Technological Transformation in Agriculture: Resource Limitations and Environmental Consequences. A Status Report on the IIASA Research Program

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TECHNOLOGICAL TRANSFORMATION IN AGRICULTURE: RESOURCE LIMITATIONS AND ENVIRONMENTAL CONSEQUENCES.

A STATUS REPORT ON THE IIASA RESEARCH PROGRAM

f i r i t S. Parikh

October, 1983 It??-83-94

Working Papers are interim reports on work of the International Institute for Applied Systems Analysis and have received only limited review. Views or opinions expressed herein do not necessarily represent those of t h e Institute or of its National Member Organizations.

INERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS 2361 Laxenburg, Austria

ACKNOWLEDGEMENTS

I would like to thank Jaroslav Hirs, Nicolaas Konijn, Sigfried Munch and Duane Reneau for t h e i r contribution to t h e task reported in this paper, and particularly Jaroslav Hirs who led this task until December

1982.

Thanks are also due to our colleagues i n t h e collaborating institutes who a r e engaged in t h e various case studies. Without their substantive contribution this paper would have remained incomplete. Finally, I would like t o thank Cynthia Enzlberger, for typing this manuscript.

The Food and Agriculture Program a t IIASA focuses i t s r e s e a r c h activities on understanding t h e n a t u r e a n d dimension of t h e world's food problems, on exploring possible alternative policies t h a t c a n help allevi- a t e c u r r e n t problems a n d prevent f u t u r e ones.

As a p a r t of t h e r e s e a r c h activities investigations of alternative p a t h s of technological transformation in a g r i c u l t u r e i n t h e context of r e s o u r c e limitations a n d long t e r m environmental consequences a r e being investigated. The purpose i s t o identify production plans s t r a - tegies which a r e sustainable. The general approach a n d methodology developed a t IIASA for t h i s investigation is being applied in several c a s e studies on t h e regional level in different countries with t h e help of colla- borating institutions. The case studies help n o t only t o validate t h e gen- e r a l methodology b u t also t o develop a n analytical tool for detailed investigations for a particular region which could t h e n be applied t o o t h e r regions. Moreover, all t h e s e case studies address c e r t a i n specific questions so as t o p e r m i t a comparative analysis.

This paper describes t h e s t a t u s of t h e study.

Kirit S. Parikh Program Leader

Food and Agriculture Program

1. Genesis

2. Issues a n d approach 3. Subtasks

3a. Global Perspective

3b. Description of Technological Alternatives 3c. Modeling of Environmental Feedback

3d. Development of a n Analytical Framework for Decision Making 3e. Country Case Studies

4. Plans and P r o s p e c t s References

-

vii

-

TECHNOLDGICAL TRANSFOmTIONS

IN

AGRICULTURF.: FtESOURCE LIMITATIONS AND ENYZROl+JMENTAL CONSEQUENCES

A Status Report o n the IXMA Research Program*

G r i t S. Parikh

1. Genesis

Food problems -- efficient production or p r o c u r e m e n t of food and t h e appropriate b s t r i b u t i o n of food among m e m b e r s of family a n d society

-

a r e endemic problems of manland. Yet t h e n a t u r e a n d dimensions of t h e s e prob- l e m s have been changing over time. As economic s y s t e m s have developed, spe- cialization h a s increased; a n d t h i s has led t o i n c r e a s e d interdependence of r u r a l a n d u r b a n a r e a s , of agricultural and nonagricultural s e c t o r s a n d of nations. The i m p o r t a n c e of public policies in resolving t h e s e problems has grown with t h i s growing interdependence of nations, reflected in increasing volumes of food t r a d e , a n d t h i s requires t h a t t h e exploration of national policy alternatives b e c a r r i e d o u t in t h e context of international t r a d e , aid, a n d capi- tal flows.

