CONFLICT RESOLUTION IN WATER RESOURCES ALLOCATION

Transcription

1 7 th Internatonal Conference on Hydronformatcs HIC 2006, Nce, FRANCE CONFLICT RESOLUTION IN WATER RESOURCES ALLOCATION MASOUD ASADZADEH ESFAHANI Graduate Research Assstant, School of Cvl and Envronmental Engneerng, Amrkabr Unversty (Tehran Polytechnc, Tehran, Iran REZA KERACHIAN Assstant Professor, Department of Cvl Engneerng, Unversty of Tehran, Tehran, Iran S. MOHAMMAD MORTAZAVI NAEINI Graduate Student, Cvl Engneerng Department, Kh.N.Toos Unversty of Technology, Tehran, Iran In ths study, an optmzaton methodology for conflct resoluton n water allocaton n rver reservor systems s presented. The objectve functon of the optmzaton model s based on the Nash barganng theory whch can ncorporate the utlty functons of the decson makers and the stakeholders as well as ther relatve authortes on the water allocaton process. The utlty functons are based on the relablty of the allocated water to dfferent sectors especally the envronmental water demands, water storage n the reservor and the quantty of the return flows. The proposed model whch ncludes an ntegrated GA based optmzaton (SGA s appled for the reservor operaton and water allocaton n Karkhe Rver-Reservor system n southern part of Iran. Results show that ths model can be effectvely used n optmal water allocaton of rver reservor systems consderng the conflctng utltes and the relatve authortes of decson makers and stakeholders. INTRODUCTION Development of economc based reservor operaton models s a classcal problem n water resources plannng and management. Applcaton of explct conflct resoluton methods n reservor operaton has receved more attentons recently. Palmer et al. [5] ntroduced "Shared Vson Model" as a procedure that allows nterested partcpatons to acheve consensus by provdng a shared vson of a system or process. Palmer et al. [6] developed a conflct resoluton model for Kum Rver Basn n Korea. They derved the trade-off between water supply relablty and n-stream flows usng a water resources smulaton model, developed n STELLA software envronment. Karamouz and Kerachan [3] used a conflct resoluton scheme n order to develop the optmal reservor operatng rules for mprovng the qualty of water suppled focusng on the natural 1

2 process of stratfcaton. They showed that ths model could be effectvely used n optmal water allocaton of rver reservor systems wth conflctng objectves. Ths paper presents an approach to develop the optmal reservor operatng polces consderng the conflctng utltes and the relatve authortes of decson makers and stakeholders. In order to nclude a conflct resoluton scheme, the Nash barganng theory (Nash [4] s used n the proposed methodology. Consderng the computatonal complexty of the problem, the Sequental Genetc Algorthms (SGA proposed by Kerachan and Karamouz (2004 s used as the optmzaton technque. A CONFLICT RESOLUTION SCHEME Conflct can occur n water resources plannng and management for a varety of reasons, but n general, water conflcts occur when people dsagree about how much water of a gven qualty s avalable at a gven tme n a regon for a specfc purpose. However, when a conflct occurs among two or more ndvduals/agences, attempts should be made to reach to an agreement. The Nash barganng theory s one of the more commonly used methods for resolvng conflcts. It ncludes stakeholders' preferences (presented by a utlty functon, as well as the dsagreement pont and the ndvdual rsk takng atttudes n the decson process. The general form of the Nash theory as presented by Karamouz et al. [2] s as follows: Let assume f ( to be the utlty functon of decson maker, and the vector of dsagreement ponts s assgned as d ( d 1,..., d n, then unque soluton of the conflct resoluton problem can be obtaned by solvng the followng optmzaton problem: Maxmze: Subject to: Z w1 w2 wn ( f1 d1 ( f2 d2...( fn d n (1 f d 1,2,..., n (2 Where, n s the number of stakeholders and the power term, w, =1, 2 n, represents ther relatve authorty or rsk-takng atttude. The above model, commonly known as the Nash product, can be used to solve a reservor operaton problem n whch dfferent decson makers and stakeholders wth conflctng utltes are exst. MODEL FORMULATION Objectve Functon The optmzaton model provdes the optmal monthly releases from each outlet durng the plannng horzon for each stakeholder. As mentoned before, the objectve functon of the model s the Nash product. Therefore, the objectve functon of the model s the multplcaton of all user agences (agrcultural, ndustral, domestc and envronmental unts utltes subtracted from ther pont of dsagreement and the utlty of water storage n the reservor for hydropower targets. The Model formulaton s as follows: 2 7 th Internatonal Conference on Hydronformatcs HIC 2006

