Basic Design Study Report on the Project for Rural Water Supply in Oromia Region in the Federal Democratic Republic of Ethiopia
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Districts of Ethiopia
Region District or Woredas Zone Remarks Afar Region Argobba Special Woreda -- Independent district/woredas Afar Region Afambo Zone 1 (Awsi Rasu) Afar Region Asayita Zone 1 (Awsi Rasu) Afar Region Chifra Zone 1 (Awsi Rasu) Afar Region Dubti Zone 1 (Awsi Rasu) Afar Region Elidar Zone 1 (Awsi Rasu) Afar Region Kori Zone 1 (Awsi Rasu) Afar Region Mille Zone 1 (Awsi Rasu) Afar Region Abala Zone 2 (Kilbet Rasu) Afar Region Afdera Zone 2 (Kilbet Rasu) Afar Region Berhale Zone 2 (Kilbet Rasu) Afar Region Dallol Zone 2 (Kilbet Rasu) Afar Region Erebti Zone 2 (Kilbet Rasu) Afar Region Koneba Zone 2 (Kilbet Rasu) Afar Region Megale Zone 2 (Kilbet Rasu) Afar Region Amibara Zone 3 (Gabi Rasu) Afar Region Awash Fentale Zone 3 (Gabi Rasu) Afar Region Bure Mudaytu Zone 3 (Gabi Rasu) Afar Region Dulecha Zone 3 (Gabi Rasu) Afar Region Gewane Zone 3 (Gabi Rasu) Afar Region Aura Zone 4 (Fantena Rasu) Afar Region Ewa Zone 4 (Fantena Rasu) Afar Region Gulina Zone 4 (Fantena Rasu) Afar Region Teru Zone 4 (Fantena Rasu) Afar Region Yalo Zone 4 (Fantena Rasu) Afar Region Dalifage (formerly known as Artuma) Zone 5 (Hari Rasu) Afar Region Dewe Zone 5 (Hari Rasu) Afar Region Hadele Ele (formerly known as Fursi) Zone 5 (Hari Rasu) Afar Region Simurobi Gele'alo Zone 5 (Hari Rasu) Afar Region Telalak Zone 5 (Hari Rasu) Amhara Region Achefer -- Defunct district/woredas Amhara Region Angolalla Terana Asagirt -- Defunct district/woredas Amhara Region Artuma Fursina Jile -- Defunct district/woredas Amhara Region Banja -- Defunct district/woredas Amhara Region Belessa -- -
Midterm Survey Protocol
Protocol for L10K Midterm Survey The Last 10 Kilometers Project JSI Research & Training Institute, Inc. Addis Ababa, Ethiopia October 2010 Contents Introduction ........................................................................................................................................................ 2 The Last Ten Kilometers Project ............................................................................................................ 3 Objective one activities cover all the L10K woredas: .......................................................................... 4 Activities for objectives two, three and four in selected woredas ...................................................... 5 The purpose of the midterm survey ....................................................................................................... 6 The midterm survey design ...................................................................................................................... 7 Annex 1: List of L10K woredas by region, implementation strategy, and implementing phase ......... 10 Annex 2: Maps.................................................................................................................................................. 11 Annex 3: Research questions with their corresponding study design ...................................................... 14 Annex 4: Baseline survey methodology ........................................................................................................ 15 Annex 5: L10K midterm survey -
Analysis of Saving Patterns by Rural Households in Guduru Districts of Oromia National Regional State, Ethiopia
Journal of Economics and Sustainable Development www.iiste.org ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) DOI: 10.7176/JESD Vol.10, No.3, 2019 Analysis of Saving Patterns by Rural Households in Guduru Districts of Oromia National Regional State, Ethiopia Agassa Gadassa 1 Adem Kedir 2* 1.Department of Statistics, College of Natural and computational Science, Ambo University P.O. Box 19, Ambo, Ethiopia 2.Department of Agro economics , College of Business and Economics, Arsi University, P.O. Box 193, Arsi Ethiopia Abstract Background : Saving level in Ethiopia is very low and little is known empirically about its patterns and determinants. Therefore, this study is aimed at analysis of saving pattern of rural households in Guduru districts. Methods : Primary data were collected from the two districts.196 respondents from Guduru districts using multistage