Smallholder Farmers Participation in Small-Scale Irrigation: The Case of Emba Alaje District, Tigray regional state, Ethiopia

DOI: https://doi.org/10.21203/rs.3.rs-1487938/v1

Abstract

The dependency on rain fed agriculture coupled with the erratic nature of rainfall is the major factors blamed for the poor performance of the agricultural sector of widespread food insecurity in the country. To solve this problem, use of the available water resources for irrigation development is the most promising option. This study was conducted to identify determinant factors of household’s participation in irrigation in the Emba Alaje district. In this study, multi-stage sampling technique was used to select 137 target respondents. The primary data were collected using an interview schedule and conducting focus group discussions and key informant interview. Various documents were reviewed to collect the secondary data. The probit model result indicates that participation in small-scale irrigation is positively and significantly influenced by livestock holding, total cultivated land size, and frequency of extension contact. Whereas, participation in small-scale irrigation is negatively influenced by age of the household head, distance to irrigation water and distance to farmer training center. participation in small-scale irrigation. To solve the problems and improve small-scale irrigation participation, the government, especially irrigation development office of the district should create awareness to farmers about utilization of irrigation scheme.  

1. Introduction

Agriculture is the mainstay of the Ethiopian economy in terms of income, employment and generation of export revenue, its contribution to GDP, although showing a slight decline over the years has remained very high, at approximately 44% (Fitsum et al., 2009).

Agriculture, the main source of livelihood in Ethiopian economy is mainly rain-fed and it depends on erratic and often insufficient rainfall despite its high-water potential. As a result, there are frequent failures of agricultural production and this forced many of the societies to lead their live dependent on assistance from different organizations for food (Abebe et al., 2011; Abebaw et al., 2015). In line with this, the agricultural practice in the country in general and in the study area in particular is rain-fed agriculture and seasonal.

To solve the problem, utilize all potential water resources must be used to feed the growing population (Hail, 2008). Agricultural irrigation has been regarded as a powerful factor for providing food security, protection against adverse drought conditions, increased prospects for employment and stable income, and greater opportunity for multiple cropping and crop diversification. Furthermore, (Hussain et al., undated) posit that access to reliable irrigation can enable farmers to adopt new technologies and intensify cultivation, leading to increased productivity, overall higher production, and greater returns from farming.

Given the importance of the irrigation, many governments have availed huge resources in establishing new schemes as well as repairing the existing ones to boost the socio-economic contribution of the agricultural sector (Todaro, 2012). Like other countries, the Ethiopian government gives more emphasis to small-scale irrigation as a means of achieving food self-sufficiency (MoFED, 2010). Small-scale irrigation schemes enable greater agricultural production than is achieved with rain-fed agriculture, help poor farmers overcome rainfall and water constraint by providing a sustainable supply of water for cultivation and livestock, strengthen the base for sustainable agriculture.

In Emba Alaje Woreda, Studies on determinant factors affecting the participation of smallholder farmers in small-scale irrigation are very limited. A few studies had been done in the area regarding on determinant factors affecting the participation of smallholder farmers in small-scale irrigation. For instance, A study conducted by Asayehegn et al. (2011), on the effect of small-scale irrigation on the income of farm households in Laelay Maichew, Tigray focus on technical aspects of irrigation schemes and very little is known for the socio-economic factors that have implications on irrigation participation.

Therefore, this study aims to fill this research gap by studying the determinant factors affecting the participation of smallholder farmers in small-scale irrigation. This may encourage the farmers to participate in irrigation and utilize water resource on their farming to boost their production directly.

2. Research Methodology

2.1. Description of the study area

2.1.1. Location

This study is conducted in Emba Alaje district located, in the Southern Zone of Tigray regional state. It is about 85Km far from the capital city of Tigray Regional State, Mekelle. It has 20 rural and 1urban Tabias. It is a part of the Southern Zone and bordered on the south by Enda mehoni, on the southwest by the Amhara Region, on the north by south eastern Zone, and on the southeast by Raya Azebo. The administrative center of this district is Adi Shehu (EADARDB, 2019).

