CHAPTER I AGROCLIMATIC CLASSIFICATION - A REVIEW SUMMARY

Transcription

1 CHAPTER I AGROCLIMATIC CLASSIFICATION - A REVIEW SUMMARY Numerous attempts have been made to classify climate with a view of finding out crop potential of different areas of the world. This may result in a modification of the distribution of crops already in practice and in many cases even introducing new crops that can substantially increase the income of the farmer. A review of the important earlier classifications has been made in this chapter. The short-comings and advantages of these classifications have been discussed. In most of the classifications average annual and monthly climatic parameters have been used. In the tropics, rainfall is the limiting factor of crop production. The average rainfall of a certain period is made-up of a large number of very low or zero figures and a small number of high values for that, period. Average rainfall occurs only in a few years. Moreover,it does not give any idea of its time distribution. Therefore, it cannot be realistic to plan on the basis of any average rainfall values, not to speak of average annual values. Probabilistic seasonal or annual rainfall and potential evapotraspiration for the corresponding period used in a few classification systems have been also discussed and their short commings are brought out.

2 CHAPTER I AGRQCLIMATIC CLASSIFICATION - A REVIEW No two places in the world would always experience exactly the same climatic condition. However, it is possible to find out, broadly, areas with similar climate with respect to ecology, agriculture and bi meteorological conditions. The classification of climate provides useful information about the ecological conditions, agricultural potentialities and general environmental features of a location. Hence, it has been a subject of interest to scientific researchers in many fields of investigation. Climatic classification is attribute-dependent and choice of attributes largely affect the classification. Obviously, selection of climatic elements and the degree of emphasis laid on these elements, depend on the purpose for which the classification is intended. A classification devised for ecological, geographical, technological or human health purpose need not serve as a useful tool to an agriculturist. There cannot be a single and unique system of climatic classification which can meet the requirements of all types of human activities fully with equal efficiency. Climatic classification has been of historic -ance in developing a broad understanding of the import- effect

3 2 of factors on crop in various environments. Most class- -ifications in this direction have been macro in concept and usually have been applied on continental or global basis. Climate limits the choice of crops and therefore the food production; in fact, climate determines the site and type of crop cultivation. As such, climatic data are increasingly being used in recent years, in agricultural research. There is a greater awareness of more precise and objective definition of the climate as a key factor in quantification of crop behaviour and in understanding variations of crop growth and the yield. In this chapter, characteristics of some, important climatic classifications have been reviewed with particular emphasis on their applicability to agricultural development. As early as 1874, Voeikov tried to classify climate on the basis of seasonal incidence of rainfall. Herbertson (1905) combined seasonal rainfall with temper- -ature to define various types of climates. De Martonne (19 25) made en attempt to classify climate with the help of an index based on seasonal rainfall and average temperature. Subsequently other workers classified world climate on similar lines, but without much significant improvement. The one suggested by Koppen (1936) based on annual and monthly means of temperature and rainfall seems to be the first approach towards general practical

4 3 application of global climatic classification. He divided the world climate into five principal groups viz., (1) Tropical rainy, (2) Dry, (3) Mild temperature rainy, (4) Cold Snow and (5) Polar climate. One of the important contributions of Koppen's system is the subdivision of climatic areas into tropical and temperate zones, using the average annual temperature as the distinguishing factor instead of the well-known latitudinal boundaries normally followed in geography. The main limitation of Koppen's classification is lack of rational basis fox selecting temperature and precipitation ranges for different climatic zones. His definition assigns the semi-arid area to tropical savanah with distinctive dry season or tropical steppe which are the areas of annuel precipitation deficiency and short unreliable rainy season. This is not entirely correct. This classification has the merit of symmetry and simplicity, but it is hardly expected that climatic types conform to so rigid a system. For example, in his methodology, the isothem of 50 F for the coldest month becomes the poleward boundary of sub-tropical climate. But this isotherm runs through Sardinia, the toe of Italy and Morea and includes whole of the northern, Mediterranean and greater part of Italian Peninsula and Greece, which in reality belong to the sub-tropical climate. Moreover neither the continuity of rainfall

