Category: Agriculture

Smallholder farmers in Madagascar are increasingly challenged by the uncertainty and variability of weather caused by climate change [21]. Since crops are predominantly rainfed, yields highly depend on water availability from precipitation and are prone to drought. Both the length and the intensity of the rainy season are becoming more and more unpredictable and the availability and use of irrigation facilities remains limited: In 2013, only 60 % of the estimated irrigation potential of 1.5 million ha (42 % of total national crop land) was equipped for irrigation [9]. Constraints to the implementation of adaptation strategies usually include limited access to technical equipment, formal credit and extension services [21]. The main irrigated crop is rice, and while temperature increases could be beneficial where low temperatures are currently a limiting factor to the growth of rice, prolonged periods of high temperatures in combination with strong winds could as well have devastating impacts on rice yields [22], [23]. Drier conditions also facilitate the spread of invasive species including the fall armyworm, which caused a yield loss of 47 % for maize in Madagascar in 2018 [8].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 10) translates into high uncertainty of drought projections (Figure 11). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will increase from 0.4 % in 2000 to 1.4 % and 2.6 % in 2080 under RCP2.6 and RCP6.0, respectively. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.04–0.8 % in 2000 to 0.9–6.5 % in 2080. The very likely range widens from 0–1.4 % in 2000 to 0.4–9 % in 2080. This means that some models project a tenfold increase of drought exposure over this time period.

Crop yield projections

In terms of yield projections, model results indicate a negative trend for cassava and maize under both RCPs (Figure 12)⁶. By 2080, compared to the year 2000, yields of cassava and maize are projected to decrease by 3.8 % and 2.7 % under RCP2.6, and by 2.6 % and 2.8 % under RCP6.0. Yields of rice and sugar cane, on the other hand, are projected to increase by 2.7 % and 9.7 % under RCP6.0 and to not change under RCP2.6. A possible explanation for the more positive results under RCP6.0 is that rice, sugar cane and cassava are so-called C3 plants, which follow a different metabolic pathway than, for example, maize (a C4 plant), and benefit more from the CO₂ fertilisation effect under higher concentration pathways. The later drop for cassava can be explained by decreasing levels of precipitation after 2050 under RCP6.0 (see Figure 5). Although some yield changes may appear small at the national level, they will likely increase more strongly in some areas and, conversely, decrease more strongly in other areas as a result of climate change impacts.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops need to be considered, yet should be carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

⁶ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ.

References

[8] FEWS NET, “Madagascar Food Security Outlook: February to September 2020,” n.p., 2020.
[9] FAO, “AQUASTAT Main Database: Irrigation and Drainage Development.” Online available: http://www.fao.org/nr/water/aquastat/data/query/index.html?lang=en [Accessed: Dec. 07, 2020].
[21] C. A. Harvey et al., “Extreme Vulnerability of Smallholder Farmers to Agricultural Risks and Climate Change in Madagascar,” Philos. Trans. R. Soc. B Biol. Sci., vol. 369, no. 1639, 2014, doi: 10.1098/rstb.2013.0089.
[22] E. Gerardeaux, M. Giner, A. Ramanantsoanirina, and J. Dusserre, “Positive Effects of Climate Change on Rice in Madagascar,” Agron. Sustain. Dev., vol. 32, no. 3, pp. 619–627, 2012, doi: 10.1007/s13593-011-0049-6.
[23] AQUASTAT, Irrigation in Africa in Figures. Rome, Italy: FAO, 2005.

Smallholder farmers in Mauritania are increasingly challenged by the uncertainty and variability of weather caused by climate change [16], [17]. Since crops are predominantly rainfed, yields highly depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited: In 2004, less than 10 % of the estimated irrigation potential of 250 000 ha (0.6 % of total national crop land) were irrigated [6]. The main irrigated crop is rice, in addition to maize, sorghum and vegetables [22]. Especially in central and northern Mauritania, soils are sandy and poor in nutrients, which complicates irrigation and crop production [22].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 10) translates into high uncertainty of drought projections (Figure 11). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will increase from 6 % in 2000 to 10 % in 2080 under RCP6.0 and decrease to 5 % under RCP2.6. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.3–19 % in 2000 to 0.6–36 % in 2080. The very likely range widens from 0–20 % in 2000 to 0.01–44 % in 2080. This means that some models project a doubling of drought exposure over this time period, while others project no change.

