Chapter Iv Land Utilization
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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 -- -
Ethiopia Country Office Humanitarian Situation Report Includes Results from Tigray Response
Ethiopia Country Office Humanitarian Situation Report Includes results from Tigray Response © UNICEF Ethiopia/2021/Nahom Tesfaye Situation in Numbers Reporting Period: May 2021 12.5 million Highlights children in need of humanitarian assistance (HNO 2021) In May, 56,354 new medical consultations were conducted in Afar, Somali and Tigray regions through the 79 UNICEF- supported Mobile Health and Nutrition Teams (MHNTs), 23.5 million 11,692 of these in Tigray through the 30 active MHNTs. people in need UNICEF reached 412,647 people in May and 2,881,630 (HNO 2021) people between January to May 2021 throughout Ethiopia with safe water for drinking, cooking, and personal hygiene 2 through the rehabilitation of non-functional water systems, 3.6 million water treatment, and water trucking; of these, 1,228,921 were internally displaced people (DTM, in Tigray 2021) Since the beginning of the Tigray crisis, UNICEF has delivered 2,352 metric tons of multi-sectoral supplies to nine 806,541 partners (including Regional Bureaus) working in the region, valued at US$ 4.6 million. registered refugees (UNHCR,31 May 2021) In May, UNICEF supported the treatment of 38,032 under 5 children with Severe Acutely Malnutrition (SAM) in Ethiopia (1,723 in Tigray); 40.6 per cent of these were in Oromia, 20.7 per cent in Somali, 15.4 percent in SNNP/Sidama, 12.7 percent in Amhara and 4.5 per cent in Tigray. A total of UNICEF Revised HAC Appeal 152,413 children in the country have been treated for SAM between January – April 2021 with UNICEF direct support 2021 -
From Dust to Dollar Gold Mining and Trade in the Sudan–Ethiopia Borderland
From Dust to Dollar Gold mining and trade in the Sudan–Ethiopia borderland [Copy and paste completed cover here} Enrico Ille, Mohamed[Copy[Copy and and paste paste Salah completed completed andcover cover here} here} Tsegaye Birhanu image here, drop from 20p5 max height of box 42p0 From Dust to Dollar Gold mining and trade in the Sudan–Ethiopia borderland Enrico Ille, Mohamed Salah and Tsegaye Birhanu Cover image: Gold washers close to Qeissan, Sudan, 25 November 2019 © Mohamed Salah This report is a product of the X-Border Local Research Network, a component of the FCDO’s Cross- Border Conflict—Evidence, Policy and Trends (XCEPT) programme, funded by UKaid from the UK government. The programme carries out research work to better understand the causes and impacts of conflict in border areas and their international dimensions. It supports more effective policymaking and development programming and builds the skills of local partners. The views expressed do not necessarily reflect the UK government’s official policies. The Rift Valley Institute works in Eastern and Central Africa to bring local knowledge to bear on social, political and economic development. Copyright © Rift Valley Institute 2021. This work is published under a Creative Commons Attribution-NonCommercial-NoDerivatives License (CC BY-NC-ND 4.0) RIFT VALLEY INSTITUTE REPORT 2 Contents Executive summary 5 1. Introduction 7 Methodology 9 2. The Blue Nile–Benishangul-Gumuz borderland 12 The two borderland states 12 The international border 14 3. Trade and mobility in the borderlands 16 The administration of trade relations 16 Constraints on mobility 18 Price differentials and borderland trade 20 Borderland relations 22 4. -
Journal of Ethnobiology and Ethnomedicine