5 4 nor its adequacy to meet evapotranspiration needs of crops was considered by Koppen. It has been, therefore, of very little use in assessing the agricultural potential of an area. Koppen'3 classification is no doubt pragmatic, as it indirectly includes the supposed effects upon man, but the criteria used for delimiting the classes are strictly speaking botanical in many cases. Prescott (1938) and Prescott and Thomas (19 49) tried to divide climate of Australia on the basis of en index derived from precipitation and evaporation. As reliable evaporation data from a reasonably dense network of stations were not available at that time, this method did not become very popular. Thornthwaite introduced the concept of potential evapotranspi ration in 19 48, which indicates the maximum atmospheric evaporation demand of plants under certain conditions. His approach takes into account some estimation of moisture requirement of plant. He used potential evapotranspi ration and rainfall in classifying climate and estimating soil water balance. Later, Thornthwaite and Mather (1955) further redefined the classification by considering rainfall along with water already held by the soil. Their approach is based on four factors viz. (i) a moisture index, (ii) seasonal variation of water deficiency or water surplus.

6 5 (iii) an index of thermal efficiency and (iv) summer concentration of thermal efficiency. He divided climate into five main classes and then further sub-divided them based on the range of moisture index. Thornthwaite's approach is both objective and rational. While the main emphasis of Koppen's classification is on the temperature limits, Thornthwaite's method utilizes moisture as well as temperature with soil playing an important role in retention and release of moisture. This approach has been criticised mainly for the use of potential evapotranspiration values estimated according to an empirical relation. Thornthwaite uses mean temperature and day length in the computation of potential evapotranspi rati on, whereas factors like radiation, wind and humidity which also affect evapotranspiration are ignored. Potential evapotranspiration estimates made by Thornthwaite's empirical relation are thus considered not fully representative. Thornthwaite's system has been applied to several regions and is found to generally agree well with the plant requirements, but the sub-divisions are not found to be of direct climatic significance for other human activities. Thornthwaite's (19 48) scheme of climatic classification was applied by Subrahmanyam (1956) to determine

7 6 climatic types of Indie and neighbourhood. He found that large areas of India are more arid than indicated by some of the earlier workers. The lacuna in his classification is the computation of potential evapotranspiration by Thornthwaite's empirical relationship which has limitation of its own. Modified technique qf Thornthwaite was adopted by Rao et al. (19 73b) to classify climate of Indie. In this study potential evapotranspiration was computed by Penman 's (1948) method. Also, instead of weighting the aridity index by a factor 0.6, the weighting factor was altogether eliminated in the moisture index formula. The water balance necessary in computation of the moisture index was worked out from monthly values of rainfall and potential evapotranspiration. A weekly water balance would probably have brought out intrinsic advantages of this method for direct agricutural applications. The mean temperature of the month was utilised by Meigs (1955) in climatic classification. Seasonal variation in precipitation was also introduced in this classification. Though claimed by him that his method is oriented towards agricultural potentials, the classification is strictly speaking applicable to the arid or desert lands. It has little use for other areas. Miller (1953) evolved a simple classification to facilitate general description of the world climates.

8 7 The system divides globe into various temperature zones and further subdivisions are introduced through precipitation. He recognised five types of temperature divisions. They are designated as hot, warm temperate, cool temperate, cold and arctic regions. He then superimposed the seasonal rainfall on the temperature zones to get the final classification. Evidently, Miller's system permits analysis of climate on a world wide scale. As such, it can and had been put into good use by Monk House (19 61), Bucknell (1966), etc., in delineating world climatic patterns. Subsequently, Miller (19 65) refined his class- -ification by introducing desert climate (hot deserts and cold deserts) and the mountain climate. However, this division allows no place for semi-arid climate. The main thrust of Miller's classification was on temperature, though for desert climate, rainfall in some quantified form has also been used. The essential requirement of crop and vegetation is continued supply of npisture and this aspect somehow has not been considered directly by Miller. This is the major deficiency in Miller's climate classification. Several climatic classifications based on monthly, seasonal or annual precipitation and temperature have been suggested and applied in practice (cf. Peguy, Shear, 1964$ Trewartha, etc.). These classifications are by and large, useful for understanding