2.1.2. Agro-ecological condition

The study area has three agro-climatic zones such as Highland (dega), Mid Highland (woinadega) and Low land (kola) dominated by Highland (dega). The annual temperature ranges between30°c and45°c with an average of 37.5°c. The main rainy season extends from late June to early September. The distribution of rainfall is, however, with large variability, untimely and irregular in nature. The elevation significantly affects the climatic condition, vegetation coverage, resource distribution, human settlement and agricultural practice (EADARDB, 2019).

2.2. Sampling technique and sample size determination

The study adopted both survey design and a multi stage sampling technique. Purposive sampling technique was used to select the study area (Emba Alaje district) due its implementation of small-scale irrigation scheme. Then, out of the total 21 kebelles found within the woreda, two kebeles (Ayba and Atsela) was purposively selected mainly based on the current practice and potential for irrigation, and their accessibility in terms of road. Then, to select the representative respondents from each two kebelles, lists of all farmers in the two kebelles were obtained and stratified into two: irrigation users and non- users. Finally, a total of 137 sample household (67 irrigation users and 70 non users) are selected from the list by simple random sampling procedure.

To determine the required sample size, the study was employed a formula developed by Yamane (1967) at 95% confidence level, 8.5% margin of errors because of limit of financial and difficulty to manage large sample size.

Where:

n = sample size for the study (137)

N = total number of household head (3281)

e = margin of errors at 8.5%.

2.3. Data Source and Methods of Data Collection

Both primary and secondary data sources were used. To generate the required primary data from different primary sources, research tools such as household survey questionnaires, key informant interview, focus group discussions and were employed. The questionnaire was first prepared in English and later translated into the local language (Tigrigna), so that the respondents can easily understand the questions. In addition to the structured survey schedule, seven key informant interviews those who have more knowledge about the area, which include elders, experts from agricultural office and development agents working in the kebele were conducted by the researcher to obtain additional information on the determinants of use of small-scale irrigation.

2.4. Methods of data analysis

2.4.1. Descriptive Analysis

Descriptive statistics such as, frequency, mean, maximum and minimum, percentage and standard deviation were employed to analyze the quantitative data. As inferential statistics such as, chi square was used to identify the associations between categorical variables while independent t- test was used to compare mean differences between two groups across the study variable.

In this study, participation to small-scale irrigation status is a dichotomous variable (1 = irrigation participant and 0 = non-participant). Hence, probit model guarantee that the estimated probabilities lie in the ranges between 0 to 1(Pindyck and Rubinfeld, 1981). So in this study probit model method was employed.

The probit model relates the probability of occurrence P of the outcome counted by Y to the predictor variables X. The model takes the form

P (X) =Φ (β0 + β1 X1 + β2 X2 +………. + βkXn)

Where Φ (Z) is the standard normal cumulative distribution function

The Probit model stands for cumulative normal probability function as below.

Y = β0 + β1(X1) +β2(X2) +………+ βn (Xn) +εi

Where: Y is the probability of farmer’s participation on small-scale irrigation

β is the parameters that are estimated by maximum likelihood

X  i  is a vector of exogenous variables that explains the participation in small-scale irrigation (e.g. age of household head, sex of the household head, education, membership to an agricultural association, access to credit,).

εi: is the error term

3.1. Definition of Variables and Hypotheses setting

3.1.1. Dependent Variables

These are variable influenced by its independent variables that fully explained. For example, in this study, participation in small-scale irrigation is dependent variable which affected by the independent variable. It is dummy values of 1 for household use small scale irrigation and 0 otherwise. In this study, Irrigation user is a household who own, rented/shared in/out or gifted in the land for direct utilization while non-irrigation user is a household who have no access to irrigated land to involve in irrigation farming.

3.1.2. Independent (explanatory) Variables

The independent variables that were hypothesized to influence the household’s decision to participate in small-scale irrigation schemes are combined effects of various factors such as: demographic, socio-economic and institutional factors. Based on review of literatures on factors influencing participation in small-scale irrigation, the following potential explanatory variables are considered in this study. These are presented as follows:

Table 1:  Summary of Independent Variables and Hypothesis

S/No.

