Amercan Journal of Agrculture and Forestry 2017; 5(3): 49-59 http://www.scencepublshnggroup.com/j/ajaf do: 10.11648/j.ajaf.20170503.13 ISSN: 2330-8583 (Prnt); ISSN: 2330-8591 (Onlne) Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa Petros Woldemaram 1, Yshak Gecho 2, * 1 Department of Rural Development and Agrcultural Extenson, Wolata Sodo Unversty, Wolata Sodo, Ethopa 2 Department of Rural Development and Agrcultural Extenson, College of Agrculture, Wolata Sodo Unversty, Wolata Sodo, Ethopa Emal address: yshakgecho@yahoo.com (Y. Gecho) * Correspondng author To cte ths artcle: Petros Woldemaram, Yshak Gecho. Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa. Amercan Journal of Agrculture and Forestry. Vol. 5, No. 3, 2017, pp. 49-59. do: 10.11648/j.ajaf.20170503.13 Receved: February 9, 2017; Accepted: February 25, 2017; Publshed: Aprl 24, 2017 Abstract: Ths study was conducted at Boloso Sore dstrct of Southern Ethopa. The objectve of ths study was to dentfy determnants of Small-scale rrgaton use. A total of 104 farmers were randomly selected and ntervewed by usng semstructured questonnare. To collect the requred data several methods lke ntervew schedule, focus group dscussons and key nformant ntervews were used. Varous documents were revewed to collect the secondary data. Descrptve statstcs, nferental statstcs (ch-square and ndependent t-test) and econometrc model analyss were used to analyze quanttatve data. As the bnary logstc regresson model result ndcates, four varables were found to be sgnfcant namely tranng, land sze and labor whch had sgnfcant and postve effect on the use of rrgaton water use at less than 10% probablty level, whle, dstance from the rver had sgnfcant and negatve effect on the use of rrgaton water at 5% sgnfcant level. Governmental and non-governmental organzatons should gve emphass on provson of tranng to create awareness creaton and skll about rrgaton technologes and ncreases ther access to use rrgaton water n the study area. They also should gve emphass on ntensfyng agrcultural producton n order to enhance the productvty of lmted land. Therefore, to allevate these problems and mprove small-scale rrgaton utlzaton, woreda (dstrct) agrcultural and rural development offce and other concerned bodes should attempt to address those factors that hnder small-scale rrgaton utlzaton n the study area. Keywords: Use of Irrgaton, Bnary Logstc Model, Boloso Sore, Wolata 1. Introducton Ethopa has untapped resource bases for agrculture development. The major resource bases for agrculture development are land, dverse agro-ecology, water resources, bo-dversty and human resources. The agrculture sector has promsng opportuntes to transform tself from subsstence to a level of modern and commercal sector. Nevertheless, the sector faces several challenges to produce adequate food supply for domestc consumpton and export earnngs. Furthermore, the agrculture sector s largely dependent on ran fed producton and s domnated by smallholder farmng systems [1]. To address subsstence farmng problem, the economc performers desgned a natonal strategc plan n 1991, Agrcultural Development Led Industralzaton (ADLI) that gves focus on rrgaton, cooperatve socetes and agrcultural technologes to answer the food demand and brng socoeconomc development n the country. Small scale rrgaton development s one of the polces wthn ths strategy. Based on ths, the federal and the regonal governments assocated wth other nternatonal and local NGOs have sgnfcantly supported to rural farmers to partcpate and use rrgaton farmng. As a result, the rrgated farmland, rrgaton producton and the number of farmers who use rrgaton n the country have notably ncreased, up to 80%, between 1990 and 2010 [2]. Estmates showed that there s suffcent water n the country to develop about 4.5 mllon hectares of whch only about 0.16 mllon ha (5% of the potental) s actually rrgated land under full rrgaton n Ethopa [3]. However, rrgated agrculture has realzed only 5% of ts estmated potental and n terms of output t accounts for approxmately 3% of the total food crop producton [4].
50 PetrosWoldemaram and YshakGecho: Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa The development of small-scale rrgaton s also one of the major nterventon to ncrease agrcultural producton n the rural parts of a country. Ths helps farmers to overcome ranfall constrant by provdng a sustanable supply of water for cultvaton and lvestock producton [5]. Irrgaton development s beng suggested as a key strategy to mprove the agrcultural productvty and to encourage the economc development [6]. Irrgaton n Ethopa contrbutes to ncrease the farmers ncome, household reslence and bufferng lvelhoods aganst shocks and stresses by producng hgher value crops for sale at market and to harvest more than once per year. In turn, ths provded them to buld up ther assets, buy more food and non-food household tems, educate ther chldren, and renvest n further ncreasng ther producton by buyng farm nputs or lvestock. However, the benefts are very unevenly dstrbuted among households [7]. Irrgaton contrbutes to lvelhood mprovement through ncreased ncome, food securty, employment opportunty, socal needs fulfllment and poverty reducton. Increase n agrcultural producton through dversfcaton and ntensfcaton of crops grown, ncreased household ncome because of on/off/non-farm employment, source of anmal feed, mprovng human health due to balanced det and easy access and utlzaton for medcaton, sol and ecology degradaton preventon and asset ownershp are contrbutons of rrgaton [8]. Accordng to Hale [9], there are four nterrelated mechansms by whch rrgated agrculture can reduce poverty, through: () ncreasng producton and ncome, and reducton of food prces, that helps very poor households meet the basc needs and assocated wth mprovements n household overall economc welfare, () protectng aganst rsks of crop loss due to erratc, unrelable or nsuffcent ranwater supples, () promotng greater use of yeld enhancng farm nputs and (v) creaton of addtonal employment, whch together enables people to move out of the poverty cycle. In the same way, Zhou and others [10] mentoned that rrgaton contrbutes to agrcultural producton n two ways: ncreasng