View metadata, citation and similar papers at core.ac.uk brought to you by CORE Journal of Ethnobiology and provided by PubMed Central Ethnomedicine BioMed Central Research Open Access Ethnomedical survey of Berta ethnic group Assosa Zone, Benishangul-Gumuz regional state, mid-west Ethiopia Teferi Flatie1, Teferi Gedif1, Kaleab Asres*2 and Tsige Gebre-Mariam1 Address: 1Department of Pharmaceutics, School of Pharmacy, Addis Ababa University, PO Box 1176, Addis Ababa, Ethiopia and 2Department of Pharmacognosy, School of Pharmacy, Addis Ababa University, PO Box 1176, Addis Ababa, Ethiopia Email: Teferi Flatie - [email protected]; Teferi Gedif - [email protected]; Kaleab Asres* - [email protected]; Tsige Gebre- Mariam - [email protected] * Corresponding author Published: 1 May 2009 Received: 17 June 2008 Accepted: 1 May 2009 Journal of Ethnobiology and Ethnomedicine 2009, 5:14 doi:10.1186/1746-4269-5-14 This article is available from: http://www.ethnobiomed.com/content/5/1/14 © 2009 Flatie et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Traditional medicine (TM) has been a major source of health care in Ethiopia as in most developing countries around the world. This survey examined the extent and factors determining the use of TM and medicinal plants by Berta community. One thousand and two hundred households (HHs) and fourteen traditional healers were interviewed using semi-structured questionnaires and six focused group discussions (FGDs) were conducted. -
From Dust to Dollar Gold Mining and Trade in the Sudan–Ethiopia Borderland
From Dust to Dollar Gold mining and trade in the Sudan–Ethiopia borderland [Copy and paste completed cover here} Enrico Ille, Mohamed[Copy[Copy and and paste paste Salah completed completed andcover cover here} here} Tsegaye Birhanu image here, drop from 20p5 max height of box 42p0 From Dust to Dollar Gold mining and trade in the Sudan–Ethiopia borderland Enrico Ille, Mohamed Salah and Tsegaye Birhanu Cover image: Gold washers close to Qeissan, Sudan, 25 November 2019 © Mohamed Salah This report is a product of the X-Border Local Research Network, a component of the FCDO’s Cross-Border Conflict Evidence, Policy and Trends (XCEPT) programme, funded by UK aid from the UK government. XCEPT brings together leading experts to examine conflict-affected borderlands, how conflicts connect across borders, and the factors that shape violent and peaceful behaviour. The X-Border Local Research Network carries out research to better understand the causes and impacts of conflict in border areas and their international dimensions. It supports more effective policymaking and development programming and builds the skills of local partners. The views expressed do not necessarily reflect the UK government’s official policies. The Rift Valley Institute works in Eastern and Central Africa to bring local knowledge to bear on social, political and economic development. Copyright © Rift Valley Institute 2021. This work is published under a Creative Commons Attribution-NonCommercial-NoDerivatives License (CC BY-NC-ND 4.0) RIFT VALLEY INSTITUTE REPORT 2 Contents Executive summary 5 1. Introduction 7 Methodology 9 2. The Blue Nile–Benishangul-Gumuz borderland 12 The two borderland states 12 The international border 14 3. -
Census Data/Projections, 1999 & 2000
Census data/Projections, 1999 & 2000 Jan - June and July - December Relief Bens., Supplementary Feeding Bens. TIGRAY Zone 1994 census 1999 beneficiaries - May '99 2000 beneficiaries - Jan 2000 July - Dec 2000 Bens Zone ID/prior Wereda Total Pop. 1999 Pop. 1999 Bens. 1999 bens % 2000 Pop. 2000 Bens 2000 bens Bens. Sup. July - Dec Bens July - Dec Bens ity Estimate of Pop. Estimate % of Pop. Feeding % of pop 1 ASEGEDE TSIMBELA 96,115 111,424 114,766 1 KAFTA HUMERA 48,690 56,445 58,138 1 LAELAY ADIYABO 79,832 92,547 5,590 6% 95,324 7,800 8% 11,300 12% Western 1 MEDEBAY ZANA 97,237 112,724 116,106 2,100 2% 4,180 4% 1 TAHTAY ADIYABO 80,934 93,825 6,420 7% 96,639 18,300 19% 24,047 25% 1 TAHTAY KORARO 83,492 96,790 