sampling techniques. Results : The study showed that 35.20, 34.69 and 30.10 % of Guduru sample household saves in kind, in cash and both in kind and in cash respectively. Multinomial regression model revealed that social and religious expenditures, distance to market, and distance to financial institutions had negative and significant effect on cash saving of household while dependency ratio had negative and significant effect on both in kind and in cash saving also information access and age of household head had positive effect. Conclusion : The pattern of the nature of saving is an important factor in determining whether the saved amount is utilized for productive purpose or not. This study indicated that rural households’ areas mainly use physical forms of saving. However, this saving in physical form in study areas was not assessed by formal financial system of the country. -
Determinants of Loan Repayment Performance of Smallholder Farmers in Horro and Abay Choman Woredas of Horoguduru- Wollega Zone, Oromia Region, Ethiopia
Journal of Agricultural Economics and Rural Development Vol. 5(3), pp. 648-655, December, 2019. © www.premierpublishers.org, ISSN: 2167-0477 Research Article Determinants of Loan Repayment Performance of Smallholder Farmers in Horro and Abay Choman woredas of Horoguduru- Wollega Zone, Oromia Region, Ethiopia *1Amsalu File, 2Oliyad Sori 1Wollega University, The Campus’s Finance Head, P.O. Box 38, Ethiopia 2Wollega University, Department of Agricultural Economics, P.O. Box 38, Ethiopia Credit repayment is one of the dominant importance for viable financial institutions. This study was aimed to identify determinants of loan repayment capacity of smallholder farmers in Horro and Abay-Chomen Woredas. The study used primary data from a sample of formal credit borrower farmers in the two woredas through structured questionnaire. A total of 120 farm households were interviewed during data collection and secondary data were collected from different organizations. The logit model results indicated that a total of fourteen explanatory variables were included in the model of which six variables were found to be significant.; among these variables, family size and expenditure in social ceremonies negatively while, credit experience, livestock, extension contact and income from off-farm activities positively influenced the loan repayment performance of smallholder farmers in the study areas. Based on the result, the study recommended that the lending institution should give attention on loan supervision and management while the borrowers should give attention on generating alternative source of income to pay the loans which is vital as it provides information that would enable to undertake effective measures with the aim of improving loan repayment in the study area. -
Vulnerability Analysis of Smallholder
Tessema and Simane Ecological Processes (2019) 8:5 https://doi.org/10.1186/s13717-019-0159-7 RESEARCH Open Access Vulnerability analysis of smallholder farmers to climate variability and change: an agro- ecological system-based approach in the Fincha’a sub-basin of the upper Blue Nile Basin of Ethiopia Israel Tessema1,2* and Belay Simane1 Abstract Background: Ethiopia is frequently cited as a country that is highly vulnerable to climate variability and change. The country’s high vulnerability arises mostly from climate-sensitive agricultural sector that suffers a lot from risks associated with rainfall variability. The vulnerability factors (exposure, sensitivity, and adaptive capacity) of the agricultural livelihoods to climate variability and change differ across agro-ecological systems (AESs). Therefore, the aim of this study was to analyze AES-specific vulnerability of smallholder farmers to climate variability and change in the Fincha’a sub-basin. We surveyed 380 respondents from 4 AESs (highland, midland, wetland, and lowland) randomly selected. Furthermore, focus group discussion and key informant interviews were also performed to supplement and substantiate the quantitative data. Livelihood vulnerability index was employed to analyze the levels of smallholders’ agriculture vulnerability to climate variability and change. Data on socioeconomic and biophysical attribute were collected and combined into the indices and vulnerability score was calculated for each agro-ecological system. Results: Considerable variation was observed across the agro-ecological systems in profile, indicator, and the three livelihood vulnerability indices-Intergovernmental Panel on Climate Change dimensions (exposure, sensitivity, and adaptive capacity) of vulnerability. The lowland AES exhibited higher exposure, low adaptive capacity, and high vulnerability, while the midland AES demonstrated lower exposure, higher adaptive capacity, and lower vulnerability. -