crop yelds, and enablng farmers to ncrease croppng ntensty and swtch to hgh-value crops. Therefore, rrgaton can be an ndspensable technologcal nterventon to ncrease household ncome. Irrgaton can beneft the poor specfcally through hgher producton, hgher yelds, lower rsks of crop falure, and hgher and all year round farm and non-farm employment [11]. Agrcultural producton n Ethopa s prmarly ran-fed, so t depends on erratc and often nsuffcent ranfall. As a result, there are frequent falures of agrcultural producton. Irrgaton has the potental to stablze agrcultural producton and mtgate the negatve mpacts of varable or nsuffcent ranfall. Irrgaton contrbutes to agrcultural producton through ncreasng crop yelds, and enablng farmers to ncrease croppng ntensty and swtch to hgh-value crops [10]. Even f Ethopa has a huge potental n terms of surface and ground water avalablty and land whch are n most cases sutable for rrgaton the adopton of small-scale rrgaton s n ts nfant stage. The major constrants that slow down the adopton of the sub-sector among others are predomnantly prmtve nature of the overall exstng producton system, shortage of agrcultural nputs and low level of user partcpaton n the development and management of rrgated agrculture, lmted traned manpower and nadequate extenson servces [12]. The current government has undertaken varous actvtes to expand rrgaton n the country. The country's strategy Agrcultural Development Led Industralzaton (ADLI) consders rrgaton development as a key nput for sustanable development. Thus, rrgaton development, partcularly small-scale rrgaton s planned to be accelerated [13]. Ethopa s beleved to have the potental of 5.1 mllon hectares of land that can be developed for rrgaton through pump, gravty, pressure, underground water, water harvestng and other mechansms [13]. In lne wth the development polcy of the country, the Zonal Government of Wolata s promotng rrgaton development so as to ncrease and stablze food producton n the zone. Accordng to wolata zone rrgaton development department [14] report, the total area cultvated for rrgaton n 2014 was 42,329 hectares and ts producton 4,952,493 quntals wth 169,316 benefcares partcpated on frst and second phase [14]. The study area Boloso Sore s endowed wth consderable and dverse natural resources, wth capacty to grow dverse annual crops. The alttude ranges from 1500 to 2300 m.a.s.l. The mean annual ranfall s 750 mm and ranges from 100 to 1400mm [15]. Therefore, the Woreda has a great potental for small-scale rrgaton. Accordng to WoADO for Boloso Sore, n 2014 a total of 3,784.3 hectares of land was covered wth rrgaton (rrgated) and a total of 582,782 Quntal of producton beneftng 15,137 Households. Therefore the objectve of ths study s to assess the contrbuton of smallscale rrgaton to household farm ncome. In the Boloso Sore Woreda (dstrct)the Government s mplementng dfferent agrcultural development program n order to acheve the food securty n rural households. Among these programs, rrgaton development s prmarly taken by the Government. In ths program, Government organzatons, nternatonal and local NGOs, mcro-fnance nsttutons, prvate sectors and farmers are nvolved at dfferent levels wth dfferent tasks whch are supply of nputs (fertlzer, mproved seeds, pestcdes, nsectcdes and farm equpments), access to credt and the others. But such nterventons are encounterng varous socal and techncal problems (lack of techncal person to mantan motor pump, mpurty of mproved seeds, non supply of nput on tme, unfarness of farmers demand and supply and lack of market access especally for vegetable crops ) that have challenged the strategy and mplementaton approaches [16]. However, the Woreda (study dstrct)lacks n-depth studes on dentfy the determnant factors that nfluence the use of rrgaton water. The program s also not well supported by complete research whch s able to examne the croppng practce and farm ncome varaton of rrgated and nonrrgated household n the Woreda. That s, t s not well
Amercan Journal of Agrculture and Forestry 2017; 5(3): 49-59 51 known the contrbuton of rrgaton on household farm ncome and to what extent the households usng rrgaton are better off than those who depend on ran-fed agrculture n the study area. Therefore, ths study was tred to fll these gaps by analyzng the determnant of rural households partcpaton n small-scale rrgaton and ts contrbuton on rural household ncome. 2. Methodology 2.1. Descrpton of the Study Area Boloso Sore, the study area,s found n Wolata Zone of Southern Ethopa. The Woreda s located about 29 km north from Sodo town and has an alttude 1800 masl. The woreda s located between 6005'0" and 7011'0"N Lattude and 3700'0"and 37050'0"E Longtude. The woreda (dstrct) covers an area of about 33,600 hectare. Admnstratvely, t s sub-dvded nto 29 rural kebeles (small admnstratve unts). It has an annual ran fall ranges from 600 mm-1330mm. The short rany season s extendng from February to Aprl. The mean annual maxmum and mnmum temperature of the area s 28.5 and 14.48co respectvely [17]. Based on tradtonal zonaton; the study area s dvded nto two agro-clmatc regons on the base of temperature and alttudes. Recently the study area s dvded nto two tradtonal clmatc zones such as Dega (hgh alttude) and Wona-Dega (md alttude). The alttude of the Degaagro-ecologcal Zone s ranges from 2300 to 2950 m.a.s.l. Mean monthly temperatures vary from 16 C, durng the coldest months and 26.5 C, durng the hottest (warmest) month. Average annual ranfall s also found 1,659 mm. The Wona-Dega, on the other hand, the alttude ranges between 1500-2300m asl [15]. 