When we began our r e s e a r c h in t h e field of food a n d a g r i c u l t u r e in 1976, we s t a r t e d with t h e s e objectives:

t o evaluate t h e n a t u r e a n d dimensions of t h e world food situation t o identify factors affecting i t

t o s u g g e s t policy alternatives a t national, regional a n d global levels

-

t o alleviate c u r r e n t food problems and

-

t o prevent food problems in t h e f u t u r e

Though we began with an emphasis on policies from a m e d u r n t e r m , 5 t o 15 years perspective, i t was soon recognized t h a t a long-term perspective is also r e q u i r e d for a comprehensive understanding of t h e food problems of t h e world. Policies directed t o solving c u r r e n t problems should be consistdent with t h e longer t e r m objectives of having a sustainable productive environment.

* Paper presented a t t h e International Seminar held a t t h e Stavropol Research Lnstitute of Agriculture, USSR, on "Results of t h e Development of Mathematical Models for Regional S y s terns of Farm Management".

Agricultural activities, a l m o s t by definition, affect t h e environment. When one produces c o r n , one also produces some associated changes in t h e soil. Ero- sion m a y be i n c r e a s e d and if chemical inputs a r e used, t h e chemical residues in t h e soil a n d in water flowing or percolating t h r o u g h s u c h fields will a l t e r t h e i r c h e m i c a l compositions. What would be t h e i m p a c t of s u c h changes on f u t u r e productivity of t h i s soil? What practices could improve o r preserve soil productivity? How i m p o r t a n t a r e t h e s e questions? How i m p o r t a n t a r e t h e s e likely t o be in f u t u r e ? The answers t o t h e s e questions depend on t h e technol- ogy used in cultivation.

One expects t h a t with t h e rising demand for food from t h e growing popula- tion of t h e world which is also becoming r i c h e r , t h e s e questions of resources t o produce a d e q u a t e food, t h e efficiency of techniques, a n d environmental conse- quences will become increasingly m o r e important in f u t u r e . This expectation is based on c e r t a i n t r e n d s t h a t we perceive.

(a) Land will have t o be cultivated m u c h more intensively t h a n a t present.

(b) The i n c r e a s e s i n inputs r e q u i r e d t o raise yields will be significant, a n d t h e costs of s o m e of t h e inputs will rise substantially. Not only is arable land use likely t o r e a c h t h e limits of i t s potential, b u t water needs may approach t h e limits t o exploitable supplies a s well.

(c) A s t h e basic a g r i c u l t u r a l r e s o u r c e s - l a n d , water a n d fertilizer

--

become m o r e s c a r c e and m o r e expensive, a technological transformation of agri- c u l t u r e will have t o t a k e place. The higher yields required, a n d changes in t h e relative prices of land, water fertilizer a n d other factors a n d inputs r e q u i r e d for agricultural production, will clearly lead t o changes in t h e t e c h n i q u e s of production.

(d) The increasing expense and u n c e r t a i n t y in energy .supply will both i n c r e a s e t h e d e m a n d for l a n d and m a k e i t h a r d e r t o obtain higher yields t h r o u g h conventional techniques.

(e) A choice of agricultural production techniques offers alternatives n o t only of intensive a s opposed to extensive cultivation but also of t h e intensification of various i n p u t s s u c h a s fertilizer a n d water. Understand- ing t h e n a t u r e of technology is critical i n formulating appropriate policies for promoting adoption a n d development of appropriate techniques.

(f) P a s t e s t i m a t e s indicate a m o r e t h a n adequate u l t i m a t e food production potential in t h e world b u t t h e s e e s t i m a t e s have n o t fully taken a c c o u n t of e n v i r o n m e n t a l consequences a n d feedbacks in l a n d productivity.

We conclude f r o m t h e foregoing (Parikh a n d Rabar, 1981) t h a t over t h e coming decades a technological transformation of agriculture will take place t h a t will be constrained by r e s o u r c e limitations a n d whose environmental implications pose questions concerning t h e sustainability of adequate produc- tion t o feed mankind.

