Assessment of the Growing Season over the Unimodal Rainfall •.• 1., Regime Region of Tanzania
.11.8.8. Yohan, 2S. B.B. Oteng'i and 2C.B. Lukorito
1Tanzania Meteorological ~gen~y (TMA): D~r es .Sal~am, TCilnzania. 2 Dept. of Meteorology, Unrverslty of Nairobi, Nairobi, ~e':lya '.'
Abstract
Most part of Tanzania experiences unimodal rainfall. The characieristics ofrainfall such as'iis; ~n;et and cessation dates, dry and wet spell lengths, frequency and number of rainy days can be, used to determine the nature of growing season; length of growing season,end of season and itsgeog;'aphic~l v~riation both latitudinally and longitudinally. This justifies the assessment of the crop growing' season' under unimodal rainfall regime by this category in order., to '. adapt agricultural practices: which result in increased crop productivity. A water balance model was used to determine the end of growZ!zg season. The method ofSivakumar (2002) was used to ewiluate dry spell ofdifJer~nt lengths and their frequencies. The results show that on the mean the growing season starts in the first week.of ,December in most ofthe region except in Kigoma where the seasolJ starts earlfer'lin the secon"Cf week of November. The growing \, . ~ . season ends in April in most of the years. Similarly, the length of the season was found to range between 131 and 150 days in Mbeya and Songea in the south and Kigoma to the .west. hi Dodoma and !ri~ga, the growing season is as short as 93 to 97 days. Variations of starting. dates for the growing season with latitude were not statistically significant, but longitudinal variations in the mean' starting dates of the growing season revealed some statisticql Significance. These results form a good basis for explaining the
) characteristics ofthe growing season in the study region.' ' 2 1 0 2
d Key words: Agrometeorology, dry spells: growing season, Tanzania, unimodal rainfall e t a d ( disrupt the phenological stages of most crops r Introduction e
h resulting in low crop yields: The ef(ect of soil s etermination of. the effective crop growing i l mo!~ture stress to,a crop depends on the type of b season is important for rainfed agriculture. u D . crop. and. th,e phenological stage 'at "Which the P
The late planting, occurrence .of dry spells within e stress occurs. Long duration -varieties suffer less h a growing season and .early cessatio~ of rainfall t yield damage than short duration varieties as long y reduce the length of the sea~on '~which in turn b vegetative period could help .. theplant to'recover d 'reduces crop' Yields. These are the 'contributing e t when water stress is relieved. Late planting will n factors of crop failure and thus food insecurity in a frequently lead to water stress at the end of t~e r A study by (1998) meastem
g thecountry~ Loma~
e ~growing season, an~ the crop yield wilVhe
c Kenya shows that a delay in planting by 10 days ~.,.' ~ . ~ . ~ / '. \" n reduced (Lomas, 1998). :." , . / e leads to yield loss by of 20%. The variability of c i The best sov.\ing time depends largely on l
growing seasons· has caused freq~ent crop failure r
e . Climatic conditions, d .and forced society to live under' it '~e~4ITing threat n uniform temperature; the occUrrence .ofrainfall is u of famine. 'Prolonged dry spells in 'i002/0J (July y decisive (MwandosyJ etal., 1998). Alusa and June) left 320,000 households (nearly 2 million • I a Mushi (1974) and Alusa (1978) used pentad w e people) spread across 47 districts in 16 regions t rainfall to predict the thean onset and cessation of a highly food in insecure (FEWS Net, 2003). Dry G rains in East Africa. Stem et al. (1982) discussed t spells are becoming increasingly commonplace in e the use of daily rainfall to obtain the start and end n i our rainy seasons. Dry spells oc~urring at b of the season. In another study, Mhita and Nassib a different developmental stages cause water stress S (1988) used the wee~y rainfall to determine the y in crops. Long dry spells may cause stress and b d e c *Corresponding author Tanzania J.Agric.Sc. (2006) Vol.7 No.1, 16-26 " u d o r p e R Assessment of the growing season over 17. variability and the onset and end of. rains, in rainfall region include cereals (maize, millet, .and Tanzania. _ sorghum) and Jmlses(beans). Millet and sorghum Rainfall alone however; cannot.adequately are .grown in semi-arid