Mali: Infrastructure

Climate change is expected to significantly affect Mali’s infrastructure sector through extreme weather events, such as flooding and droughts (Figure 12). High precipitation amounts can lead to flooding of roads, while high temperatures can cause roads, bridges and protective structures to develop cracks and degrade more quickly. Transport infrastructure is very vulnerable to extreme weather events, yet essential for social, economic and agricultural livelihoods. Roads serve communities to trade their goods and access healthcare, education, credit as well as other services, especially in rural and remote areas. The absence of railways, seasonal navigability of the Niger River and limited airport facilities increase Mali’s reliance on road transportation. Yet, Mali has one of the lowest road densities in Africa with an average of 38 km / 1 000 km² [24]. Furthermore, only 17 % of Mali’s rural population lives within 2 km of an all-season road, which is 60 % below the African average [24]. Therefore, investments will have to be made into building climate-resilient road networks.

Extreme weather events will also have devastating effects on human settlements and economic production sites, especially in urban areas with high population densities like Bamako or Sikasso. Informal settlements are particularly vulnerable to extreme weather events: Makeshift homes are often built in unstable geographical locations including river banks, where flooding can lead to loss of housing, contamination of water, injury or death. Dwellers usually have low adaptive capacity to respond to such events due to high levels of poverty and a lack of risk-reducing infrastructures. For example, heavy rains in July and August 2018 caused flooding in different regions across Mali, particularly affecting communities along the Niger River including Bamako, Gao, Koulikoro, Mopti, Segou and Timbuktu [25]. A total of 137 000 people were affected (the highest number compared to the previous 6 years), 6 350 houses were destroyed and 2 680 head of cattle were killed [25]. Flooding and droughts will also affect hydropower generation: Mali draws 60 % of its energy from hydropower, with a total installed capacity of 528 MW in 2014 [26]. However, variability in precipitation and climatic conditions could severely disrupt hydropower generation.

Despite the risk of infrastructure damage being likely to increase due to climate change, precise predictions of the location and the extent of exposure are difficult to make. For example, projections of river flood events are subject to substantial modelling uncertainty, largely due to the uncertainty of future projections of precipitation amounts and their spatial distribution, affecting flood occurrence (see also Figure 4). In the case of Mali, projections for both RCP2.6 and RCP6.0 show almost no change in the exposure of major roads to river floods. In 2000, 1.7 % of major roads were exposed to river floods at least once a year, while by 2080, this value is projected to change to 1.9 % under RCP2.6 and to 2.0 % under RCP6.0. Similarly, exposure of urban land area to river floods is projected to hardly change under either RCP (Figure 13).

Figure 12: Projections of major roads exposed to river floods at least once a year for Mali for different GHG emissions scenarios.
Figure 13: Projections of urban land area exposed to river floods at least once a year for Mali for different GHG emissions scenarios.

While three of four models project an increase in the exposure of the GDP to heatwaves, the magnitude of the increase is subject to high modelling uncertainty with one model projecting very strong and two models projecting weaker increases (Figure 14). Median model projections for RCP2.6 show an increase from 2.2 % in 2000 to 8.7 % by 2080, whereas under RCP6.0, exposure is projected to increase to 15.2 %. It is recommended that policy planners start identifying heat-sensitive economic production sites and activities, and integrating climate adaptation strategies, such as improved, solar-powered cooling systems, “cool roof” isolation materials or switching the operating hours from day to night [27].

Figure 14: Exposure of GDP in Mali to heatwaves for different GHG emissions scenarios.

References

[24] C. Briceño-Garmendia, C. Dominguez, and N. Pushak, “Mali’s Infrastructure: A Continental Perspective,” Washington, D.C., 2011.
[25] OCHA, “Humanitarian Bulletin Mali (July-August 2018),” Bamako, Mali, 2018.
[26] UNIDO and ICSHP, “World Small Hydropower Development Report 2016,” Vienna, Austria and Hangzhou, China, 2016.
[27] M. Dabaieh, O. Wanas, M. A. Hegazy, and E. Johansson, “Reducing Cooling Demands in a Hot Dry Climate: A Simulation Study for Non-Insulated Passive Cool Roof Thermal Performance in Residential Buildings,” Energy Build., vol. 89, pp. 142–152, 2015.