2.2. Samplng Technque and Sample Sze Determnaton In ths study a mult- stage samplng procedure was employed. In the frst stage, the study area selected purposvely as small-scale rrgaton practce s avalable n the Woreda. In the second stage, out of 11 rrgaton usng Kebeles fve Kebeles whch have hgh access of small-scale rrgaton were selected purposvely. In the thrd stage, samplng frame (complete vllage household lsts) was obtaned from each Kebeles admnstratve offce. In the fourth stage, the total households n the fve sample Kebeleswas stratfed nto the two strata (rrgaton water user and non-user households).in the ffth stage, smple random samplng technques was appled to select the sample unt from each strata at each kebele va probablty proportonate to sze procedure. From the total 4498 household found n fve samples Kebeles, 104 sample households were selected. Hence, sample sze of rrgaton user and non-user respondent households was 60 and 44 respectvely. The sample sze for ths study determnant by Yamane formula [18]. n= 1+() Where: n = Sample sze; N= Total number of households n the selected Kebeles; e = precson level or samplng of error 9.7% (0.097); n= 4498 1+4494(0.097) =104 2.3. Data Source and Methods of Collecton Both qualtatve and quanttatve data were collected from prmary and secondary sources. Prmary data for the study were collected from selected sample households, Focus Group Dscusson, and ntervew wth Key Informants (commttee members of water user's assocatons, peasant assocaton executve commttee members, Women development army, development agents and Woreda rrgaton development experts) and feld observatons. Secondary data were collected from wrtten documents from Woreda agrcultural development offce and from other publshed and unpublshed materals. A structured questonnare was desgned and pre-tested for household survey. The survey was to collect data related to household's demographc, socoeconomc characterstcs, farmng system, small scale rrgaton practce and marketng stuaton, the possble factors determnng the use of small scale rrgaton, dfferent actvtes and the contrbuton of rrgaton on household ncome. The developed structured questonnare was translated n to Amharc for the convenence of data collecton durng household survey. The secondary data was obtaned from publshed and unpublshed documents; CSA, governmental offce and non-governmental reports, agrcultural offce, books, Journals, research report and other sources lke webstes are also mportant secondary data sources. 2.4. Methods of Data Analyss The quanttatve data was coded and entered nto SPSSv16, then analyzed by usng descrptve statstcs such as frequency, mean, chart and percentage. The statstcal sgnfcance of the varables n the descrptve part was tested for both dummy and contnuous varables usng ch-square and t-test, respectvely. Econometrc Model: To dentfy the determnants that nfluence the use of rrgaton water, the bnary logstc regresson analyss was employed. It s selected because of the model relevance to deal wth dependent varables that are dchotomous n nature. The model asssts n estmatng the probablty of rrgaton water use status of a household that can take one of the two values, use of rrgaton and non use. Accordng to Gujarat [19], the functonal form of the logt model s presented as follows: Y 1 X ( 0 1 (1) + X) 1+ e β β P= E ( ) = P= E Y = X 1 1 e Z + Where P s a probablty of a th household beng use of
52 PetrosWoldemaram and YshakGecho: Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa rrgaton and ranges from 0 to 1; Z s a functonal form ofmexplanatory varables(x) whch s expressed as: Z = β 0 + m =1 β X, =1, 2, 3----------m (2) Where; β0s the ntercept and βare the slope parameters n the model. The slope tells how the log-odds n favor of a gven household usng rrgaton water status change as ndependent varables change. If P s the probablty of a household beng use of rrgaton, then 1- P ndcates the probablty of a gven household s non usng rrgaton water, whch can be gven as: 1 1-P = Z 1+ e Dvdng equaton (1) by equaton (3) and smplfyng gves Z e = 1 P P =1 + e 1+ e Equaton (4) ndcates the odds rato n favor/n terms of a gven household usng rrgaton water. It s the rato of the probablty that a household wll use rrgaton water to the probablty he wll not use. Lastly, the logt model s obtaned by takng the natural logarsm of equaton (4) as follows: Z Z (3) (4) P L = ln 1 P = β0 + β 1X (5) Where; P =the probablty that Y=1 (that a gven household s usng rrgaton water); 1-P =the probablty that Y=0 (that a gven household does not use rrgaton water); L=the natural log of the odds rato or logt; β =the slope, measures the change n L (logt) for a unt change n explanatory varables (X); P β 0=the ntercept. It s the value of the log odd rato, 1+ P, when X or explanatory varable s zero. Thus, f the stochastc dsturbance term (U) s taken nto consderaton the logt model becomes L = β0 + β 1X+U The Dependent Varable Use of Irrgaton Water (UIRRW): In ths study, the dependent varable s the use of rrgaton water. It s a dummy varable, 1 f a household used rrgaton and 0 otherwse. Table 1. The summary of ndependent varables, descrpton ther measurements and expected relatonshp wth dependent varable. No Independent Varables Varable Types Unts of Measurement Expected Relatonshp wth dependent varables 1 Land holdng sze Contnuous Hectare + 2. Agrcultural labor. Contnuous PE + 3. Educaton status Contnuous Grade + 4. Sex Dummy 0 and 1 + 5. Age Contnuous Year - 6. Farm dstance Contnuous Km - 7. Contact to DAs Contnuous No of contact + 8. Lvestock holdng sze Contnuous TLU + 9 Tranng Dummy 0 and 1 + 10 Number of Oxen Contnuous number + 11 Use of Credt Dummy 0 and 1 + 12 Membershp n Coop. Dummy 0 and 1 + 3. Results and Dscusson Ths secton presents and dscusses the results of the feld data that has been conducted to address specfc objectves of the study. The secton also descrbes three core ponts. These nclude the status of rrgaton practces; descrptve statstcs results of explanatory varables; nterpretaton and dscussons of model results. 3.1. The Status of Irrgaton Practces n the Study Area 3.1.1. Farmers Experence on Irrgaton Practce n the Study Area A Small-Scale Irrgaton practce n the Woreda (dstrct) s a recent hstory. However, the nformaton gathered from Focus group dscusson (FGD) partcpants revealed that n the area the Small-Scale Irrgaton practces begun a decade ago. Now a day, the Small-Scale Irrgaton practces n the area dramatcally expanded and the farmers croppng practces also changed from dependng on producton of feld crops nto mostly dependng on producton of vegetables especally cabbage, tomato and pepper. The expansons of Small-Scale Irrgaton practce also ncrease farmers croppng frequences, use of mproved farm nputs (mproved seeds and chemcal fertlzer) and also ncreased farm productvty. 3.1.2. Small-Scale Irrgaton Performance of the Study Area The study area has a great potental for small-scale rrgaton. Informaton gathered from Woreda farm and natural resource offce and water development offce ndcated that snce 2014 there were 3,784.3 hectares of land