areas of central Tanzania, detennine the wetness· or dryness of, a ,place where 0 .rainfall· amount .an4 distribution 'are' because in the tropics'rainfall is the most variable' limiting.for maize. J" of all climatic elements' (Idow and Gbuyiro;" 2002). Alusa and Gwage (1979) suggested the Tabie i :!.tat~tude~ longitude and-altitude of examination of dry spells in which a rainy (wet) J the stations, used in the study day is defined as a day with at least 5 mm of rainfall or with rain exceeding the. potential " evapotranspiration '(PET) for the region. Mahoo Station Latitude Longitude Altitude et al.. (1999). defines the start of the growing seaso~ as the first -perio'ci with running total of at (OS) (OE) (m) least 20 mm of rain -in four'consecutive days with Kigoma 4.86 29.63 885 at least two days being wet and no dry spell of more than 10 days in the next thirty days. The Tabora 5.08 32.83 1182 growing period for most crops continues beyond Dodoma 6.12 35.77 1120 the rainy season and, to a greater or lesser extent, crops often mature on moisture reserves stored in Iringa 7.3 35.2 1428 the soil profile. When the rains start early the Mbeya 8.93 33.47 1759 season is likely to be· longer, however, early rainfall (November) over unimodal areas is Mtwara 10.35 40.18 113' variable (Mhita and Nassib, 1988). Gommes and Songea 10.67 35.58 1036 Houssiau' (1982) developed the rainfall variability zones in Tanzania based on the risk of crop ) 2 failure. In their study, it was found that the length 1 0 of the growing season in the southern and western 2 d regions was between 130 - 160 days, and 90 days e t a for central region. d ( The main objective of this paper was to r e examine the characteristics of the growing season h s i l with a view to determine the start of the effective b u growing season over the unimodal rainfall regime P e of Tanzania. h t 10, y b d e Materials and Methods t i . - n a r g Stuc;ly1area and its cliinat~logy .. , . " L.ongi"de(degffts)E e c The study area covers the unimodal rainfall n e c regime as developed by Gommes and i I ~~gion Figure 1: Map of Tanzania showing rainfall l r Houssiau' (1982) as shown in Table 1 and Figure patterns (Modified from GQmmes and Houssiau, e d 1. Th~ seven stations together with their n 1982) u coorduiates and altitudes that were considered in y a this strldy area are presented in Table 1. In the Th~ '~limatt G "mvua iza ,,{~aka" start in December and end in Zone (ITCZ. Intrusion of moist westerly t e April (Mhita and Nassib, 1988). The unimodal airstreams over western Tanzania from the Congo n i b regime is experienced if! southern, south western, basin during southern summer brings seasonal a S central, and we.stern p~of the country. Centra\, rainfall over south - western and western parts of y b Tanzania is 'a semi - arid region with some, parts .' the country. Because the coastline and the' d e receiving annual rainf~fl of less than 400 mm. highland areas of Tanzania. are meridionally - c u The major annual crops: grown in the unimodal oriented, the winds are much more meridional d o r p e R 18 I.B.B. Y onah et al than zonal, and the main convergence zone suffers considerable analysis of dry spells, the method displacement and· distortion. used by Alusa Highland and Gwage (1979) was adopted, areas'act as highclevelheat sources where a dry spell and, wl1ich, continues' into combine with, orographic ,.lifting another month or dekad was of the . air, broke~ into' resulting in intensification two.' In this study the dry spell of. "rain producing' frequencies, mechanisms in mountain F; were deterinined by the fOTmula areas. Diurnally Sivakumar of modified climates (2002), given as in equation in East Africa are areas near 1. coastlines, "lakes, "escarpments.'~ and' fuountaih F~ N(Di) xIOO% ranges (Brown and Cocheine," 1973). The m modified pressure ...... gradient between tropical :.(Equation 1) , Indian, and- Atlan fic. where. N(Di) ()ceans, . 'ana 'enhanced' is the riiImb~r of occurrences of dry easterlies prevent' spell length D, the meridional branch of the fOr'exampl~ 5 days~~6 days, . .'.> 20 ITCZ from expandini~ days for the to the east over East Africa, prescribed period i, arid m is the' hence delaying the rainy number of years (seasons) season' onset (Camberlin' . of data. . . and Okooia, 2003). ,;.'