CC BY
31
УДК 556.18:519.8
V.I. Elfimov, H. Khakzad
PFUR
A FUZZY GROUP DECISION MAKING APPROACH TO SELECT THE BEST ALTERNATIVE FOR SUSTAINABLE SEDIMENT MANAGEMENT IN THE DEZ DAM RESERVOIR
The purpose of this research is to develop a new fuzzy group decision making algorithm and apply it to select the most preferred alternative for sediment management in the Dez dam reservoir. In this way, nine potential alternatives for sediment management in the Dez reservoir and four criteria (technical and executive requirements, economic factors, social welfare, environmental impacts) are selected. In order to evaluate different alternatives, firstly, the collective group weight of each alternative is calculated considering assessment of a group consisting of four criteria. And after that, the best alternative is selected using the proposed fuzzy group decision making methodology. The results of this study showed the efficiency of the application of fuzzy group decision making in sediment management. Application of the proposed method helps to balance the whole criteria and to select the best alternative.
Key words: fuzzy group decision making, sediment management, risk management.
The current estimate of total reservoir storage worldwide is around 7.000 km3. This storage is used for water supply, irrigation, power generation and flood control. Concerns about the loss of reservoir capacity due to sedimentation were raised in a World Bank publication in 1987 (Mahmood, 1987, [1]) and have been recently expressed in many forums and publications. Table 1 shows the worldwide distribution of storage, power generation and sedimentation rates. It is estimated that between 0.5 and 1.0 percent of global water storage volume is lost annually as a result of sedimentation (White, 2001 [2]).
Tab. i. Worldwide storage, power and sedimentation
Region Number of large dams Storage (km3) Total Power (GW) Hydropower production in 1995 (TWh/yr) Annual loss due to sedimentation (% of residual storage)
Worldwide 45.571 6.325 675 2.643 0.5...1
Europe 5.497 1.083 170 552 0.17...0.2
North America 7.205 1.845 140 658 0.2
South and Central America 1.498 1.039 120 575 0.1
North Africa 280 188 4.5 14 0.08.1.5
Sub Saharan Africa 966 575 16 48 0.23
Middle East 895 224 14.5 57 1.5
Asia (excluding China) 7.230 861 145 534 0.3.1.0
China 22.000 510 65 205 2.3
© Elfimov V.l., Khakzad H., 2014
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The «creeping» problem of sedimentation has several implications. First, the lost storage capacity has an opportunity cost in the form of replacement costs for construction of a new storage if the present level of supply is to be maintained. Second, there are direct losses in the form of fewer hydropower production capacity available for sale, less irrigated land to produce food and reduced flood routing capacity. Third, the filled reservoirs with no benefits to pay for their maintenance will continue to be a liability to their owners and could become a hazard. Finally, this sediment storage can hold significant implications for ecosystem downstream of large river systems (WCD, 2000 [3]; Woodward, 1995 [4]). Substantial sedimentation problems experienced within many national and international reservoirs, make sediment management in reservoirs a widespread problem (Morris and Fan, 1998 [5]).
Basing on literature and existing experiences a list of alternatives for sediment control of dam reservoirs can be found. The techniques can be categorized as follows (Annandale, 2003 [6]).
1. Reducing sediment inflows: 1-1) watershed management; 1-2) upstream check structures; 1-3) reservoir bypass; 1-4) off-channel storage.
2. Managing sediments within the reservoir: 2-1) operating rules; 2-2) tactical dredging.
3. Evacuation of sediments from the reservoir: 3-1) flushing; 3-2) sluicing; 3-3) density current venting; 3-4) mechanical removal (dredging, dry excavation, hydrosuction).
4. Replacing lost storage: 4-1) increased dam height; 4-2) construction of a new dam.
5. Decommissioning.
The literature on sediment management in reservoirs has focused mostly on engineering aspects (Morris and Fan, 1998 [5]). The review undertaken for the project revealed that there is very few, if any, published information on the economics of reservoir sedimentation and its implication for sustainable development. In order to assess the economic feasibility of sediment management the strategies should be able to answer two related questions: 1) Is the extra cost incurred in undertaking sediment management activities worthwhile in terms of extending the productive life of a dam? 2) Is it economic to extend the life of a dam indefinitely?
Up to now in too many cases insufficient attention has been paid to the environmental and social impacts of sediment management projects. Environmental and social issues must be accorded a status equal to, if not higher than, economic expediency. Potential environmental and social impacts and where possible potential opportunities for enhancement need to be identified early on the project life cycle so that they can be investigated thoroughly and be dealt with appropriately during project development.
