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Determinants of Adoption of Rainwater Harvesting Technology: The Case of Gursum District, East Hararghe Zone, Ethiopia

Received: 20 October 2016    Accepted: 07 November 2016    Published: 08 December 2017
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Abstract

This study aimed at identifying the determinants of Rainwater Harvesting (RWH) technology adoption for irrigation and farmers practice in water harvesting against drought in Gursum district, Eastern Hararghe zone. The specific objectives were assessing farmer's perception towards the RWH technology and determining the major factors affecting adoption of RWH technology by smallholder farmers in the study area. The data was collected from both primary and secondary sources. The primary data for this study was collected from 150 farmers through application of appropriate statistical procedures while secondary data was gathered from various sources like zonal and district Bureau of Agriculture and Rural Development and district of water bureau. This study has used multi-stage sampling technique in which both purposive and random sampling techniques were applied to select the required sampling units from the total population under study. Likert Scale was employed to measure the perception of respondents towards RWH technology, and binary logit model was used to analyse the factors that affect RWH technology. Both descriptive and econometric data analysis techniques were applied. Logistic regression estimation revealed that farm experience of household head, education level, family size, labor availability, distance to market, Total Tropical Livestock Unit (TTLU) perception and external support have significantly affected the RWH technology adoption decision of households in study area. The finding of this study indicated that any effort in promoting and adopting of RWH practice should recognize the socio-economic, technique, institutional, physical and psychological characteristics for better adoption of RWH technology. Taking the specific characteristics of farmers into account in introducing and promoting RWH may help policymakers to come up with projects that can easily accepted by farmers.

DOI 10.11648/j.ss.20170606.15
Published in Social Sciences (Volume 6, Issue 6, December 2017)
Page(s) 174-181
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Rainwater Harvesting, Binary Logit Model, Likert Scale, Adoption Determinants, Gursum

References
[1] Alamneh, D. 2003. Integrated Natural Resource Management to Enhance Food Security: The case for community based approaches in Ethiopia. Working paper No. 16 Food and Agriculture Organization of the United Nations, Rome.
[2] Amemiya T., 1981. Qualitative Response Models: A Survey. Journal of Economic Literature, 19: 48-53.
[3] Awlachew, S. B., Merrey, D. J., Kamara, A. B., Van Koppen, B., penning de Vries, F., Boelee, E., Makombe, G., 2005. Experiences and opportunities for promoting small-scale micro irrigation and rainwater harvesting for food security in Ethiopia. Colombo, Sri Lanka: IWMI. V. 86. (Working paper 98).
[4] Aziz Shikur and Tesfaye Beshah (2013), Analysis of influencing factors in adoption of rainwater harvesting technology to combat the ever changing climate variability in Lanfuro Woreda, Southern region, Ethiopia. Wudpecker Journal of Agricultural Research ISSN 2315-7259, Vol. 2(1), pp. 015 - 027, January 2013.
[5] FAO, 2006. Manual for participatory Rapid Diagnosis and Action Planning for Irrigated Agriculture. Rome. Italy.
[6] Gujarati, N., 1995. Basic Econometrics. Third Edition. McGraw-Hill, Inc. New York.
[7] Hosmer, D., and S. Lemeshew, 1989. Applied Logistic Regression. A Wiley-Inter Science Publication, New York.
[8] Jafer Mume and Aman Kemal (2014), Factor Affecting Rain-Water-Harvesting Technology Adoption and Farmers Practices against Drought and Water Shortage in Eastern Hararghe Low Land, Ethiopia. International Journal of Agricultural Science, Research and Technology in Extension and Education Systems (IJASRT in EESs) Available online on: www.ijasrt.com
[9] Kansana, H. S., Sharma, R. P., and Sharma, S. K., 1996. Knowledge and Adoption of Wheat Technologies among Contact and Non-contact farmers. Agricultural Science, Digest Karnal, 16:154-156.
[10] Maddala S., 1983. Limited Dependent and Qualitative Variables in Econometrics. Economic Society Monographs. Cambridge University Press, USA. 67p.
[11] Melaku Gorfu, 2005. Adoption and profitability of Kenyan Top Bar Hive Bee Keeping Technology: A study in Ambasel Woreda. Msc Thesis Alemaya Universty, Ethiopia.
[12] Mesfin Astatkie, 2005. Analysis of factors influencing adoption of Triticale (X-Tritcosecale Witmack) and its impact: M.sc Thesis. Alemaya University, Ethiopia.
[13] Molla Tafere, 2005. Farmers’ Response and Willingness to Participate in Water Harvesting Practices: a case study in Dejen district/East Gojam zone M.Sc Thesis. Alemaya University, Alemaya.
[14] MoWR, 2010. Agricultural water Management National Situation Analysis. (AgWater Solutions) website http://awm-solutions.iwmi.org).
[15] Ngigi. N. Stphen, 2003. Rainwater harvesting for improved food security. Promising Technologies in the Great Horn of Africa Rainwater Partnership Kenya Rainwater Association.
[16] Pindyck, R., and C. Rubinfeld, 1981. Econometric Models and Econometric Forecasts. Second Edition. McGraw-Hill book Co. New York.
[17] Tesfaye Zegeye, 2001. Adoption of Improved Maize Technologies and Inorganic Fertilizer in North Western Ethiopia. EARO Research report. Addis Ababa, Ethiopia.
[18] UNEP, 2009. “Rainwater harvesting a life line for human being.” A report prepared for UNEP by Stockholm Environment Institute.
Author Information
  • Agricultural Extension Research Team, Fedis Agricultural Research Center, Harar, Ethiopia