9 8 and furnishing a general idea of global climates. But these cannot be used for delineating a region into different zones for modern agricultural planning and handling associated problems. This is because enhancing and stabilizing agriculture involves increasing the length of the growing period through better soil and water management by matching appropriate crops/cultivars to appropriate climatic zone on a micro-scale rather than macro-scale. While planning cropping pattern, development of irrigation, etc. the planner should have an idea of the risk he is taking in accepting a certain climatic classification. It is obvious that the steps taken by the planner will depend heavily on his choice of the risk level. This was achieved for the first time by Wallen and Perrin (1962). In their study they used the probability of receiving a certain amount of annual rainfall, inter-annual variability and continentality. On this basis they classified climate of the Near and Middle East, where annual rainfall varies from 100 to 800mm and assessed the agricultural potential of that region. They divided the area into 12 climatic zones and found close relationship between the reliable rainfall and development of crop, where reliable rainfall was defined as a period having at least 25 mm of monthly rainfall and 100 percent relative inter-annual variability.

10 9 Troll (1965) proposed a classification, called the seasonal climates of the earth, which utilizes two main variables; thermal and hygric seasons. The emphasis in his classification is on the duration of arid and humid months rather than assignment of climatic boundaries based on annual values of precipitation, temperature and humidity. A month is called humid when the rainfall exceeds potential evapo transpiration 7 otherwise it is called an arid month. Based on the number of arid and humid months, Troll divided tropics into seven climatic zones. Troll's system of classification is unique, because it does not use average annual precipitation amount. Use of monthly values over annual amounts, represents strength rather than a weakness of classification. It is well-known that annual average value furnishes very little information about the agricultural potential of a place. Although the number of months used by him as a criterion do not describe the entire rainy season, it, is in no way, diminishes the value of the respective climatic types, because of the direct correlation between the overall effectiveness of the rainy season and number of months with precipitation equal to or more than potential evapo transpiration. Troll's classification, though unique, has scope for some improvements. Because of the large variability

11 10 of rainfall in the tropics and the associated risk to stabilize crop production the use of mean monthly amount of rainfall in this approach is the obvious limitation. Use of monthly values may be adequate for ecological classification, but not for crop planning purposes, since month is too long a pe,riod particularly for critical crop growth phases. Troll's treatment is no doubt rational in delineating climate in a broad sense, but is not adequate to provide a detailed and smaller scale information needed for agriculture. Its range of figures for each climatic type is so broad that some of the types overlap over each other. Not only that, a few climatic types demarcated on the basis of Troll's classification have been found to be, in fact erroneous (Chowdhury and Sarwade, 198 2). Another drawback in. Troll's method is that it does not provide an understanding of rainfall distribution over the growing period. It also does not provide an objective index of actual moisture availability for successful crop production. It seems most likely that Troll did not have access to significantly large volume of data which is essential to define and classify world climates. Matching the duration of crop growth cycle to that of water availability in different regions is an important task in agricultural planning. In this connection, periods during which the rainfall exceeds selected levels of evapotranspiration is one of the most useful indices

12 11 of assessing agricultural potential. In the studies of Cocheme' and Franquin (1967) on semi-arid areas of the Sahara in West Africa and Brown and Cocheme' (1969) on the highlands of East Africa, five different limits of water availability were chosen. Apart from rainfall, the available water in the root zone (i.e., sum of rainfall and soil moisture) was also compared with evapotranspiration and crop water availability calendars were prepared for the seeding, emergence, growth and maturation phases of the crop growth. These methods have definitely some merits in that, the length of the growing season which is closely linked to the agricultural potential could be determined for a particular location. However, Raman and Murthy (1971) noticed that the climatic classifications do not show a simple relationship with the length of water availability periods. PapadaXis (1966) evolved a new climatic classification of the world using average daily maximum aftd minimum temperature for different months, the potential evapotranspiration, water balance and occurrence of dry and wet seasons. Information on severity of winter length of frost free season, leaching rainfall, drought stress, etc. were also incorporated in the classification. In 19 75, PapadaXis modified his earlier classification to include climatic constraints, soil limitations and farming systems. His classification is much oriented