3 Maxmze: 12 year {( f 1 n do, ( f j1 Subject to: nst d ag j, do, d wdo, ag ( f nd, wag } d nd, wnd, ( f env, d env, wenv, ( f R R l, 1,2,...,12 year (4 l1 S 1 S I R 1,2,...,12 year 1 (5 S S (6 mn S max R Rmax, (7 h =G(S (8 R max, =F(h (9 All Varables 0 Where: : month ndex j: agrcultural unt ndex n st : number of stakeholders (agrcultural, ndustral, domestc and envronmental unts (f ag,d ag,w ag,(f do,,d do,,w do,,(f nd,,d nd,,w nd,,(f st,,d st,,w st,,(f env,,d env,,w env, : utlty functon, dsagreement pont and relatve authorty of, j th agrcultural unt, domestc unt, ndustral unt, water storage n the reservor, envronmental unt n month respectvely. R : total release durng month (mllon cubc meters. R l, : allocated water to stakeholder l n month (mllon cubc meters. S 1 : reservor storage at the begnnng of the plannng horzon (mllon cubc meters. S : reservor storage at the begnnng of month (mllon cubc meters. I : nflow durng month (mllon cubc meters. S mn : reservor storage n ts mnmum water level. S max : reservor storage n ts maxmum water level. h : water storage level durng month (meter. G( : a functon of reservor storage at the begnnng of month, determnng water storage level. R max, : maxmum possble release durng month (mllon cubc meters. F( : a functon of water storage level durng month, determnng maxmum possble release. Stakeholders' utlty functons are related to ther allocated water each month. In addton, water storage utlty functon s related to the water storage at the begnnng of each month. Equatons (8 and (9 are, n fact, reservor ratng-curve that determnes the maxmum possble release n each month consderng water storage level, capacty and poston of each outlet. St, d St, wst, (3 7 th Internatonal Conference on Hydronformatcs HIC