Crop yield projections

In terms of yield projections, model results indicate high uncertainty (Figure 12)⁶. Compared to the year 2000, yields of cow peas are projected to decrease by 6 % under RCP2.6 and increase by 4 % under RCP6.0. A possible explanation for the positive results under RCP6.0 is that cow peas are so-called C3 plants, which follow a different metabolic pathway than maize, millet and sorghum (C4 plants), and benefit more from the CO₂ fertilisation effect under higher concentration pathways. For maize, the trend is reversed: Under RCP2.6, yields are projected to slightly increase by 3 % and decrease by 11 % under RCP6.0. Millet and sorghum are projected to gain 8 % under RCP2.6 and 6 % under RCP6.0. The higher increases under RCP2.6 can be explained by higher precipitation projections under RCP2.6 (Figure 5). Finally, yields of rice are projected to not change under either RCP, however, some models project an increase of up to 200 %. Although some yield changes may appear small at the national level, they will likely increase more strongly in some areas and, conversely, decrease more strongly in other areas as a result of climate change impacts.

Overall, adaptation strategies such as switching to improved varieties in climate change-sensitive crops need to be considered, yet should be carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

⁶ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ. Maize, millet and sorghum are modelled for all countries, except for Madagascar.

References

[6] FAO, “AQUASTAT Database.” Online available: http://www.fao.org/nr/water/aquastat/data/query/index.html?lang=en [Accessed: 07-May-2020].
[16] K. Sissoko, H. van Keulen, J. Verhagen, V. Tekken, and A. Battaglini, “Agriculture, Livelihoods and Climate Change in the West African Sahel,” Reg. Environ. Chang., vol. 11, no. 1, pp. 119–125, 2011.
[17] P. Ozer, Y. C. Hountondji, J. Gassani, B. Djaby, and D. L. F, “Évolution récente des extrêmes pluviométriques en Mauritanie (1933–2010),” XXVIIeme Colloq. l’Association Int. Climatol., pp. 394–400, 2014.
[22] Y. M. Bachir and A. Ould Hamadi Sherif, “Mauritania Livelihood Zoning Plus,” Washington, D.C. and Madrid, Spain, 2013.

Smallholder farmers in Chad are increasingly challenged by the uncertainty and variability of weather that climate change causes [17], [18]. Since crops are predominantly rainfed, they depend on water availability from precipitation. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited due to high costs of initial investment, inefficient use of water resources and a lack of water storage and delivery techniques [27]. In 2002, less than 8 % of the estimated irrigation potential of 335 000 ha (0.7 % of the total national crop land) was irrigated [6]. Especially in central and northern Chad, soils are poor in nutrients, sandy and shallow, which has a negative effect on water retention, making soils vulnerable to drying and erosion [28].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 9) translates into high uncertainty of drought projections (Figure 10). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will hardly change in response to global warming. However, there are models that project a strong increase in drought exposure. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.6–5.5 % in 2000 to 0.5–12.7 % in 2080. The very likely range widens from 0.1–15.8 % in 2000 to 0.1–25.0 % in 2080. This means that some models project up to a twofold increase in drought exposure over this time period, while others project no change.