Mali: Agriculture

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

Figure 10: Projections of crop land area exposed to drought at least once a year for Mali for different GHG emissions scenarios.

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

Figure 11: Projections of crop yield changes for major staple crops in Mali for different GHG emissions scenarios assuming constant land use and agricultural management.

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.

Mali: Water resources

Over the last decades, Mali has experienced strong seasonal and annual variations in precipitation, which present a major constraint to agricultural production [16], [17]. Mali was hit by severe droughts between 1970 and 2000 as a result of declining levels of precipitation since the mid-1950s. Although precipitation levels recovered towards the year 2000, they have remained below the national average of the past century [18]. The 2012 Sahel drought affected a total of 4.6 million people in Mali [19]. Extreme droughts tend to have a cascading effect: First, lack of water reduces crop yields, which increases the risk of food insecurity for people and their livestock, which in turn limits their capacity to cope with future droughts. Transhumance used to be an effective way to deal with variations in precipitation and droughts in Mali. However, people’s reliance on this type of pastoralism has been challenged by increasingly unpredictable precipitation patterns. The resulting lack of pastures and water has led to increasing competition over these scarce resources, particularly along the Niger River and in the Inner Niger Delta. Other factors complicating transhumance include poor natural resource management, population growth, conflicts between farmers and herders and terrorist activities in the greater region, making this mode of living less profitable and sometimes even dangerous [20].

Per capita water availability

Figure 8: Projections of water availability from precipitation per capita and year with (A) national population held constant at year 2000 level and (B) changing population in line with SSP2 projections for different GHG emissions scenarios, relative to the year 2000.

Current projections of water availability in Mali display high uncertainty under both GHG emissions scenarios. Assuming a constant population level, multi-model median projections suggest only slight decreases in water availability over Mali by the end of the century under both emissions scenarios (Figure 8A). Yet, when accounting for population growth according to SSP2 projections5, per capita water availability for Mali is projected to decline by 77 % by 2080 relative to the year 2000 under both scenarios (Figure 8B). While this decline is primarily driven by population growth, rather than climate change, it highlights the great urgency to invest in water saving measures and technologies for future water consumption.

Spatial distribution of water availability

Figure 9: Water availability from precipitation (runoff) projections for Mali for different GHG emissions scenarios.

Projections of future water availability from precipitation vary depending on the region and scenario (Figure 9). In line with precipitation projections, water availability is projected to decline by 20 % in the south-west of Mali by 2080 under both RCPs. In the northern half of the country, however, water availability is projected to increase by 15 % under RCP2.6. Under RCP6.0, model agreement on these increases is low towards the end of the century. This modelling uncertainty, along with the high natural variability of precipitation, contributes to uncertain future water availability in particular in the north of Mali.

5 Shared Socio-economic Pathways (SSPs) outline a narrative of potential global futures, including estimates of broad characteristics such as country level population, GDP or rate of urbanisation. Five different SSPs outline future realities according to a combination of high and low future socio-economic challenges for mitigation and adaptation. SSP2 represents the “middle of the road”-pathway.

References

[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.
[18] USAID, “A Climate Trend Analysis of Mali,” Washington, D.C., 2012.
[19] World Bank, “Sahel Drought Situation Report No. 9: Burkina Faso, Chad, Mali, Mauritania, Niger, Nigeria, Senegal,” Washington, D.C., 2012.
[20] UNOWAS, “Pastoralism and Security in West Africa and the Sahel,” n.p., 2018.

Mali: Climate

Temperature

Figure 2: Air temperature projections for Mali for different GHG emissions scenarios.