Therefore, technical feasibility studies, environmental concerns, economic factors and social welfare should be considered to select the best alternative to extend the useful life of reservoirs. This study is focused on developing a fuzzy group decision making approach for balancing all the criteria and evaluating the feasibility of applying this method in selecting the best possible alternative for sediment management in the Dez dam reservoir.
1. Material and Method
1.1. Sediment management alternatives in Dez dam reservoir. This study is carried out at the Dez reservoir, which is located in the south of Iran. The Dez dam (Persian: jj ¿J) is a large hydroelectric dam in Iran, which was completed in 1963 by an Italian consortium (Fig. 1). At the time of the construction, the Dez dam was Iran>s biggest development project. Dez is a 203 m high double curvature arch dam, and the crest of Dez dam is 352 m above the sea level. The original reservoir volume was 3.315 million m3, and the volume of sediment estimated at 840 MCM for a 50-year period. An underground powerhouse contains eight 65 MW units for a total installed capacity of 520 MW. The minimum and maximum water level of the reservoir operation are 300 and 352 m from the sea level respectively. Although the project has been well-preserved, the project is now more than 40 years old and reaching its midlife period.
Fig. 1. Photo of Dez Dam Project (a) and a plan view of Dez reservoir (b)
Table 2 summarizes some key information that was supplied on the hydrology and reservoir characteristics. The useful life of Dez reservoir is threatened by a sediment delta, which is approaching the dam's intake tunnels. The hydrographic work in 2002 showed that sedimentation reduced the useful storage of the reservoir of the Dez dam from 3315.6 to 2700 MCM (19 % reduction). The difference between the levels of the inlet of turbine and bed surface of deposited sediment is 14 m, with the rate of 2 m/year (Fig. 2).
Tab. 2. The summary of hydrology and reservoir characteristics
Description Unit Value
Mean Annual Discharge of Dez River m3/s 260
Average Annual Runoff Volume of Dez River million m3 8.200
Mean Annual sediment load million t/year 17.4
Start of Reservoir Filling year 1962 (NOV)
Normal Range of Reservoir Elevation m 310...350
Initial Reservoir Storage Volume million m3 3315.6
Average Rate of Sediment Infilling million m3/year 15.8
Therefore, sediment management in the Dez reservoir is essential and of considerable importance. A list of potential alternatives can be sub-divided into four general concepts as follows (Dezab and ACTRES, 2004 [7]): 1) watershed rehabilitation; 2) sediment flushing and routing; 3) sediment removal and disposal; 4) dam raising. Each of the above concepts includes three or four sub-alternatives to achieve extension of reservoir life. Tab. 3 shows a technical and executive requirements of nine alternatives of sediment management in the Dez dam reservoir.
In order to select the best alternative, the environmental effects caused by flushing, dredging and associated disposal as well as dam heightening must be considered. The environmental effects of flushing operation due to concentrations of sediment could include effects on fish, impacts on recreational water use, domestic and livestock water supplies. In order to decrease the flushing effect on environment needs to be confined to relatively short-time intervals if Severity Index criteria are to be maintained.