Crop yield projections

Climate change will have a negative impact on yields of maize, millet and sorghum (Figure 11)⁶. While maize is sensitive to hot temperatures above 35 °C, millet and sorghum have higher tolerance for hot temperatures and dry periods [29]. Still, model results indicate a negative yield trend for all three crops under both RCPs with a stronger decrease under RCP6.0. Compared to the year 2000, amounts are projected to decline by 7.4 % for maize and 9.6 % for millet and sorghum by 2080 under RCP6.0. Under RCP2.6, yields of maize are projected to decline by 2.9 % and yields of millet and sorghum by 6.5 %. Yields of rice, on the contrary, are projected to gain from climate change. Under RCP6.0, projections show an increase by 3.8 % by 2080 relative to the year 2000. These positive results under RCP6.0 can be mainly explained by the CO₂ fertilisation effect, which benefits plant growth. Rice is a so-called C3 plant, which follows a different metabolic pathway than maize, millet and sorghum (C4 plants), and benefits more from higher concentration pathways. Yields of groundnuts are projected to decrease under RCP2.6 and increase under RCP6.0. The decrease under RCP2.6 can be explained by non-temperature related parameters such as changes in precipitation, while the increase under RCP6.0 can be explained by the CO₂ fertilisation effect.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops should be considered, yet carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

⁶ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ. Maize, millet and sorghum are modelled for all countries, except for Madagascar.

References

[6] AQUASTAT, “Irrigation and Drainage Development,” 2002. Online available: http://www.fao.org/nr/water/aquastat/data/query/resultshtml. [Accessed: 17-Apr-2020].
[17] B. Sarr et al., “Adapting to Climate Variability and Change in Smallholder Farming Communities: A Case Study From Burkina Faso, Chad and Niger (CVCADAPT),” J. Agric. Ext. Rural Dev., vol. 7, no. 1, pp. 16–27, 2015.
[18] P. Maharana, A. Y. Abdel-Lathif, and K. C. Pattnayak, “Observed Climate Variability Over Chad Using Multiple Observational and Reanalysis Datasets,” Glob. Planet. Change, vol. 162, pp. 252–265, 2018.
[27] FAO and Lake Chad Basin Commission, “Adaptive Water Management in the Lake Chad Basin,” Rome, Italy and N’Djamena, Chad, 2009.
[28] A. Jones et al., Soil Atlas of Africa. Luxembourg, Luxembourg: European Commission, Publications Office of the European Commission, 2013.

Smallholder farmers in Côte d’Ivoire are increasingly challenged by the uncertainty and variability of weather that climate change causes [25]. Since crops are predominantly rainfed, yields depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited due to low levels of mechanisation and lack of public investment [7]. The national crop land suitable for irrigation is estimated at 430 685 ha. Currently, only 8 % of this area is irrigated [7].

Crop land exposure to drought

The high uncertainty of water availability projections (Figure 10) translates into high uncertainty of drought projections (Figure 11). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will barely change in response to global warming. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.2–7 % in 2000 to 0.1–23 % in 2080. The very likely range widens from 0–25 % in 2000 to 0–54 % in 2080. This means that most models project a significant increase in drought exposure over this time period.

Crop yield projections

Climate change will have a negative impact on yields of maize, millet and sorghum (Figure 12)⁶. While maize is sensitive to hot temperatures above 35 °C, millet and sorghum usually tolerate hot temperatures and dry periods better [26]. Still, model results indicate a negative yield trend for all three crops under both RCPs with a stronger decrease under RCP6.0. Compared to 2000, yields are projected to decline by 9 % for maize and 10 % for millet and sorghum by 2080 under RCP6.0. Under RCP2.6, yields of maize, millet and sorghum are projected to decline by 5 %. Yields of rice and cassava are projected to gain from climate change. Under RCP6.0, crop yields are projected to increase by 5 % for rice and 22 % for cassava by 2080 relative to the year 2000. Under RCP2.6, yields of rice and cassava are projected to barely change. These positive results under RCP6.0 can be ascribed to the CO₂ fertilisation effect, which benefits plant growth. Rice and cassava are so-called C3 plants, which follow a different metabolic pathway than maize (C4 plant) and benefit more from higher concentration pathways. However, projections of rice and cassava are characterised by higher modelling uncertainty. Hence, it is likely that crop yields will increase more strongly in some areas and, conversely, decrease more strongly in other areas as a result of climate change impacts.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops should be considered, yet carefully weighed against adverse outcomes, such as resulting decline of agro-biodiversity and loss of local crop types.

