A new soil-moisture based classification of raindays and drydays …ousmane/print/Onset/Kamara... · 2010. 1. 6. · Leone, using a simple water balance model to estimate soil moisture

Theor. Appl. Climatol. 56, 199 213 (1997) Theoretical

Applied matol-ogy

© Springer-Verlag 1997 Printed in Austria

1 Department of Geography and Planning, University of New England, Australia 2Department of Geography, Chinese University of Hong Kong

A New Soil-Moisture Based Classification of Raindays and Drydays and its Application to Sierra Leone

S. I. Kamara 1 and I. J. Jackson 2

With 7 Figures

Received October 30, 1994 Revised December 1, 1995

Summary

The paper proposes a new classification of raindays and drydays incorporating soil moisture status. This is of particular value for agricultural purposes and also allows the adoption of a low rainfall threshold to distinguish between raindays and drydays. This is important since, as indicated in the paper, small falls may be important and yet in the tropics, for agricultural purposes, a high threshold is often adopted to take account of the high evaporative demand of the atmosphere. Soil moisture is expressed as a percentage of available soil moisture storage capacity (SMSC) and conditions are described as deficit, limiting, adequate, and surplus, if soil moisture levels are 0-29%, 30 59%, 60-100% and > 100% of SMSC respectively. Combining this with rainday and dryday occurrence, three types of drydays and four types of raindays are identified. This rain-soil moisture index classification more nearly approaches a universal definition suitable for different tropical regions than previous ones. Application of the concept is illustrated with data from Sierra Leone, using a simple water balance model to estimate soil moisture.

1. Introduction

This paper introduces a new classification of raindays and drydays incorporating soil moisture status which is particularly appropriate for agriculture. In many tropical areas where seasonal variations in temperature are not a major limiting factor to plant growth, the timing, duration, and overall quality of the growing season are mainly determined by the local rainfall regime, although

other factors such as evaporation rates, soil and crop types are also important. Among the variety of rainfall attributes that determine the character of the local rainfall regime and hence the growing season(s), the number of raindays and their distribution during the year are of major significance.

The appropriate rainfall threshold to separate raindays from drydays has been the subject of considerable debate, since purpose, as well as other environmental and human factors, must be considered. These other factors preclude the adoption of a universal threshold suitable for all circumstances. In the tropics, a high threshold is often adopted to take into account the high evaporative demand of the atmosphere. However, as is suggested below, small rainfall amounts may be important, presenting a dilemma. For agricultural purposes, soil moisture is a better indicator of water available to plants than rainfall on a particular day. Furthermore, incorporation of soil moisture status into the classification of raindays and drydays has the advantage that a low rainfall threshold can be used, which acknowledges the possible importance of light falls.

2. Definitions of Raindays and Drydays

As a background to the new classification, it is appropriate to consider previous definitions of

200 S.I. Kamara and I. J. Jackson

raindays and drydays under two headings, meteorological and agricultural.

2.1 Meteorological Rainday/Dryday Definitions

"Meteorological" ra inday/dryday definitions are widely used in the atmospheric sciences, especially where the main interest lies in the distinction between occurrence and non-occurrence of rainfall. These definitions are generally not concerned with the effects of rainfall on a particular human activity, or its adequacy in satisfying a specific need such as crop-water requirements. To the atmospheric scientist, a rainday is usually defined as a period of twenty-four hours with total rainfall equal to or greater than the minimum measurable amount, as distinct from a dryday when either no rain falls at all or when its amount is too small to be measurable by standard methods, this being termed a "trace" amount. The definition of "minimum measurable" rainfall varies between countries. In countries where rainfall measurements are made in imperial units, the "minimum measurable" rainfall is normally set at 0.01 inches (0.25 mm). Many countries using the metric system, on the other hand, adopt a threshold value of 0.1 mm of rainfall for a rainday. However, countries with the same minimum measurable rainfall may use different rainfall thresholds to define raindays. Among Francophone West African countries for instance, the threshold value for a rainday has been found to vary from 0.1 mm to 2.0ram (Shijder, 1986).