99,694 2,800 3% 2,800 3% 1 TSEGEDE 59,846 69,378 71,459 1 TSILEMTI 97,630 113,180 37,990 34% 116,575 43,000 37% 15,050 46,074 40% 1 WELKAIT 90,186 104,550 107,687 Sub Total 733,962 850,863 50,000 6% 876,389 74,000 8% 15,050 88,401 10% *2 ABERGELE 58,373 67,670 11,480 17% 69,700 52,200 75% 18,270 67,430 97% *2 ADWA 109,203 126,596 9,940 8% 130,394 39,600 30% 13,860 58,600 45% 2 DEGUA TEMBEN 89,037 103,218 7,360 7% 106,315 34,000 32% 11,900 44,000 41% Central 2 ENTICHO 131,168 152,060 22,850 15% 156,621 82,300 53% 28,805 92,300 59% 2 KOLA TEMBEN 113,712 131,823 12,040 9% 135,778 62,700 46% 21,945 67,700 50% 2 LAELAY MAYCHEW 90,123 104,477 3,840 4% 107,612 19,600 18% 6,860 22,941 21% 2 MEREB LEHE 78,094 90,532 14,900 16% 93,248 57,500 62% 20,125 75,158 81% *2 NAEDER ADET 84,942 98,471 15,000 15% 101,425 40,800 40% 14,280 62,803 62% 2 -
Using Data to Target and Scale-Up Girls' Support Programs and Child Marriage Prevention
OCTOBER 2017 POLICY BRIEF Using Data to Target and Scale-Up Girls’ Support Programs and Child Marriage Prevention Of the women in the world today, approximately other sexually transmitted infections. Child marriage 250,000,000 were married before the age of 15, and is most prevalent in South Asia and sub-Saharan another approximately 450,000,000 were married Africa. Though median age at first marriage has been between the ages of 15 and 18 (United Nations on the rise over the past three decades, Ethiopia falls Children’s Fund 2014). Though child marriage is in the top 10 countries with the highest rates of child declining globally, it is estimated that over 100 million marriage: among 20-49-year-old women, 58 percent girls under age 18 will be married in the next decade were married or in union before the age of 18. (UNICEF 2015). Risk for child marriage varies, even Despite this, few programs to prevent child marriage within a country, with risk factors including things have been implemented and most of those remain such as poverty, ethnic group, and rural residency. The small-scale and unevaluated. A 2012 review of child detrimental effects of child marriage, however, are marriage interventions in developing countries found universal: girls who are married as children lose their that the most effective approaches in delaying child childhood and often become socially isolated; have marriage were those that offered incentives, such limited educational and employment opportunities; as conditional cash transfers or provision of school and, being young and lacking skills to negotiate safer materials, and those that empower girls directly sex, are vulnerable to early pregnancy (and its many through interventions such as girls’ groups and associated negative consequences) and HIV and training (Lee-Rife et al 2012). -
D.Table 9.5-1 Number of PCO Planned 1
D.Table 9.5-1 Number of PCO Planned 1. Tigrey No. Woredas Phase 1 Phase 2 Phase 3 Expected Connecting Point 1 Adwa 13 Per Filed Survey by ETC 2(*) Hawzen 12 3(*) Wukro 7 Per Feasibility Study 4(*) Samre 13 Per Filed Survey by ETC 5 Alamata 10 Total 55 1 Tahtay Adiyabo 8 2 Medebay Zana 10 3 Laelay Mayechew 10 4 Kola Temben 11 5 Abergele 7 Per Filed Survey by ETC 6 Ganta Afeshum 15 7 Atsbi Wenberta 9 8 Enderta 14 9(*) Hintalo Wajirat 16 10 Ofla 15 Total 115 1 Kafta Humer 5 2 Laelay Adiyabo 8 3 Tahtay Koraro 8 4 Asegede Tsimbela 10 5 Tselemti 7 6(**) Welkait 7 7(**) Tsegede 6 8 Mereb Lehe 10 9(*) Enticho 21 10(**) Werie Lehe 16 Per Filed Survey by ETC 11 Tahtay Maychew 8 12(*)(**) Naeder Adet 9 13 Degua temben 9 14 Gulomahda 11 15 Erob 10 16 Saesi Tsaedaemba 14 17 Alage 13 18 Endmehoni 9 19(**) Rayaazebo 12 20 Ahferom 15 Total 208 1/14 Tigrey D.Table 9.5-1 Number of PCO Planned 2. Affar No. Woredas Phase 1 Phase 2 Phase 3 Expected Connecting Point 1 Ayisaita 3 2 Dubti 5 Per Filed Survey by ETC 3 Chifra 2 Total 10 1(*) Mile 1 2(*) Elidar 1 3 Koneba 4 4 Berahle 4 Per Filed Survey by ETC 5 Amibara 5 6 Gewane 1 7 Ewa 1 8 Dewele 1 Total 18 1 Ere Bti 1 2 Abala 2 3 Megale 1 4 Dalul 4 5 Afdera 1 6 Awash Fentale 3 7 Dulecha 1 8 Bure Mudaytu 1 Per Filed Survey by ETC 9 Arboba Special Woreda 1 10 Aura 1 11 Teru 1 12 Yalo 1 13 Gulina 1 14 Telalak 1 15 Simurobi 1 Total 21 2/14 Affar D.Table 9.5-1 Number of PCO Planned 3. -