In response to increasing greenhouse gas (GHG) concentrations, air temperature over Mali is projected to rise by 2.0 to 4.6 °C (very likely range) by 2080 relative to the year 1876, depending on the future GHG emissions scenario (Figure 2). Compared to pre-industrial levels, median climate model temperature increases over Mali amount to approximately 2.2 °C in 2030, 2.6 °C in 2050 and 2.7 °C in 2080 under the low emissions scenario RCP2.6. Under the medium / high emissions scenario RCP6.0, median climate model temperature increases amount to 2.2 °C in 2030, 2.8 °C in 2050 and 4.0 °C in 2080.

Very hot days

Figure 3: Projections of the annual number of very hot days (daily maximum temperature above 35 °C) for Mali for different GHG emissions scenarios.

In line with rising mean annual temperatures, the annual number of very hot days (days with daily maximum temperature above 35 °C) is projected to rise dramatically and with high certainty all over Mali (Figure 3). Under the medium / high emissions scenario RCP6.0, the multi-model median, averaged over the whole country, projects 23 more very hot days per year in 2030 than in 2000, 34 more in 2050 and 59 more in 2080. In some parts, especially in central Mali, this amounts to about 300 days per year by 2080.

Precipitation

Figure 4: Annual mean precipitation projections for Mali for different GHG emissions scenarios, relative to the year 2000.

Models project no clear trend for precipitation, which is due to high uncertainty and natural year-to-year variability (Figure 4). Out of the four climate models underlying this analysis, one model projects an increase in mean annual precipitation over Mali, one model projects no change, while two models project a decrease under RCP6.0. Median model projections for RCP2.6 show a slight decrease of 2 mm in precipitation until 2080, while median model projections for RCP6.0 show a stronger precipitation decrease of 10 mm by 2080 compared to year 2000.

Heavy precipitation events

Figure 5: Projections of the number of days with heavy precipitation over Mali for different GHG emissions scenarios, relative to the year 2000.

In response to global warming, heavy precipitation events are expected to become more intense in many parts of the world due to the increased water vapour holding capacity of a warmer atmosphere. At the same time, the number of days with heavy precipitation events is expected to increase. However, this tendency cannot be found in climate projections for Mali: Two models project a decrease, one projects no change and only one model projects an increase. Median climate model projections show a slight decrease in the number of days with heavy precipitation from 7.7 in the year 2000 to 7.5 (RCP2.6) and 7.3 (RCP6.0) by 2080 (Figure 5).

Soil moisture

Figure 6: Soil moisture projections for Mali for different GHG emissions scenarios, relative to the year 2000.

Soil moisture is an important indicator for drought conditions. In addition to soil parameters and management, it depends on both precipitation and evapotranspiration and therefore also on temperature, as higher temperatures translate to higher potential evapotranspiration. Annual mean top 1-m soil moisture projections for Mali show no change under RCP2.6 and a decrease of 3.7 % under RCP6.0 by 2080 compared to the year 2000 (Figure 6). However, there is considerable spatial variability and modelling uncertainty, as different hydrological models project different directions of change, which makes it difficult to identify a clear trend.

Potential evapotranspiration

Figure 7: Potential evapotranspiration projections for Mali for different GHG emissions scenarios, relative to the year 2000.

Potential evapotranspiration is the amount of water that would be evaporated and transpired if sufficient water was available at and below the land surface. Since warmer air can hold more water vapour, it is expected that global warming will increase potential evapotranspiration in most regions of the world. In line with this expectation, hydrological projections for Mali indicate a stronger rise of potential evapotranspiration under RCP6.0 than under RCP2.6 (Figure 7). Under RCP6.0, potential evapotranspiration is projected to increase by 2.4 % in 2030, 3.7 % in 2050 and 7.0 % in 2080 compared to year 2000 levels.