. . N (0 ' ) = L f·· (Equation 2) and , j = I I J . Data source, handling and analysis Daily rainfall fij is the frequency of data covering a period of 21 years the length ,of dry spell of from 1980 period, i, for the monthj. to 2000 was obtained from the The spatial extent of d!y Tanzania spells lasting at least Meteorological Agency (TMA). f day, 3 days, ?days, 7 da~s, The 10 days, 15 days, analysis carried out included the following: and 20 days were presented as seasonal average cumulative • Determination of the frequency in Fig. 2. statistical For each station characteristics of rainfall dekadal analysis of dry spell over the unimodal frequency rainfall regime of length of 5 days or ioriger days ~nd 10 • Determination or longer was determined as percentages of the dry spell length and of their occurrences for the study frequency period. ". C' • Determination ) of the date of start of 2 the Start and 1 effective growing season end of the growing season 0 The 2 • start of the growing Determination of the length of the season was taken to be d effective the first e growing occasion after 1sl October t season (day 275) with a running total of at d • Latitudinal and longitudinal least 20 mm of rain' in ( variation four in the consecutive r mean start days with at least two days e of the effective growing season being wet h and no dry spell of s more than 10 days i in the next l thirtY days b beginning within the next five days. In u Long term seasonal rainfall analysis this case, a P rainy day was defined To as a day with e determine the characteristics of rainfall more thim 5.0 h over mm of rainfall. The t end of the the growing season, the long-term season y seasonal (cessation date) was de,termined based b rainfall on,. was analyzed using standard statistical the simple water d balance as was derived e formulae for by t the mean, standard deviation and the Dennett et al. (1983). Here n coefficient amount of water in the a of variation (CV). soil on day r i+.l is given by equation3. g ,//, e c \ ,~ : ; ,", n Lellgth and Wi+1 = Wi + Pi ,E ...... e frequency of dry spells (Equation 3) " c 1 '. i Daily l rainfall records were used to analyse r dry e spell length and frequency Where Pi is the dail~ rainfall d using the INSTAT and E is daily n program at threshold rainy evapotranspirati6n, tak~nhere "as u day of 5.0 5.0 mm.per day mm. y Monthly throughounhe and dekadal dry spell season. \Wi is the amount a frequencies of water, of in w various lengths including 1 t~e soil/on day i. \ Maximum e day, 2 days, 3 days'" water storage t · .. , cap,!-city of a and 20 the soil days were determined. A dekad .was was: taken to be 100 mm. The G defined as a period end of the season was t defined of 10' days between the lSI as the first day tha( e and th lh Wi becomes n 10 and the 11 th zero and remaiI}s i and 20 of each month, the' at zero for more b last dekad of than five days.' a the· month having 8, 9, 10 or 11 days' Values 'of rllyan, standard S (WMO, 1966). deviation, coefficienf y To enable mo?-thly ilJ:d dekadal of' variation (C.V) at b .' d e c u d o r p e R Assessment of the growing season over 19 robability levels of 20,50, arid 80 percent were critical',,· values . (' 'from Student, .i-test .were ~ISO determined for onset arid erid-ofthe season. . compared' with table values at 9.5%' cori'fident le~elaiJ.dnj2·degre:es:offreedoni: ' ,;. '. " ~ ,. ,:', ; ~ Length of the growing season. .. .. l,t·. .' t '. _.~ , Complete growing ·season duration .(le~gth)· was Results and Discussion: <,::';7. determined based on the method used' by Segele and Lamb (2003) where )he effective growing season is the period between onset and cessation Long term , s¢as~nal. rainfall dates. The cessation dates' derived from water characteristics balance, takes care of the dry spells that occur Means, standard deviations and coefficients, of during the seas~n. . . , j , variation (CV) were obtained from the long-term seasonal rainfall for the stations studied, that is, Latitudinal and longitudinal variation in Kigoma, Tabora, Mbeya, Songea, Iringa, Dodoma the mean start of the season, . and Mtwara (Table 2). Seasonal mean rainfall In determining the variation in the' mean start of ranged from 581 mm (Iringa) to '103~ mm the growing season with latitude and longitude,' (Songea). The lowest values (less than 600 mm) seven stations with their mean starting dates of were observed over Iringa (581 mm) and Dodoma the growing ~eason were arranged in ascending (589 mm), while other stations (Kigoma, Tabora, order of magnitudes of either latitudes or Mbeya, Songea, and Mtwara) receive mean longitudes. The correlation coefficients (r) rainfall of above 700 mm. Rainfall values at between the' mean' starting day (date) of the Iringa and Dodoma are quite iow in meeting the effective growing season (in Julian days) and seasonal water requirements for a'crop like maize, latitudes or lon~i.