Amercan Journal of Agrculture and Forestry 2017; 5(3): 49-59 53 was covered wth rrgaton (rrgated farm) and 582,782 Quntal of yeld was obtaned by 15,137 Households. So, rrgaton user farmers use water only from rver by three water dverson methods such as concrete water dverson from rver, tradtonal water dverson from rver and usng motorzed pumps water dverson from rver. Ths s because of most of water harvestng technologes are not functonal due to problem of farmers atttude especally on water harvestng technology whch was very low. 3.2. Descrptve Statstcal Result of Factors Affectng Irrgaton Use In ths secton, the sample households demographc, soco-economc and nsttutonal factors are dscussed so as to understand the characterstcs the study households. 3.2.1. Demographc Factors 1) Sex of the respondent In the study area sex determne the use of rrgaton water. The results presented n Table 2 shows that out of the total rrgaton user respondents 66% were males and 33% were females. From the total non-user respondents, about 34% were males and 67% were females. The proporton of males n the case of rrgaton user respondents was more than that of nonrrgaton user respondents. Male-headed households are n a better poston to use rrgaton than the female headed ones. Moreover, wth regard to farmng experence males are better than the female farmers. The lterature cted n Mesfn [20] ndcates that female-headed households have less access to mproved technologes, land and extenson than male headed household [21]. The Ch-square value also shows that, at 1% probablty level, sex of respondents had sgnfcant relatonshp wth the use of rrgaton water. Ths sgnfcance relatonshp shows that when the varaton n sex between two groups has ts own mplcatons on the use of rrgaton. Therefore, male farmers have better chance to use of rrgaton water. Table 2. Sex of the respondents. User Non-user Total Ch-square value Sex Female 9 33 18 67 27 100 Male 51 66 9 34 77 100 8.865 *** Source: Own feld survey 2016.P-value = 0.004***, Sgnfcant at 1% level. 2) Age of Respondents The survey results ndcates that from the total respondents 63.5% were aged ranges from 20-40 years old (Table 3). But out of the total rrgaton user respondents 63.3% were aged ranges from 20-40 years old whle from the total non-user 63.6% were aged ranges from 20-40 years old. The mean age of total respondents was 38.98. However, the mean age of rrgaton user respondents was 39.38 years old and non-user respondents was 38.43 years old. The t-value shows that the mean age of the two groups were not sgnfcantly dfferent. Other fndng ndcated that age has both postve and negatve relatonshp wth access to rrgaton water due to ts nonlnearty [22]. So, as the age ncreases, the demand for rrgaton technology would be expected to ncrease frst due to workng capacty and then after sometmes t decreases. It also affects households ncome postvely and then negatvely. Therefore, t would have an nverted U-shaped relatonshp n both cases. Table 3. Age of the respondents. Age category User Non-user Total 20 40 38 63.3 28 63.6 66 63.5 41 60 21 35 14 31.8 35 33.7 61 80 1 1.7 2 4.6 3 2.9 Mean 39.38 38.43 38.98 SD 9.71 10.64 10.07 t-value 0.474 Source: Own feld survey of 2016.P-value = 0.637 3.2.2. Soco-Economc Factors 1) Land Sze Land holdng plays great role n usng rrgaton water n the study area. The study revealed that land sze of rrgaton user respondents was greater than non-user respondents(table 4). The mean value of land holdng of total respondents was 0.512 hectare. But the average land sze of rrgaton user was 0.63 hectares whle t was only 0.35 hectares for non-user respondents. The t-value shows that there was sgnfcant mean dfference of the land holdng sze between rrgaton user and non-user respondents household. Ths sgnfcance mean varaton shows that the varaton n the land holdng sze between two groups has ts own mplcatons on the utlzaton of rrgaton water. Therefore, better land holder farmers have better chance to use rrgaton. If small land holdng, the only opton s ntensve producton or producng two to three tmes a year. Land holdng determnes the type and amount of producton n the context of small holders [9]. Therefore, t affects rrgaton water utlzaton decson postvely. Table 4. Land sze of the respondent households. Land sze User Non-user Total <0.5 28 46.7 39 88.6 67 64.4 0.51-1 28 46.7 5 11.4 33 31.7 1.1-1.5 4 6.7 - - 4 3.8 Mean 0.63 0.35 0.512 SD 0.35 0.24 0.339 t-value 4.48*** Source: Own feld survey of 2016.P-value = 0.000***, Sgnfcant at 1% level. 2) Oxen ownershp Lke n most parts of Ethopa, oxen are the engnes for agrcultural works n the study area. There s a symbolc relatonshp between crop producton and oxen ownershp n the mxed farmng system. Oxen provde manure and draught power to crop cultvaton, therefore used to boost crop producton. Teressa and Hedhues [23] reported that adopton of mproved technology s postvely nfluenced by oxen
54 PetrosWoldemaram and YshakGecho: Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa ownershp. Partcularly more oxen owner has more probablty to use rrgaton and ploughng more land on tme. Asthe result n the table 16 shows that out of the total respondents 48.1% have no oxen n ther household. However, out of the total user respondent 43.3% have 1-2 oxen. Whereas out of the total non-users 61.4 have no oxen. The mean for oxen ownershp of total respondents was 0.692. However, the mean for user s 0.883 whle the mean of nonuser 0.431 (Table 5). The t-value shows that there s sgnfcant mean dfference n the number of oxen owned between two groups. Therefore, ths sgnfcant mean dfference has ts own mplcaton on the use of rrgaton water. So, the respondents who have large number of oxen have better opportunty to use rrgaton. Table 5. Oxen ownershp of the respondents. User Non-user Total No oxen 23 38.3 27 61.4 50 48.1 1-2 26 43.3 15 34.1 41 39.4 3-5 11 18.3 2 4.5 13 12.5 Mean 0.883 0.431 0.692 SD 0.94 0.586 0.836 t-value 2.807*** Source: Own feld survey of 2016.P-value = 0.006***, Sgnfcant at 1% level. 