Adaptation and Resistance of Smart Valleys Bunds in Sudanians’ Lowland: Experience in Four Lowlands in Burkina Faso

Delphine, Bama Nati Aïssata; Niang, Dial; Mahama, Gbané; Ouédraogo, Ibrahima; Bassirou, Boube; Vanessa, Ngnepi Toukep Elvire

doi:10.12691/ajwr-7-2-3

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…It is an attribute of technology and is involved in soil fertility management. In fact, the positive effect of this factor is expected on the adoption of innovation (Delphine et al, 2019).…”

Section: Drainagementioning

confidence: 99%

Determinants of smart valley technology adoption in lowland rice farming: Evidence from Burkina Faso

Adama¹,

Bama²,

Tassembédo³

et al. 2020

Net J Agric Sci

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The overall objective of this study is to identify the major factors affecting smart valley new technologies in lowland by rice farmers in Burkina Faso. Managing flood and water retention in lowland rice farming is still the biggest challenge in West Africa particularly in Burkina Faso. In order to face this challenge Africa Rice funded a project to promote this technology in Burkina Faso during 2018 and 2020. Surveys on 145 rice farmers spread in 6 villages were carried out. A Probit model was used to analyse the key factors affecting the adoption decision. The results show that women are the highest adopters (76.36%) of smart valley technology. Also, about 92.19% of the adopters have access to technical support structures (extension services, research and NGOs) compared to 7.81% of the non-adopters. The analysis show also that schooling level, rice farming experience, contact with agricultural extension and research institutes, additional cost due to the technology and the yield are key factors influencing the farmers adoption decisions. The additional cost due to smart valley construction is affecting negatively the decision to adopt it. This factor is the key to enhance the adoption rate because all the beneficiaries recognize that smart valley is able to manage drought and flood effectively; but the cost still unreachable to lowland rice farmers.

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Section: Drainagementioning

confidence: 99%

Determinants of smart valley technology adoption in lowland rice farming: Evidence from Burkina Faso

Adama¹,

Bama²,

Tassembédo³

et al. 2020

Net J Agric Sci

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“…The measurement device consisted of an adapted smart valley part [14] of 5 ha and an undeveloped part of 5 ha as a control on each of the three lowlands. Six-teen tubes, eight of which in the smart valley area and eight in the undeveloped area, were installed in the shallows, allowing humidity to be measured at a depth of 10, 20, 30, 40 cm.…”

Section: Soil Moisture Measurement Devicementioning

confidence: 99%

Impact of Smart Valley on Soil Moisture Content and Rice Yield in Some Lowlands in Burkina Faso

Delphine¹,

Elliott²,

Mahanat³

et al. 2020

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To reduce the impact of rainfall variability on lowland rice yields, Burkina Faso state develops lowlands for small rice farmers. However, the high cost of these infrastructures makes impossible to duplicate them to satisfy the needs which are enormous. The Smart-Valley technology which is actually popularized in certain coastal countries of West Africa would therefore be a boon to increase the productivity of the Sudanese lowlands if it well regulates runoff. The object of this study was therefore to know if smart valley technology could increase soil moisture in order to mitigate the impact of drought's pockets on rice cultivation in the Sudanese lowlands. The experiment takes place in three lowlands during the rainy seasons 2018 and 2019. The climatic data comes from the meteorological stations in the study areas as well as those installed on the sites. The infiltration measurements were carried out using the double Muntz ring. The soil moisture measurement device consisted of a smart valley area of 5 ha and an undeveloped area of 5 ha per site. Sixteen tubes were installed per lowland allowing the humidity to be measured at a depth of 10, 20, 30, 40 cm using a probe. Four rice varieties, Ory-lux6, FKR62N, FKR19 and FKR64 were tested on plots of 0.25 ha per variety in the smart valley and undeveloped parts. The results showed that the humidity level was 12% higher in the smart-valley plots throughout the cycle compared to the unmanaged area. In addition, humidity decreases rapidly in unmanaged plots as rain becomes increasingly scarce. Finally, the smart-valley development allowed an average

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“…With this in mind, this study "Numerical modeling of river sedimentation", applied to lowland of Sindou, during wet season 2019, is being carried out as part of the CSA Burkina Faso project, funded by the German development corporation (GIZ). The technics used at the lowland are "smart-valleys" development [4][5][6], which have already proven their worth in Benin and Togo [7,8]. These technics will help mitigate the climate effects on producers.…”

Section: Introductionmentioning

confidence: 99%

Numerical Modeling of River Sedimentation: Application to the Rice Farming Lowlands of Sindou, Burkina-Faso

Delphine¹,

Michée²,

Lèye³

2020

HYD

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The development of the shallows has become essential in the fight against hunger in Burkina Faso. In addition, rivers there are subject to massive silting up caused by erosion. These sedimentary deposits tend to gradually reduce the flow section, thus promoting the retention of pollutants in streams. So in order to prevent this phenomenon, it is important to have tools to predict the evolution of sedimentation. The coupled equation of Shallow-water-Exner, treated from the complete system, was used in this study. Indeed, the complexity of the analytical resolution of this equation requires to adopt a numerical resolution. The finite volume method was chosen. The first step was to collect sedimentation data from the lowland of Sindou using locally made tools. Simulations are carried out in order to test the model's performance. Sensitivity analysis showed that the model is sensitive to disturbances in friction and slope parameters of the field. The results showed the tool's ability to simulate the sedimentation of actual unsatisfactory cases. In fact, bad appreciation of parameters, friction and the absence of the topographic data generate a large margin of error between the simulated and observed values showing a difference in the shape of the carried sediments curves.

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Adaptation and Resistance of Smart Valleys Bunds in Sudanians’ Lowland: Experience in Four Lowlands in Burkina Faso

Cited by 3 publications

References 11 publications

Determinants of smart valley technology adoption in lowland rice farming: Evidence from Burkina Faso

Determinants of smart valley technology adoption in lowland rice farming: Evidence from Burkina Faso

Impact of Smart Valley on Soil Moisture Content and Rice Yield in Some Lowlands in Burkina Faso

Numerical Modeling of River Sedimentation: Application to the Rice Farming Lowlands of Sindou, Burkina-Faso

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