  • Haramaya University School of Rural Development and Agricultural Extension, Haramaya, Ethiopia

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    Nasir Siraj, Fekadu Beyene. (2017). Determinants of Adoption of Rainwater Harvesting Technology: The Case of Gursum District, East Hararghe Zone, Ethiopia. Social Sciences, 6(6), 174-181. https://doi.org/10.11648/j.ss.20170606.15

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    Nasir Siraj; Fekadu Beyene. Determinants of Adoption of Rainwater Harvesting Technology: The Case of Gursum District, East Hararghe Zone, Ethiopia. Soc. Sci. 2017, 6(6), 174-181. doi: 10.11648/j.ss.20170606.15

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    AMA Style

    Nasir Siraj, Fekadu Beyene. Determinants of Adoption of Rainwater Harvesting Technology: The Case of Gursum District, East Hararghe Zone, Ethiopia. Soc Sci. 2017;6(6):174-181. doi: 10.11648/j.ss.20170606.15

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  • @article{10.11648/j.ss.20170606.15,
      author = {Nasir Siraj and Fekadu Beyene},
      title = {Determinants of Adoption of Rainwater Harvesting Technology: The Case of Gursum District, East Hararghe Zone, Ethiopia},
      journal = {Social Sciences},
      volume = {6},
      number = {6},
      pages = {174-181},
      doi = {10.11648/j.ss.20170606.15},
      url = {https://doi.org/10.11648/j.ss.20170606.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ss.20170606.15},
      abstract = {This study aimed at identifying the determinants of Rainwater Harvesting (RWH) technology adoption for irrigation and farmers practice in water harvesting against drought in Gursum district, Eastern Hararghe zone. The specific objectives were assessing farmer's perception towards the RWH technology and determining the major factors affecting adoption of RWH technology by smallholder farmers in the study area. The data was collected from both primary and secondary sources. The primary data for this study was collected from 150 farmers through application of appropriate statistical procedures while secondary data was gathered from various sources like zonal and district Bureau of Agriculture and Rural Development and district of water bureau. This study has used multi-stage sampling technique in which both purposive and random sampling techniques were applied to select the required sampling units from the total population under study. Likert Scale was employed to measure the perception of respondents towards RWH technology, and binary logit model was used to analyse the factors that affect RWH technology. Both descriptive and econometric data analysis techniques were applied. Logistic regression estimation revealed that farm experience of household head, education level, family size, labor availability, distance to market, Total Tropical Livestock Unit (TTLU) perception and external support have significantly affected the RWH technology adoption decision of households in study area. The finding of this study indicated that any effort in promoting and adopting of RWH practice should recognize the socio-economic, technique, institutional, physical and psychological characteristics for better adoption of RWH technology. Taking the specific characteristics of farmers into account in introducing and promoting RWH may help policymakers to come up with projects that can easily accepted by farmers.},
     year = {2017}
    }
    

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    AU  - Nasir Siraj
    AU  - Fekadu Beyene
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    AB  - This study aimed at identifying the determinants of Rainwater Harvesting (RWH) technology adoption for irrigation and farmers practice in water harvesting against drought in Gursum district, Eastern Hararghe zone. The specific objectives were assessing farmer's perception towards the RWH technology and determining the major factors affecting adoption of RWH technology by smallholder farmers in the study area. The data was collected from both primary and secondary sources. The primary data for this study was collected from 150 farmers through application of appropriate statistical procedures while secondary data was gathered from various sources like zonal and district Bureau of Agriculture and Rural Development and district of water bureau. This study has used multi-stage sampling technique in which both purposive and random sampling techniques were applied to select the required sampling units from the total population under study. Likert Scale was employed to measure the perception of respondents towards RWH technology, and binary logit model was used to analyse the factors that affect RWH technology. Both descriptive and econometric data analysis techniques were applied. Logistic regression estimation revealed that farm experience of household head, education level, family size, labor availability, distance to market, Total Tropical Livestock Unit (TTLU) perception and external support have significantly affected the RWH technology adoption decision of households in study area. The finding of this study indicated that any effort in promoting and adopting of RWH practice should recognize the socio-economic, technique, institutional, physical and psychological characteristics for better adoption of RWH technology. Taking the specific characteristics of farmers into account in introducing and promoting RWH may help policymakers to come up with projects that can easily accepted by farmers.
    VL  - 6
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