3) Educaton Level of the Respondents Educaton s one of the mportant varables, whch ncreases farmer s ablty to acqure process and use nformaton relevant to use rrgaton technologes. As the results shown n table 6, about 51.9% attended prmary educaton whereas 37.5% not attended. However, out of the total user respondents 61.7% attended prmary educaton whle out of the total rrgaton non-user respondents 54.5% dd not attended prmary educaton. Wth respect to hgh school level educaton, rrgaton users also share hgh proporton than non-users. Generally, these fgures ndcate users have better educatonal background than non-users. The t-value shows that there was sgnfcant mean deference n the educaton level of respondents between two groups at 10% sgnfcant level. Ths sgnfcance mean dfference shows that the varaton n the educaton level of farmers between two groups has ts own mplcatons on the utlzaton of rrgaton water. Therefore, better educated farmers have better chance to use rrgaton because educaton equps ndvduals wth the necessary knowledge of how to make lvng. Lterate ndvduals are very ambtous to get nformaton and use t. As agrculture s a dynamc occupaton, the conservaton practces and agrcultural producton technologes are always comng up wth better knowledge. So f the household head s lterate he wll be very prone to accept extenson servces and rrgaton use ncludng any other ncome generatng actvtes. Prevous research results have also revealed that educaton would nfluence adopton postvely [24]. Table 6. Educaton level of the respondents. Educaton Level User Non-user Total Not attended 15 25 24 54.5 39 37.5 1-8 37 61.7 17 38.6 54 51.9 9-12 7 11.7 2 4.5 9 8.7 >12 1 1.7 1 2.3 2 1.9 Mean 5.32 2.66 4.19 SD 9.11 3.28 7.33 t-value 1.848* Source: Own feld survey of 2016.P-value =0.068*, Sgnfcant at 10% level. 4) Lvestock Holdng The survey results obtaned from respondents household n Table7 show that out of the overall respondent s majorty (91.3%) of respondents own a maxmum of 6 TLU. Out of the total rrgaton user (90%) of them have maxmum of 6 TLU whle smlarly 93.2% of non-user respondents have maxmum of 6 TLU. The rrgaton user respondents household mean lvestock holdng n TLU s 3.82 and that of non-user respondents household mean lvestock holdng n TLU s 3.75. The t-value shows that, there was no sgnfcant mean dfference of lvestock holdng n TLU between user and non-user. Table 7. Number of lvestock holdng n TLU by the respondents household. Lvestock Holdng User Non-user Total <6 54 90 41 93.2 95 91.3 >6 6 10 3 6.8 9 8.7 Mean 3.82 3.75 3.79 SD 1.79 1.64 1.72 t-value 0.19 Source: Own feld survey of 2016.P-value = 0.847 5) Agrcultural Labor The results n Table 8 show that from the total respondent households about 56.8% had agrcultural labor greater than 6 Persons days equvalent. However, the majorty 98.3% of rrgaton user respondents household had agrcultural labor greater than 6 persons days equvalent whle 93.2% of nonuser respondents household agrcultural labor between 4.1-6 person days equvalent. Whle, the mean of user respondents household agrcultural labor force was equal to 3.07 Person days equvalent and that of non-user respondents household was equal to 2.31 Person days equvalent. The t-value shows that at 1% sgnfcant level, there was sgnfcant mean dfference n agrcultural labor between user and non-user respondents household. Ths sgnfcance mean varaton shows that the varaton n agrcultural labor between two groups has ts own mplcatons on the utlzaton of rrgaton water. Therefore, farmers who have larger agrcultural labor sze have better chance to use rrgaton. Famly actve labor force has strong postve relatonshp wth household ncome [25].
Amercan Journal of Agrculture and Forestry 2017; 5(3): 49-59 55 Table 8. Agrcultural labor n person day s equvalent. Agrcultural Labor User Non-user Total 2.1 4 1 1.7 3 6.8 4 3.8 4.1 6 - - 41 93.2 41 39.4 >6 59 98.3 - - 59 56.8 Mean 3.07 2.31 2.75 SD 1.32 0.60 1.13 t-value 3.58*** Source: Own feld survey of 2016.P-value = 0.001***, Sgnfcant at 1% level. 3.2.3. Insttutonal Factors 1) Use of Credt The survey results n Table 9 show that n 2015/16 out of the total respondents, about 64.4% used credt. However, out of the total respondents, about 76.7% were rrgaton user respondents and 47.7% were non-user respondents use credt last year. The Ch-square value shows that there was sgnfcant relatonshp between the use of credt and rrgaton water use at 1% sgnfcant level. Ths sgnfcance relatonshp shows that the varaton n the credt use between two groups has ts own mplcatons on the utlzaton of rrgaton water. Those households, who have access to credt, have better possblty to use t and spend on actvtes they want. Ether they purchase agrcultural nput (mproved seed, fertlzer, rrgaton equpments, etc.,) or they purchase lvestock for resale after they fattened them. All these actvtes ncrease ncome of the household. Prevous research result reported by Tesfaye and Alemu [26] confrmed that access to credt postvely nfluence adopton of technology. The possble explanaton s that, those households who have access to credt became capable of usng rrgaton than those who have no access to credt.therefore, credt used farmers have better chance to use rrgaton than non-used. Use of credt Table 9. Use of credt by the respondents household n 2015/16. User Non-user Total Ch-square value No 14 23.3 23 52.3 37 35.6 Yes 46 76.7 21 47.7 67 64.4 9.27*** Source: Own feld survey 2016.P-value = 0.004***, Sgnfcant at 1% level. 