~des were determined using the which requires about 750 mm. This amount may standard PearsoJ?, correlation formula found in be sufficient for crops like millet and sorghum, most statistical' text books and in Okoola and which are tolerant to drought, although farmers in ) 2 Salano (2002). Positive correlation coefficients these areas prefer planting maize. The CV values 1 0 indicate late onset of the season with increase in in Table 2 represent the variability of the seasonal 2 d latitude southwards, while the negative values ofr rainfall. The CVs ranged from 14.3% (Kigoma) e t a indicate early onset with increasing latitude to 29.2% (Dodoma), while at Mtwara it was d ( southwards. For longitudes, the positive values of 26.4%. The high values of CV over the growing r e r, indicate the late onset of the season with period imply a high uncertainty in rainfall hence h s i l increasing longitudes, and vice-versa for negative in crop yields (Mahoo et aI., 1999). b u values of r. To determine if, the correlation P e coefficients were, statistically significant the· h ...... t •...•• _. , :l • ..., " , • y b Table 2:M~a~~; standl,lrd '~eviatiol1s,and ~o~'fficients of variation for long-term rainfall at stations d e , used in'the s'iudy"': -' ", ' , t n I a days, 15 days, and r , f •. . I .. g Station' ~goma Tab~ra Mbeya Songea Iringa Dodoma', Mtwara 20 days; and high e c 'frequency of short, n e c i 924.7 .743.7 1035.2 580.8 589.1 1008.3 duration of dry l Me,nl. / .. 94~,8 r spells that last at· e d least 1 day and 3 n Std. dfviation l3'?0 212.1 152.9 183.1 120.9 172.0 266.5 u Coefficient of days over central y I·, " a variatipn(%) 14) 22.9 20.6 1.7.7 20.8 29.2 , 26.4 Tanzania w e t ,~ y • (Dodoma). It also a , /, G shows that there is a general decrease of t The length and frequency of dry spells e frequency ~of ~ry spells of short durations (I day n Figure' 2 shows the spatial distribution of the i b or longer and 3 days or longer) from west to east, a average frequency of dry spells of various lengths S for example, from Kigoma (34.6) to Dodoma y (or durations) at threshold rainy day of 5.0 mm. b (23). Another increase for 1 and 3 days or longer The results from Figur~ 2 show low frequency of d e dry spells is from Dodoma (23) to Mtwara (28.7). c dry spells of long durat~on of at least 7 days, 10 u d o r p e R 20 I.B.B. Yonah etal the There is an increase of frequency of dry spells of other three (Iringa, Songea and, Tabora) stations. durations of 5, 7, and 10 days or more, from Some dry spells overlapped. .intwo or more Songea to Dodoma across the longitudes (Fig ..2). times. The results show that periods of Minimum average frequency of dry spells lastmg rainfall during early rainy season (November) are 20 days or more were 0.3 (Kigoma) and 0.6 frequently accompanied by ruy"spells which may (Mtwara), compared with maximu~ value. of 2 last 5 or 10 days or longer; During fIrst dekad of observed over Dodoma. The two statIOns Klgoma November, the stations e~perience betweep: 80 and Mtwara are located near water bodies, and 100% dry spells ~f 5 days or 10nger.Kig'?ma namely, Lake Tanganyika and the Indian Ocean, indicated t4e minimum record ,(5%) of dry spells while Dodoma in the central part of the country. that last either' ten days or longer during the fIrst These results reveal the association of high dekad of November. Increase 'of dry spells is frequency of short duration dry spells with Congo observed during third dekad of January and airmass and presence of water bodies in the February and early March as shown in Fig. 3. In vicinity. This is to be expected as convective Kigoma, 10 day or longer dry spell starts during activity may result in scattered rain resulting in the third dekad of February, Mbeya (fIrst and many short dry spells. On the other hand, dry second dekads of March), and