13 12 towards agriculture and. crop requirements and he was able to explain the distribution of crops. His method is, as such, a definite improvement on earlier classifications for assessing crop potential of any region. But it is difficult to use it, particularly in India, since it involves computation of numerous complex types and sub-types. His argument in using the monthly data in classification that all meteorological statistics are given by month, also is not very convincing. Moreover, for agricultural purposes month is too long a period. Use of weekly values would have made the classification really agriculturally oriented, but would have made the computations still more complicated. The studies mentioned so far, except that of Wallen and Perrin (1962), do not deal with the risk factor involved in any planning. It goes without say- -ing that the planner, be he a farmer or a hydrologist, must know the risk he is going to take in his endeavour. The study using average or nomial rainfall cannot include this risk factor. In the dry farming tract or the low rainfall areas, there is considerable year to year deviation of rainfall from its normal value. In these areas, the normal rainfall (monthly, seasonal or annual) is too small to meet the full water requirements of the crops. But experience shows that on a number of occasions crops are successfully raised in these areas.

14 13 Apparently, in such years, the rainfall is more than the normal value and meets the water demands of the crops. So for any crop planning purpose, one should know chances of meeting the water requirement of the crops. Accordingly, the planning has to be done on a probabilistic basis, which eventually takes into account the chance of success or failure. This aspect of the risk factor associated with any planning purpose was dealt by Hargreaves (19 71 and 19 74). He developed a very useful index as a measure of adequacy of precipitation in meeting the plant moisture requirements. He called this index as Moisture Availability Index (MAI) and defined it as a ratio of the monthly value of precipitation at 75% level of probability based ort long term records to evepotranspiration. He showed a broad relationship between MAI and the moisture deficit. The main emphasis in Hergreaves* classification is on the number of continuous months when MAI is equal to or greater than The period when MAI < 0.34 is presumed as utterly unsuitable for growing crops. He classified climates into four groups viz. very arid, arid, semi-arid, and wet-arid as shown on the next page and accordingly suggested cropping pattern for rainfed agriculture.

15 * > 14. Criteria All months with MAI ^ 0.33 One or two months with MAI of 0.34 or above Climatic Classification Very arid Arid Productivity Classification Not suitable for rainfed agriculture Limited suitability for rainfed agriculture 1 Three or four consecutive months with MAI of or above Semi arid Production possible for crops requiring 3-4 months' growing period Five or more consecutive months with MAI 0.34 Wet arid Production possible for crops requiring a good level Of moisture adequacy during 5 or more months i. < - Hargreaves' work which was done with special refer-* ence to north east Brazil an area of deficient rainfall is an important landmark in the agro-climatic classification. Risk involved in the agricultural enterprise, the degree of moisture inadequacy or otherwise during the crop season, determination, of the crop growing period, etc. are all taken care of, in this classification. However, the approach has a few major short-comings j (1) Month as the unit of tine, is fairly long period for agricultural purposes. (2) The probability level and the ranges of MAI appeared rather arbitrary. (3) Only one risk level i.e., 75% has been chosen

16 15 which appears quite high for areas normally receiving low rainfall. The above deficiencies in the Hargreaves method impose some restrictions on the universality of the use of the MAI as a climatic classification system* Methods based on the pattern analysis have greatly influenced classification in various scientific fields. Their impact has been most profound in field such as microbiology where previous classification based oh a large number of criteria were generally unstable and unsatisfactory (Cowea, 1963). The effect of pattern analysis on classification in agricultural science has been much less marked, though some application in soil science and plant and animal ecology has been made (Moore and Russell, 19 67, Webb et a_l_., 19 71, Moore et al., 1972, etc.). Russell and Moore (1976) applied pattern analysis to climatic data of Africa and Australia in seeking homoclimates. The stations were treated as a single set and date for 16 climatic attributes on a monthly basis were used. This method no doubt has a number of potentially useful agricultural applications. It could provide, besides homoclimates in different parts, classification relating to the distribution of specific plant genotype which may be of value in explaining past biogeographic events. The main disadvantages of classification are