2) Contact wth Agrcultural Development Agents Extenson agents provde crucal farmng nformaton n the study area especally n the applcaton of rrgaton water for farmng actvtes. The results n the Table 10 show that from the total respondents 47.1% of them have contact wth DA more than 5 tmes per month. However, out of the total users 73.3% contacted more than 5 tmes per month wth Development Agents whle (72.7%) of non-user respondents contacted 3-5 tme per month wth them n last croppng season. The mean contact of rrgaton user respondents household wth Agrcultural Development Agents was 3.75 tmes per month; whle t was only 1.13 tmes per month for non-user respondents. The t-value shows that at 1% sgnfcant level, there was sgnfcant mean dfference n number of contact wth Agrcultural Development Agents between user and non-user respondents. Therefore, farmers who had better contact wth DAs have better chance to use rrgaton. Other smlar studes also came up wth postve and sgnfcant relatonshp [22]. Table 10. Number of contact of the respondents household wth Agrcultural Development Agents per month. Contact User Non-user Total <2 15 25 7 15.9 22 21.2 3-5 1 1.7 32 72.7 33 31.7 >5 44 73.3 5 11.4 49 47.1 Mean 3.75 1.13 2.64 SD 2.69 1.15 2.51 t-value 6.04*** Source: Own feld survey of 2016.P-value = 0.000***, Sgnfcant at 1% level. 3) Attendng on Tranng The survey results obtaned from the respondents household n the Table 11 show that n 2015/16 from the total respondents, 61.6% of them attended tranng on rrgaton related practce. However, out of the total rrgaton user respondents more than half (70%) attended tranng on rrgaton related practce. However, from the total non-user respondents household, about 52.3% dd not attend tranng on rrgaton related practce. The Ch-square value shows that there was sgnfcant relatonshp between farmers partcpaton n tranng and use of rrgaton water at 1% probablty level. Ths sgnfcance relatonshp shows that the varaton n the attendng of tranng between two groups has ts own mplcatons on the utlzaton of rrgaton water. Therefore, better attended farmers have better chance to use rrgaton. Attended on tranng. Table 11. Farmers partcpaton on tranng program 2015/16. User Non-user Total Ch-square value No 18 30 23 52.3 41 39.4 Yes 42 70 21 47.7 63 61.6 24.934*** Source: Own feld survey 2016.P-value = 0.004***, Sgnfcant at 1% level. 4) Membershp n Cooperatves The survey results n Table 12 show that out of the total respondents about, 35.6% was member n cooperatve. However, comparng the two categores about 56.7% respondents from those users of rrgaton were member n cooperatve, whle only 37% from non-users were the member n cooperatve. The Ch-square value shows that there was sgnfcant relatonshp between the membershp n cooperatve and use of rrgaton at 10% sgnfcant level. Ths sgnfcance relatonshp shows that farmers who are member n cooperatve have more chance to use rrgaton.
56 PetrosWoldemaram and YshakGecho: Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa Table 12. Respondents membershp n cooperatves 2015/16. Ch-square User Non-user Total Membershp value No 34 43.3 33 75 67 64.4 Yes 26 56.7 11 25 37 35.6 3.72* Source: Own feld survey 2016.P-value = 0.064*, Sgnfcant at 10% level. 5) Farm Dstance from Rvers The survey result shows that out of the total respondents household 43.3% of the respondents s located <0.5Km away from the rver (Table 13). However, out of the total user respondents, about 73.3% found n farm dstance of<0.5km away from rvers. Whle from the total non-user respondents, about 56.8% respondents found n farm dstance of>1.5km from rvers. The mean of user respondents farm dstance from rvers s 0.46Km and the mean of non-user respondents farm dstance from rvers s 1.82Km. The t-value shows that, at 1% sgnfcant level there was sgnfcant dfference n mean farm dstance from rver between user and non-user household. Ths sgnfcance mean varaton shows that the varaton n dstance from rver between two groups has ts own mplcatons on the utlzaton of rrgaton water. Therefore, farmers farms near to the rver have better chance to use rrgaton. Hence, they can more lkely produce two to three tmes a year. For nstance, users have locaton advantage to explot hgher volume of rrgaton water than the tal-end groups [6]. Table 13. Respondents household farm dstance from Rvers (Km). Farm Dstance User Non-user Total <0.5 44 73.3 1 2.3 45 43.3 0.51-1 15 25 15 34.1 30 28.8 1.1-1.5 1 1.7 3 6.8 3 2.9 >1.5 - - 25 56.8 25 25 Mean 0.46 1.82 1.03 SD 0.29 0.91 0.921 t-value -10.86*** Source: Own feld survey of 2016.P-value = 0.000***, Sgnfcant at 1% level. 4.3. Bnary Logt Model Result of Irrgaton Use n the Study Area Farmers decson to use rrgaton s determned by varous, socoeconomc, agro-ecologcal and nsttutonal factors. Numerous lteratures ndcate a lot of explanatory varables, whch have sgnfcance nfluence on rrgaton use. In vew of ths, efforts were made to nclude varables found relevant n the model n order to try to learn the response of the farmers n the study area. In ths secton, selected explanatory varables were used to estmate the logstc regresson model to analyze the determnants of households behavor on rrgaton water use.a Logt model was ft to estmate the effects of the hypotheszed explanatory varables on the probabltes of beng rrgaton user or not. Before the estmaton of the model parameters, t was found mportant to look nto the problem of Multcolnearty or assocaton among dfferent selected explanatory varables. For ths case, the VIF were used to test the assocaton between contnuous explanatory varables. To avod serous problem of Multcolnearty, t s qute essental to omt the varable wth the VIF value exceeds 10 (ths wll happen f R 2 exceeds 0.90.e. hghly correlated) from the Logt analyss. Lkewse, the degree of assocaton among dscrete varables was measured wth contngency coeffcent test based on ch-square. The values of contngency ranges between 0 and 1, wth zero ndcatng no assocaton between the varables and values close to 1 ndcatng hgh degree of assocaton. Fnally, a set of 12 explanatory varables (8 contnuous and 4 dscrete) were ncluded n the logstc analyss. These varables were selected on the bass of theoretcal explanatons, personal observatons and the results of the survey studes. To determne the best subset of explanatory varables that are good predctors of the dependent varable, the logstc regresson was estmated usng the method of maxmum lkelhood estmaton, whch s avalable n statstcal software program (SPSS verson 16). All the above-mentoned varables were entered n a sngle step. The defnton and unt of measurement of the varables used n the model are presented n Table 1. The varous goodness of ft measures state that the model fts that data well. The value of Pearson ch-square test shows the overall goodness of ft the model s at less than 1% probablty level. Another measure of goodness of ft