⁶ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ. Maize, millet and sorghum are modelled for all countries except for Madagascar.

References

[7] FAO, “Adapting Irrigation to Climate Change (AICCA): Côte d’Ivoire.” Online available: http://www.fao.org/in-action/aicca/country-activities/cote-divoire/background/en [Accessed: 27-Jan-2020].
[25] D. Noufé, G. Mahé, B. Kamagaté, Servat, A. Goula Bi Tié, and I. Savané, “Impact du changement climatique sur la production agricole: le cas du bassin de la Comoé en Côte d’Ivoire,” Hydrol. Sci. J., vol. 60, no. 11, pp. 1972–1983, 2015.

Smallholder farmers in Uganda are increasingly challenged by the uncertainty and variability of weather that climate change causes [19], [20]. Since crops are predominantly rainfed, they depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited due to high operation costs, limited extension services and problems regarding irrigation management [21]. Currently, only 0.5 % of the national crop land suitable for irrigation (3.03 million hectares) is irrigated [7]. The main irrigated crop is rice, followed by sugar cane, maize and vegetables [21].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 9) translates into high uncertainty of drought projections (Figure 10). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will hardly change in response to global warming. However, there are models that project a strong increase in drought exposure. Under RCP2.6, the likely range of drought exposure of the national crop land area per year widens from 0–0.4 % in 2000 to 0–1.7 % in 2080. The very likely range widens from 0–2.3 % in 2000 to 0–17.1 % in 2080. This means that some models project up to a tenfold increase in drought exposure over this time period, while others project no change.

Crop yield projections

Climate change will have a negative impact on yields of maize, millet and sorghum (Figure 11)⁵. While maize is sensitive to hot temperatures above 35 °C, millet and sorghum tolerate hot temperatures and dry periods better [22]. Still, model results indicate a negative yield trend for all three crops under both RCPs. Compared to the year 2000, amounts are projected to decline by 6 % for maize and 13 % for millet and sorghum by 2080 under either RCP. Yield projections for groundnuts and cassava vary depending on the scenario. Under RCP2.6, yields are projected to decline by 7 % for groundnuts and 12 % for cassava. Under RCP6.0, groundnut yields are projected to gain from climate change with an increase of 4 %, while cassava yields are projected to decline by 2 % by 2080 relative to the year 2000. The decrease under RCP2.6 can be explained by non-temperature related parameters such as changes in precipitation, while the RCP6.0 results can be explained by the CO₂ fertilisation effect under higher concentration pathways. Groundnuts and cassava are so-called C3 plants, which follow a different metabolic pathway than maize, millet and sorghum (C4 plants), and benefit more from higher CO₂ concentration.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops should be considered, yet carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

⁵ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ. Maize, millet and sorghum are modelled for all countries.

References

[7] Ministry of Agriculture Animal Industry and Fisheries and Ministry of Water and Environment, “National Irrigation Policy: Agricultural Transformation Through Irrigation Development,” Entebbe, Uganda, 2017.
[19] F. M. Mwaura and G. Okoboi, “Climate Variability and Crop Production in Uganda,” J. Sustain. Dev., vol. 7, no. 2, pp. 159–172, 2014.
[20] V. Sridharan, E. P. Ramos, E. Zepeda, B. Boehlert, A. Shivakumar, C. Taliotis, and M. Howells, “The Impact of Climate Change on Crop Production in Uganda: An Integrated Systems Assessment With Water and Energy Implications,” Water, vol. 11, pp. 1–24, 2019.
[21] J. Wanyama, H. Ssegane, I. Kisekka, A. J. Komakech, N. Banadda, A. Zziwa, T. O. Ebong, C. Mutumba, N. Kiggundu, R. K. Kayizi, D. B. Mucunguzi, and F. L. Kiyimba, “Irrigation Development in Uganda: Constraints, Lessons Learned and Future Perspectives,” J. Irrig. Drain. Eng., vol. 143, no. 5, pp. 1–10, 2017.