Fig. 2. Sediment longitudinal profile of Dez Reservoir
Tab. 3. Sediment management alternatives
Alternative No. Alternative Description Characteristics Assumptions
1 Sediment Flushing — 'Base Case' — Existing Irrigation Outlet rehabilitation Rehabilitation of the existing low-level irrigation outlets. Flush part of sediment wedge near dam and turbidity current at times of high inflows. Remainder of turbidity current sediment accumulated at dam or eventually passes through the power units. As a consequence of flushing, the regulating reservoir and some passage of sediment downstream are also required. Downstream sediment concentrations are controlled by outlet operation to minimize environmental effects Flushing through irrigation outlets several times per year keeps power intakes clear until delta reaches all the way to the dam. Power facility and spill flows require to dilute sediment
Continuation of tab. 3
Alternative No. Alternative Description Characteristics Assumptions
2 Sediment Flushing — Irrigation Outlet Conversion, Flushing Turbidity Current Conversion of irrigation outlet equipment (3 outlets) in order to handle sediment on a long-term basis. Flush of the part of sediments near dam and turbidity current at times of high inflows. As a consequence of flushing, the regulating reservoir and some passage of sediment downstream is also required. Downstream sediment concentrations are controlled by outlet operation to minimize environmental effects Flushing through irrigation outlets several times per year keeps power intakes clear until delta reaches all the way to the dam. Power facility and spill flows required to dilute sediment. TSS concentrations controlled to maintain Severity Index are equal to or less than 8.0
3 Sediment Bypass/ Flushing — Irrigation outlet with small Mini-hydro Conversion of irrigation outlet equipment (3 outlets) to handle sediment on a long-term basis. Addition of small hydro unit to one outlet Pass turbidity currents in wet season through small hydro facility. Passage of sediment in this manner, supplemented by flushing through irrigation outlets (if required) keeps power intakes clear until delta reaches all the way to the dam. Power facility and spill flows required to dilute sediment concentrations with irrigation outlet flushing with irrigation outlet flushing. With operation of the small unit TSS concentrations, with regular power flow would average 200.250 mg/l
4 Sediment Flushing —Access Tunnel Flushing Two alternatives using the existing cofferdam construction access tunnel upstream of grout curtain and into penstock leading to diversion tunnel and valve outlet facility Flushing through low level tunnel facility say two to three times per year keeps power intakes clear until delta reaches all the way to the dam. Flushing flow is about 120 m3/s in order to accept unlined section of access tunnel upstream of grout curtain. Power facility and spill flows required to dilute sediment concentrations. Once delta reaches dam tunnel will be sufficient to create cone of flushing sufficient to keep power intake clear
5 Sediment Reduction — Watershed Management Terracing, small check dams and or large dams, only viable means of reducing sediment inflows. Likely requires public education program 20 year implementation plan, including public education, institutional strengthening and policy and regulation development. Requires the active involvement of the Province as well as Environment, Agriculture, Natural Resource and other government agencies
End of tab. 3
Alternative No. Alternative Description Characteristics Assumptions
6 Dredging Over Dam into River Continuous dredging would be required throughout the canyon reach and would result in an annual excavation between 500.000 to 1.000.000 m3 depending upon the behavior of the turbidity current This alternative would require opening of one or more valves of the low-level irrigation outlet resulting in the releases ranging from 30 to 90 m3/s
7 Dredging over dam Dredging machine in reservoir with discharge directed downstream through spillway tunnels. As a consequence, dredging of the regulating reservoir and some passage of sediment downstream are also required Quotations received from Europe on the basis of best estimates of cost. Since there is significant variation in these costs the estimation of a range of values will be used to test sensitivity of results
8 Sediment removal in upper delta in dry season Machine excavation in delta area at times of low reservoir elevation and off site truck disposal
9 Dam Raising Increase in dam height by up to 10-m say. Increase in the height of intake and spillway deck and associated hydro mechanical equipment capabilities
The effects of dredging are dependent on the type of dredger used. They include: 1) loss of invertebrate habitat: removal of sediments will result in the removal of invertebrates that are the major component of the diet of several fish species and destruction of their habitat; 2) suspended sediment: the extent of the increased suspended sediment in the water column is highly dependent on the type of dredger used with a clam-type dredge most likely to increase suspended sediment and an airlift dredger or suction dredge less likely to significantly increase suspended sediment; 3) entrainment of fish and fish eggs: loss of fish during dredging operations has been identified as a problem with suction and air lift dredges; 4) loss of aquatic vegetation and fish habitat: dredging can remove aquatic vegetation and other structures, which act as fish habitat. In the case of the Dez reservoir, the sediment dynamics are such that rooted aquatic vegetation beds have not developed and the structures such as shoals are in constant flux.
The effects of sediment disposal are highly dependent on the site chosen for disposal. They include: 1) loss of land: the area near the Dez reservoir is very arid and generally has little value in terms of agriculture or pasture. Selection of a site that has little or no current use would negate any impacts on land use; 2) loss of sediment to adjacent water courses: selection and/or engineering of a site must ensure that sediment will not be eroded and enter adjacent water courses; 3) effects on communities: land based disposal of sediment requires the transport of the dredged material to the disposal site. A transportation route should be selected to ensure that effects on local communities, including noise, dust and traffic congestion, are minimized.