during the fIrst spells of long duration are found in drier areas dekad of March for Dodoma, ~nd MtWara. These' (i.e. Dodoma). These obserVations are similar to widespread dry spells that influence the region what Alusa and Gwage (1979) observed over between January and March are' due' to, Mandera, Kenya and Dodoma Tanzania. Who modifIcation of the ITCZ, resulting from large hypothesized that the drier areas get their rains scale circulation systems rather than the local from more organized synoptic scale systems with influences. The study by Camberlin and Okoola a few short dry spells' occurrmg during the time of (2003) observed a late onset of long niins over', the rams. . East Africa during March. They suggested that the! SOr------, modifIed pressure gradient between the tropical - __ 1 d.a.y 0:1" m;Qft ----3&.y,o.r:a:a:.n: Indian and Atlantic. oceans, and' ) . ___ 1 JI;IOft enhanced 45 ______.:s ~ or 1'60" 4iYf or 2 ___ IOd.;,yil O)':trk)tt easterlies prevent 1 -"'-IS~or~~ the meridional _____ 2D d.a.)I'S or t'DDn branch of the 0 40 2 ITCZ from expanding to the east over East Africa, d 35 e hence delaying the onset for long rains. t While the a condition leads to late d (30 onset of long rams over ( g r bimodal regions of Tanzania, over unimodal e i 25 h region it leads to the s observed dry spells: i ~20 l b The high frequency of dry spells during u 115 the P onset of rainy season during November e 10 indicates h unreliability of early rains m the region' t y and therefore r~infall in that time, cannot be used, b for planting d but for land prepa:ratt~n. Where dry e Kigoma Teboro t MbeyG Servea Irt'va DocI;Imp. ....warD seedirIg is practiced, particularly n in semi-arid a r areas of central Tanzania replanting may be" g " Figure 2: Seasonal fr~quency distribution of , '/.' e required because these farly rains may be eno}lgh c the dry spells of various lengths n at a threshold to cause germination e rainy of t)1e see,ds. The crop may c 'day . i l die due to prolonged diy spells'°clurmg this stage. r of5.0 mm e These observations • are similar to what Mhita and d j' , , n Nassib (1988) 'obseryed on early rainfall u Figure 3 shows the occurrence of dry spells for y (November) 'over unimodal areas. H9wever, in a the period during the rainy season at four , t .' ',' w Kigoma where the dtiy spells are of lower e (Kigoma, t Dodoma', Mbeya and Mtwara) of the a frequency early rains m\ty lead to seven stations studied. long growtn~, G Similar results, but not season. t e presented here for lack of space, were obtained for n i b a S y b d e c u d o r p e R Assessment ~f the growing season over 21 120:~------~ 120,------. 110 - 5" days or longer 110 _. ------10 days or longer --+--5 days or longer 100 ~ 100 "'."·10 days or longer [) 90 iii 80 G g. 70 53 70 . => -1= 60 0- 'lil ~ 60 , , fr 50 QJ , . '. I ~, _ " . 5!' '50' ~ 40 ~ C':' .,c: 30 , ~ "'" 40 , '\ ,, .~'., ,', \.------'.- . ~ 20 ~ ~ ... ,; 0 ~ 30 --""" j . 10 : ~\ / .'" ~,,,'.\,'o,' " ... ~ .;.~ " '20 ...... ,.-_ ...... ,- 0 t-,,,.-.,.....,.,,,.I~TO___r_,__TO___r_,.:TO_l. ,,/ 10 .. "", ,.:' ...., ,. " o+-~~~~~~~~~~~~~~~~ Nov. Dec. Jan. Feb. March April Dekads and Months Figure: 3a. Kigoma Oekads and Months Figure: 3d. Mtwara 120 .------~ --t-- 5 days or longer 110 , '···.···10 days or longer Figure 3: The percentage mean dry spell frequency for (a) Kigoma, (b) Dodoma (c) ~ Mbeya and (d) Mtw~ra, :" Start and' end of the .growing~eason .~ 50 , 0 , , , ',I' In Kigoma the season may start as early a~ lat~ ' ~ . . '" .. .- 0' ) C:: , 40, " . October to as late as late Novymber, while th~ 2 , -'.. 1 , ~ 30 end of season is early April to e~rly May (Table 0 2 co Q) 2Q 3). In Tabora the season may start as early a~ the d "o e ::2 t third week of November to as late as fIrst week of 10 , 0 a 0-0 d January, and end as early as early April to as late ( o +-,,-.-..-.-.-,,-.-..-.-""-.~ r as early May. In Mbeya the season may start as e h s early as late November to as htte as the fourth i Nov. l b week of December, and ends at early April to as u Dekadsand Months P late as 'early May. In the other stations (except e h : -:' :.Dodoma, where. the season. starts after mid t ,,' ..Figure: 3 b. P9dQma ~ :.' .. '. y December) the results show that the season starts b 1 20 .