The use of such small rainfall amounts as the threshold to define a rainday has been questioned by some researchers (Stern et al., 1982), mainly because of their doubtful value to crops (see dis- cussion of agricultural definitions below), but also because of the reliability with which they are measured, especially by non-professional ob- servers. Another related problem is the common practice in rainfall observation to round off measurements to the nearest tenth of an inch or millimetre so that a reading of, say, 0.05 mm becomes 0.1 mm. Concerns have also been raised about the possibility of atmospheric water vapour condensing directly into the gauge overnight, to be read as rainfall the following morning by an unsuspecting observer. For these, and other rea- sons, a value higher than the minimum measurable rainfall amount has been suggested by some researchers as being more appropriate for the "meteorological" definition of a rainday.

Table 1 presents examples of meteorological ra inday/dryday definitions that have been used in different parts of the tropics. There is a considerable range in threshold values. In India, Banerji and Chabra (1963) recommend 4 .0mm or more, while they quote the Indian Meteorological Department 's specification of 2.5ram. In West Africa, Garbutt et al. (1981) consider only days with 0.85 mm or more as raindays, pointing out that in many parts of the region rainfall less than 1.0 mm accounts for 20% of the raindays, but only 2% of the annual rainfall total. In his analysis of raindays in Nigeria, Olaniran (1987), omits all

Table 1. Selected "MeteorologicaI" D@nitions of Tropical Raindays

Author Geographic Region Rainfall Threshold

Barnerji and Chabra (1963) Subbarramayya and Kumar (1978) De Jardins (1982) Garbutt et al. (1981) Jackson (1988) Nieuwolt (1977) Olaniran (1987) Olaniran and Sumner (1989) Raman and Krishan (1958) Sierra Leone Met. Department

Sumner (1988) Yap (1973)

Asia (India) 4.00 mm Asia (India) 2.50 mm Eastern Australia 0.25 mm West Africa 0.85 mm Northern Australia 0.25 mm Tropics (General) 2.00 mm W. Africa (Nigeria) 2.00 mm W. Africa (Nigeria) 1.00 mm Asia (India) 0.25 mm W. Africa (Sierra Leone) 0.25 mm

(0.10mm Tropics (General) 0.25 mm Asia (Malaysia) 0.25 mm

since 1975)

A New Soil-Moisture Based Classification of Raindays and Drydays 201

days with rainfall less than 2 mm, in support of Nieuwolt's (1977) assertion that they are not significant in the warm tropics.

Despite misgivings about the accuracy with which small rainfall amounts can be measured, it would be wrong to ignore them completely. From a physical climatological point, the occurrence of light rainfall following a period of continuous dry weather may signify a major change in atmospheric conditions over an area, and hence an increased chance for rainfall in the following day (s) if those conditions persist. Yap (1973), Jackson (1981), and many others have shown that rainfall occurrence in the tropics is strongly dependent on conditions on the previous day(s). In many cases, conditions during the previous two days are important.

2.2 Agricultural Rainday/ Dryday Definitions

"Agricultural" rainday/dryday definitions are concerned with the significance of rainfall for various facets of agriculture. Most agricultural definitions emphasise the adequacy of rainfall for meeting plant-water needs. Such an emphasis is a simplification of reality since plants basically get their water from the soil, not directly from rainfall.

In the tropics, light rainfall is commonly considered to be ineffective because of the high evaporative demand of the atmosphere. It is argued that higher thresholds are more appropriate in defining an agricultural rainday in the tropics. However, not only can light rainfall be significant in several ways, as indicated below, but also, the factors and processes that govern the amount of rainfall that enters the soil profile, and the propor- tion of that amount which eventually becomes

available to plants, are both numerous and very complex.

Table 2 presents examples of agricultural rainday and dryday definitions. In his analysis of rainfall for planning rice cropping systems in Asia, Sastry (1976) defines a "dry" day as "a day with rainfall less than 6 mm in 24 hours, which is based on the fact that the average potential evapotranspiration rate is about 5mm/24 hr". Nieuwolt (1989) proposes a much lower threshold of 1.0 mm per day for a tropical rainy day, pointing out that rainfall less than this amount does not significantly contribute to the moisture requirements of crops in the tropics. It is also argued that the total rainfall amount produced from series of days with less than 1.0 mm is usually relatively small.