2. Issues and approach

Since we anticipate over t h e coming decades a technological transforma- tion of a g r i c u l t u r e t h a t will be constrained by resource limitations and t h a t could have serious environmental consequences, a n u m b e r of important; ques- tions arise.

What a r e t h e a l t e r n a t i v e technologies likely to be available within t h e n e x t 20 y e a r s a n d beyond?

What would be t h e appropriate combinations of t h e s e technologies in a given region ( c o u n t r y ) u n d e r variovs scenarios for r e s o u r c e availability a n d food demand?

What sustainable potential production c a n be achieved with t h e given r e s o u r c e s , with t h e available technological a l t e r n a t i v e s , a n d considering t h e possible environmental consequences i n a region, in a country, and a t a global level?

The e l e m e n t s of t h e s y s t e m a n d i t s dynamics t h a t we have t o study a r e shown schematically in Figure 1.

Soil Alternative

I

Climate Yleld Input

1

Genetic

Cultural mental practices Model

I

I

Economic Associated

I

Decision Environmental

I

Model for -Effects, e.g.

Choice of

n

soil erosion

I

I

Techniques

I

r a t e r logging.

e t c .

, I

Modified soil Climate Genetic Cultural practices

Environ- mental Model

period t I .period t+l -b

mure 1. Schematic diagram of analytical elements

Table 1. Technological transformation of agriculture: analytical framework -- concept

{P;] Trade Prices Resource Base

Given

Area in zone z Regional Requirements and {A"' fenilityclassf

Fixed capital stock,

{F'l

Water, Energy

Find Activity Intensities (xt

/

^which

Maximize net trade surplus meet domestic requirement and are sustainable

I ^{!zts { 2)}

⁼ [at] 6 t

1

Resource Limits { x t /

<

/A&/; [b] ( y t /

<

(F:J output Levels h t / = [ u J { x t /

Sustainability

N t /

^{h t - 1}

/

Demand

I-

( Q t / > i R t / + I E t

I

Feedback lat] = f l q t - , I of

Bads {A&/= g ~ A f , ~ - ~ , ~~1

L

Multi-objective

Large System Optimization

S o u r c e : Food f o r All in a Sustainable World , IIASA, Laxenburg, SR-81-2, pg 21.

The initial conception of t h e problem and approach a r e described in Hirs, J.

(1981) a n d in Reneau, van Asseldonk and Frohberg (1981). A conceptual frame- work is shown in Table 1. The model shown can be used for a nation or for a subregion in a nation. Given t h e prices a t which t h e region can t r a d e exter- nally, i t s domestic prices a n d domestic requirements, those agricultural activi- ties a r e t o be selected t h a t would maximize net income from agriculture sub- ject to c e r t a i n constraints. Among these is included a sustainability c o n s t r a i n t a s well a s environmental feedback relations.

Based on t h i s framework a n u m b e r of subtasks were identified and work was organized around t h a t . Our program approach i s different from past approaches in t h a t we t a k e into account both environmental feedbacks and economic considerations i n an i n t e g r a t e d framework.

In addition we a r e carrying out, with t h e help of a network of collaborating institutions (Table 2 ) , a n u m b e r of case studies which help in validating o u r approach a n d in understanding t h e complexity of t h e syst,em. The case studies are s o selected as t o r e p r e s e n t various agricultural a n d economic organiza- tional systems. We shall also obtain a broad global perspective.

Table 2. Network of Collaborating institutions

Bulgarian Academy of Sciences, Research Laboratory "Problems of the Food Complex", Sofia, Bulgaria

Biological Faculty, Sofia University, Bulgaria

Research Institute for Economics of Agriculture and Nutrition, Prague, CSSR Institute for Rational Management and Work, Prague, CSSR

Dept. for Research and Development, Institute for t h e Rationalization and Management of Agriculture, Trnava, CSSR

Humboldt University, Dept. of Crop Production, Berlin. German Democratic Republic Karl-Marx University of Economic Sciences, Dept. of Agricultural Economics. Budapest, Hungary

Agricultural University, Debrecen, Hungary CNR - IATA, University of Florence, Italy

The Food and Agriculture Organization of the United Nations, Rome, Italy.