---,----;------'-----::-._-, -:------:-:--:-""""':-----, d 110 :' early December to aslate as' ~arly February. The e ~ t 5 days or longer , .100 n ;I'. , ------·10 days ?r longer 'end of the season in Iringa and Dodoma is more a - 90 r certain and occurs in April, latest being the start g 1:>1 80 e 1 of the fourth, week of the month. The probable c ~ 70 n e g • .start of growing season varies from 18 days c 160/ i i l '" 50 (Mbeya and Songea) to 37 days (Mtwara) as r ~. e '! 'C ~O compared to the mean cessation dates, which vary d c:: n ~ 30 ., from 10 days (Dodoma) to 21 days (Mtwara) u ::0: y 20 (Table 3). The CVs for the mean start of the a /"-'.', ,i 10 .',; .. ~--.--'" .... w .' ~ -... ,' . season ranged from 3.3 to 5%, while that of the e 0 +-r-r--r_,__.-,....,---.---i--r-'l'--r-,----,---,.--,~ t I a i end of the season were between 9 and 17.2%. In G t Jan, semi-arid areas high eVs were' observed during e n -Oekads an,fMonths i the onset of the rains and during the cessation of b I . " a the ~ains(Ngana, 1990). The high coeffIcient of S Figure,: 3c. Mbeya , y vaii~tion implies 'high uncertainty 10 the' crop b 'yield (Hatibu i1Od,Mahoo, 20(0) . .' . -.'. d e " , c u d o r p e R 22 I.B.B. Yonah et at Table 3: Dates of onset and cessation of the growing season at the stations studied Onset dates at different probabilities Cessation dates at different probabilities Station 20% SO%. ' '- 80% s.d. 20% SO% 80% s.d Kigoma 30-0ct II-Nov .I-Dec , I-Apr 9-Apr 2-May .. 20 19 Tabora , .' 18-Nov I-Dec 'S-Jan 22 2-Apr 24-Apr 8-May 17 Mbeya 24-Nov 9-Dec 27-Dec 18 S-Apr .- I-May 8-May -- " IS Songea ,-- 3-Dec 18-Dec 31cDec 18 16-AjJf 27-Apr 7-May II lringa - ; I.'· . ' 6-Dec 31-Dec 2-Feb 33 I "Apr . S-Apr 2 I-Apr II , Dodoma ; ... 21-Dec 4-Jan 26-Jan 21 I-Apr .. S-Apr 23-Apr \0 Mtwara I-Dec , 13-Dec I-Feb 37 27-Apr 13-May 31-May 21 - Length of the growing season , southern Tanzania was between 130 - 160 'days, and The minimum lengths vary from 42 days'over ~verage of 90 days in central Tanzania. The~e v~lues Iringa to 94 days over Kigoma (Table 4). The ~y Gommes and Houssiau (1982) are comparable to maximum lengths vary from 126 days (Dodoma) what was observed in this study. The coefficients of to 219 days (Mtwara). However, on average the variation (c. V) for the length of the growing season growing season is longest over Kigoma 050 ranged from 16.1% (Mbeya) to 33.1% (Mtwara). days), while the central region (Dodonia) arid The high C. V values were observed for the length of ) Iringa experience the shortest growing season of the growing season over the central region and 2 1 0 93 and 97 days respectively:' A study: by Mtwara and to a great extent they contribute to crop 2 d Gommes and Houssiau (1982) found'.'that the failure and hence high uncertainty in crop yields. e t length of the growing seasori ..' a d • ; I . ( r e Table 4. Lengths of the growing seasons ~t various ~tations used in the,study h s , i .. l I: b ~ u Kigoma Tabora Mbeya ~ Songea Iringa'. Dodoma Mtwara P e h t Season 4.86°S 5.08°S 8.93°S 10.66°S 7.78°S 6.16°s 10.35°S y b d 29.63°E 32.83°E 33.46°E 35.48°E 35.7°E 35.76°E 40.18°E e t n a 94 85 90 76 42 47 48 .- r Min length g e Max length 196 175 181 169 145 126 219 c n e c i Mean 150 134 '139 131 97 93 137 l \ r e d Std. deviation 25 27:8 .22. 22 29 1~ \ 45 n " u I. , 16.7 y C.V(%) 20.7 16.1, 17.1 30.2 ,20.8 33.1 a / I w e t \ a G Length of the season,and the critical periods of JaIlUary, and second and third dekads of t e n for crop water stress ' February; when the crop is at late vegetative and i b Dekadal niinfall distribution over Kigonla (Fig. reproductive stages. Dekadal rainfall distribution a S Aa) is above 'maximum over Tabora is above 50 mm with a maximum of y 40~·.mffi.~iih'- a of~7b.nllp. b dUring the thiid dtikid of Nov~inber.Ralnf~ll.