The assumption that rainfall must enter the root zone for it to be agriculturally significant is somewhat erroneous since plants can directly uti- lize at least some rainwater on the surface of leaves (Chang, 1968). Also, in seasonally wet-dry climates, or in low rainfall areas, occasional light showers can be useful for the growth and survival of plants. For example, Glover and Gwynne (1962) demonstrated the significance of light rainfall for the growth of maize under arid and semi- arid conditions in East Africa. By concentrating intercepted rainwater at their base, maize plants were able to survive during dry periods.

Light rainfall can also be of major epidemiolog- ical significance. Leaf-wetness conditions or high surface humidities resulting from rainfall, combined with high temperatures, provide ideal micro- climatic conditions for the growth and spread of certain animal and plant fungal, viral and bacte- rial diseases (Emmett et al., 1991). For example, according to Magory and Watchel (1991) the

Table 2. Selected "Agricuhural" D@nitions of Tropical Raindays

Author Geographic Region Rainfall Threshold

Alusa and Gwange (1978) East Africa (Kenya) 1.00ram Jackson (1981) Tropics (General) 1.00 mm Jackson (1986) Tropics (General) 0.30 mm Nieuwolt (1968) Tropics (General) 0.25 mm Nieuwolt (1989) Tropics (General) 1.00 mm Rees et al. (1991) East Africa (Somalia) 2.00ram Sastry (1976) Asia (India) 6.00 mm Sivakumar (1992) W. Africa (Niger) 0.85 mm Stern et al. (1981) W. Africa & India 0.85ram Stern et al. (1982) W. Africa & India 0.10ram


occurrence of 1-3 mm of rainfall during a warm night can lead to severe secondary infection (i.e. leaf-to-leaf and leaf-to-branch movement) of downy mildew disease in grapes. Also, in disease control programmes through spraying, water droplets on the surface of leaves prior to spraying can act as a "sticking agent", which is beneficial, whereas the occurrence of rainfall within one to two days after spraying may dilute the chemicals, or when heavy, act as a "washing agent", thereby reducing the effectiveness of the treatment (de Villiers, 1966; Wang, 1967).

Apart from direct effects on crops and diseases, light rainfall intercepted by vegetation, which then evaporates, may influence plant transpira- tion. Additionally, under high temperature conditions, the use of energy to evaporate intercepted water helps to cool and hence reduce the heat load on plants. Light rainfall reaching the soil surface may similarly reduce upper level soil temperatures and perhaps upward moisture movement from the root zone.

2.3 The need for a new Classification of wet and dry days

Much of the above debate about appropriate thresholds to separate dry and wet days is related to meeting plant water needs. Therefore it seems appropriate to introduce soil moisture into the classification to take this factor into account. By doing this, it then becomes possible to adopt a low threshold to define a rainday, which is important given the value of light rainfalls as suggested above.

3. A new Rainday/Dryday and Soil Moisture Classification

The two stage classification first of all separates raindays from drydays using a low rainfall threshold such as the minimum measurable rainfall for a particular country. Next, four soil moisture limits are set, based upon the percentage of soil moisture storage capacity (SMSC) in the soil on each day (Table 3). SMSC is taken to be that available to plants. The lower limit of plant-available water was set at 30% of the assumed SMSC. Below this limit, water was regarded as not being readily available to plants, and "deficit" conditions were assumed to prevail. Jones and Guimaraes (1979) and Jones (1980) used a similar threshold for upland rice.

Table 3. Soil Moisture Class Intervals and their Descriptions

Soil Moisture Class Description (% of SMSC)

0 29 "Deficit" 30-59 "Limiting" 69-100 "Adequate" > 100 "Surplus"

Most field crops begin to suffer stress when the soil water content falls below about 60% SMSC (Doorembos and Pruit, 1977; Radulovich, 1987; Raddatz, 1992). All days with soil moisture content between the lower limit of readily extractable water (30% SMSC) and the 60% storage level were therefore considered to experience "limiting" moisture conditions.