Name of Variables

Symbol

Variable Type

Hypothesis 

1

Age of Household Head

AGEHH

Continuous

+

2

Education Level of Household

EDUCHH

Dummy

+

3

Family Size

FAMIZ

Continuous

+

4

Size of Cultivated Land

TTLANSIZE

Continuous

+

5

Total Livestock Holding

TLU

Continuous

+

6

Off/Non-Farm Income 

OFF/NON

Continuous

_

7

Access to Credit Facility

ACCREDIT

Dummy

+

8

Access to Market Information

ACCMRKT

Dummy

+

9

Frequency of extension Contacts 

FREQEXTNCONT

Continuous

+

10

Distance to Farmer Training Center

DISFTC

Continuous

_

11

Distance to Water Sources

DISWARS

Continuous

_

12

Membership Cooperatives

MEMCOOP

Dummy

+

Source: Summery from Literature

3. Results And Discussion

3.1. Socio-economic and demographic characteristics of sample households

3.1.1. Distributions of Sample Households by Continuous Variables

The mean age of irrigation-user and non-irrigation user household head were found to be 41.8 and 40.4 years with the standard deviations of 8.59 and 10.29, respectively. According to the results, there was no significant difference in the mean age of the household heads between irrigation-user and non-irrigation user household. This indicates that, similar distribution of age between irrigation users and non-users. When we compare the average household sizes between irrigation users and non-users, average family size for irrigation-user is 4.65 (± 1.48) persons and 4.2 (± 1.47) persons for non- irrigation users. The t-test revealed that mean difference between the two groups with regarding family size is statistically significant at 10 percent significance level. This implies the household who has large family size can best utilize irrigation than those who do not have.

The mean land holding for users of irrigation is 1.57 (± 0.54) hectares and the corresponding figure of land holding for non-users of irrigation is 1.00(± 0.44) hectares. The t-test revealed that means difference between the two groups with regarding land holding sized is statistically significant at 1 percent significance level. The mean livestock holding in Tropical Livestock Unit (TLU) for the sample households is 2.49, where the minimum is 0.00 and the maximum is 20. Mean livestock holding for irrigation user household heads is 3.13 (± 1.19) TLU and mean livestock holding for non-users of irrigation is 1.87 (± .91) TLU (Table 3). The t-test result showed that the mean comparison of the two groups with regard to livestock holding is statistically significant at 1percent significance level. The average distance of irrigation users to village is 0.64(± 0.45) hrs.; the corresponding figure of non-user household is 1.87(± 0.85) hrs. The t-test result for mean difference of the two groups with regard to distance to the irrigation scheme is statistically significant at 1percent significance level.

 
Table 2

Distributions of Sample Household Head by Continuous Variables

Variables

Total

Irrigation-user

Non-irrigation user

  
 

Mean

Std.

Mean

Std.

Mean

Std.

t-value

p-value

Age

41.1

9.49

41.8

8.59

40.4

10.29

0.52

0.37

Family size

4.43

1.48

4.65

1.48

4.2

1.47

1.75

0.08*

Size of cultivated land

1.28

.56

1.57

.54

1.00

.44

6.70

0.0000***

Livestock holding

2.49

1.22

3.13

1.19

1.87

.91

6.94

0.0000***

Distance to water

1.27

.92

.64

.45

1.87

.85

-10.5

0.0000 ***

Frequency of extension contact

1.62

1.1

2.22

1.01

1.05

.89

7.13

0.0000***
Source: Own survey result, 2019 *, *** means significant at 10%, and 1% significance level respectively


3.1.2. Distributions of Sample Household Head by Categorical Variables

The survey result showed that out of the total 137 sampled households, 64.23% and 33.77% were male headed and female headed respectively. The result also indicated that 41(61.19%) and 26(38.81%) of irrigation user households and 47(67.14%) and 23(32.86%) of irrigation non-user households were male headed and female headed households respectively. This implies that sex distribution among irrigation users and non-users were similar.