Smallholder farmers in Kenya are increasingly challenged by the uncertainty and variability of weather caused by climate change [21], [22]. Since most crops are rainfed, yields depend on water availability from precipitation. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited due to poor extension services and irrigation management, and lack of credit and technical equipment [23]. In 2003, only 28 % of the potential area (1 % of crop land) was irrigated [24]. The main irrigated crops are vegetables, fruit, coffee, rice and maize [23].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 10) translates into high uncertainty of drought projections (Figure 11). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will only slightly increase in response to gobal warming, while other models project a strong increase. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0–0.8 % in 2000 to 0–1.6 % in 2080. The very likely range widens from 0–1.9 % in 2000 to 0–9.8 % in 2080. This means that some models project a fivefold increase in crop land area exposed to drought over this time period, while others project no change.

Crop yield projections

Climate change will have a negative impact on yields of millet and sorghum (Figure 12)⁵. Compared to 2000, yields are projected to decline by 8.0 % under RCP2.6 and by 5.3 % under RCP6.0 by 2080. The stronger decrease under RCP2.6 can be explained by non-temperature related parameters such as changes in precipitation, while the weaker decrease under RCP6.0 can be explained by the CO₂ fertilisation effect under higher concentration pathways, which benefits plant growth. Yields of cassava are projected to gain from climate change, with a 25 % increase under RCP6.0. Cassava is a C3 plant, which follows a different metabolic pathway than millet, sorghum and maize (C4 plants), and benefits more from the CO₂ fertilisation effect. Yields of maize, wheat and cow peas are projected to decrease slightly under RCP2.6 and to not change under RCP6.0, with the exception of cow peas which are projected to increase by 10.2 % under RCP6.0. Although there appears to be almost no change in multi-model median national-level yields of maize and wheat, some models simulate considerable increases. Regional climate variability will likely cause crop yields to increase in some areas and decrease in others.

Overall, adaptation strategies such as switching to high-yielding improved varieties in climate change sensitive crops need to be considered, yet should be carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and a loss of local crop types.

⁵ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ. Maize, millet and sorghum are modelled for all countries.

References

[21] M. Herrero, C. Ringler, J. van de Steeg, P. Thornton, T. Zhu, E. Bryan, A. Omolo, J. Koo, and A. Notenbaert, “Climate Variability and Climate Change: Impacts on Kenyan Agriculture,” Washington, D.C. and Nairobi, Kenya, 2010.
[22] E. Bryan, C. Ringler, B. Okoba, C. Roncoli, S. Silvestri, and M. Herrero, “Adapting Agriculture to Climate Change in Kenya: Household Strategies and Determinants,” J. Environ. Manage., vol. 114, pp. 26–35, 2013.
[23] FAO, “Irrigation Market Brief: Kenya,” Rome, Italy, 2015.
[24] AQUASTAT, “Irrigation and Drainage Development,” 2002.

Smallholder farmers in Tanzania are increasingly challenged by the uncertainty and variability of weather caused by climate change [19], [20]. Since crops are predominantly rainfed, they depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation remains limited. The national crop land suitable for irrigation is estimated at 29.4 million ha [7]. Currently, only 1.5 % of this potential is irrigated. However, Tanzania has been investing in irrigation and is planning to almost triple its total irrigated area to 1.24 million ha by 2035 [21]. This expansion is motivated by hopes to increase the productivity of rice, which, along with maize, is the main irrigated crop in Tanzania [21].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 10) translates into high uncertainty of drought projections (Figure 11). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will increase by a factor of five in response to global warming. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.05–1.0 % in 2000 to 0.5–6.2 % in 2080. The very likely range widens from 0.01–1.8 % in 2000 to 0.2–10.1 % in 2080. This means that most models project a significant increase in drought exposure over this time period.