ETHIOPIA: Benishangul Gumuz Region Flash Update 6 January 2021
ETHIOPIA: Benishangul Gumuz Region Flash Update 6 January 2021 HIGHLIGHTS • Between end of July 2020 and 04 January 2021, more than 101,000 people were displaced by violence from A M H A R A Bullen, Dangur, Dibate, Guba, Mandura and Wombera Guba woredas of Metekel zone in Dangura Benishangul Gumuz Region 647 Pawe (BGR). 5,728 • Due to the deteriorating security situation in the zone, 12,808 Sedal Madira humanitarian access and life- Metekel saving assistance to the 28,000 returnees and 101,000 SUDAN B E N I SHA N G U L Sherkole G U M U Z new IDPs is challenging. Kurmuk • The regional Government has Wenbera Debati 23,121 been providing limited life- Menge 7,885 51,003 saving assistance since July Homosha Bulen 2020 using armed escorts. Undulu • Clusters at sub-national level Asosa Bilidigilu have been mapping resources Assosa Zayi but so far insecurity has not Kemeshi allowed transporting staff and Dembi O R O M I A commodities to affected Bambasi O R O M I A areas. Maokomo Kamashi • Special The federal Government is in C Mizyiga the process of establishing an Affected zone Emergency Coordination N A ## No. of IDPs per woreda Nekemte Center (ECC) in Metekel zone D UBLI to coordinate the P IDPs movement humanitarian response to the SU RE Humanitarian Western Hub IDPs. SOUTH OF SITUATION OVERVIEW Security in Metekel Zone of Benishangul Gumuz Region (BGR) has been gradually deteriorating since 2019, and more intensely so in recent months. On 23 December 2020, 207 individuals lost their lives in one day reportedly following an attack by unidentified armed groups (UAGs). -
Chapter Iii Socio-Economic Characteristics of the Population in Agricultural Households
CHAPTER III SOCIO-ECONOMIC CHARACTERISTICS OF THE POPULATION IN AGRICULTURAL HOUSEHOLDS 1 INTRODUCTION Population as a producer and consumer is closely related with agriculture. On the one hand, population affects production in general and agricultural outputs in particular by furnishing the required labour. On the other hand, the size of a population and its anticipated growth is the main factor determining food consumption requirements. Regarding the balance between population and consumption, if more people are to be fed than the food or services produced, saving and capital investments will be negatively affected. Moreover, population growth also negatively influences agriculture by putting pressure on the environment, such as water, fertility of land, . etc. Population size further influence productivity mainly through the diversification and specialization of the economy, the size of the market, and the importance of foreign trade. Not only the size, but also the socio-economic characteristics of the population of the agricultural households are important to the agricultural production. Study of the nature of the agricultural sector of a country will not be complete without proper understanding of the socio-economic characteristics of the population engaged in it. The population statistics of the agricultural households can be used to describe the characteristics and distribution of the population in space, its density and degree of concentration, the fluctuation in its rate of growth and the movement from one area to another. Data on population and agriculture will also help in finding out what percentage of resources will be needed at a particular time for the meeting of basic needs of the people and what amount of socially useful and productive labour is available in the country, regardless of whether labour or capital intensive techniques will suit the nation's economy. -