Some potential effects of dam heightening include: 1) effects on local settlements: there are at least two villages that may require resettlement due to an in-
creased water level of the Dez reservoir; 2) effects on water quality: based on temperature and oxygen profiles taken in the Dez reservoir, it appears that the reservoir does not stratify and oxygen levels are relatively high throughout the water column; 3) although the land adjacent to the reservoir is arid and of low agricultural potential, some part of it is planted during the rainy season and used to graze livestock by local residents; 4) fish: increasing the depth of the reservoir may alter the existing fish habitat, but may replace this habitat with new habitat in the newly flooded areas. If the water quality of the reservoir, however, was to change significantly, it could have a deleterious impact on the fish community. Table 4 presents a comparison of sediment management alternatives based on selected environmental criteria. It does not consider cost or the alternative's ability to meet sediment management objectives. Each criterion or effect is given a weight (from 1 to 3) basing on its importance to the local population or ecosystem and the ability to mitigate the effect. Each option is then rated for each effect on a scale from 1 (benefit) to 3 (major long-term effect). The total is the sum of the multiples of the rating times the weighting. Basing on this analysis watershed management is the best alternative while flushing, as is now practiced, is the worst alternative.
Tab. 4. Environmental Evaluation of the Alternatives
Effect Weight Flushing "Do Nothing" Flushing (Converted Low-Level Outlet) Watershed Management Mini Hydro Dredging Dam Heightening
Fish
Adults 2 1 1 0 1 1 1
Eggs 2 2 2 0 1 1 0
Habitat 2 2 2 -1 1 1 1
Migration 1 0 0 0 0 0 0
Fishing 3 1 1 0 1 0 0
Water Users
Domestic 2 1 1 -1 1 0 0
Recreation 3 1 1 0 1 0 0
Industry 1 1 1 0 1 0 0
Irrigation 2 1 1 0 1 0 0
Livestock 1 1 1 1 1 0 0
Water Quality 2 1 1 -1 1 1 1
Terrestrial
Loss of land 2 0 0 0 0 1 1
Wildlife 2 0 0 -1 0 1 1
Resettlement 3 0 0 0 0 0 2
The general methodology applied to the economic evaluation of the alternatives considered in the current study is based on the discounted cash flow (DCF) technique to compute the present values of future cash flows that an investment would generate. "Constant price" analysis was the basis for the evaluation which implies that all
the prices and wages rise uniformly with general inflation and therefore, there will be no change in the real prices of various products. Table 5 summarizes the preliminary economic evaluations for the various alternatives.
Tab. 5. Preliminary economic evaluations of the Alternatives
ID No. Management Alternative Description Benefits Net Costs Total mln Dollar
i Irrigation Outlet Rehabilitation Rehabilitate existing Howell Bunger valves minimum required to maintain drawdown capability Some storage and sediment exclusion benefit 9.48
2 Irrigation Outlet Replacement Replace Howell Bunger valve with slide gate Storage and sediment exclusion benefit 14.46
3 Irrigation Outlet Replacement plus Mini-Hydro Same as Alternative 2 with the addition of a mini-hydro unit to one of the irrigation outlets Same as Alt 4 Option 5 plus mini-hydro 33.36
4 Access Tunnel Flushing Opening of the exiting upstream cofferdam access tunnel Storage and sediment exclusion benefit 15.60
5 Watershed Rehabilitation 15-yr implementation period 10 % to 20 % effective in reducing sediment load Storage increase but no sediment exclusion benefit 40.86
6 Dredging Over Dam into River IHC Quotation Dredging near the dam — Disposal over spillway Dredging d/s regulating pond Storage and sediment exclusion benefit 49.65
7 Dredging Over Dam into River Damen Quotation Same as Alternative 6 Lowest dredging quotation received Storage and sediment exclusion benefit 12.72
8 Excavation of Upper Delta Excavate coarse delta material — Sediment through powerhouse Storage increase but no sediment exclusion benefit 16.87
9 Dam Raising Raising limited to 10 m Sediment would continue to build in wedge Storage increase but no sediment exclusion benefit 52.09
1.2. Fuzzy group decision making. In Aggregation stage, all criteria' attributes are usually combined to form final rating for each alternative by aggregation operator. In the proposed algorithm, the ordered weighted averaging (OWA) operator is used to aggregate individual attributes. An OWA operator is an aggregation operator with an associated vector of weights ^" wi = 1, w e[0,1]" (Smolikova R., Wachowiak M.P. 2002 [8], Yager R.R. 1988 [9], 1993 [10], 1994 [11]), so that:
Fw ( x) = ¿ wib, we I"
(1)
with b. denoting the z'th largest element in x1,..., xn. The weighting vector is calculated as follow:
i=i
= 2[nJ- 2( VJ' ' = 1 n- (2)
Q is a linguistic quantifier that represents the concept of fuzzy majority and is used to calculate the weighting vector. A fuzzy linguistic quantifier may be defined as follows:
0 if: r < a;
r - a -n
if: r < a; (3)
Q(r) =
b - a i if: r > b
where (a, b) are the ranges of linguistic quantifier Q symbolically. The most common linguistic fuzzy quantifiers used are "most", "at least half", and "as many as possible". Their ranges are given as (3, 8), (0, 5) and (5, 1), respectively (Choudhurya, A.K. et al., 2006 [12]).