Kyoto University, Agricultural Engineering Dept. Faculty of Agriculture, Japan Centre for World Food Studies, Wageningen, the Netherlands

United Nations Fund for Population Activities, N.Y., U.S.A.

National College of Food Technology, University of Reading, U.K.

The Center for Agricultural and Rural Development, Iowa State University of Science and Technology. U.S.A.

Texas A & M University, Dept. of Agricultural Economics, U.S.A.

U.S. Dept. of Agriculture, Agriculture Research Service, Southeast Watershed Research Laboratory, Tifton, GA. U.S.A.

All-Union Lnstitute of Information and Technical Economic Research in Agriculture, Mos- cow, U.S.S.R.

Lenin All Union Academy of Agricultural Sciences, U.S.S.R.

Moscow State University, U.S.S.R.

The Stavropol Research Institute of Agriculture, U.S.S.R.

Computer Centre of t h e USSR Academy of Sciences, U.S.S.R.

Institute of Agrochemistry and Soil Sciences, U.S.S.R.

3. Subtasks

The various s u b t a s k s we identified a r e as follows:

(a) A global perspective: estimation of t h e population supporting capacity of t h e world with a n d without conservation

(b) Description of technological alternatives inclu&ng associated environmen- t a l bads a n d goods which come a s joint products

(c) Modeling of t h e environmental feedback mechanism.

(d) Development of an analytical framework for decision making.

( e ) Country case s t u d i e s (i) Nitra district,' CSSR (ii) Stavropol region, USSR (iii) Iowa S t a t e , U.S.A.

(iv) Suwa Region, Japan (v) Mugello Region, Italy (vi) Hungary

These s u b t a s k s a n d t h e progress achieved in t h e m a r e now described in t u r n .

3a. Global Perspective

Objectives of p a r t of this subtask were realized t h r o u g h a collaborative study with FA0 aild UNFPA Estimates of population supporting capacities of t h e developing countries were made.

The world h a s adequate resources t o feed m a n k i n d now a n d i n t h e future.

Estimates of t h e population supporting capacities of t h e developing countries of t h e world based on agro-climatic data show t h a t most developing regions, though n o t all c o u n t r i e s , have adequate potential t o support projected popula- tions by 2000. These r e s u l t s , s u m m a r i z e d in Table 3, show t h a t t h e l a n d of t h e five regions t o g e t h e r could, even with low level of inputs, m e e t t h e food need of 2.0 t i m e s t h e year 1975 population and 1.5 t i m e s t h e food needs of t h e projected year 2000 population. Even individually t h e regions have t h e potential t o be self-sufficient using low level of inputs excepting South West Asia which would n e e d high level of inputs.

With high level of inputs t h e potential population supporting capacity of t h e developing c o u n t r i e s is 9 t i m e s t h e projected population of t h e year 2000.

I t should be emphasized, however, t h a t t h e s e e s t i m a t e s a r e for agronomic potentials and do n o t tell us how m u c h i t will c o s t t o realize t h e m . The large agricultural potential of developing c o u n t r i e s would r e q u i r e m u c h resources of capital, knowledge, skills a n d organization. Moreover i t is also a s s u m e d t h a t m e a s u r e s would b e taken t o conserve soil productivity. These conservation m e a s u r e s would also n e e d additional resources. The scope for e x t e r n a l assis- t a n c e from g o v e r n m e n t s a n d i n d u s t r y is large, and unless it is mobilized today's hunger problem will r e m a i n with u s for a long t i m e .