~t 80 mm during the second dekad of December d e c Kigoma goes belo~4() rillii dUring the third dekad (Fig. 4b). Rainfall at Tabora goes below 50 mm u d o r p e R Assessment of the growing season over 23 during the fIrst dekad of January, and second and 80 third dekads of; February, 'when the crop is at 70 vegetative and reproductive growth stages, thereby affecting' its growth. Mbeya has high 60 rainfall between 60 - 70 mm per dekad during the s' 50 -5, period between the second dekad of December 40 and February, and third dekad of March (Fig.4c), ~ 'OJ" Low values, between 40 - 55 mm per dekad, on I>: 30 the other hand, are common during the period 20 between -the third dekad of February and second 10 dekad of March. Hence a crop of maize can hardly grow successfully. For Songea (Fig. 4d), there is a distinct dekadal rainfall characteristic with 'January being the wettest month receiving or , Vegetative Reproductive Maturation Harvest about95 mmof rainfall per dekad. The dry period molwity (third dekad of February) ~during intermediate DekadfMonth and phenological stages season receives between 60 aIidBO mm of rainfalL 130 days crop cycle , • 11:\·' .'; , \ Figure 4 (c): Mbeya 80,------~ 70 110 ,------, 100 90 80 's' 70 g 60 ~ 50 ) ~ 40 20 '" 2 1 30 0 10 20 2 d 10 e t a d ( r Vegel.ttive Reproductive M aturuion Harvest e DekadlMonth and phenological stages h malurity s i 130 days crop cycle l DekadIMonth and phenological stages b 130 days crop cyd. u Figure 4(a): Kigoma P e Figure (d): Songea h t y 90T------~--~--~--"~,~,~~~_, b d e 80 t , 'Figure 4: Rainfall distribution during different n 70 I a phenological stages 'of maize with crop cycle of r g '8"60 , .130 days for (a) Kigoma, (b) Tabora, (c) Mbeya e c n S ~O' and (d) 'Songea. Phenological phases are based e , c ~-' i . on fractional crop cycle;' vegetative phase l , :~ 40 // r (0.42), reproductive phase (0.33), and e .ct: ,}O d n 20 maturation phase (0.25). After maturation u phase the crop j' starts drying and can be y 10 a harVested (FAO; i986) , , w O,+-.-~,,_._T~~_,_,,_,_._._,_,_,," e t a G t e n i " , maturity b a S - DekadIMotith and phenological stages y b 130 days crop cycle ' d e c Figure 4 (b): Tabora u d o r p e R 24 ~ I.B.B. Yonah et a/ ~~------, its vegetative, rep.roductive, 'and 'early maturation stages.;The dry spell disrupts its growth cyde.· " I 50 ~ ':' 1'he observed, ~ decrease in 'rainfall ' as;~ciate~d with-high frequency of drJ"spells of, l;ngeF" durations, during' -reproductive~' stage ' (flowering 'l:mdgiain formation) for maize 'and millet/sorghum could lead into :yieldlreduction. 10 and hence' affect 'the' economyof:the 'farmers; ~' most of who_m'rdy on' crop~j;roduction for their T income.':Howeverj~iii "areas With lOng groWing seas~ns;"~ay~'150;days or :~more;, 'long duration.:~ maize 'varieties' :and' inillet/sorghum· could be-' Dekadlmonth and phenological stage groWn 'since they suffer less' yield ; damage than' 100 days crop cycle short 'duration varieties' asl6ng vegetative .. , 5 Figure (a) :Iringa period could help the plant' to recover when' water stress is relieved. Late planting will': , frequently lead to drought stress at the end: of; , the growing season, and the crop yield may be ~~------, reduced by 20% (Lomas, 1998). JO Latitudinal and longitudinal variations i,? the mean start of the season There was.. a positive corr~lition (r!=, 0.41) between the mean starting date of the season and latitude, though' ~ot signifIcant. Positive and ) signifIcant correlation (r = 0.83) was observed 2 10 1 between the mean start of the groWing season and 0 2 iongitude. This indicates that the variation in the d e t ~-:mean startof~he growing seasmris from north to a d ( south and from. west to east, witb early onset for r e st~tion~ to the north 'and western side of the h DekadIMonth and phenological stages s i region. This relationship is more' longitudinal than l 100 days crop cycle b latitudinal. For example, there is a tirne lag of 2 u Figure 5b: Dodoma P weeks between the mean start of the season over e th h t Kigoma (l4 November) and Tabora (151 y Figure 5: Rainfall distribution during different b _. December), and the season starts at least: one d phenological stages of millet/sorghum with crop e month later in other areas. , t cycle of 100 days for (a) Iringa and (b) Dodoma. n These results differ from' what' Kowal a r Phenological phases are based. on fnictiona~:~~op , g and Knabe (1972) observed ~ver northern e cycle; vegetative phase (0.42), reproductive phase c Nigeria, ~he}e there was it goodcorrelatipni{ = n e (0.33), and maturation phase ~ (0'.25). ' After c 0.88) between latitude\and mean start of the rains. i l maturation phase the crop starts drying and can be These results however, show the importance of r I I. ' e harvested (FAG, f986) d the westerly Wind regime (Congo airmass), which n Iringa and, Dodoma' exhibit similar u mak~s the ITCZ over the East Africa more active y rainfall 'patterns;' with the wet period receiving