Between the 60% storage level and field capacity (FC) (simply defined as the water remaining in a soil when free drainage has ceased following saturation of the soil), water supply was assumed to be "adequate", and freely available to plants, although availability also depends on several factors including rooting depth and density, soil characteristics and prevailing weather conditions. Above FC all "surplus" water was assumed lost to plants, although this "surplus" may take some time to drain beyond root range and hence could be available for a time.

By taking into account both the rainfall state as defined above, and the soil moisture class, each day was then assigned to one of seven possible rain-soil moisture categories (Table 4). The classification recognises the fact that non-occurrence of rainfall does not necessarily imply lack of moisture for crop use, even under rain-fed conditions. Indeed, occasions do exist when the soil contains abundant moisture reserves from previous rain to sustain a crop during a dry (rainless) spell. In other words, "meteorological" dryness does not necessarily coincide with "agricultural" dryness. On the other hand, rain may fall several times after a period of dry weather, without necessarily resulting in a build up of soil moisture sufficient to launch and/or sustain a crop.

Ideally, soil moisture data from field measurements could be used in the classification. How- ever, particularly in tropical regions where such data are rare, a water balance approach can be adopted to estimate soil moisture. Water balance

A New Soil-Moisture Based Classification of Raindays and Drydays

Table 4. Classification of Tropical Raindays and Drydays

203

Rainfall State Soil Moisture Designation (%SMSC)

General Description

*No Rain

**Rain

0 29 Type I Dryday 30-59 Type II Dryday 60-100 Type l I I Dryday

0 29 Type I Rainday 30 59 Type II Rainday 60 100 Type l I I Rainday > 100 Type 1V Rainday

No rain with "deficit" soil moisture No rain with "limiting" soil moisture No rain with "adequate" soil moisture

Rain with "deficit" soil moisture Rain with "limiting" soil moisture Rain with "adequate" soil moisture Rain with "surplus" soil moisture

* < 0.25mm ** 0.25ram or more

models of varying degress of complexity are widely used for agroclimatological purposes (Jackson, 1989). However, in the tropics, lack of data often means that a relatively simple model must be used.

4. Application to Sierra Leone

4.1 Background and Water Balance Model Adopted

To illustrate the use of the classification, the approach is applied to Sierra Leone, West Africa, where rainfed agriculture is of great importance. The land rises from coastal plains to a low plateau (300-1000 m) in the northern and eastern interior (Fig. 1). There are two main seasons; a dry season (December-April) and a wet season (May-Novem- ber). Total annual rainfall varies from over 4000 mm in some of the coastal regions, with small areas in excess of 5000mm, to 2000mm in the extreme north (Fig. 5). Numbers of raindays (at least 0.25ram) range from about 140 to over 180 (Fig. 4). Mean temperatures are at least 18 °C in every month. Agriculture is the mainstay of the economy, providing a livelihood for nearly 75% of the population. Slash-and-burn cultivation is widely practiced. Over 90% of agricultural land depends upon rainfall rather than irrigation and hence investigations of rainfall characteristics are of great value.

The threshold to distinguish dry from wet days was taken as the minimum measurable rainfall in Sierra Leone (0.25mm). In the absence of soil moisture measurements, a water balance model was used to assess available soil moisture, based upon daily rainfall and estimated evapotranspira-

tion (Et). The latter consists of 10-day mean values calculated by the Land Resources Survey Project (1980) according to Frere's (1972) format for com- puting Penman's (1948) values. The use of mean Et values is unlikely to create problems since this parameter is far less variable in time and space than rainfall (van Bavel, 1953; Norman et al., 1984). Also, crop water requirements vary with type, variety and stage of growth and develop- ment. Hence their representation by a single variable (Et) is in any case a generalisation, but appropriate when the aim is to examine conditions over the whole country, without reference to a specific crop. Also since the need was to repre- sent the situation under a range of conditions (i.e. over all of Sierra Leone) rather than to monitor detailed hydrological processes at specific loca- tions, a simple water balance model, based on the following assumptions and simplifications, was considered appropriate.

(i) In the absence of measured or estimated soil moisture storage capacities (SMSC) at individ- ual rain-gauge sites, a constant value of 100 mm SMSC was adopted, which is regarded as a realistic assumption for the study area (LRSP, 1980).