Generic structure of the proposed algorithm is presented in 15 steps as follow (Fig 2):
Step 1) Each criteria in the group, expresses his/her attributes on each alternative in a different preference mentioned formats. In these assessments, ordinal preferences of alternatives are represented by Q's, which defines preference-ordering evaluation given by DM' to the alternative x. Fuzzy preference relation is expressed by Km, where k'm c X * X with membership function c X x X ^ [0,1] and Mki (Xs ,Xm ) = Km, where X = {x1, ..., xn} is a finite set of alternatives. Value km defines a ratio of the fuzzy preference intensity of alternative xs to xm. Multiplicative preference relations are represented as A', where A' c X x X, A' = a'm and a'sm is a ratio of the fuzzy preference intensity of alternative xs to xm given by DM' (Saaty T.L. 1980 [13]). Utility function is shown as U, where DM' explains his/her Attributes on alternatives as n-tuple utility values. Utility value of alternative xs given by DM' is presented by u's e [0,1].
Step 2) Information from step (1) is transformed into fuzzy preference relationship by an appropriate transformation function. A common transformation between the various preferences is as follow (Chiclana F. et al. 1998 [14]):
u )2
K' = V s /_. (4)
() +(um)
Km={('+3n-f); (5)
Km = 2 (1 + log9 aSm ). (6)
Step 3) Proposed OWA operator to form collective attributes relation aggregates individual fuzzy relations.
k = 0Q (k1 , ..., km ) = Vmw.k' , (7)
s, m Q \ sm' ' sm I / t '=1 i sm ' v '
where k is a ratio of the fuzzy group preference of alternative x to x and Q is a
sm j & it it s m ^
fuzzy linguistic quantifier that represents the concept of fuzzy majority and is used to calculate the weighting vector. A fuzzy linguistic quantifier is defined as function (3).
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Step 4) Quantifier guided dominance degree (QGDD). of the alternative x . is calculated. This quantity calculates the dominance of the alternative x . over other alternatives and collective alternative (Eq. 8), where Pq(x) defines the preference degree or intensity of the alternative x. over other alternatives given by DMq.
Step 5) The difference between individual attributes and group attributes is calculated by using Eq. 9. Where b e [0, 1]. Parameter b controls the rigorousness of
the consensus process; S (C) represents the degree of proximity of individual opin-
q
ion to collective attributes. Pq(x.) and Pg(x.) represent the evaluation given by DMq and collective evaluation to the alternative x., respectively.
qgdd = pq (x )=*> q ..., Ky^j- (8)
S (C) = \pq(x,)-Pg(x,)|. (9)
Step 6) Calculation of S(C)p's, S(C)ms' the minimum and the maximum difference between individual attributes with collective attributes, respectively.
Step 7) Aggregated average of disagreement of all the criteria on each alternative x. (CM(C.)) and on all the alternatives (CM(C)) is calculated as:
CM (C)=*e (s (C.), -, S» (C. ))=! >A (C.); (10)
CM (C ) = oe (CM (c ), ..., CM (C )) = £ ! wCM (c.). (11)
Step 8) Aggregated average of the agreement of all the criteria on each alternative is calculated as:
GC (C, ) = 1 -
CM (C )- -5 (C, )P'S
S(C, )" - -s (C f
(12)
Step 9) The average of minimum and maximum disagreement of all criteria on all alternatives (GSCL(C)), (GWCL(C)) are calculated by following functions, respectively:
GSCL(C) = Oe (S(C )№, ..., S(C„ )PiS)ys(C, )№ ; (13)
GWCL(C) = Oq (S(Cj )Nts, ..., S(Cnf) = X>S(Ct f. (14)
Step 10) The consensus measure on all the alternatives (GC) is obtained as follow:
GSCL (C)- CM (C)
GC = 1---V-. (15)
GSCL (C )- GWCL (C )
Step 11) If GC > CL, the process is finished and calculated QGDDs in step 4, assigned as relative importance of criteria, because QGDD. is the dominance of the criterion c . over other criteria. These values are used as collective weights of attributes for selecting the best possible alternative.
