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Data for the evaluation of irrigation development interventions in Northern Ethiopia

This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters cons...

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Autores principales: Yigzaw, Negusse, Mburu, John, Ogutu, Chris Ackello, Whitney, Cory, Luedeling, Eike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717167/
https://www.ncbi.nlm.nih.gov/pubmed/31489351
http://dx.doi.org/10.1016/j.dib.2019.104342
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author Yigzaw, Negusse
Mburu, John
Ogutu, Chris Ackello
Whitney, Cory
Luedeling, Eike
author_facet Yigzaw, Negusse
Mburu, John
Ogutu, Chris Ackello
Whitney, Cory
Luedeling, Eike
author_sort Yigzaw, Negusse
collection PubMed
description This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention.
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spelling pubmed-67171672019-09-05 Data for the evaluation of irrigation development interventions in Northern Ethiopia Yigzaw, Negusse Mburu, John Ogutu, Chris Ackello Whitney, Cory Luedeling, Eike Data Brief Environmental Science This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention. Elsevier 2019-08-01 /pmc/articles/PMC6717167/ /pubmed/31489351 http://dx.doi.org/10.1016/j.dib.2019.104342 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Environmental Science
Yigzaw, Negusse
Mburu, John
Ogutu, Chris Ackello
Whitney, Cory
Luedeling, Eike
Data for the evaluation of irrigation development interventions in Northern Ethiopia
title Data for the evaluation of irrigation development interventions in Northern Ethiopia
title_full Data for the evaluation of irrigation development interventions in Northern Ethiopia
title_fullStr Data for the evaluation of irrigation development interventions in Northern Ethiopia
title_full_unstemmed Data for the evaluation of irrigation development interventions in Northern Ethiopia
title_short Data for the evaluation of irrigation development interventions in Northern Ethiopia
title_sort data for the evaluation of irrigation development interventions in northern ethiopia
topic Environmental Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717167/
https://www.ncbi.nlm.nih.gov/pubmed/31489351
http://dx.doi.org/10.1016/j.dib.2019.104342
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