MULTI-OBJECTIVE APPROACH FOR EVALUATION OF FARMING SYSTEMS IN KUTTANAD REGION OF KERALA STATE, INDIA: A MODEL FOR DECISION MAKING

8/14/2019 MULTI-OBJECTIVE APPROACH FOR EVALUATION OF FARMING SYSTEMS IN KUTTANAD REGION OF KERALA STATE, INDI

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MULTI-OBJECTIVE APPROACH FOR EVALUATIONOF FARMING SYSTEMS IN KUTTANAD REGION OFKERALA STATE, INDIA: A MODEL FOR DECISIONMAKING

M. KRISHNAN* and B.N. SHARMA

*Central Institute of Brackishwater Aquaculture, 141, Marshalls Road, Egmore, Madras 600 008, IndiaDivision of Agricultural Economics, Indian Agricultural Research Institute, New Delhi 110 012, India

ABSTRACT

Multi-objective analysis, via the constraint approach, of paddy-fishery enterprise system in theKuttanad region of Kerala State. lndia, is attempted to develop a trade-off analysis between paddy

and fishery systems and to suggest optimal operating policies for the Thaneernukhom salt-waterbarrage for maximizing the returns from the region.

Both primary an secondary data were collected and used in formulating the linearprogramming matrix, which formed the basis of the multi-objective analysis and the trade-offanalysis by way of transformation curves.

The trade-off analysis revealed a greater pay-off in gross area at the ideal point of paddyarea anti-ideal point of fish area. The shift in area from fish to paddy was greater in all the threecases than vice versa. The net benefit-loss figures arrived from actual andnormative values of areaand income generated showed an estimated maximum loss of 39.69% (1981-82) to a minimum loss20.89% (1984-85) during the 1980s for the region.

Income was greater per unit area allocated from fish culture than from paddy cultivation.The study offered three alternatives for planners. The highest income. Rs. 340.30 million, could begenerated from the region by keeping the barrage open year-round. The highest paddy productioncould be obtained by keeping the barrage closed for 6 months. A via media solution is to keep the

barrage open for 3 months (mid-December to March). This would provide an income of Rs. 267 8million.

Key words: project evaluation, multi-objective programming, trade-off analysis, transformationcurves

Kuttanad region is a waterlogged low-lying area in South-central Kerala that hasproven advantage in paddy cultivation over other regions in the state. Yields andarea under paddy in Kuttanad have been consistent in comparison to other districtsof Kerala, which show a steady decline (BKH Consulting Engineers, 1989).Kuttanad offers practically no scope for crops other than paddy because of its

geographical location. Brackishwater fish and shrimp are cultured on a commercial

J. Aqua. Trop., 11 (1996) 205-213 Oxford & IBH Publishing Co. Pvt. Ltd.


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scale in the paddy fields. This culture. owing to the tidal ingress of sea water viathe Vembanad lake, is an age-old avocation and is practised seasonally or in anintegrated manner with paddy and perennially in a few locations (Shetty, 1965).

Till 1975. the agricultural activities of Kuttanad were governed by nature. Inan effort to encourage paddy cultivation and also in an apparent effort to improvethe sown area under paddy in the state, the Government of Kerala commissioned

in 1975 the Thaneermukhom salt-water barrage across the Vembanad lake to helpthe paddy farmers of Kuttanad to raise the punja (summer) crop well protectedfrom the tidal influx of the ease water during December to March. The barrage,originally scheduled to be closed for 3 months from mid-December to mid-Marchevery year, is now closed for almost 6 months each year owing to the indisciplinedway in which the punja crop came to be cultivated from October to April of everyyear and also because of the growers vociferous protests of crop damage in casethe barrier was opened before the onset of the monsoon.

This barrier has reportedly led to steady and substantial decline in thediversity and population of aquatic species including shrimps (Kurup and Samuel,1985). It also had a significant adverse impact on the fisherfolk of the region, whoare losing substantial production and consequently income (Venugopal, 1992).

It is obvious that the unique and traditional farming system in the region hasbeen disturbed. An attempt to resolve this complex problem arising out ofconflicting interests of paddy farmers on the one hand and the fish farmers on theother in the context of the barrage operations should consider the various issuesand multiple objectives.