2. Results and discussions
A multi objective problem in sustainable sediment management was considered to investigate the application of the proposed algorithm. In order to have an effective discussion on the case study, a sensitivity analysis of the model is necessary. Basing on the tables 3 to 5, we considered 9 alternatives and 4 criteria (Technical and execu-
tive requirements, Economic development, Social welfare, Environment impacts). The revised hierarchy is indicated in Figure 3, consisting of four main criteria and 12 attributes.
Goal Criteria Attributes
Sustainable sediment management
Simplicity of Operation and Maintenance, Construction Technology, Capabilities of Phased Operation
Technical and executive requirements
Range of Environmental Impacts, Studies of Watershed Conservation, Balancing of Water Resources
Environmental impacts —
Economic factors B/C, Risk of Investments, Base for Supplementary Projects
Social welfare Resettlement of People, Recreation, Tourism and Additional Facilities, Public Participation
Fig. 3. Hierarchy of Criteria
For fuzzy group decision making, a decision matrix is usually required prior to the beginning of the process. The decision matrix contains competitive alternatives row-wise, with their attributes' ratings. In order to normalize the decision matrix, normal distribution and central limit theorem has been utilized (Tab. 6). Also, the proposed fuzzy group decision making approach is implemented to select the most effective alternative response scenario against this risk. The occurrence of this risk would have negative impacts on the sediment management and may lead to project cost overrun, project delay and poor quality. It should be emphasized that this evaluation was made basing on the proposed case and in different situations the outcome of the assessment could vary depending on the actual requirements and restraints.
Tab. 6. Normalization of the decision matrix for sustainable sediment management in Dez dam reservoir
Alternative No. Technical and executive requirements Environmental impacts Economic factors Social welfare
Irrigation Outlet Rehabilitation 5.0 2.5 5.GG З
Irrigation Outlet Replacement 4.5 З^ З.21 2
Irrigation Outlet Replacement plus Mini-Hydro 4.0 З^ 1.ЗЗ З
Access Tunnel Flushing 4.0 i.G З.27 i
Watershed Rehabilitation 2.0 5.G i.G7 2
Dredging Over Dam into River IHC Quotation 1.0 2.5 G.S2 i
End of tab. 6
Alternative No. Technical and executive requirements Environmental impacts Economic factors Social welfare
Dredging Over Dam into River Damen Quotation 1.0 3.G 3.9S i
Excavation of Upper Delta 2.5 3.G 2.9б 3
Dam Raising 2.0 4.G G.77 2
In OWA method, the risk level is accounted in an explicit manner. If a > 1, it indicates pessimism or risk-averse decision maker. If a = 1, it means decisionmaker is neutral. Finally, a < 1 represents optimistic or risk-prone decision-maker. The order weights of OWA operator depend on the project manager's optimistic/ pessimistic view on the risk. According to the values of Table 6 and equations (11), (12), (14) and (15), the disagreement measure on all the alternatives (CM(C)) and the average of minimum and maximum disagreement on all the alternatives (GSCL(C)), (GWCL(C)) are calculated for each level of risk (Tab. 7—9).