(ii) 100% infiltration was assumed. (iii) Evaporative loss was not 'modulated' i.e. not

influenced by soil moisture. Such influence is recognised in the use of four soil moisture categories indicated in the previous section. However, as already indicated, the variation in conditions suggested that a simple un- modulated water balance approach was sufficient in this case, particularly given


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A simple daily water balance model of the following form was adopted:

Wbx = W b x - 1 + Rx - E + S

where Wb x = Water balance on day "x", denoting water stored in the soil profile, (cannot exceed SMSC), W b x - 1 = Water balance on the previous day, R x = Rainfall on day "x", E = Estimated daily evaporation (using 10-day mean values), S = Surplus (not available to plants).

Having computed the water balance for the entire record, days were then assigned to one of the four soil moisture classes in Table 3.

4.2 Frequency of day Types

Table 5 shows the mean annual number of the three dryday and four rainday categories at eight stations for the 30 year period 1948-1977. The most frequently occurring days are drydays with "deficit" soil moisture (Type I drydays), followed by raindays with "surplus" soil moisture (Type IV raindays), accounting for 30-42% and 16-28% of the total number of days respectively. The high frequency of occurrence of these two categories of days is evidence of a climatic regime characterised by extreme conditions of dryness and wetness, with serious agricultural and hydrological implications.

Between 21 and 36% of the annual total number of days fell within the Type III categories, meaning that whether or not it rained there was


Table 5. Mean Annual Number of Raindays and Drydays at Selected Stations (I948-1977) and Percentages of Annual Totals

Station Day Type

Type I Type II Type III Type I Type II Type III Type IV Dryday Dryday Dryday Rainday Rainday Rainday Rainday

Kabala 151 19 57 17 9 56 57 41% 5% 16% 5% 3% 15% 17%

Yengema 112 20 83 13 7 48 82 33% 6% 23% 4% 2% 13% 23%

Makeni 124 15 57 15 5 48 102 34% 4% 16% 4% 1% 13% 28%

Rokupr 145 13 54 11 5 41 96 40% 4% 15% 3% 1% 11% 26%

Freetown 142 16 49 15 6 51 86 39% 4% 13% 4% 2% 14% 24%

N2 River 155 15 50 11 6 27 102 42% 4% 14% 3% 2% 7% 28%

Bo 11t 17 59 18 6 59 96 30% 5% 16% 5% 2% 16% 26%

Solon 113 17 73 14 6 56 86 31% 5% 20% 4% 2% 15% 24%

always an "adequate" supply of soil moisture to support plant growth. Of these, drydays with "adequate" soil moisture (Type III drydays) ac- counted for 13-22% of all days.

In Table 5, the low frequency of raindays with "deficit" and "limiting" soil moisture (i.e. Types I and II raindays) does not mean, of course, that most storms add considerable moisture to the soil. As elsewhere in the tropics, much of the rain is produced by a limited percentage of storms. It is an indication of the fact that on many days with only small amounts, soil moisture reserves are still adequate.

A twenty year (1950-1969) data set for thirty stations was used to investigate spatial variations in the average annual occurrence of day types (Figs. 2-3). The spatial patterns of the various types are very different from one another and also differ from those of mean annual numbers of raindays (Fig. 4) and mean annual rainfall (Fig. 5). Therefore, spatial patterns of occurrence of the different day types could not be predicted from patterns of rainfall variables such as mean annual rainfall or total numbers of raindays.

4.3 Seasonal Distribution of day Types

For many practical purposes the most important aspects of rainfall are its timing and distribution

during the year. Seasonality is reflected in the calendar of agricultural activities and hydrological regimes. Although spatial patterns vary (Figs. 2 and 3), it is useful to illustrate seasonal variations using data for a northern station (Ka- bala) and one from the south (Bo). Using a 30 year data set (1948-1977), the median, upper and lower quartiles, 10% and 90% limits of the numbers of different types of rainday and dryday in 10 day periods (decades) were computed for each station (Figs. 6 7).