Table 3. Potential/present population ratios under alternative technologies

Level of Inputs Low

Intermediate High

Low

Intermediate High

Year 1975 Potential: P r e s e n t Population Ratios

Africa Southwest South Central Southeast Average

Asia America America Asia

Year 2000 Potential: Projected Population Ratios

S o u r c e : Higgins, Kassam, a n d Naiken (FAO), Shah (IIASA) and Calderoni (UN):

Can t h e l a n d s u p p o r t t h e population

--

t h e r e s u l t s of a FAO/UNFPA/IIASA study,

"Land resources for populations of t h e future". Populi, UNFPR, N.Y., Vol. 9, 1982.

The results shown in Table 3 a r e from a study c a r r i e d out by FAP of IIASA jointly with FA0 a n d LTNFPA soil d a t a a t t h e level of u n i t s of 10000 h e c t a r e s with climatic data were evaluated from agronomic principles t o arrive a t crop

production potential for various suitable crops. These were f u r t h e r processed to c o n s t r u c t various scenarios for agricultural production for different coun- tries. These evaluations give us guidance on t h e following:

-

How does t h e country's cropping p a t t e r n reflect its natural advantages?

-

Which a r e a s and which crops offer t h e m o s t chance for f u r t h e r develop- m e n t ?

- How m u c h resources would be needed t o realize desired growth potentials.

3b. Description of Technological Alternatives

Description of technological alternatives was approached from n u m b e r of different perspectives.

(a) Comparative assessment of p r e s e n t technologies

Through a n u m b e r of collaborative publications (Nazarenko. V. 1981, 1982a, 1982b, and Nazarenko e t a1 1983a, 1983b), comparative description of present technologies in different countries for selected activities were described. This was t h e outcome of o u r collaboration with t h e All Union Insti- t u t e of Information a n d Technical Economic Research in Agriculture, Moscow.

(b) Non traditional technologies

Non-traditional technologies which a r e , or a r e likely t o be available duing t h e next 20 y e a r s for t h e production of food, feed or bio-energy from non- traditional sources were reviewed through a series of t h r e e task force meetings held a t IIASA, Tbilisi S t a t e University, USSR and Sofia University, Bulgaria. The proceedings of t h e s e task force meetings a r e already published: (see: Hirs, J.

(1981), Hirs, J. and S. Miinch (1982), Worgan J. (1983)). The preparatory work for t h e t a s k force meetings was carried out jointly with t h e Department of Food, Science and Technology, Tbilisi S t a t e University, USSR, t h e National College of Food Technology, University of Reading, U.K., t h e Academy of Sciences, Bulgaria and t h e University of Sofia Bulgaria.

(c) Description of mechanical aspects of crop production.

Quantitative descriptions of technological alternatives available t o produce a particular product or service follow one of two paths, depending on disci- plinary bias a s well a s on t h e problem a t hand. Thus engineers and technolo- gists who a r e usually c o n c e r n e d with decisions a t t h e field or factory level prefer descriptions which r e f e r t o specific machines used in particular processes. Economists c o n c e r n e d with decisions a t t h e industry or t h e econ- omy level, on t h e o t h e r hand, prefer a production function in which only an aggregate m e a s u r e of m a c h i n e r y a n d equipment

--

e.g. dollars o r roubles worth of capital

--

^{is used.}

The dichotomy between t h e description of field-level techniques and sector-level production function is particularly severe for agriculture, where t h e soil a n d climate c h a r a c t e r i s t i c s s e e m t o m a k e each field a s e p a r a t e and non-reproducible observation. This poses a formidable difficulty in exploring a t a regional level optimum s t r a t e g i e s for agricultural development in a way t h a t satisfactorily deals with t h e i n t e r a c t i o n s between agricultural technology, cul- tivation a n d m a n a g e m e n t practices, t h e environmental consequences of these, and t h e i r i m p a c t on soil and water r e s o u r c e quality.

A desirable s c h e m e for description of technological options should a s f a r as possible m e e t t h e following requirements:

(a) I t should r e l a t e specific micro-level processes and operations to a rela- tively aggregated production function.

