Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa
Irrigation for smallholder farming systems is an important approach for sustainable intensification and increased productivity in Sub-Saharan Africa, provided investments in irrigation are properly targeted and accompanied by complementary improvements. Many GIS-based tools have been developed to id...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | Inglés |
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Elsevier
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/77038 |
| _version_ | 1855542415384903680 |
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| author | Katic, Pamela G. Morris, J. |
| author_browse | Katic, Pamela G. Morris, J. |
| author_facet | Katic, Pamela G. Morris, J. |
| author_sort | Katic, Pamela G. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Irrigation for smallholder farming systems is an important approach for sustainable intensification and increased productivity in Sub-Saharan Africa, provided investments in irrigation are properly targeted and accompanied by complementary improvements. Many GIS-based tools have been developed to identify suitable areas for investments in different types of small scale irrigation (SSI), but they do not explicitly address uncertainty on the data input and on the determination of factors that affect success of an investment in a given context. This paper addresses this problem by presenting an application of a decision-support targeting tool based on Bayesian networks (BNs) that can be used by non-expert policy-makers and investors to assess the potential success of specific technologies used for groundwater-based SSI. A case study application for the White Volta Basin in West Africa is presented to illustrate the BN approach. |
| format | Journal Article |
| id | CGSpace77038 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace770382024-08-27T10:37:23Z Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa Katic, Pamela G. Morris, J. groundwater small scale farming river basins smallholders intensification geographical information systems investment decision support systems living standards drip irrigation water availability case studies Irrigation for smallholder farming systems is an important approach for sustainable intensification and increased productivity in Sub-Saharan Africa, provided investments in irrigation are properly targeted and accompanied by complementary improvements. Many GIS-based tools have been developed to identify suitable areas for investments in different types of small scale irrigation (SSI), but they do not explicitly address uncertainty on the data input and on the determination of factors that affect success of an investment in a given context. This paper addresses this problem by presenting an application of a decision-support targeting tool based on Bayesian networks (BNs) that can be used by non-expert policy-makers and investors to assess the potential success of specific technologies used for groundwater-based SSI. A case study application for the White Volta Basin in West Africa is presented to illustrate the BN approach. 2016-08 2016-09-13T08:46:59Z 2016-09-13T08:46:59Z Journal Article https://hdl.handle.net/10568/77038 en Limited Access Elsevier Katic, Pamela; Morris, J. 2016. Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa. Environmental Modelling and Software, 82:44-72. doi: 10.1016/j.envsoft.2016.04.004 |
| spellingShingle | groundwater small scale farming river basins smallholders intensification geographical information systems investment decision support systems living standards drip irrigation water availability case studies Katic, Pamela G. Morris, J. Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa |
| title | Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa |
| title_full | Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa |
| title_fullStr | Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa |
| title_full_unstemmed | Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa |
| title_short | Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in Sub-Saharan Africa |
| title_sort | targeting investments in small scale groundwater irrigation using bayesian networks for a data scarce river basin in sub saharan africa |
| topic | groundwater small scale farming river basins smallholders intensification geographical information systems investment decision support systems living standards drip irrigation water availability case studies |
| url | https://hdl.handle.net/10568/77038 |
| work_keys_str_mv | AT katicpamelag targetinginvestmentsinsmallscalegroundwaterirrigationusingbayesiannetworksforadatascarceriverbasininsubsaharanafrica AT morrisj targetinginvestmentsinsmallscalegroundwaterirrigationusingbayesiannetworksforadatascarceriverbasininsubsaharanafrica |