Crop yield projections

In terms of yield projections, millet, sorghum, rice, groundnuts and cassava are projected to gain from climate change (Figure 12)⁵. Under RCP6.0, crop yields are projected to increase by 22 % for millet and sorghum, 18 % for rice, 22 % for groundnuts and 31 % for cassava by 2080 relative to the year 2000. These positive results can be ascribed to the CO₂ fertilisation effect, which benefits plant growth. Rice, groundnuts and cassava are so-called C3 plants, which follow a different metabolic pathway than maize (C4 plant), and thus benefit more from the CO₂ fertilisation effects under higher concentration pathways. Maize yields are projected to slightly decrease under RCP2.6 and remain at current levels under RCP6.0. The decrease under RCP2.6 can be explained by non-temperature related parameters such as changes in precipitation patterns, while the projections for RCP6.0 can be explained by CO₂ fertilisation. Regional climate variability will likely cause crop yields to increase in some areas, while simultaneously decreasing in others.

Overall, adaptation strategies such as switching to high-yielding improved varieties in climate change sensitive crops should be considered, yet carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and a loss of local crop types.

⁵ Modelling data is available for a selected number of crops only. Hence, the crops listed on page 2 may differ. Maize, millet and sorghum are modelled for all countries.

References

[19] P. M. Luhunga, A. L. Kijazi, L. Chang’a, A. Kondowe, H. Ng’ongolo, and H. Mtongori, “Climate Change Projections for Tanzania Based on High-Resolution Regional Climate Models From the Coordinated Regional Climate Downscaling Experiment (CORDEX)-Africa,” Front. Environ. Sci., vol. 6, no. October, pp. 1–20, 2018.
[20] P. Rowhani, D. B. Lobell, M. Linderman, and N. Ramankutty, “Climate Variability and Crop Production in Tanzania,” Agric. For. Meteorol., vol. 151, no. 4, pp. 449–460, 2011.
[21] JICA, “The Project on the Revision of National Irrigation Master Plan in the United Republic of Tanzania,” Tokyo, Japan, 2018.

Smallholder farmers in Mali are increasingly challenged by the uncertainty and variability of weather that climate change causes [16], [17]. Since crops are predominantly rainfed, crop yields depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited despite Mali’s considerable irrigation potential of approximately 566 000 ha (1.4 % of the national crop land) [21], [22]. Currently, only 30 % of that potential is irrigated [6]. Especially in central and northern Mali, soils are sandy and poor in nutrients, which complicates irrigation and crop production.

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 9) translates into high uncertainty of drought projections (Figure 10). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will hardly change in response to global warming. However, there are models that project a strong increase in drought exposure. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.2–4.5 % in 2000 to 0.03–15.0 % in 2080. The very likely range widens from 0.1–13.6 % in 2000 to 0.02–29.4 % in 2080. This means that some models project up to a threefold increase in drought exposure over this time period, while others project no change.

Crop yield projections

In terms of yield projections, model results indicate a negative trend for maize, millet, sorghum and groundnuts (Figure 11). While maize is sensitive to hot temperatures above 35 °C, millet, sorghum and groundnuts tolerate hot temperatures and dry periods better [23]. Compared to the year 2000, yields are projected to decline by 13 % for maize, 12 % for millet and sorghum, and 7 % for groundnuts by 2080 under RCP6.0. Under RCP2.6, yields are projected to decline by 8 % for maize, 8 % for millet and sorghum, and 14 % for groundnuts. Yields of rice, on the contrary, are projected to gain from climate change. Under RCP6.0, yields are projected to increase by 29 % by 2080 relative to the year 2000. A possible explanation for the positive results under RCP6.0 is that rice is a socalled C3 plant, which follows a different metabolic pathway than maize, millet and sorghum (C4 plants), and benefits more from the CO2 fertilisation effect under higher concentration pathways. Yields of cow peas are projected to decrease under RCP2.6 and remain unchanged under RCP6.0. The decrease under RCP2.6 can be explained by non-temperature related parameters such as changes in precipitation, while the trend under RCP6.0 can be explained by the CO2 fertilisation effect. This explanation also applies to the projected stronger decrease in yields of groundnuts under RCP2.6.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops need to be considered, yet should be carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