Grain Market Research Project
Grain Market Research Project PROMOTING FERTILIZER USE IN ETHIOPIA: THE IMPLICATIONS OF IMPROVING GRAIN MARKET PERFORMANCE, INPUT MARKET EFFICIENCY, AND FARM MANAGEMENT Mulat Demeke Ali Said T.S. Jayne WORKING PAPER 5 GRAIN MARKET RESEARCH PROJECT MINISTRY OF ECONOMIC DEVELOPMENT AND COOPERATION ADDIS ABABA MARCH 1997 PROMOTING FERTILIZER USE IN ETHIOPIA: THE IMPLICATIONS OF IMPROVING GRAIN MARKET PERFORMANCE, INPUT MARKET EFFICIENCY, AND FARM MANAGEMENT MULAT DEMEKE ALI SAID T.S. JAYNE MARCH 1997 This is a revised and expanded version of a paper presented at the Grain Market Research Project Discussion Forum, November 8-9, 1996, Sodere, Ethiopia, sponsored by the Ministry of Economic Development and Cooperation, Government of Ethiopia. Mulat Demeke is Lecturer, Addis Ababa University, Ali Said is Research Scholar, Ministry of Economic Development and Cooperation; and T.S. Jayne is Visiting Associate Professor, Michigan State University. The authors thank Aklu Girgre, Daniel Molla, Asres Workneh, Steven Franzel, Valerie Kelly, and Jim Shaffer for comments on a previous draft. TABLE OF CONTENTS 1. BACKGROUND ...................................................... 1 2. THE PROFITABILITY OF FERTILIZER USE .............................. 7 2.1. Factors Influencing Fertilizer Use .................................. 7 2.2. Measuring the Profitability of Fertilizer .............................. 7 (a) The value-cost ratio (VCR)................................ 8 (b) The reservation price of fertilizer........................... 10 3. THE EFFECTS OF IMPROVING FERTILIZER MARKET .................... 14 3.1. Implications for Fertilizer Prices .................................. 14 3.2. The Impact on Fertilizer Profitability ............................... 21 4. THE IMPLICATIONS OF IMPROVING THE OUTPUT MARKET.............. 23 5. IMPROVING THE YIELD RESPONSE TO FERTILIZERS.................... 26 5.1. Constraints to Improved Yield Response ............................ 26 5.2. The Implications of Improving Output Response ...................... 31 5.3. -
Analysis of Productivity and Efficiency of Maize Production in Gardega-Jarte District of Ethiopia
World Journal of Agricultural Sciences 15 (3): 180-193, 2019 ISSN 1817-3047 © IDOSI Publications, 2019 DOI: 10.5829/idosi.wjas.2019.180.193 Analysis of Productivity and Efficiency of Maize Production in Gardega-Jarte District of Ethiopia 12Hika Wana and Afsaw Lemessa 1Wollega University, Department of Agricultural Economics, P.O. Box, 395, Nekempt, Ethiopia 2Gardega-Jarte, Agricultural Office, P.O. Box, Shambu, Ethiopia Abstract: The aim of the study was to estimate technical efficiency of smallholder farmers in maize production in case of Jardega Jarte districts with specific objectives to estimate the level of technical efficiency and to identify factors affecting technical efficiency in the study area. The study used cross-sectional data and the data were collected from sample representative respondents of 168 randomly selected farm households. Cobb-Douglas production function and the Stochastic Frontier Model were used to identify factors influencing productivity and efficiency. The hypotheses tests confirm that, the adequacy of Cobb-Douglas the appropriateness of using SFA the joint statistical significance of inefficiency effects; the appropriateness of using Half- normal and Exponential distribution for one sided error; and nature of the stochastic production function. The maximum likelihood parameter estimates showed that all input variables have positive and significant effect on production. The estimated Cob Douglas production function revealed that all inputs labor in hour, maize cultivated land, Dap, Urea, Seed, oxen have positive -
In Search of Shelter the Case of Hawassa, Ethiopia