(b) I t should facilitate a r e p r e s e n t a t i o n of technological options t h a t can be u s e d in analysis for system-level optimization. This m e a n s t h a t t h e result- ing analytical model should be compu tationally manage able. For example, if t h e model is a l i n e a r programming one, t h e size of LP t h a t is g e n e r a t e d should be reasonable.

(c) I t should account for technological progress in a way t h a t could be useful for projecting such progress.

(d) I t should identify t h e e l e m e n t s of technology which a r e s i t e and situation specific a n d those which provide a universal description of technology which is applicable t o o t h e r situations, so t h a t with every case study t h e d a t a bank grows in a meaningful way.

We have outlined a s c h e m e t h a t m e e t s t h e s e needs. This will r e s u l t in a d a t a bank with following components:

A. Crop production activity m a t r i x

Note h e r e t h a t n e i t h e r p a r t A n o r p a r t B of t h e m a t r i x is affected by t h e t e c h n i c a l progress t h a t takes place in mechanical e q u i p m e n t development.

P a r t A e m b o b e s t h e information from t h e g e n e t i c a n d agronomic aspects a n d varies only when t h e r e is g e n e t i c technical progress. P a r t B embodies agro- nomic aspects relating t o soil a n d r e m a i n s invariant t o technological develop- m e n t s in t h e m a c h i n e r y s e c t o r a s well a s t o genetical progress.

B. Operation o u t p u t activity m a t r i c e s

For e a c h operation o n e m a t r i x will define t h e alternatives available for pro- ducing t h e output of t h a t operation.

As new machines a r e developed and new d a t a a r e available, t h e s e m a t r i c e s have t o be a u g m e n t e d by additional rows a n d columns. But i t should be noted t h a t t h e s e m a t r i c e s a r e largely independent of variations in soil a n d climate.

Thus t h e y a r e "universal" descriptions of technology.

Crop production activity m a t r i x

lnpu t s

Main yield Joint yield 1 Joint yield 2 Seeds Fertilizer Pesticides Operation O1 Operation O2

Operation 0,

L

soil 1 soil 2

c r o p 1 alternatives

...

soil s crop c

To illustrate how t h i s can be done, we have e s t i m a t e d output functions for some agricultural operations based on experimental data from Hungary.

For demonstration purposes we neglect equipment and labor a n d consider just two a t t r i b u t e s of t r a c t o r s , horsepower a n d date of first use.

A general model is postulated for all the operations.

where

s l and s2 a r e dummy variables for soil type 1 and 2;

intensity of operation r e f e r s to

depth in crns for ploughing and discing width in crns between rows for cultivation yield of g r a i n s in t o n s / h e c t a r e s

Ht

is t h e horse power of t h e t r a c t o r first introduced i n year t t is vintage y e a r ( t

=

66 for 1966, e t c . )

The r e s u l t s of t h e various regressions a r e given in Table 4. The regression results a r e remarkably good. The t statistics a r e mostly highly significant and the signs of coefficients a r e with one exception right. Thus t h e approach sug- gested h e r e is very promising and systematic work c a n be very fruitful. This is described in g r e a t e r detail in Parikh (1983).

(d) Describing agronomic a n d chemical aspects of c r o p production.

Whereas t h e technological options of labour and capital substitutions may be considered to be m o r e or less universally applicable, t h e relationship between water a n d fertilizer inputs and crop yields depend critically on soil and climate. Moreover, erosion levels a n d soil c h e m i s t r y changes also depend on soil and climate. Since we want t o explore the dynamics of technological alter- natives soil quality changes have t o be quantitatively generated in such a dynamic context. Thus we have t o relate climate, soil, genetic a n d cultural practices t o o u t p u t s a shown schematically i n l?igure 2.

A major effort was m a d e a t IIASA t o extend a n d computerize t h e Crop and Environmental model (CE) model originally developed by t h e Centre for World Food Studies, (1980). This is described in g r e a t e r detail by Konijn N. (1983).