MATERIALS AND METHODS

The nature of conflicting objectives forces the economists and planners to have abroader and more comprehensive notion of the project and its evaluation. Thenature of the problem and the type of empirical data dictate the specific model tobe used, although non-availability of reliable and relevant empirical data limits thescope of mathematical modelling in farming system studies (Maji 1991).

Multiple-criteria decision making became acceptable to researchers in 1972(Romero and Rehman, 1989). Its superiority over the standard linear programmingapproach has been often repeated. The choice of appropriate approach of multi-objective analysis in the attempt to model the Kuttanad farming system in thecontext of enabling a trade-off between paddy and fish farming systems andsuitable operating policies for the Thaneermukhom salt-water barrage formaximizing the returns from the region rests on the capacity of the methodology to(1) maximize the returns from paddy farming, (2) maximize the returns from fishfarming, and (3) facilitate a trade-off between the two enterprises.

Of the available approaches to multi-objective analysis (Thampapillal, 1978;Willis and Perlack. 1980; Sandiford, 1986), multi-objective programming via theconstraint approach (Romero and Rehman, 1989) offered the most appropriateand correct methodology.

Primary data were collected from 150 farmers, 50 each from Karapadam,Kari, and Kayal lands. All data relating to agricultural operations pertaining topaddy, fish, paddy-fish-paddy, and paddy-cum-fish farming were collected.Secondary data on macrovariables such as gross cropped area, availability of


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human labour, bullock labour, tractor hours, fertilizers, and teed for each type werecollected from various sources for the period under analysis.

The standard linear programming matrix was developed and formed thebasis of the constraint approach to multi-objective programming. The generalnature of the multi-objective programming problem with q objectives can be statedas follows (Romero and Rehman, 1989):

Eff Z(X) = [Z1(X), Z2(X),.. Zq(X)]

Sub to :XFwhere Effsearch for the efficient solutions and F= feasible set.

The initial and useful information of the constraints approach to multi-objective programming was generated by optimizing one of the objectives(maximizing area paddy1) while the other (maximizing area under fish1) wasspecified ass restraint. This mathematical programming problem can be stated as

Maximize Zk(X).

Sub to:XF

Zj(X)Lj J=1,2,k-1, k+1,..q

where Zk (X) is the objective to be optimized. Through parametric variation of theright side L1, the efficient set was generated.

This methodology enabled us to generate the pay-off matrix containing thedeal and the anti-ideal values for maximization of paddy area and fish area. Thevalues when converted to monetary terms by using the farm harvest prices andyields gave the range of returns from paddy and fish. The ideal and anti-idealvalues defined the upper and lower bounds for the range where the parameterL1can vary. Parameterizing L1 for values belonging to the interval, an approximationof the efficient set was obtained. Efficient solutions were generated when theparametric constraints were binding at the optimal solutions.

Trade-offs

The trade-off between two criteria meant the amount of achievement of onecriterion that was sacrificed to gain a unitary increase in the other one. Given two efficient solutions X1 and X2 the trade-off between thejth orkth criteria is given

Tjk=)()(

)()(21

21

XfXf

XfXf

kk

jj

where fj= maximization of padd area and f k maximization of fish area

The trade-off provided index for measuring the opportunity cost of criterion

in terms of another.

1Statistics on paddy area and fish area have been used in lieu of production statistics owing to the

non-availability of the latter on a time series basis. Trial runs made with the objective ofmaximization of paddy/fish production did not indicate any substantial difference in the levels ofproduction of either, between values of the efficient set, thus justifying the use of area figures as aproxy for production in generating the efficient set.


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The transformation curves

The area transformation curves were derived from the efficient set(s)generated turns through the constraints approach of the multi-objectiveprogramming. The iso-revenue curve for each year considered was derived as aratio of the farm harvest prices of the commodities under study. Graphically the

normative equilibrium of the region for each year with respect to area of paddy/fishis defined by the point of tangency of the respective transformation curve and thehighest iso-relevant curve.

Non loss-benefit evaluation

The regions net loss/benefit was arrived at by subtracting the actual area underpaddy and fish farming from the transformation curve in real and monetary termson an annual basis.

Programming situation for evolving operating policies for theThaneermukhom barrier

The standard linear programming matrix was used to arrive at normative figures ofarea under paddy and fish farming in each land type by suitably simulating theobjective function row for three different scenarios of barrage operations. Threesets of these optimal plans were worked out for the three land types and puttogether in a single pay-off matrix representing the region.