In search of shelter The case of Hawassa, Ethiopia Emma Grant, Gemechu Desta, Yeraswork Admassie, Faraz Hassan, Sophie Stevens and Meheret Ayenew Working Paper Urban Keywords: January 2020 Urbanisation, Informal Settlements, Urban Poverty, Housing About the authors Emma Grant, senior expert, Social Development Direct Gemechu Desta, executive director, Econvalue Consult Yeraswork Admassie, former associate professor of sociology, Addis Ababa University Faraz Hassan, senior urban specialist, Social Development Direct Sophie Stevens, principal consultant, Social Development Direct Meheret Ayenew, senior public policy researcher Acknowledgements With special thanks to Kussia Bekele, senior civil society advisor and research assistant. All photos were taken by members of the Ethiopia research team. The research was funded by the UK Department for International Development’s East Africa Research Fund (EARF) and contributed to the EARF’s research programme: Shaping East African Cities as Systems to Work Better for All. This material has been funded by UK aid from the UK government. However, the views expressed do not necessarily reflect the UK government’s official policies. Produced by IIED’s Human Settlements group The Human Settlements Group works to reduce poverty and improve health and housing conditions in the urban centres of Africa, Asia and Latin America. It seeks to combine this with promoting good governance and more ecologically sustainable patterns of urban development and rural-urban linkages. About Econvalue Consult Econvalue Consult offers advanced policy research expertise on a range of social and economic topics. About Social Development Direct Social Development Direct (SDDirect) provides high-quality, innovative and expert social development assistance and research services. Published by IIED, January 2020 Grant, E, Desta, G, Admassie, Y, Hassan, F, Stevens, S and Ayenew, M (2019) In search of shelter: the case of Hawassa, Ethiopia. -
ETHIOPIA Selfhelpafrica.Org 2020-21 1 2020-21 Alemnesh Tereda, 28, and Marsenesh Lenina, 29, Injaffo Multi Barley Coop, Gumer
ETHIOPIA selfhelpafrica.org 2020-21 1 2020-21 Alemnesh Tereda, 28, and Marsenesh Lenina, 29, Injaffo Multi barley Coop, Gumer caling up agricultural production, improving nutrition Last year, the organisation was involved in implementing security, developing new enterprise and market close to a dozen development projects, all of which Sopportunities for farmers, strengthening community- are being undertaken in collaboration with local and/or based seed production and building climate resilience, are international partners. all key areas of Self Help Africa’s work in Ethiopia. ETHIOPIA PROJECT KEY Scaling up RuSACCOs Strengthening & Scaling up of rehabilitaion of degraded lands and enhancement of livelihoods in Lake Ziway catchment ERITREA Feed the Future Gondar Dairy for Development Stronger Together: Linking Primary Seed and Seep Cooperative Union Addis Ababa Climate-Smart Agriculture SOMALILAND Capacity Building of Farmer Butajira Training Centers Unleashing the productive ETHIOPIA capacity of poor people through Graduation Approach in Ethiopia Integrated Community Development SOMALIA Livelihood Enhancement: Working Inclusively for Transformation KENYA 2 Implementing Programme Programme Donor Total Budget Time Frame Partner Area Climate-Smart Irish Aid € 806,695 2015 SOS Sahel, SNNP region 01 Agriculture (CSA) Farm Africa, 2019 Vita MF: Scaling Up Irish League of € 420,000 2020 Zonal Departments of N/Shewa Zone of 02 Rural Savings and Credit international Finance & Economic Amhara, N/Shewa Credit Cooperatives Development 2022 Cooperation -
Oromia Region Administrative Map(As of 27 March 2013)