The comparison by use of irrigation showed that 46 (68.66%) of irrigation users and 53 (75.71%) of non-users of irrigation are illiterate and 21(31.34%) of users and 17(24.29%) of non-users are literate in the study area. The chi-square test (χ2 = 0.85) shows that there is no significant relationship between use of irrigation and level of education.

The comparison by use of irrigation showed that 44 (65.67) users and 25 (35.71%) non-users take credit. From irrigation users of sample household heads, 34.33 percent of the sample respondents and from the non-user, 64.29 percent households said that they don’t take credit and complained for its high interest rate. The chi-square test result (χ2 = 12.28) indicated that there is statistically significant relationship between the use of irrigation and access to credit at 1 percent significance level.

According to the survey result 49 (73.13%) of users and 29(41.43%) of non-users get training and the corresponding figure that shows have no access to training of users and non-users is 18(26.87%) and 41(58.57%) respectively. There was statistically significant difference at 1 percent between irrigation users and non-users in terms of the distribution of households who received training on irrigation practice.

 
Table 3

Distributions of Sample Household Head by Categorical Variables

Variables

  

Total

Irrigation-user

Non-irrigation user

  
 

Category

N

%

N

%

N

%

χ2-value

P-value

Sex

male

88

64.23

41

61.19

47

67.14

0.52

0.468

Female

49

33.77

26

38.81

23

32.86

Education

Literate

38

27.74

21

31.34

17

24.29

0.85

0.356

illiterate

99

72.26

46

68.66

53

75.71

Access to training

Yes

29

41.3

49

73.13

29

41.43

14.03

0.000***

No

59

43.07

18

26.87

41

58.57

Access to credit

Yes

69

50.36

44

65.67

25

35.71

12.28

0.000***

No

68

49.64

23

34.33

45

64.29

Access to market

Information

Yes

104

75.91

62

92.54

42

60.00

19.82

0.000***

No

33

24.09

5

7.46

28

40.00
Source: Own survey result, 2019 **, *** means significant at 5 and 1% level respectively


3.2. Determinant Factors Affecting Farmer’s Participation on Small-scale Irrigation

Results presented in Table 7 below showed that the estimated model appears to perform well for the intended matching exercise. The likelihood ratio chi-square value 73.50 revealed that the overall fitness of the model was found significant at 1% significance level. This indicates the model’s estimate fit the data at an acceptable level. Moreover, the small value of Pseudo-R2 (0.77) showed that irrigation user households do not have much distinct characteristics over non-user households and as such finding a good match between irrigation user and non-user households becomes easier.

Out of the total 12 independent variables only six variables were significant such as, Households with large livestock holding, large cultivable land and, and frequency of extension contact were identified using probit regression found to have positive relationship and significantly affecting probability of participation in small-scale irrigation. However, age of the household, distance to FTC and irrigation water sources was found to influence participation in small-scale irrigation negatively and significantly.

Table 4: Probit Model for the Determinants of Participation in Small-scale Irrigation

Variable

dy/dx

Std. Err.

            z          

            P>z

Agehh

-.0379603

.01182

-3.21

0.001***

educlehh*   

.0467409

.28352

.16

0.8690

Famiz

.0804611

.05952

1.35

0.176

Ttlansize

.7467513

.18006

4.15

0.000***

Tlu

.2320531

.07712

3.01

0.003***

credit*   

.0896396

.19173

0.47

0.640 

Freqextncont

.2298971

.09145

2.51

0.012 **

Disftc

-.0135482

.00607

-2.23

0.026 **

Diswars

-.8531831

.15865

-5.38

0.000***

partsa~g*   

.2510201

.18769

1.34

0.181 

annino~t

.0000327

.00003

1.01

0.313

accmar~o*  

-.0121527

.22704

-0.05

0.957 

Number of obs.        =     137

Wald chi2(12)        =       73.50

Prob > chi2         =0.0000

Log pseudo likelihood = -21.494          

Pseudo R2            =0.7740

Source: Own survey result, 2019   **, *** means significant at 5% and 1% significance level respectively

Age of the Household Head (AGEHH)

Consistent with that of our prior expectation the age of household head influences the probability of participation in small-scale irrigation negatively and significant at 1% level of significance. The marginal effect of age indicated that as a farmer’s age increases by 1 year from the mean value, the probability of participation in small-scale irrigation decreased by 3.7 percent. This may be because the use of irrigation is labor intensive and exhaustive work that the older household heads cannot tolerate this challenge.