4 Sequental Genetc Algorthms Genetc Algorthms are adaptve methods tryng to mtate the bologcal and genetc process and can be successfully appled to the optmzaton problems. The man feld of applcaton of GAs ncludes problems wth hgh complexty and non-lnear behavor such as reservor operaton. In ths study, a GA based optmzaton algorthm enttled Sequental Genetc Algorthms (SGA, proposed by Kerachan and Karamouz [3], whch s based on the sequental game theory s used. In ths methodology, the number of chromosome genes (chromosome length s sequentally ncreased to effectvely lead the ntal feasble solutons to the global optmal soluton. In ths study, the gene values are the monthly release from the dfferent outlets for each stakeholder. In the frst step, a small record of nflow s selected and the optmal monthly releases from outlets for each stakeholder are obtaned usng the tradtonal GA based optmzaton model. Then, the chromosome length s ncreased for the second step and the optmal soluton of the frst step s terated n the second part of the new chromosomes for ntal generaton. The optmal soluton of ths step s obtaned usng tradtonal GA based optmzaton model. For future steps, the chromosome length s stll ncreased. For each step, the optmal soluton of the prevous step and the average of ts genes are located n the frst and the second part of the new chromosomes consequently; the optmal soluton of each step s obtaned usng tradtonal GA based optmzaton model. Each step can vary from one month to 1 or 2 years. The step length s determned based on the convergence characterstcs of the GA model. In ths study, 1 year s selected for the length of each step. Ths sequental method effectvely reduces the computatonal burden of GA-based models n long-term plannng and management of water resources. Studes show that some characterstcs of GA methods such as the number of populaton, mutaton and crossover probablty are hghly related to the length of chromosomes (Gen and Chang [1], Wardlaw and Sharf [7]. Therefore, n ths study, mutaton probablty, the most sensble characterstc to the varaton of chromosomes length, s consdered varable so that t can be reduced by ncreasng the length of chromosomes. CASE STUDY The proposed optmzaton procedure s used for optmal operaton of Karkheh rverreservor system n southern part of Iran. Karkheh reservor, the largest dam n Iran, wth a volume of 7600 mllon cubc meters, supples the demands of the agrcultural, domestc, ndustral, and envronmental sectors. Karkheh Dam has three outlets and one spllway, whch can be used for selectve wthdrawal. There are sx agrcultural lands wth the total area of about 340,000 hectares, an ndustral complex, a town and one envronmental checkpont (Hoor-Al- Azm Wetland downstream of Karkheh Reservor showed n Fgure 1. For a 20-year plannng horzon, each chromosome n SGA model has bts (5bts 12months 20years (6agrcultural+1ndustral+1domestc+1envronmental. 4 7 th Internatonal Conference on Hydronformatcs HIC 2006

5 The utlty functons of dfferent stakeholders of the system are consdered to be as follows: Fgure 1. Irrgaton networks n the study area. Agrcultural Sector: The man objectve of ths sector s supplyng agrcultural water demands of all sx zones, whch have the most water demands downstream of Karkheh reservor. The utlty of ths sector related to the water supply s based on the water supply relablty. The mportance of agrcultural water supply s vared from one season to another. Therefore, n ths study, the utlty functon for water supply to each agrcultural zone s assumed as: 1 f Aag, 120 Autumn : f ag, ( Aag, (125 Aag, f 60 Aag, 120 (10 0 f 0 Aag, 60 1 f Aag, 125 Wnter: fag, ( Aag, (125 Aag, f 70 Aag, 125 (11 0 f 0 Aag, 70 7 th Internatonal Conference on Hydronformatcs HIC

6 1 f Aag, 150 Sprng : fag, ( Aag, (150 Aag, f 80 Aag, 150 (12 0 f 0 Aag, 80 1 f Aag, 200 Summer : fag, ( Aag, (200 Aag, f 70 Aag, 200 (13 0 f 0 Aag, 70 Where A ag, s the percentage of suppled agrcultural water demand n agrcultural zone j n month. Domestc Sector: The man objectve of ths sector s supplyng water to domestc demands. Consderng the mportance of the domestc water supply, the most favorte range s 90 to 100 percent. Therefore, the utlty functon of the decson makers n ths sector for the relablty of domestc water supply s assumed as: 1 f Ado, 100 f do, ( Ado, 1 0.1(100 Ado, f 90 Ado, 100 (14 0 f Ado, 90 Where A do, s the percentage of the suppled domestc water demand n month. Industral Sector: The man objectve of ths sector s supplyng water to ndustral demands. The utlty functon of the decson makers n ths sector for the relablty of ndustral water supply s assumed as: 1 f And, 100 f nd, ( And, (15 0 f And, 100 Where A nd, s the percentage of the suppled ndustral water demand n month. Envronmental Sector: The envronmental water supply n the Karkheh Rver s the man concern of ths sector. The avalable data shows that the dscharge of 80 MCM per month s needed for Karkheh ecosystem; the envronmental utlty functon for rver flow s formulated as follows: 1 f Qenv, 80 MCM fenv, ( Qenv, (80 Qenv, f 50 Qenv, 80 MCM (16 0 f Qenv, 50 MCM Where, Q env, s the n-stream flow at Hoor-al-Azm control pont n month. Reservor Storage Utlty: The reservor storage utlty s developed consderng the mnmum and maxmum allowable water level n each month and the hydropower ntake level. The utlty functon of the decson makers n ths sector for reservor water storage s: 6 7 th Internatonal Conference on Hydronformatcs HIC 2006