Type I drydays with "deficit" soil moisture (Fig. 6a) are dominant between the 34th-gth decades (early December to late March), with a median of 7-10 days per decade, and few or none between the 18th-33rd decades (late June to late November). However, there is considerable inter- annual variability in the number of such days between the 9th and 15th decades (late March to late May), and between the 34th-36th decades (December), indicating uncertainty in conditions at the start and finish of the rainy season. "Type I" drydays, which are a combination of "meteorological" and "agricultural" dryness, are generally associated with seasonal drought conditions, with adverse effects on crops and water supply, especially if such conditions persist for considerable lengths of time, as they do in Sierra Leone. How- ever, such days can be advantageous for certain


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agricultural operations. For example, in the "slash-and-burn" system of farming, which is prevalent in many tropical areas such as Sierra Leone, dry spells associated with "Type I" drydays provide ideal "fire weather" conditions during the burning phase of the operation.

Type II drydays with "limiting" soil moisture (Fig. 6b) show a bi-modal seasonal distribution,

with a primary peak of about 3 days per decade between the 32nd-36th decades (mid-November to late December), and a minor peak between the 12th-16th decades (late April to early May). Type III drydays with "adequate" soil moisture (Fig. 6c) are experienced at both stations between the 1 lth-35th decades (April-December). There is a minor peak around the 15th-16th decades, fol-


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lowed by a mid-season trough (21st-27th decades) and a primary peak with a median maximum of 6 days per decade between the 30th-33rd decades. The larger number of types II and III drydays with either limiting or adequate soil moisture at the end of the rainy season than at the start reflects

the build up of soil moisture during the season. Although on both type III days (dry and rainy), adequate soil moisture may be available at the start of the growing season to ensure the germina- tion and emergence of a crop, in many low-lying tropical areas soil temperatures may reach levels

208

Fig. 4. Mean annual number of raindays (at least 0.25 ram)

S. I. Kamara and I. J. Jackson

which can be fatal to young plants. However, type III raindays (or irrigation) will reduce the dangers of high soil temperatures because of evaporative cooling (Jenson et al., 1990). On the other hand, frequent showers can also produce leaf-wetness

Fig. 5. Mean annual rainfall distribution (mm)

conditions which may lead to increased disease incidence.

Both Types I and II raindays with "deficit" and "limiting" soil moisture are few. The former occur between the lst-15th decades (January-May) in

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the south (Bo) and the 9th-15th decades (March- May) in the north (Kabala), but rarely exceed 4 days per decade (Fig. 7a). As in many tropical areas with distinct dry and wet seasons, the soil is often bare and liable to erosion after a long dry

season. Where farmers burn their farm plots as a means of land preparation, there is a heavy reliance on the residual ash for soil fertility. Under such conditions, light rainfall ("Type I" raindays) helps to bind the top soil or loose ash, thereby

210 S.I . Kamara and I. J. Jackson

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making it less vulnerable to erosion by local whirl- winds (dust devils), and early season rainstorms. Type II raindays occur mainly between the 9th- 16th decades (late March to early June) but are generally less than 3 days per decade (Fig. 7b).

Preferred times of occurrence of Type III raindays with "adequate" soil moisture (Fig. 7c) are generally between the 9th-36th decades (late March to late December) in the south and the 14th-33rd decades (mid May to late November) in


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Decade

30 33 36

Fig. 7. Seasonal distribution of raindays at two stations. 7A = Type I raindays; 7B = Type II raindays; 7C = Type III raindays; 7D = Type IV raindays

the north. At Kabala in the north, a seasonal peak with a median of 4 days per decade is attained between the 19th-24th decades. Up to 9 days per decade may be experienced during the 23rd decade, although conditions are highly variable

from year to year. At Bo in the south, Type I l l raindays are more widely distributed during the year (Figure 7c). Only the first 8 decades have no such days, although most decades have 6 or less of this type.

212 s.I. Kamara and I. J. Jackson

Type IV raindays with "surplus" soil moisture are the second most frequent type of day. They generally occur between the 12th-34th decades (late April to early December) in the south (Bo) and the 15th-32th decades in the north (Fig. 7d). At Kabala, the peak with a median of 6 days per decade occurs during the 26th decade (mid- September). Bo has quite a number of decades with a median of 6 or more. Type IV raindays with "surplus" soil moisture are associated with flood- ing and erosion hazards, as well as leaching of mineral nutrients.