Benishangul-Gumuz Region
Situation Analysis of Children and Women: Benishangul-Gumuz Region Situation Analysis of Children and Women: Benishangul-Gumuz Region ABSTRACT The Situation Analysis covers selected dimensions of child well-being in Benishangul-Gumuz Regional State. It builds on the national Situation Analysis of Children and Women in Ethiopia (2019) and on other existing research, with inputs from specialists in Government, UNICEF Ethiopia and other partners. It has an estimated population of approximately 1.1 million people, which constitutes 1.1% of the total Ethiopian population. The population is young: 13 per cent is under-five years of age and 44 per cent is under 18 years of age. Since 1999/00, Benishangul-Gumuz has experienced an impressive 28 percentage point decline in monetary poverty, but 27 per cent of the population are still poor; the second highest in the country after Tigray and higher than the national average of 24 per cent. SITUATION ANALYSIS OF CHILDREN AND WOMEN: BENISHANGUL-GUMUZ REGION 4 Food poverty continued a steep decline from 55 per cent in 1999/00 to 24 per cent in 2015/16; close to the national average of 25 per cent. In Benishangul-Gumuz, in 2014, only 1.1 per cent of rural households were in the PSNP compared to 11 per cent of households at the national level In 2011, the under-five mortality rate in Benishangul-Gumuz was the highest in Ethiopia (169 per 1,000 live births); this declined significantly, but is still very high: 96 deaths per 1,000 births, which is the second highest in the country after Afar. -
Phenotypic Characterization of Donkeys in Benishangul Gumuz National Regional State
2020 SCIENCELINE Online Journal of Animal and Feed Research Volume 10, Issue 1: 25-35; January 25, 2020 ISSN 2228-7701 PHENOTYPIC CHARACTERIZATION OF DONKEYS IN BENISHANGUL GUMUZ NATIONAL REGIONAL STATE Amine MUSTEFA1, Abraham ASSEFA1, Manaye MISGANAW1, Fasil GETACHEW2, Solomon ABEGAZ3, Abebe HAILU1 and Yibrehu EMSHAW1 1Ethiopian Biodiversity Institute, P. O. Box 30726, Addis Ababa, Ethiopia 2ILRI (International Livestock Research Institute), P. O. Box 5689, Addis Ababa, Ethiopia 3EIAR (Ethiopian Institute of Agricultural Research, Debre-Zeit Agricultural Research Center), P. O. Box Bishoftu, Ethiopia Email: [email protected]; : 0000-0003-3788-4156 Supporting Information Revised: December December Revised: 1 November Received: PII: S222877012000004 DOI: https://dx.doi.org/10.36380/scil.2020.ojafr RESEARCH ABSTRACT: Fifteen morphometric measurements and eighteen qualitative traits were recorded on 323 randomly sampled adult donkeys (123 jacks and 200 jennets) to meet an objective of characterizing a heterogeneous donkey population of three phenotypic types (Sinnar, the locals and their crosses) found in Benishangul Gumuz region of Ethiopia. The General Linear Model and non-parametric test (chi-square) procedures of SAS software were used for the analysis of the morphometric data and qualitative traits, respectively. Means were separated using the Tukey-Kramer test. The studied morphometric measurements ARTICLE were significantly affected by the phenotypic type and partially affected by sex and sample location /district. 27 - 3 , 20 Sinnar donkeys were significantly bigger and heavier than the local and the crosses. However, for some of the 10 , 2019 morphometric measurements no significance difference was observed between Sinnar and crosses implying 19 the presence of heterosis. Heart girth measurements for Sinnar, local and crosses were 110.61±0.436, 106.18±0.448 and 108.87±1.251, respectively.