a during the rainy season. It was observed by w about 50 rom of rainfall per dekad (Fig. 5a and e Brown and Cocheme (1973) that the ITCZ over t a 5b). During the period between the second East Africa suffers considerable displilcerrient and G t dekad of February and fIrst dekad of March, e distortion due the m~ridion~L, pattern, of East n rainfall at Iringa is less than 40 rom per dekad. i African coastline and highlands, which cause b a The observation was experienced during the winds, to be more meridional than elsewhere in S y third dekad of January and February, and fIrst equatorial areas. b dekad of March when the millet/sorghum is at d e c u d o r p e R Assessment of the growing season over 25 ConClusion's" ' '.' " " Tropicali" Meteorology' MeetiiLg, Nairobi, .... ~ .! _ : I ~: __ ~_ I Kenya. 133-140 Pp.. ' . In most 9f the' areas of unimodal rainfall regime, dry 'spell fieqi.i~n~y is higher during the period BrowiL,-L.H. and:J,.Cocheme. ;1973. A study of cloSe• "'}to' onset (., . I'·and towards the end of- the • season. L' J.the . agroClirilatology~- of: the highlandS of The ,mean start of the growing season is the fIrst '~ Eastern, Africa .. ~JAOIWMO Int!!ragt;ncy ..: ':J>roject ,on "Agroclimatology, 'TecIul'., Note week of the month of December for all station~ ,_ 'No., 125. WMO, Geneva;'. Switzerland. except Kigoma where th~ growing se'ason starts a' bit earlier in the second week ofNoveITiber.~The WMONo. 339: 5-14Pp. gro~ng; Season ends in April in most of the years. The decrease in rainfall during' iiliernlediate Carriberlin,:,P: and R:E. Okoola. 2003~ The onset arid cessation~of the long rains in East Africa season (February and March) when the. crop is a~ reproductive and, matuiation phenologic~i phas~i; and' their, interannual variability. Theoretical usually lead' to reduced yit';lds, The' va'dation in ;0' arid Applied Climatology. Spring-Verlag, the'mean start -of' tb6'- growing' season ~ls- ,from Austria. 75:43"54. • l'\.. ~ ~ ,. - . '-,. , - , - north to south and fi6p.\ w~st to 'east, with early onset for stations to the north' arid western side of Dennett, M.D., Rodgers, J.A. and R.D. Stern. 1983. Independence of rainfalls through the the region, though the relationship IS more longitudinal thari iatitudinaL rainy season and the implications for the estimation of rainfall probabilities. Journal of Climatology 3: 375-384. Ac~owledgements FAO, 1986. Early agrometeorological crop yield Weare grateful to the Department of assessment, FAG Plant Production and Meteoroiogy, University of Nairobi, for the Protection Paper, No. 73. FAO, Rome. ) technical support and use of library facilities. We 2 1 wish ·to' extend our sincere appreciation to the FEWS Net. 2003. Tanzania Food Securi~ report. 0 2 sponsor, the TaAzania Meteorological Agency Famine Early Warning Systems Network d e t (TMA) for providing financial support and (FEWS Net). November 14, 2003. Food and a d Early Warning System Network (FEWS ( meteorological data used in this study. r Net). Dar es Salaam, Tanzania. e h s i l b References Gommes, R.A. and M. Houssiau. 1982. Rainfall u P variabili~, types of growing seasons and e h Alusa, A.L. 1978. A Note on the Onset of the cereal yields in Tanzania. Proc. of the Tech. t y Rains in East Africa. East African Institute Conf. on Climate in Africa. WMO/OMM b d for Meteorological Training and Research Publication no. 596: 312-324. e t n Nairobi. Research Report no. 3/78. 1-18Pp. a r Hatibu, N. and H.F. Mahoo. (Edn). 2000. g e c Alusa, IA.L. and P.M. Gwage. 1979. The Rainwater Harvesting for Natural Resources n e ocyurrence of dry spells during the East Management. A Planning Guide for c i l Africa"n long rains. In: Castelino, J.B. and Tanzania. Regional Land Management Unit r I e C.P .M. Khamala. (Eds). The, Role of Water (RELMA) Technical Handbook Series, d n in Development. Proceedings of no.22. RELMAISIDA, Nairobi, Kenya. u Re~ources th y thd 13 Annual Symposium of the East a I ' w African Academy, September 1977. Kenya Idow, O.S. and S.O. Gbuyiro. 2002. Agricultural e t a National Academy for Advanced Arts and Planning of Farm Operations in the Tropical G t Sciences. 21-35 Pp. Rainforest and Guinea Savanna Area of e n i Nigeria. J. African Meteorological Society b a Alusa, A.L. and M.T. Mushi. 1974. A study of 5(2): 1-9. 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