7 0 f h m. a. s. l ( h f 160 h m. a. s. l. fst, ( h 1 (17 1 f 180 h m. a. s. l. 0 f h m. a. s. l. Where h +1 s water level above see level at the end of month. RESULTS and DISCUSSION In ths study, the avalable 20 years of Karkheh Rver monthly stream flow data s used for water allocaton from Karkheh reservor to downstream demands. Demands data were avalable just n the begnnng and at the end of plannng horzon. Therefore, requred nformaton was produced durng these 20 years consderng developng plans of the regon and usng system dynamcs smulaton. Standard operatng polces (SOP are wdely used for reservor operaton n Iran. In ths study, a comparson between SOP and the proposed model results s made. Fgure 2 shows the varaton of water storage volume durng the plannng horzon. As t can be seen, water storage s often n the most favorte range n the proposed SGA model whle t would not be n the range n about 10 years usng standard operatng polces. Fgure 2. Varaton of water storage Table1 presents the most mportant results of the developed model conssts of relablty of allocated water to dfferent users, mnmum percentage of the suppled water demands, average and mnmum of water storage n the reservor. The results 7 th Internatonal Conference on Hydronformatcs HIC

8 show that the developed model can be effectvely used n the proposed reservor operaton model. In the SGA model, the relatve weghts (authortes of the stakeholders are consdered to be equal to the values presented n Table 1. SGA model shows that on the average, more than 85 percentage of downstream water demands can be provded at the development stage. Table 1. Optmal values of allocated water Conflctng sectors Relatve weght (authorty Agrcultural 0.21 Industral 0.26 Domestc 0.26 Envronmental 0.26 Reservor 0.01 Results topc SGA SOP Relablty of allocated water (% Mnmum percentage of demand supply (% Relablty of allocated water (% Mnmum percentage of demand supply (% Relablty of allocated water (% Mnmum percentage of demand supply (% Relablty of allocated water (% Mnmum percentage of demand supply (% Average water storage (MCM Mnmum water storage (MCM REFERENCES [1] Gen, M.R. and Chang, L., (2000, Genetc Algorthm and Engneerng Optmzaton Wley Europe Publcaton. [2] Karamouz M, Szdarovszky F., and Zahrae B., (2003, Water Resources Systems Analyss, Lews Publshers. [3] Kerachan R., and Karamouz M., (2004, Waste-Load Allocaton Model for Seasonal Rver Water Qualty Management: Applcaton of Sequental Dynamc Genetc Algorthms, J. Scenta Iranca, forthcomng. [4] Nash J. F., Two-person cooperatve game, (1953, Econometra, Vol. 21 [5] Palmer, R. N., Werck, W. J., Mac Ewan, A., and Woods, A. W. (1999. "Modelng water resources opportuntes, challenges and trade-offs: the use of shared vson modelng for negotaton and conflct resoluton." Proceedngs of the 26 th Annual Conference, Water Resources, Plannng and Management, ASCE. [6] Palmer, R. N., Ryu, J., Jeong, S., and Km, Y. O. (2002. "An applcaton of water conflct resoluton n the Kum rver basn, Korea." Proceedngs of ASCE Envronmental and Water Resources Insttute Conference, Vrgna, May [7] Wardlaw, R. and Sharf, M. (1999. Evaluaton of Genetc Algorthms for Optmal Reservor Syatem Operaton J. Water Resour. Plng. and Mgnt., ASCE, 125(1, th Internatonal Conference on Hydronformatcs HIC 2006