References

[6] FAO, “Country Fact Sheet on Food and Agriculture Policy Trends: Mali,” Rome, Italy, 2017.
[16] B. Traore, M. Corbeels, M. T. van Wijk, M. C. Rufino, and K. E. Giller, “Effects of Climate Variability and Climate Change on Crop Production in Southern Mali,” Eur. J. Agron., vol. 49, pp. 115–125, 2013.
[17] B. Sultan, P. Roudier, P. Quirion, A. Alhassane, B. Muller, M. Dingkuhn, P. Ciais, M. Guimberteau, S. Traore, and C. Baron, “Assessing Climate Change Impacts on Sorghum and Millet Yields in the Sudanian and Sahelian Savannas of West Africa,” Environ. Res. Lett., vol. 8, pp. 1–9, 2013.
[21] AQUASTAT, “Irrigation and drainage development.” Online available: http://www.fao.org/nr/water/aquastat/data/query/results.html [Accessed: 06-Jul-2020].
[22] FAO, “Mali Country Profile,” 2016. Online available: http://www. fao.org/countryprofiles/index/en/?iso3=MLI [Accessed: 21-Feb-2020].
[23] USAID, “Climate Risk in Food for Peace Geographies: Kenya,” Washington, D.C., 2019.

Smallholder farmers in Niger are increasingly challenged by the uncertainty and variability of weather that climate change causes [23]. Since crops are predominantly rainfed, yields highly depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited: In 2010, less than 33 % of the estimated irrigation potential of 270 000 ha (0.6 % of total national crop land) were irrigated [8]. Irrigated crops include onions, sesame and cow peas [24]. Large parts of Niger’s soils are severely degraded due to unsustainable farming techniques and grazing practices, limiting opportunities for crop production [25].

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 9) translates into high uncertainty of drought projections (Figure 10). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will hardly change in response to global warming. However, there are models that project an increase in drought exposure. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.4-6.0 % in 2000 to 0.5–12.1 % in 2080. The very likely range widens from 0.1-18.0 % in 2000 to 0.1–40.6 % in 2080. This means that some models project a doubling of drought exposure over this time period, while others project no change.

Crop yield projections

In terms of yield projections, model results indicate a negative yield trend for maize under either RCP (Figure 11). Compared to the year 2000, maize yields are projected to decline by 5.3 % under RCP2.6 and by 2.7 % under RCP6.0 by 2080. However, yields of millet and sorghum, cow peas and groundnuts are projected to gain from climate change. Under RCP6.0, crop yields are projected to increase by 3.8 % for millet and sorghum, 54 % for cow peas and 52 % for groundnuts by 2080 relative to the year 2000. A possible explanation for the positive results under RCP6.0 is that cow peas and groundnuts are so-called C3 plants, which follow a different metabolic pathway than maize, millet and sorghum (C4 plants), and benefit more from the CO2 fertilisation effect under higher concentration pathways. Although yield changes of maize, millet and sorghum appear to be small at the national level, they will likely increase more strongly in some areas and, conversely, decrease more strongly in other areas as a result of climate change impacts.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops need to be considered, yet should be carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

References

[23] O. Mertz, S. D’haen, A. Maiga, I. B. Moussa, B. Barbier, A. Diouf, D. Diallo, E. D. Da, and D. Dabi, “Climate Variability and Environmental Stress in the Sudan-Sahel Zone of West Africa,” Ambio, vol. 41, no. 4, pp. 380–392, 2012.
[24] FAO, “Adapting Irrigation to Climate Change (Aicca): Background,” 2020. Online available: http://www.fao.org/in-action/ aicca/country-activities/niger/background/en [Accessed: 16-Jan-2020].
[25] I. Soumana and T. Abasse, “Effects of Physical and Biological Treatments in Restoring Degraded Crusted Soil in Niger,” Res. J. Agric. Environ. Manag., vol. 3, no. 10, pp. 560–568, 2014.