Distance of Residence from Irrigation Scheme (DISWARS)

Consistent with a priori expectation this variable influence small-scale irrigation participation decision negatively and statistically significant at 1% significance level and. The negative relationship tells us that when the household head’s residence is far from the irrigation scheme, the household heads have less participation in irrigation. The marginal effect of this variable shows that as the distance from the farmers’ residence to the water source increases by 1hour from the mean value, the probability of participation in small-scale irrigation decreases by 85.3 percentage points, keeping all other variables constant. The finding of this study is similar to the findings by Kinfe et al. (2012) that household’s residence to water sources is found to have a significant and negative relationship to the probability of participation in small scale irrigation.

Distance to Farmers Training Center (DISFTC)

as expected, coefficient of this variable has negative relationship with irrigation participation and it is statistically significant at 5% significance level. The marginal effect of this variable indicated that as the walking distance to the farmer training center from the residence increases by 1hour from the mean value, the probability of participation in small-scale irrigation decreases by 1.3 percent. This indicates that the longer the distance from home to the farmer training centers and/or development agent offices, the lower is the probability to start and use irrigation. This is consistent with Moll (2004, found that the farmer training center is a source of information for the Tibia resident.

Size of Cultivated Land (TTLANSIZE)

Consistent with a priori expectation farm size influences the probability of participate in small-scale irrigation positively and significant at 1% significance level. The marginal effect of this variable indicates that as the size of cultivated land increases by one hectare from the mean value, the probability of participation in small-scale irrigation increases by 74.6 percentage points, keeping all other variables constant. This means that households who have more land are more likely to participate in small-scale irrigation as compared to households who have less land. This result is consistent with the finding of Mohammed and Jema (2013) as well as Martey et al (2013) who also obtained that farm size influenced the household heads decision to participate in agricultural projects.

Livestock Holding (TLU)

Consistent with a priori expectation livestock holding influences the probability of participation in small-scale irrigation positively and significant at 1% level of significance. The marginal effect shows that as the number of livestock in tropical livestock unit increases by one unit from mean value, the probability to participate in small-scale irrigation increases by 23.2 percentage points, keeping all other variables constant. This relationship implies that household with more livestock possession might have the capacity to generate cash income to purchase input and could be able to take more risk associated with use of irrigation. The same result was reported by Desale (2008) and Yenetila (2007) that livestock holding has positive influence on participation decision in small-scale irrigation.

Frequency of Extension Contact (FREQEXTNCONT)

This variable is consistent with the original hypothesis it has positive association with irrigation participation and significant at 5% level of significance level. The marginal effect shows that as frequency of extension contact increases by one unit from mean value, the probability to participate in small-scale irrigation increases by 22 percentage points, keeping all other variables constant. The possible explanation is that development agents are the major sources of information, provides technical support, advice on use of the availability of technology, facilitate the use of input to farmers, encourage for extension package participation and other development issues for rural farmer which may have positive aggregated impact for enhancing production and productivities. This result is consistent with that of reported by Ransom et al.(2003) and Ouma, (2002).

4. Summary And Conclusion

This study examined the factors determining participation in small-scale irrigation by the farm households. The sample of 137 farm households selected by multi-stage sampling technique were used in the analysis. Descriptive results indicated that irrigation user and non-user households showed a statistically significant mean difference in terms of family size, cultivated land size, livestock holding, access to credit use, distance from irrigation water sources and frequency of extension contact.

The result of the probit model indicated that, Households with large livestock holding, large cultivable and, and frequency of extension contact found to have positively and significantly affected probability of farmers participation in small-scale irrigation. However, age of the household distance to FTC and irrigation water sources was found to influence participation in small-scale irrigation negatively and significantly.