1. Optimal plan for period of closure of the barrier from mid-December toJune.

2. Optimal plan for the period of the closure of the barrier from mid-December to mid-March.

3. Optimal plan for no closure situation.

RESULTS AND DISCUSSION

Table 1 represents the pay-off matrices of area transformation in the ideal and theanti-ideal situations in Karapadam, Kari, and Kayal lands. The best values aregiven in bold along the main diagonal.

Table 2 accounts for the major factors that can be deduced from the pay-offmatrices of the different land types of Kuttanad. The gross cropped area was51,489 ha at the ideal point of paddy area and anti-ideal point of fish area inKarapadam lands. For the same parameter it s 20,024 and 13,757 ha in Kari and

Kayal lands respectively. This indicated a cropping intensity of 154.10% inKarapadam lands, 166.05% in Kari lands, and 145.36% in Kayal lands. The grosscropped area was 41,488 ha at the ideal point of fish area and anti-ideal point ofpaddy area in Karapadam lands, indicating a cropping intensity of 149.59% in theformer and 142.86% in the latter land type. ldeal returns were maximum inKarapadam lands at Rs 330.61 million. The total ideal returns for Kuttanad wouldbe Rs 515.56 million. The pay-off matrices also provided an index of theopportunity cost of paddy and fish farming in terms of shifts in area from oneenterprises to the other. The ratio of shift in area from fish to paddy was greater in


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all land types than vice versa. This shift was maximum in the Kayal lands in theratio of 1:5.85 ha, and lowest in Kari lands at 1:3.92 ha. The shift from paddy tofish was maximum in Karapadam lands in the ratio of 1:3.92 ha

The use of transformation cures and the principle of iso-revenue curves insolving situations of bicriterion problems was available in Cohon et al (1979),

Vedula and Rogers (1981), and Long (1990).

Table 1. Pay-off matrix of area transformation (ha)

Particulars Paddy Fish Returns (PS million,)

KarapadamPaddy 43,420 10,017 226.78Fish 8,069 31,471 183.86Returns (Rs million) 221.86 188.85 330.61KariPaddy 15,951 7,560 88.16Fish 4,073 10,479 60.07

Returns (Rs million) 76.62 71.61 103.07KayalPaddy 11,750 5,016 59.81Fish 2,007 8,504 49.39Returns (Rs million) 51.35 57.85 81.88

Table 2. Factors emerging from pay-off matrices of different land types of Kuttanad

Particulars Karapadam Kari Kayal

GCA 1(ha) 51489 20024 13757GCA 2 (ha) 41488 18039 13520Ideal returns (Rs Million) 330.61 103.07 81.88

Shift in area 1 (ha) 1:5.38 1:3.92 1:5.85Shift in area 2 (ha) 1:3.14 1:1.39 1:1.69

GCA 1 = gross cropped at the ideal point of paddy area and anti-ideal point offish area.

GCA 2 = gross cropped at the Ideal point of paddy area and anti-ideal point ofpaddy area.

Ideal returns = maximum returns possible as a combination of ideal points ofpaddy and fish areas.Shift in area 1= shift in area from fish to paddyShift in area 2 = shift in area from paddy to fish.


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Table 4. Income area and production of paddy and fish in Kuttanad region under

different scenarios of barrage operations (area in ha, production inthousand t , profits in Rs. Million)

Period of

barrageclosures

Scenarios Z

(Rs. M)

Paddy area Fish area Paddy

Prod.

Fish

Prod.

Decemberto June

I 212.90 78,818. 80 7,202.8 315.3 3.3

Decemberto March

II 267.80 75,787.80 21, 768.5 250.10 7.3

Noclosing

III 340.30 63,371.70 50,523.0 190.10 9.3

actual figures was 39.69%. It was 32.54% in 1981-82 20.89% in 1984-85, and27.62% in 1988-89. This analysis helped in estimation of the possible losses thathad been sustained by Kuttanad over the time considered.

In the context of both ex-ante and ex-post evaluation of prolects simulationoffers a comprehensive methodology for assessment of large scale and complexsystems (Budnick et al. 1988). In a broad sense simulation is a methodology forconducting experiments using a model of the real system (Lal, 1990).

Using simulation income, area and production of paddy and fish for eachland type of Kuttanad for three different scenarios of barrage operations have beenoptimized independently and presented in a single matrix (Table 4).