Smallholder farmers in Burkina Faso are increasingly challenged by the uncertainty and variability of weather that climate change causes [18], [19]. Since crops are predominantly rainfed, they depend on water availability from precipitation and are prone to drought. However, the length and intensity of the rainy season is becoming increasingly unpredictable and the use of irrigation facilities remains limited due to high costs of initial investment, problems regarding the maintenance of the equipment and harsh environmental conditions [20]. Currently, only 0.5 % of the total national crop land and 27 % of the estimated irrigation potential of 233 500 ha are irrigated [21], [22]. Especially in northern Burkina Faso, soils are poor in nutrients, sandy and shallow, which makes them vulnerable to drying, erosion and flooding [23]. 

Crop land exposure to drought

Currently, the high uncertainty of projections regarding water availability (Figure 9) translates into high uncertainty of drought projections (Figure 10). According to the median over all models employed for this analysis, the national crop land area exposed to at least one drought per year will hardly change in response to global warming. However, there are models that project a strong increase in drought exposure. Under RCP6.0, the likely range of drought exposure of the national crop land area per year widens from 0.07–3.8 % in 2000 to 0.04–16.0 % in 2080. The very likely range widens from 0.01–12.0 % in 2000 to 0.01–29.0 % in 2080. This means that some models project up to a fourfold increase in drought exposure over this time period, while others project no change.

Crop yield projections

Climate change will have a negative impact on yields of maize, millet and sorghum (Figure 11). While maize is sensitive to hot temperatures above 35 °C, millet and sorghum tolerate hot temperatures and dry periods better [24]. Still, model results indicate a negative yield trend for all three crops under both RCPs with a stronger decrease under RCP6.0. Compared to the year 2000, amounts are projected to decline by 12.0 % for maize and 7.5 % for millet and sorghum by 2080 under RCP6.0. Under RCP2.6, yields of maize are projected to decline by 8.4 % and yields of millet and sorghum by 5.2 %, whereas yields of cow peas and rice are projected to gain from climate change. Under RCP6.0, projections show an increase in yield by 16.2 % for cow peas and 27.0 % for rice by 2080 relative to the year 2000. An explanation for the positive results under RCP6.0 is that cow peas and rice are so-called C3 plants, which follow a different metabolic pathway than maize, millet and sorghum (C4 plants), and benefit more from the CO2 fertilisation effect under higher concentration pathways. Yields of groundnuts are projected to decrease under RCP2.6 and slightly increase under RCP6.0. The decrease under RCP2.6 can be explained by non-temperature related parameters such as changes in precipitation, while the increase under RCP6.0 can be explained by the CO2 fertilisation effect.

Overall, adaptation strategies such as switching to improved varieties in climate change sensitive crops should be considered, yet carefully weighed against adverse outcomes, such as a resulting decline of agro-biodiversity and loss of local crop types.

References

[18] B. Barbier, H. Yacouba, H. Karambiri, M. Zoromé, and B. Somé, “Human Vulnerability to Climate Variability in the Sahel: Farmers’ Adaptation Strategies in Northern Burkina Faso,” Environ. Manage., vol. 43, no. 5, pp. 790–803, 2009.
[19] B. Sarr et al., “Adapting to Climate Variability and Change in Smallholder Farming Communities: A Case Study From Burkina Faso, Chad and Niger (CVCADAPT),” J. Agric. Ext. Rural Dev., vol. 7, no. 1, pp. 16–27, 2015.
[20] J. Wanvoeke, J. P. Venot, C. De Fraiture, and M. Zwarteveen, “Smallholder Drip Irrigation in Burkina Faso: The Role of Development Brokers,” J. Dev. Stud., vol. 52, no. 7, pp. 1019–1033, 2016.
[21] R. E. Namara and H. Sally, “Proceedings of the Workshop on Irrigation in West Africa: Current Status and a View to the Future,” Colombo, Sri Lanka, 2014.
[22] USAID, “Country Profile: Property Rights and Resource Governance in Burkina Faso,” Washington, D.C., 2017.
[23] USAID, “Climate Risks in Food for Peace Geographies: Burkina Faso,” Washington, D.C., 2017.
[24] USAID, “Climate Risk in Food for Peace Geographies: Kenya,” Washington, D.C., 2019.