis results

H1 Having the confirmatory relationship between natural elements and water security Significance

H2 Having the confirmatory relationship between demand and water security Insignificance

H3 Having the confirmatory relationship between policy mechanism and water security Significance

H4 Having the confirmatory relationship between surface water and natural elements Significance

H5 Having the confirmatory relationship between groundwater and natural elements Significance

H6 Having the confirmatory relationship between topography, geomorphology and natural elements Insignificance

H7 Having the confirmatory relationship between land covering and natural elements Significance

H8 Having the confirmatory relationship between climate change and natural elements Insignificance

H9 Having the confirmatory relationship between geohazard and natural elements Insignificance

H10 Having the confirmatory relationship between hydroelectricity and water demand Significance

H11 Having the confirmatory relationship between living and water demand Significance

H12 Having the confirmatory relationship between agriculture and water demand Significance

H13 Having the confirmatory relationship between industry and water demand Significance

H14 Having the confirmatory relationship between tourism, sevices and water demand Significance

H15 Having the confirmatory relationship between invironmental flow and water Insignificance

H16 Having the confirmatory relationship between politics, diplomacy and policy mechanism Insignificance

H17 Having the confirmatory relationship between eduation, Significance

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communication and policy mechanism

H18 Having the confirmatory relationship between policy and legislation and policy mechanism Significance

H19 Having the confirmatory relationship between crime, terrorism and policy mechanism Insignificance

The research indicates that water security is mainly affected by the natural

elements (there are three factor groups including surface water, groundwater and land covering) and the policy mechanism (including education and communications, policy and legislation). In details, surface water includes 05 observations with impact of surface water 1, 2, 4-6 (due to flood and the shortage of surface water in dry season for living, cultivation and livestock); The groundwater includes 03 observations with impact which are groundwater 1, 5, 6 (cultivation and livestock are likely to cause the pollution of groundwater due to the use of agricultural chemicals by the residents without the management of state agencies); Land covering includes 02 observations with impact that are land covering 1, 2 (a decline in land covering of vegetation due to farming practices and urbanization); education and communication elements include 05 observations with impact of education and communication 2-6 (due to the low awareness of residents in water protection in Da River, the propaganda and education to raise awareness of the people in the water security protection in the locality have been limited); policy and legislation include 06 observations with the impact of policy and legislation 1-6 (because the locals residents are not knowed the policies relating to the protection of water resources; the use of water and chemicals in agriculture production has not been strictly controlled by the local government; some policies on the water resource protection are not close to the real situation of the locality). Acknowledgements This study is the product of the research topic: "Research on the model construction in the water security assurance- applying the test for the water use for hydroelectricity in the mainstream of Da River". Code: 2015.02.15 References 1. Bindra SP, Hamidb A, Salemc H, Hamudad K, Abulifae S (2014). Sustainable

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