Optimizing for each of the scenarios independently ,for income, area, andproduction of paddy and fish in each of the land types, it may be seen that incomefor the region was maximum at As 340.13 million under scenario Ill with no closureof the barrage. Income was maximum at Rs.267.84 million under scenario II

indicating a lower revenue of As 72.47 million than the income obtained underscenario III. Under scenario I the income was Rs 127.38 million less than underscenario Ill. Paddy area and production was the highest under scenario I withbarrage being closed from December to June. It was the lowest under scenario III.Contrarily, area and production under fish farming was maximum under scenario Illand lowest under scenario I.

It is obvious that contribution to income was greater per unit area/productionfrom fish than from paddy farming. The analysis thus offered alternatives to policymakers to (1) maximize income from the region by opting for no closure of thebarrage (2) enhance production of both paddy and fish while maximizing incomereasonably well by closing the barrage from December to March or (3) maximizeproduction of paddy from the region when the barrage remains closed for 6 months

from mid-December to June.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the assistance given to the project by theRegional Research Station Kerala Agricultural University, Kumarakom andMancompu, the Fish Farmers Development Agency, Alleppey, Statistical Office,Kuttanad Taluk and District Statistical Office, Alleppey The first author expresseshis thanks to the Post Graduate School, Indian Agricultural Research institute, New


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Delhi for the senior fellowship awarded for conducting this project and also Dr.E.G. Silas, former Vice Chancellor Kerala Agricultural University for hisconstructive suggestions on an earlier draft of the paper.

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Netherlands, Ministry of Foreign Affairs, Amsterdam, 483 pp.Budnick, Frank S., McLeavey Dennis and Mojena, Richard. (1988). Principles of

operations Research for Management. Richard D. Irwin Inc., Homewood,Illinois, 988 pp.

Cohon, J.L., Church R.L., and Sheer, D.P. (1979). Generating multiobjective trade-offs: An algorithm for bicriterion problem. Water Resources Res. 15:1001-1010.

Gilbert, Sylvia. (1993). Market information and fisheries management. Amultiobjective analysis. Aquaculture and seafood markets: public policy,consumer behaviour and industry relationships. University of RhodeIsland/Oregon State University Research Paper Series. OSU-93-103.

Krishnan, M. (1994). Multiobjective analysis of paddy-fishery enterprise systems in

the Kuttanad region of Kerala State. Ph. D. thesis, Division of AgriculturalEconomics, Indian Agricultural Research Institute, New Delhi, 197 pp.

Kurup, Madhusoodhana B., and Samuel, C.T. (1985). Fish and fishery resourcesof Vembanad Lake. In Harvest and Post Harvest Technoloqy of Fish.Society of Fisheries Technologists Cochin, pp. 77-82

Lal Babu. (1990) Impact of Farakka barrage on the hydrological changes andproductivitv potential of Hooghly Estuary J. Inland Fish Soc. India, 22 (1 &2):38-42.

Long, Roger B. (1990). A trade off analysis of alternative water uses. WaterResources Bull., 26(1).

Maji, C.C. (1990). Farming systems approach to research Indian J. Agro. Econ.,XLVI(3): 403-411.

Romero, C., and Rehman, T. (1989) Multiple criteria Analysis for AgriculturalDecisions. Elsevier Science Publishes B.V. Amsterdam, 255 pp.

Sandiford, Francis. (1986) An analysis multiobjective decision making for theScottish inshore fishery. J. Agric. Eon., 37(2):207-219.

Shetty, H.P.C. (1965). Observations on the fish and fisheries of the Vembanadbackwaters, Kerala Froc. Nat. Acad. Sci. India, Secion B 35(1):115-130.

Thampapillai, D.J. (1978) Methods of multiple objective planning. Word Agric.Econ. Sociol. Abst., 20(12):803-813.

Vedulla, S., and Rogers, P.P. (1981). Multiobiective analysis or irrigation planningin river basin development. Water Resources Res., 17(5):1304-1310.

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Coimbatore ed., p. 4.Willis, C.E and Perlack, R..D. (1980). A comparison for generating techniques andgoal programming for public investment, multiple objective decisionmaking.Amer. J. Agric. Econ. 62:66-74

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MULTI-OBJECTIVE APPROACH FOR EVALUATION OF FARMING SYSTEMS IN KUTTANAD REGION OF KERALA STATE, INDIA: A MODEL FOR DECISION MAKING