5. Conclusions

This classification system provides a more com- plete and useful characterisation of water-related aspects of the agricultural environment than descriptions based on either rainfall or soil moisture levels alone. It allows the use of a low rainfall threshold to separate dry from rain days, an advantage given the possible importance of light falls. Soil moisture is a better indicator of water available to plants on a particular day than rainfall on that day. The ways in which the occurrence of different types of day can be related to various aspects of agriculture are illustrated using Sierra Leone as an example. The Sierra Leone data also show that the spatial patterns in numbers of occurrences of the different types of days may not be related to spatial patterns in, say, mean annual rainfall or total numbers of raindays.

The approach comes nearer to a universal classification system than one based, for example, only on a rainfall threshold. If necessary, the approach could be modified to meet the needs of different tropical environments, for example by changing the rainfall threshold separating raindays from drydays, or changing the categories of percentage of available soil moisture storage capacity. As shown by the Sierra Leone example, the approach can be used with limited and general- ised data. However, it could also use more detailed information, for example, actual soil moisture measurements, perhaps for a range of soils, specific crop water requirements, or a more refined water balance model, given the availability of necessary data.

References

Alusa, A. L., Gwanga, P. M., 1978: The Occurrence of Dry Spells During the East African Long Rains. Kenya Met. Dpt. Res. Report No. 2, 79.

Banerji, S., Chabra, M. B., 1963: Drought conditions in the Telangana Division (Andhra Praadesh) during the South West monsoon season. Indian J. Met. Geophy., 14 (4) 403- 415.

Chang, J. H., 1968: Climate and Agriculture. Chicago: Aldine. De Jardins, R. G., 1982: An Analysis of Sequences of Rain-

days and Drydays over a Region of South-East Queens- land. unpublished PhD Thesis, University of New England.

De Villiers, E. A., 1966: Plant diseases, insects and the weather, in Agromet. Proceed. of WMO Seminar, Mel- bourne, Australia.

Doorenbos, J., Pruitt, W. O., 1977: Crop Water Requirements. FAO Irrigation and Drainage Paper No. 24, 144, Rome.

Emmett, R. W., Madge, D. G., Magarey, P. A., Biggins, L. T., Wicks, T. J., 1991: Agrometeorology and Powdery Mildew of Grapes. Proc. Conf. Agric. Met. Australian Bureau of Meteorology, Melbourne.

Frere, M., Popov, G. F., 1972: Agrometeorological Crop Monitoring and Forecasting. FAO, Rome.

Garbutt, D. J., Stern, R. D., Dennett, M. D., Elston, J., 1981: A Comparison of the rainfall climates of eleven places in West Africa using a two-part model for daily rainfall. Arch. Met. Geoph. Biokl. Series B, 29, 137-155.

Glover, J., Gwynne, M. D., 1962: Light rainfall and plant survival in East Africa: (1) Maize. J. Eco., 50, 111-118.

Jackson, I. J., 1981: Dependence of wet and dry days in the tripics. Arch. Met. Geoph. Biokl., Series B, 29, 167-179.

Jackson, I. J., 1981: Relationships between raindays, mean daily rainfall intensity and monthly rainfall in the tropics. J. ClimatoI., 6, 117-134.

Jackson, I. J., 1988: Daily rainfall over northern Australia: deviations from the world pattern. J. CIimatoI., 8, 463-476.

Jackson, I. J., 1989: Climate, Water and Agriculture in the Tropics, 2nd edn. London: Longman and Chichester: J. Wiley, 377pp.

Jensen, M. E., Burman, R. D., Allen, R. G., (eds.) 1990: Evapotranspiration and Irrigation Water Requirements. New York: American Society of Civil Engineers.

Jones, C. A., 1981: Effect of drought stress on % filled grains in upland rice. Trop. Agric., 58 (3), 201-203.

Jones, C. A., Guimaraes, C. M., 1979: The field water balance of a red yellow latosol under upland rice: Effect of leaf area index on drought stress. In: Lal, R., Greenland, D. J. (eds.) Soil Physical Properties and Crop production in the Tropics. New York: John Wiley, pp. 139-147.