s based on a method that classfes the predcted value of the dependent varable, use of rrgaton, as 1 f used and 0 otherwse. Ths classfcaton s the result of cross-classfyng the outcome varable, y, wth a dchotomous varable whose values are derved from the estmated logstc probabltes. In ths approach, estmated probabltes are used to predct group membershp. They say that, f the model predcts group membershp accurately accordng to some crtera, then ths s thought to provde evdence that the model fts. The model explaned about 98.1% of the total varaton n the sample for use rrgaton. Correctly predcted fgures for users were about 100%; whle correctly predcted sample sze for nonusers were 95.5%. Table 14. The Bnary Logstc Regresson results of ndependent varables. Odds Varable Coef S.E Wald Sg rato DSWS -8.672 3.816 5.165.023**.00016 SEX(1) -3.442 2.163 2.531.112.032 Age.145.102 2.017.156 1.155 LANS 10.595 5.090 4.332.037** 3.9924 OX.074 1.330.003.956 1.077 Coop(1) -1.255 2.177.332.564.285 TLU.615.598 1.057.304 1.850 Labor 3.108 1.770 3.084.079* 22.374 CODA.012.338.001.972 1.012 TIAN(1) 3.559 2.110 2.847.092*.028 USCR(1) -.905 1.438.396.529.405 EDUL 1.416 1.072 1.743.187 4.120
Amercan Journal of Agrculture and Forestry 2017; 5(3): 49-59 57 Varable Coef S.E Wald Sg Odds rato Constant -12.137 8.146 2.220.136.00016 Correctly predcted user 100 Correctly predcted non user 95.5 Overall percentage 98.1 Ch-square value 122.333*** -2Loglkelhood 19.37 Sample sze 104 a. Varable(s) entered on step 1: DSWS, SEX, Age, LANS, OX, Coop, TLU, Labor, CODA, TIAN, USCR, EDUL. *, and ** represent sgnfcant at 10% and 5% level respectvely. Source: Computed from feld survey data, 2016 Among the 12 varables used n the model, 4 varables were found sgnfcantly nfluencng the use of rrgaton water at less than 10% probablty level (Table 14).wth respect to use rrgaton wth less than 10% of the probablty level whereas 2 varables were sgnfcant wth respect to use rrgaton wth less than 5% of the probablty level. These varables nclude Farm sze (LANS),Dstance from the rvers (DSWS), Agrcultural labor (Labor) and Tranng (TIAN) and whereas the rest 8 of the 12 explanatory varables were found to have no sgnfcant nfluence on use of rrgaton. The effect of the sgnfcant explanatory varables on use of rrgaton n study area s dscussed below: The agrcultural labor (Labor):Ths varable had sgnfcant and postve effect on the use of rrgaton water at 10% sgnfcant level. The model result ndcated that those households who wth large labor force had better chance to use rrgaton water. The odd rato also revealed that as the labor force n the household ncreases by 1 unt the probablty of usng rrgaton ncreases by 2237.4 tmes. The nformaton gathered from focus group dscuss (FGD) partcpants revealed that, n the study area, rrgaton s labor ntensve practce and t needs hgh labor for constructon of canals, dverson of water from rves and applcaton of water on the farm. Smlar study by Hodder [27] ndcated that rrgaton farmng s extremely labour ntensve. Tranng (TIAN):Ths had sgnfcant and postve effects on the use of rrgaton water at 10% sgnfcant level.as the result ndcates those farmers who partcpated n the tranng had more chance to use rrgaton water than non-traned. The result obtaned from key nformants ntervew revealed that n the study area the traned farmers easly understood the operaton and adopt mprove rrgaton technologes whch s ncrease ther access to use of rrgaton water through lftng wth rrgaton technologes (motorzed water pump) from the sources even f ther farm s not accessble to rrgate through gravty force. Ths may due to rrgaton users who get techncal advce and tranng or those are well aware of the advantage of agrcultural technologes and adopt new technologes. The value of the odds rato ndcates that partcpaton n rrgaton related tranng program ncreases the probablty of usng rrgaton by 2.8 percent. Ths result s consstent wth fndngs by [28]. The farm dstance from the rvers (DSWS): had sgnfcant and negatve effect on the use of rrgaton water at 5% sgnfcant level. The result ndcated that as dstance to the water sourse ncreases by 1Km the probablty of usng rrgaton water decrease by 0.01 percent. The model result ndcated that those households whose farm s located far from the rvers had less chance to use rrgaton water and vce versa. Because, n the study area the major water source for rrgaton s rvers. When the farm s far from man rrgaton canals whch was constructed from the rvers, t needs hgh labor, fnancal and tme costs to construct subcanals towards ndvdual farm and mnmze the chances to use rrgaton water.smlar study conducted by Abonesh [22] n whch the household heads that lve near the rrgaton scheme have more chance to use rrgaton water than those household heads who are far from rrgaton water consderng that households near the rrgaton scheme do not ncur addtonal costs of transportaton and travelng tme. Farm sze (FRMSZ): It was found that farm sze had postvely and sgnfcantly nfluenced the probablty of use of rrgaton at 5% sgnfcant level.ths result mples that farmers wth large farm sze are more lkely to use rrgaton than those farmers who have small land sze. As observed n study area farm sze s very mportant resource to use rrgaton, because farmers on ther small land grow dfferent crops, rear dfferent anmals, and thereby lkely to generate suffcent ncome, whch could help them to buy agrcultural nputs. The odds rato of 3.9924 for farm sze ndcates that, other thngs beng constant, the odds rato n favor of usng rrgaton ncreases by a factor of 399.24 as the farm sze ncreases by one hectare. The result of ths study confrms the earler fndngs of Nkonyaet and others [29]. 4. Conclusons and Recommendatons Ths study has dentfed key factors that nfluence use of rrgaton n the study area. Ths nsght s also useful to rethnk about the barrers of use of rrgaton.therefore, the result can be used by polcy makers to promote technologcal change that s drectly needed for the economc development of the country. In the study area one of man constrants for rrgaton nonuser respondents household are dstance from rvers and man rrgaton canals. These factors were negatvely and sgnfcantly affected the use of rrgaton water at 5% sgnfcant level. The major sources of rrgaton water n the study area are rvers. The avalablty of water from rvers s decreases durng dry season so t was not relable even for rrgaton users farm that located far dstance from the rvers. Moreover, n the study area there s an opportunty to use Shallow Well due to favorable agro-ecology and locaton. Some farmers n the study area have used Motorzed Water Pumps for rrgaton purposes and t creates access to them to use rrgaton water through lftng from water sources even f ther farms are not accessble to rrgate through gravty force. However, the access to use such equpment s lmted due to hgh purchasng, mantenance, fuel and hose cost. The Commttees have hgh responsblty to manage