To solve the problems and improve small-scale irrigation participation, the government, especially irrigation development office of the district should attempt to hamper factors that hinder participation in small-scale irrigation and enhance factors that initiates participation in small-scale irrigation identified in the study area.

Declarations

ACKNOWLEDGEMENTS

Let me use this opportunity to thank Mekelle University for offering me a scholarship to pursue my MSc study and NORAD project for granting and allowing me to do my thesis research project. I deeply appreciate the support of the Department of Rural Development and Agricultural Extension (RDAE) and Mekelle University for the institutional support to get the scholarship. 

 I am very gland to acknowledge the sample households and staff of Ayba and Atsela kebelles for their willingness and patience in responding to my questionnaire at the expenses of their invaluable time.        

Authors’ contribution

Moges Girmay and workie Sahlu both of them authors contribute in the following activities

References

  1. Abdi, E., & Teshome, G. (2015). The Impact of Boset-Fentalle Irrigation on the Income of Agro Pastoralist in Fentalle District of Oromia National Regional State, Ethiopia (Doctoral dissertation, Haramaya University).
  2. Abebaw Abiyu, Mesfin Tebeje and Ermias Mekonnen. 2015. Determinants of small-scale irrigation utilization by smallholder farmers in rift valley basin, Wolaita zone, Ethiopia. Journal of Natural Sciences Research. 5(21): 2224–3186.
  3. Abebe Ejigu, Bihon Kassa and Gebremedhin Yihdego. 2011. Determinants of land allocation to irrigation and its wealth effect: Evidence from northern Ethiopia. Journal of the Drylands, 4(2): 310–319.
  4. Agerie, N. (2013). Determinants of smallholder rural farm households’ participation in small scale irrigation and its effect on income in North Gondar zone: a cross-sectional approach (evidence from Dembia Woreda) (Doctoral dissertation, Mekelle University).
  5. Asayehegn, K., Yirga, C., & Rajan, S. (2011). Effect of small-scale irrigation on the income of rural farm households: The case of Laelay Maichew District, Central Tigray, Ethiopia. Journal of Stored Products and Postharvest Research, 2(10), 208–215.
  6. Awulachew, S. (2006, March). Improved agricultural water management: Assessment of constraints and opportunities for agricultural development in Ethiopia. In Best practices and technologies for small scale agricultural water management in Ethiopia. Proceedings of a MoARD/MoWR/USAID/IWMI Symposium and Exhibition held at Ghion Hotel, Addis Ababa, Ethiopia, 7–9 March, 2006. (p. 23).
  7. Haile T. 2008.Impact of irrigation development on poverty reduction in Northern Ethiopia (dissertation), National University of Ireland, Cork.
  8. Haji, J., & Jirane, A. (2015). Determinants of Use of Small-Scale Irrigation and its Effects on Household Food Security: The Case of Bako Tibe District, West Shoa, Ethiopia (Doctoral dissertation, Haramaya University).
  9. Kinfe Aseyehegn, Chilot Yirga and Sundar R. 2012. Effect of small-scale irrigation on the income of rural farm households: The Case of Laelay Maichew District, Central Tigray, Ethiopia. Journal of Agricultural Sciences, 7(1): 43–57.
  10. MOFED.2010. Trends and prospects for meeting MDGs by 2015, millennium Development goal report. [Internet].[Cited 2011 July 4]. Addis Ababa, Ethiopia. Available from: http//www.dagethiopia.org.
  11. Muez, H. (2014). The Impact of Small-Scale Irrigation on Rural household Food Security: The case of Emba Alaje woreda (Doctoral dissertation, Mekelle University).
  12. Pindyck,Robert S.and Rubinfeld, Daniel L. 1981.Econometric Models and Economic Forecasts.2 n dEd McGraw-Hill Book Co.New York.
  13. Yamane, T. 1967. Statistics: An Introductory Analysis, 2nd Edution. New York: Harper and Row.