Tab. 7. Result of OWA for each Alternative if: a = 0.6 (Risk — prone)
GWCL GSCL CMC GC It is aggregated
Management alternative G.2S6 G G.G4S9 G.S2S
S(C)(N) S(C)(Ps) CM(C) GC(C-)
Irrigation Outlet Rehabilitation G.375 G G.G4i G.S9G +
Irrigation Outlet Replacement G.625 G G.GS9 0.856 +
Irrigation Outlet Replacement plus Mini-Hydro G.375 G 0.067 G.Si9 -
Access Tunnel Flushing G.S75 G G.i5G 0.827 -
Watershed Rehabilitation g.625 G G.iG3 0.834 +
Dredging Over Dam into River IHC Quotation G.S75 G G.i45 0.834 +
Dredging Over Dam into River Damen Quotation G.S75 G G.i62 G.Si4 -
Excavation of Upper Delta G.375 G 0.062 0.834 +
Dam Raising G.625 G G.iG9 0.825 -
Tab. 8. Result of OWA for each Alternative if: a = 1 (Neutral)
GWCL GSCL CMC GC It is aggregated
Management alternative G.i4G G 0.007 0.954
S(C)(N) S(Ci)(Pis) CM(C) GC(C-)
Irrigation Outlet Rehabilitation G.375 G 0.009 0.975 +
Irrigation Outlet Replacement G.625 G 0.025 0.96 +
End of tab. 8
GWCL GSCL CMC GC It is aggregated
Management alternative 0.140 0 0.007 0.954
S(Q(N) S(C)(P.) CM(C) GC(C)
Irrigation Outlet Replacement plus Mini-Hydro 0.375 0 0.021 0.941 -
Access Tunnel Flushing 0.S75 0 0.046 0.946 -
Watershed Rehabilitation 0.625 0 0.031 0.95 -
Dredging Over Dam into River IHC Quotation 0.S75 0 0.043 0.95 -
Dredging Over Dam into River Damen Quotation 0.S75 0 0.053 0.939 -
Excavation of Upper Delta 0.375 0 0.01S 0.95 -
Dam Raising 0.625 0 0.034 0.945 -
Tab. 9. Result of OWA for each Alternative if: a = 3 (Risk — aversion)
GWCL GSCL CMC GC
Management alternative 0.005221 0 5.52E-07 0.999S94 It is
S(C)(N) S(C) (p.) CM(C) GC(C) aggregated
Irrigation Outlet Rehabilitation 0.375 0 5.86E-06 0.9999S4 +
Irrigation Outlet Replacement 0.625 0 5.08E-05 0.999919 +
Irrigation Outlet Replacement plus Mini-Hydro 0.375 0 8.4E-05 0.999776 -
Access Tunnel Flushing 0.S75 0 0.000146 0.999S33 -
Watershed Rehabilitation 0.625 0 7.81E-05 0.999S75 -
Dredging Over Dam into River IHC Quotation 0.S75 0 0.000109 0.999S75 -
Dredging Over Dam into River Damen Quotation 0.S75 0 0.000221 0.99974S -
Excavation of Upper Delta 0.375 0 4.69E-05 0.999S75 -
Dam Raising 0.625 0 0.000115 0.999S16 -
According to the obtained final weighting vector and the value of the tables 7—9 for each level of risk (a = 0.6, 1, 3) by OWA approach, the alternative "Irrigation Outlet Rehabilitation" is obtained as the most preferred (with maximum average of agreement of all the criteria among the alternatives (GC(C )) and minimum average of disagreement of all the criteria among the alternatives (CM(C.)) alternative to the aimed sustainable sediment management in Dez dam reservoir.
3. Conclusions
In this study, a fuzzy group decision making approach is exerted to perform sediment management in Dez dam reservoir in various levels of risk. The 11 steps fuzzy group decision making algorithm was applied to a sediment management with nine different alternatives and four criteria (Technical and executive requirements, Economic factors, Social welfare, Environmental impacts). The model is well suited,
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where criteria have varying degree of importance as well as uncertain values. The result of the study indicated that "Irrigation Outlet Rehabilitation" is the best alternative response for various levels of risk in Dez dam reservoir. Application of the proposed algorithm of ranking sediment management alternatives showed that this method provides a powerful tool for the selection of optimum response scenario against the identified risks.
References
1. Mahmood K. Reservoir Sedimentation: Impact, Extent and Mitigation. World Bank Technical Paper 71, Washington, DC, 1987.
2. White W.R. Evacuation of Sediments from Reservoirs. London, Thomas Telford, 2001.
3. WCD. Dams and Development. A New Framework for Decision-making. London, Earthscan publications Ltd., 2000, 356 p.
4. Woodward J.C. Patterns of Erosion and Suspended Sediment Yield in Mediterranean River Basins. In: I.D.L. Foster, A.M. Gurnell and B.W. Webb (Editors). Sediment and Water Quality in River Catchments. Wiley, Chichester, 1995, pp. 365—389.
5. Morris G., Fan J. Reservoir Sedimentation Handbook; Design and Management of Dams, Reservoirs and Watersheds for Sustainable Use. McGraw Hill, New York, 1998.
6. Annandale G.W., Palmieri A., Shah F., Dinar A. Reservoir Conservation. Volume I. The World Bank, 2003.
7. Dezab Consulting Engineers in Association with ACTRES international. Dez Dam Rehabilitation Project, Contract No. 81-5M334 Stage 2, Task 1 — Reservoir Operation Review and Sediment Study. 2004.