17 16 related to the extent to which these classifications are method dependent. Pattern analysis is attribute* dependent and the choice of attributes largely affect the classification. Also, all the data required in the analysis may not be available for-all the stations. Finally, this classification is not as much useful in determining crop potential as it is for identifying closely similar climatic locations from a massive data set of a large number of locations. As has been mentioned above, month is too long a period compared to different crop growth phases and most of the earlier workers have used month as a unit of time for the climatic classification. Plant breeders are constantly evolving shorter duration varieties with e view to producing as many crops in a year as posbible. Use of monthly rainfall, as a parameter in classification suffers from another defect also. There are areas where even at the height of wet season the daily rainfall fluctuates enormously in amount, so much so that a mohth's average rainfall can be realised in only a few days (say, a week or even less), while the rest of the month may go dry. Rainfall of such large magnitude can cause irrepar~ able damage to the crop at any stages of its growth. Therefore there is a need to use a smaller unit like a fortnight or a week as the unit of time for agro-climatic classification. Such an approach was adopted by Sarker

18 17 and Biswas (1980) in classifying climate for agricultural purposes, using Incomplete Gamma distribution model. They used weekly rainfall date of 87 stations over dry farming tract of India. An index called the Optimum Moisture Availability Index (OMAI) was calculated 4 This is defined as the ratio of the Assured Rainfall (AR) at 50% probability level to Potential Evapo Transpiration (PET). Depending upon the magnitude and duration of OMAI, the dry farming tract was divided into four different classes. Further subdivision was made based on the water stress period. Sarker and Biswas have no doubt removed some of the deficiencies in Hargreaves* method by (1) using weekly rainfall instead of the monthly value, ( 2) lowering down the risk factor to 50% probability level, (3) using two different levels viz., 0.3 -tee 0.7 of moisture availability index s the first one was considered necessary for the survival of a crop and the second, essential for the active crop growth. Their method* however, has a few short-comings t (1) In using incomplete Gamma distribution in their approach they have assumed independence of weekly rainfall.

19 18 (2) Crop assessment has been done by accumulating weekly minimum assured rainfall for a particular period. In reality, the rainfall for that period may be more than that accumulated. (3) Moisture stress periods considered by them do not give an exact idea of continuous dry spell, since continuity in rainfall occurrence has been ignored. The ratio of rainfall and the potential evapotranspiration has been used by Chowdhury and Sarwade (1982) in climatic classification of India. They have given different weights to the monthly values of the ratio to evolve a climatic index. The main objection to this system is on the use of monthly values. This approach may be useful for ecological purposes, but has limited use in agroclimatic classification and determination of agricultural potential. Gahzalli and Nienwolf (1982) also used a risk factor in agroclimatic zoning of Malaysia. The monthly rainfall at 80% probability level expressed as a percentage of potential evapotranspiration was used by them as Agricultural Rainfall Index (ARI). ARI values were subsequently used for crop selection. of this system is on the use of month The major drawback as a unit.

20 19 Reddy (1983) proposed a method based on rainfall and potential evapotranspiration for classifying semiarid tropics into agronomicelly homogeneous zones. He introduced a term "available effective rainy period" for this purpose. This period is defined as number of consecutive weeks jn which the 1.4 week moving average of the ratio of rainfall to potential evapotranspiration is greater than Reddy's method allows a relevant and realistic assessment of agroclimatic environment and agriculture potential of a region. It considers week as a unit and also takes into account, though indirectly, a risk factor. It however suffers, from a few limitations, as given below :- (1) This method is strictly applicable for semiarid areas. (2) It uses a large number of variables, some of which do not have much relevance to the crop growing processes and (3) In agriculture, it is the continuous dry spells that adversely affect the crop growth and the yield. Reddy's use of just number of dry spells without considering the continuity in the growing period cannot bring out the stress to which a growing crop may be actually subjected to.

21 20 With this brief introduction on agroclimatic classification, we now proceed to the subsequent chapters where we have studied and presented the results of wet and dry sequences, weekly rainfall probability and agroclimatic classification for the dry farming tract of the State of Kama take of India.