Examples of t h e type of o u t p u t t h a t can be obtained from s u c h a model a r e shown graphically in Figure 3a a n d 3b. The CE model has been applied exten- sively for t h e Stavropol region and hundreds of r u n s have been made for different crops, soils and c l i m a t e years. What is now under progress is valida- tion of t h e model. Ideally we would like t o see t h a t t h e plots in Figure 4 will be a s t r a i g h t line through t h e origin with a slope of 1 (45 degrees).

However, since no model can include everything, we a r e satisfied if we obtain a relationship a s shown in Figure 5, which can t,hen be used a s a calibra- tion curve.

Such validation, calibration work is c u r r e n t l y u n d e r progress. This is being carried o u t with t h e help of Stavropol Institute of Agriculture, and is described in detail by Petrova L. (1983).

Table 4. Estimated Agricultural Operations Output Functions.

Soil 1 Soil 2 intensity vintage* tractor

RZ

F

Operation Constant dummy dummy of of horse

operation tractor power

00 0 1 0 e 7 @ a DF

Ploughng

Discing Operation Precultivation Operations Row Cultivation Maize Harvesting

*

Vintage (years of first introduction of t r a c t o r ) coefficient

p

obtained by divid- ing t h e e s t i m a t e d coefficient pa by a , t h e coefficient of t r a c t o r h o r s e power; t h e t-values shown u n d e r /3 a r e t values of ( pa )

Values in ( ) a r e t-values

yield-input relationship soil loss &

. c h e m i c a l residues

Figure 2. The Crop and Environmental Model in a dynamic context

LAND CLASS-2

N I T RA. CZECHOSLOVAKIA CORN

At. Phosphorus becomes limiting A t A Potassium becomes limiting YIELD

Ikglhal

APPLIED NITROGEN Ikg/ha) 5000

m u r e 3a. Yield response to fertilizers of corn under climates of Merent years.

--

1980

LAND CLASS 3 NITRA N I T R A, CZECHOSLOVAKIA

CORN YIELD

1000

t

At

.

Phosphorus becomes limiting 0

0 50 100 150

APPLIED NITROGEN (kdha)

m e 3b. Yield response to fertilizers of corn under climates of Merent years.

Yield Yield

Observed

Yield predicted

X

^{by CE}

Observed

FSgure 4. Validation of the crop Figure 5. Calibration of the crop and environmental model. and environmental model.

3c. Modelmg of Euvironmental Feedback

An environmental feedback has been developed as a part of t h e Crop and Environmental Model for t h e Stavropol Case Study developed by Konijn N.

(1983). The effects on soil quality of erosion due t o wind and water, and of chemical changes due t o applications of fertilizers and pesticides, water leach- ing and waterlogging and due t o organic m a t t e r decay should be modeled.

Currently, erosion due t o water and changes due t o fertilizers, water leach- ing and organic decay a r e taken into account. It is proposed t o introduce wind erosion in future, whereas effects of water logging is not planned for t h e near future. The schematic relationship of t h e CE model and t h e model of environ- m e n t a l feedback (= SQM

=

soil quality modification model) are shown in Figure 2.

3d. Development of an Analytical Framework for Decision Making.

In t h e recursive scheme of Figure 1, t h e economic decision model can be a conventional choice of technique type linear programming model. Yet an important technical problem arises in t h a t the number of soil classes increases exponentially. Starting with one soil class, if each year x crops a r e grown, it is conceivable t h a t in t years xt soil classes will result. The problem soon becomes computationally impracticable.

To g e t around t h e problem a simplifying assumption is needed. Three alternative approaches are suggested.

(i) Assume t h a t only one crop is grown on one type of soil and with only one technology.

(ii) The same constancy of number of soils can be obtained by permitting grow- ing of different crops on one soil but by averaging all the soil quality changes due to these crops for t h e same soil.

(iii) Consider t h a t e a c h multi-period rotation is a s e p a r a t e activity a n d a choice i s made among s u c h rotations spanning many years.