8. Smolíková R., Wachowiak M.P. Aggregation Operators for Selection Problems. Fuzzy Sets and Systems. 2002, vol. 131, no. 1, pp. 23—34.
9. Yager R.R. On Ordered Weighted Averaging Aggregation Operators in Multi-criteria Decision Making. IEEE Trans.Systems, Man Cybernet. 1988, vol. 18, pp. 183—190.
10. Yager R.R. Families of OWA Operators. Fuzzy Sets and Systems. 1993, vol. 59, pp. 125—148.
11. Yager R.R. Aggregation Operators and Fuzzy Systems Modeling. Fuzzy Sets and Systems. 1994, vol. 67, pp. 129—145.
12. Choudhurya A.K., Shankarb R., Tiwari M.K. Consensus-based Intelligent Group Decision-making Model for the Selection of Advanced Technology. Journal of Decision Support Systems. 2006, vol. 42, pp. 1776—1799.
13. Saaty T.L. The Analytic Hierarchy Process. McGraw-Hill, New York, 1980.
14. Chiclana F., Herrera F., Herrera-Viedma E. Integrating Three Representation, Models in Fuzzy Multipurpose Decision Making Based on Fuzzy Preference Relations. Fuzzy Sets Systems, 1998, vol. 97, pp. 277—291.
Received in july 2014.
About the authors: Elfimov Valeriy Ivanovich — Candidate of Technical Sciences, Associate Professor, Department of Hydraulics and Hydraulic Engineering Structures, Peoples' Friendship University of Russia (PFUR), 6 Miklukho-Maklaya str., Moscow, 117198, Russian Federation; +7 (495) 952-08-31; [email protected];
Khakzad Hamid — postgraduate student, Department of Hydraulics and Hydraulic Engineering Structures, Peoples' Friendship University of Russia (PFUR), 6 Miklukho-Maklaya str., Moscow, 117198, Russian Federation; +7 (495) 952-08-31; khakzad.hamid@ mail.ru.
For citation: Elfimov V.I., Khakzad H. A Fuzzy Group Decision Making Approach to Select the Best Alternative for Sustainable Sediment Management in the Dez Dam Reservoir. VestnikMGSU [Proceedings of Moscow State University of Civil Engineering]. 2014, no. 10, pp. 153—167.
В.И. Елфимов, Х. Хакзад
ВЫБОР НАИЛУЧШЕГО РАЦИОНАЛЬНОГО СПОСОБА УДАЛЕНИЯ ОСАДОЧНЫХ ВЕЩЕСТВ МЕТОДОМ НЕЧЕТКИХ ГРУПП ДЛЯ ПЛОТИНЫ ДЕЗ
Целью данного исследования является развитие нового алгоритма принятия решений методом нечетких групп для выбора предпочтительного способа удаления осадочных веществ из бассейна плотины Дез. Выбраны девять потенциальных альтернативных решений для удаления осадочных веществ и четыре критерия (технические и административные требования, экономические факторы, социальное благополучие, воздействие на окружающую среду). Для того, чтобы оценить различные решения, во-первых, высчитывается весомость группы и осуществляется ее оценка по четырем критериям. После этого выбирается наилучшее решение при помощи предложенного метода нечетких групп. Результаты данного исследования показали эффективность применения методики нечетких групп в управлении осадочными веществами. Применение предложенного метода помогает сбалансировать все критерии и выбрать наилучшее решение.
Ключевые слова: принятие решения методом нечетких групп, удаление осадочных веществ, управление рисками.
Поступила в редакцию в июле 2014 г.
Для цитирования: Елфимов Валерий Иванович — кандидат технических наук, доцент кафедры гидравлики и гидротехнических сооружений, Российский университет дружбы народов (ФГБОУ ВПО «РУДН»), 117198, г Москва, ул. Миклухо-Маклая, д. 6, 8 (495) 952-08-31, [email protected];
Хакзад Хамид — аспирант кафедры гидравлики и гидротехнических сооружений, Российский университет дружбы народов (ФГБОУ ВПО «РУДН»), 117198, г Москва, ул. Миклухо-Маклая, д. 6, 8 (495) 952-08-31, [email protected].
Для цитирования: Elfimov V.I., Khakzad H. A Fuzzy Group Decision Making Approach to Select the Best Alternative for Sustainable Sediment Management in the Dez Dam Reservoir // Вестник МГСУ. 2014. № 10. С. 153—167.