58 PetrosWoldemaram and YshakGecho: Determnants of Small-Scale Irrgaton Use: The Case of Boloso Sore Dstrct, Wolata Zone, Southern Ethopa rrgaton water used from rvers. However, these commttees have not well functon ther responsbltes. Therefore, t was negatvely affects the far dstrbuton of rrgaton water for the users n sample Kebeles. Small-scale rrgaton s mportant development effort to ensure farm ncome f properly mplemented. Based on the emprcal fndngs reported n ths thess, the followng recommendatons are forwarded. a) Dstance from rvers had sgnfcant and negatve effect on the use of rrgaton water and the major sources of rrgaton water n the study area are rvers. It s recommended that government, NGO and other stakeholders should focus on constructon of new man rrgaton canals for farmers whose land s far from the rvers. Because t mnmzes dstance from rvers and man rrgaton canals, consequently, creates an opportunty to shft non-users to use rrgaton water n the study area. Therefore, n addton to rver water t s better to ntate farmers to develop and use water harvestng technology at (pond and sprng development) communty and household level and shallow well at household. It s lkely to be valuable for future rrgaton development. b) Tranng had sgnfcant and postve effect on the use of rrgaton water. Therefore, governmental and nongovernmental organzatons should gve emphass on provson of tranng about awareness creaton and operaton of rrgaton technologes for the farmers and that mproves farmers awareness and skll about rrgaton technologes and ncreases ther access to use rrgaton water n the study area. Tranng should be gven contnuously; otherwse, a one-tme tranng, an rregular and partal tranng cannot brng about a desred effect on the use of rrgaton. c) Agrcultural labor had sgnfcant and postve effect on the use of rrgaton water. Therefore, governmental and non-governmental organzatons should gve emphass on provson of credt for farmers and that mproves ther fnancal captal to purchase mproved equpments and rent labor and that fll the gap of famly labor shortage. Consequently, creates an opportunty to shft non-users to use rrgaton water n the study area. d) The results of ths study showed that sze of cultvated land s postvely and sgnfcantly nfluenced the probablty of use of rrgaton and t was one of the most constranng factors. The possblty of ts expanson mechansm s very dffcult n the study area due to the absence of bleak land. Thus, to mtgate the problem of cultvated land scarcty, the exstng land must be ntensvely used. For ths purpose, farmers should rather be encouraged to use ntensve agrcultural producton methods. In ths regard, the current effort of the government to promote small-scale rrgaton scheme and water harvestng technologes should be further expanded and strengthened n order to enhance farm households ncome level. e) Expandng the capacty of the mcro rrgaton users and creatng addtonal access through ntegrated water nvestment s mportant to ncrease agrcultural ncome and hence leads to mprove household s welfare. f) Addng to the qualty, expanson n ts quantty and dstrbuton, solvng or at least mtgatng the problems t faces, creatng awareness through tranng and extenson and expanson of credt servces are mportant factors to ncrease and mprove n qualty and amount of rrgaton, and results to ncrease ncome. g) Expandng the capacty of small-scale rrgaton agrculture and creatng addtonal access through ntegrated water nvestment s mportant to ncrease agrcultural producton and productvty whch leads to ncrease household s ncome. References [1] Mutsvangwa T and Doranall, K. 2006.Agrculture and Sustanable Development, Netherlands The Hague Unversty Press of KoroIrgaton Scheme Ars Zone. An MSc. Thess presented to Haramaya Unversty. Partcpaton. Adds Ababa: Forum for Socal Studes. Partcpaton. Adds Ababa: Forum for Socal Studes. [2] CSA (Central Statstcal Authorty), 2012.Agrcultural Sample Survey for Strategc Household Income. M.Sc. Thess. Alemaya Unversty, Ethopa: 61PP. [3] MoWE, (Mnstry of Water and Energy), 2011. Water and Development quarterly bulletn MWR: Adds Ababa. [4] MoFED (Mnstry of Fnance and Economc Development), 2007. Ethopa: Buldng on Progress: A Plan for Accelerated and Sustaned Development to End Poverty (PASDEP), Annual Progress Report 2005/06, Adds Abeba, Ethopa. [5] FAO (Food and Agrcultural Organzaton), 2003.Irrgaton n Afrca South of the Sahara.FAO Investment Center Techncal Paper 5. FAO: Rome. [6] Bhattara M, Sakthvadvel R, Hussen I., 2002. Irrgaton mpacts on ncome nequalty and poverty allevaton: Polcy ssues and optons for mproved management of rrgaton systems. Colombo, Sr Lanka: Internatonal Water Management Insttute (IWMI)Workng Paper No. 39. [7] Eshetu S, Belete B, Goshu D, Kassa B, Tamru D, Worku E, Lema Z, Delelegn A, Tucker J., 2010. Income dversfcaton through mproved rrgaton schemes: Evdence from Gorogutu dstrct, eastern Ethopa. [8] Asayehegn, K., 2012. Negatve mpact of small-scale rrgaton schemes: A case study of Central Tgray regonal state, Ethopa. Agrcultural Research and RevewsVol.1(3). Authorty of Ethopa: Annual Report, Adds Ababa, Ethopa. 2015. [9] Hale, T., 2008.Impact of rrgaton development on poverty reducton n Northern Ethopa. PhD thess, Natonal Unversty of Ireland, Cork. [10] Zhou, S. D., 2008. Factors affectng Chnese farmers' decsons to adopt a water-savng technology. Canadan Journal of Agrcultural Economcs 56 (1): 51-61. Dessalegne, R. (1999). Water Resources Development n Ethopa: Issues of Sustanablty.