Land Resoruces Survey Project, 1980: Agro-ecological Atlas of Sierra Leone: a survey and appraisal of climate and crop resources. Technical Report No 5, Freetown.

Megory, P. A., Watchel, M. F., 1991: Agrometeorology and Downy Mildew of Grapes. Conf. Agric. Met. 17-19 July, Melbourne. Australian Bureau of Meteorology.

Nieuwolt, S., 1977: Tropical Climatology. Chichester: John Wiley, pp. 102-128.


Nieuwolt, S., 1986: Agricultural droughts in the tropics. Theor. Appl. Climatol., 37, 29-38.

Nieuwolt, S., 1989: Estimating the agricultural risks of tropical rainfall. Agric. Forest.. Meteor., 45, 251-263.

Norman, M. J. T, Pearson, C. J., Seal, P. G., 1984: The Ecophysiology of Tropical Crops. Cambridge: Cambridge Univ. Press, 369pp.

Olaniran, D. J., 1987: A study of the seasonal variation of rain-days of different categories in Nigeria in relation to the miller station type of tropical continents. Theor. Appl. Climatol., 38, 198 209.

Olaniran, D. J., Sumner, G. N., 1989: Climatic change in Nigeria: variations in rainfall receipt per rain-day. Weather, 44, 242-248.

Penman, H. L., 1948: Natural evaporation from open water bare soil and grass. Proceedings Royal Society, 193, 120- 145.

Raddatz, R. L., 1992: Agroclimatic Overview of the Canadian Prairies. Drought Network News, 4 (3), 16-17.

Radulovich, R., 1987: Aqua: a model to evaluate water deficits and excess in tropical cropping. Part 1: Basic assumptions and yields. Agric. Forest. Meteor., 40, 305 321.

Raman, P. K., Krishan, A., 1958: Runs of dry and wet spells during Southwest Monsoon and onset of Monsoon along the west coast of India. Indian J. Met. Geophy., 21, 105-116.

Rees, D. J., Omar, A. M., Rodol, O., 1991: Implications of the rainfall climate of Southern Somalia for semi-mechanized rain-fed crop production. Agric. Forest. Meteor., 56, 21 31.

Sastry, D. S. N., 1976: Climate and Crop Planning with particular Reference to Rainfall. Climate and Rice IRRI Symposium. 51 63.

Sierra Leone Meterological Department, 1951: Annual Re- port Ereetown.

Sivakumar, M. V. K., 1992: Exploiting rainy season potential from the onset of rains in the Sahelian zone of West Africa. Agric. Forest. Meteor., 51,321-332.

Snijders, T. A. B., 1986: Interstation correlations and non- stationarity of Burkina Faso rainfall. J. Climate. Appl. Meteor., 25, 524 531.

Stern, R. D., Dennett, M. D., Garbutt, D. J., 1981: The start of the rains in West Africa. J. Climate., 1, 59 68.

Stern, R. D., Dennett, M. D., Dale, I. C., 1982: Methods for analysing daily rainfall measurements to give useful ag- ronomic results. 1. Direct methods. Exp. Agric., 18, 223 236.

Subbramayya, I., Bhanu Kumar, O. S. R. U., 1978: The onset and the northern limit of the South-West Monsoon over India. Met. Mag., 107, 37-49.

Sumner, G., 1988: Precipitation Process and Analysis. New York: John Wiley.

Van Bavel, C. H. M., 1953: A drought criterion and its application in evaluating drought incidence and hazard. Agron. J., 45, 167-172.

Wang, J. Y., 1967: Agricultural Meteorology. Agricultural Weather Information Service. San Jose, California.

Yap, W. C., 1973: The occurrence of wet and dry spells in Sungei Buloh, Selangor. Meteor. Magazine., 102, 102- 240.

Authors' addresses: S.I. Kamara, Department of Geogra- phy and Planning, University of New England, Australia; Dr. I. J. Jackson, Department of Geography, the Chinese Univer- sity of Hong Kong, Shatin, New Territories, Hong Kong.

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A new soil-moisture based classification of raindays and drydays …ousmane/print/Onset/Kamara... · 2010. 1. 6. · Leone, using a simple water balance model to estimate soil moisture