The m a t h e m a t i c a l description of decision making s c h e m e s a r e given in Ereshko (1983).

3e. Country Case Studies

The different c o u n t r y case studies a r e a t various stages of completion t h e i r c u r r e n t s t a t u s a n d expected d a t e of completion a r e indicated below.

(i) Nitra district, CSSR.

Data collection and model formulation have been completed. Preliminary r e s u l t s from t h e model have already been obtained. Results a r e expected by t h e e n d of 1983.

(ii) Stavropol Region, USSR.

As is obvious from t h e various papers presented a t t h i s s e m i n a r , d a t a col- lection and modeling a r e completed. Preliminary r u n s have been made. A pro- cess of intensive testing a n d p a r a m e t e r turning of t h e CE model is u n d e r way a n d a fully operational model can be expected by early 1984. (see also, Nikonov e t al. 1982)

(iii) Iowa State, USA

The case s t u d y model was t h e first t o g e t ready (Heady a n d Langley, 1981), a n d r e s u l t s a r e now already available.

(iv) Suwa Region, Japan

Data collection is completed and modeling is in progress a n d r e s u l t s a r e expected in e a r l y 1984.

(v) Mugello region, Italy

Soil a n d c l i m a t e d a t a a r e computerized a n d automatic processing s y s t e m s e t up. Use of CE model is s t a r t e d . Results a r e expected t o be available i n 1984.

(Maracchi, G. 1982)

(4 H ~ 4 F - Y

The s t u d y covers t h e whole country. Following a n a s s e s s m e n t of t h e agro- economical potential of Hungary (Harnos, Z. 1982), t h e modeling methodology was defined (Csaki, Harnos, Valyi, 1982). The study is progressing well and r e s u l t s a r e e x p e c t e d by early 1984.

4. Plans and Prospects

The contribution of FAP of IIASA in t h e s e case studies have been of two types. We have developed t h e methodology and we have played a catalytic role in initiating s t u d i e s as well a s tr'lggering collaboration among different insti- t u t e s even within a c o u n t r y . By t h e e n d of 1983 o u r work in methodological refinement would be completed.

What t h e n r e m a i n s is t o bring together t h e r e s u l t s a t t h e various case s t u - dies, m a k e a comparative evaluation and prepare a final report. When s u c h a g e t t o g e t h e r of t h e various case study participants c a n be organized depends on t h e a c t u a l progress of t h e case studies. Yet spring of 1984 s e e m s a reasonable date.

References

Centre for World Food Studies. 1980. The Model of Physical Crop Production.

Wageningen, The Netherlands, SOW-80-5

Csaki, C., Z. Harnos, a n d 1. Valyi. 1982. Methodology for the Investigation of Long Term Consequences of Development in Hungarian Agriculture

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An IIASA FAP Task 2 Case Study. IIASA, Laxenburg, Austria. WP-82-62 Ereshko, F., V. Lebedev and K. Parikh. 1983. Decision-rnalang and simulation

experiments for the Stavropol system of models (mathematical description) IIASA, Laxenburg, Austria. (forthcoming)

Harnos, Z. 1982. The Survey of the Agroeconomical Potential of Hungary -- A Brief Summary. IIASA, Laxenburg, Austria. CP-82-21

Heady, E.O. and J.k Langley. 1981. Specification of a Regional-National Recur- sive Model for IIASA/FAP's Iowa Task 2 Case Study. IIASA, Laxenburg, Austria. WP-81-90

Higgins, Kassam, and Naiken (FAO), Shah (IIASA) and Calderoni (UN): 1982. Can t h e land support the population

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Hirs, J. 1981. The Technology Module. In: Food for All in a Sustainable World:

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Iakirnets, V.N. and D. Reneau. 1982. Methods for Generating Preferable Tech- nology Activities for a LP Model. IIASA, Laxenburg, Austria. WP-82-105.

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