ETHIOPIA: Oromia Region Administrative Map (as of 27 March 2013) Amhara Gundo Meskel ! Amuru Dera Kelo ! Agemsa BENISHANGUL ! Jangir Ibantu ! ! Filikilik Hidabu GUMUZ Kiremu ! ! Wara AMHARA Haro ! Obera Jarte Gosha Dire ! ! Abote ! Tsiyon Jars!o ! Ejere Limu Ayana ! Kiremu Alibo ! Jardega Hose Tulu Miki Haro ! ! Kokofe Ababo Mana Mendi ! Gebre ! Gida ! Guracha ! ! Degem AFAR ! Gelila SomHbo oro Abay ! ! Sibu Kiltu Kewo Kere ! Biriti Degem DIRE DAWA Ayana ! ! Fiche Benguwa Chomen Dobi Abuna Ali ! K! ara ! Kuyu Debre Tsige ! Toba Guduru Dedu ! Doro ! ! Achane G/Be!ret Minare Debre ! Mendida Shambu Daleti ! Libanos Weberi Abe Chulute! Jemo ! Abichuna Kombolcha West Limu Hor!o ! Meta Yaya Gota Dongoro Kombolcha Ginde Kachisi Lefo ! Muke Turi Melka Chinaksen ! Gne'a ! N!ejo Fincha!-a Kembolcha R!obi ! Adda Gulele Rafu Jarso ! ! ! Wuchale ! Nopa ! Beret Mekoda Muger ! ! Wellega Nejo ! Goro Kulubi ! ! Funyan Debeka Boji Shikute Berga Jida ! Kombolcha Kober Guto Guduru ! !Duber Water Kersa Haro Jarso ! ! Debra ! ! Bira Gudetu ! Bila Seyo Chobi Kembibit Gutu Che!lenko ! ! Welenkombi Gorfo ! ! Begi Jarso Dirmeji Gida Bila Jimma ! Ketket Mulo ! Kersa Maya Bila Gola ! ! ! Sheno ! Kobo Alem Kondole ! ! Bicho ! Deder Gursum Muklemi Hena Sibu ! Chancho Wenoda ! Mieso Doba Kurfa Maya Beg!i Deboko ! Rare Mida ! Goja Shino Inchini Sululta Aleltu Babile Jimma Mulo ! Meta Guliso Golo Sire Hunde! Deder Chele ! Tobi Lalo ! Mekenejo Bitile ! Kegn Aleltu ! Tulo ! Harawacha ! ! ! ! Rob G! obu Genete ! Ifata Jeldu Lafto Girawa ! Gawo Inango ! Sendafa Mieso Hirna -
ETHIOPIA - National Hot Spot Map 31 May 2010
ETHIOPIA - National Hot Spot Map 31 May 2010 R Legend Eritrea E Tigray R egion !ª D 450 ho uses burned do wn d ue to th e re ce nt International Boundary !ª !ª Ahferom Sudan Tahtay Erob fire incid ent in Keft a hum era woreda. I nhabitan ts Laelay Ahferom !ª Regional Boundary > Mereb Leke " !ª S are repo rted to be lef t out o f sh elter; UNI CEF !ª Adiyabo Adiyabo Gulomekeda W W W 7 Dalul E !Ò Laelay togethe r w ith the regiona l g ove rnm ent is Zonal Boundary North Western A Kafta Humera Maychew Eastern !ª sup portin g the victim s with provision o f wate r Measle Cas es Woreda Boundary Central and oth er imm ediate n eeds Measles co ntinues to b e re ported > Western Berahle with new four cases in Arada Zone 2 Lakes WBN BN Tsel emt !A !ª A! Sub-city,Ad dis Ababa ; and one Addi Arekay> W b Afa r Region N b Afdera Military Operation BeyedaB Ab Ala ! case in Ahfe rom woreda, Tig ray > > bb The re a re d isplaced pe ople from fo ur A Debark > > b o N W b B N Abergele Erebtoi B N W Southern keb eles of Mille and also five kebeles B N Janam ora Moegale Bidu Dabat Wag HiomraW B of Da llol woreda s (400 0 persons) a ff ected Hot Spot Areas AWD C ases N N N > N > B B W Sahl a B W > B N W Raya A zebo due to flo oding from Awash rive r an d ru n Since t he beg in nin g of th e year, Wegera B N No Data/No Humanitarian Concern > Ziquala Sekota B a total of 967 cases of AWD w ith East bb BN > Teru > off fro m Tigray highlands, respective ly. -
Integration of Variable Renewable Energy in The
INTEGRATION OF VARIABLE RENEWABLE ENERGY IN THE NATIONAL ELECTRIC SYSTEM OF ETHIOPIA ABSTRACT FEBRUARY 2019 The study frame has been crafted and developed in close coordination with the Ethiopian Electric Power (EEP), coordinated by RES4Africa in 2018 in partnership with Enel Foundation and with the technical support of CESI. Acknowlegments Supervisor: Luca Marena, RES4Africa Working group members: Ulderico Bagalini, Bruno Cova, Andrea Prudenzi, CESI – Leonhard Braun, Daniele Paladini, RES4AFRICA – Tesfaye Batu, Daniel Mulatu, Bizuayehu Tesfaye, Mulat Azene, Melaku Yigzaw, Estifanos Gebru, Ethiopian Electric Power – Mirko Armiento, Giuseppe Montesano, Enel Foundation Special thanks to Carlo Papa (Enel Foundation) for supporting the study. Executive Summary Ethiopia is endowed with outstanding and diversified renewable energy resources, namely hydro, wind, solar, geothermal, and biomass. For many decades, the development of the electricity sector was based on the exploitation of huge hydro resources that made the electric power system dependent on water and particularly exposed to the climate change. The non-hydro renewable sources can be efficiently exploited in the power sector to improve energy diversification and support both short- and long-term power system resilience, in order to cope with current and future water challenges related to climate change and to support the national strategy to become a world class exporter of large amounts of clean and cheap renewable energies. However, the deployment of RES generation, especially if variable as in the case of PV and wind, shall be accurately designed to ensure the compliance with reliability standards and security constraints. The following study is focused on the integration of variable renewables into the Ethiopian electrical grid considering the development scenario until 2030.