Launch of the Ethiopia climate risk analysis

The launch took place as part of a virtual event organized by the Ethiopian Environment, Forest and Climate Change Commission (EFCCC) and the German Embassy in Ethiopia and was moderated by Mariamawit Solomon from GIZ. After opening remarks by Laura Schmidt, Head of Development Cooperation at the German Embassy in Ethiopia, and H.E. Prof. Fekadu Beyene from the EFCCC, the PIK team presented key insights from the climate risk study for Ethiopia. In addition, a corresponding climate risk profile was launched. The presentation was accompanied by a lively discussion in the chat and followed by a Q&A round with questions addressing the methods, findings, existing research and Ethiopia’s NAP and NDC planning. The second part of the event was a panel discussion on the question of how to bring the study results into action. Dr. Adefires Worku (EFCCC), Dr. Teferi Demissie (CGIAR/CCAFS) and Gebru Jember Endalew (LDC Initiative for Effective Adaptation and Resilience, LIFE-AR) shared their perspectives on this question, agreeing upon the important role played by science in effective climate adaptation.

The full analysis and complimentary documents are available in the Downloads section.

Smallholder farms in Tigray region, using irrigation techniques to cope with dry conditions
Agricultural cultivation areas in Ethiopia
Agricultural cultivation areas in Ethiopia
Agricultural cultivation areas in Ethiopia
Agricultural cultivation areas in Ethiopia
Agricultural cultivation areas in Ethiopia

Ethiopia climate risk analysis published

The study provides a comprehensive overview on future climate risks in Ethiopia’s agricultural sector, such as related to water availability, weather extremes and crop yields, derived from state-of-the-art impact models. It also features a spatial vulnerability assessment, which guides targeting of adaptation interventions. Based on the impact analysis, adaptation needs for Ethiopia were identified and suitable adaptation strategies selected and evaluated together with the Ethiopian government and local stakeholders, to provide recommendations for adaptation. The study and complimentary documents are available in the Downloads section.

 

Ethiopia Climate Risk Analysis
Ethiopia Climate Risk Analysis
Ethiopia Climate Risk Analysis

Niger: Human health

Climate change threatens the health and sanitation sector through more frequent incidences of heatwaves, floods, droughts and storms. Among the key health challenges in Niger are morbidity and mortality through vector-borne diseases such as malaria, waterborne diseases related to extreme weather events (e.g. flooding) such as diarrhoea and cholera, respiratory diseases, meningitis, measles, injury and mortality through extreme weather events as well as climate impacts on food and water supply, which can increase the risk of malnutrition and hunger [34]. Many of these challenges are expected to become more severe under climate change. According to the World Health Organization (WHO), Niger recorded around 8 million cases of malaria in 2018 [35]. Climate change is likely to have an impact on malaria transmission periods and the geographic range of vector-borne diseases: In Niger, the general malaria risk is projected to fall due to rising temperatures, however, some regions are likely to become more vulnerable to malaria, for instance, due to more frequent incidences of flooding [36], [37]. A study found that temperature increases and low humidity due to climate change have the potential to prepone the seasonal onset of meningitis and significantly increase the number of meningitis cases [38], [39]. Niger is part of the so-called Meningitis Belt, which largely coincides with the Sahel region and which is where the majority of meningitis epidemics occur. In 2015, the country suffered from a major meningitis epidemic with 8 500 reported cases and 573 deaths [40]. Climate change also poses a threat to food security since households in Niger depend on agricultural production for up to 40 % of their food consumption [5].

Exposure to heatwaves

Figure 17: Projections of population exposure to heatwaves at least once a year for Niger for different GHG emissions scenarios.

Rising temperatures will result in more frequent heatwaves in Niger, leading to increased heat-related mortality. Under RCP6.0, the population affected by at least one heatwave per year is projected to increase from 1.7 % in 2000 to 12 % in 2080 (Figure 17).

Heat-related mortality

Figure 18: Projections of heatrelated mortality for Niger for different GHG emissions scenarios assuming no adaptation to increased heat.

Furthermore, under RCP6.0, heat-related mortality will likely increase from about 3 to about 10 deaths per 100 000 people per year, which translates to an increase by a factor of more than three towards the end of the century compared to year 2000 levels, provided that no adaptation to hotter conditions will take place (Figure 18). Under RCP2.6, heat-related mortality is projected to increase to about 6 deaths per 100 000 people per year in 2080.

References

[34] WHO, “Health Compendium Consolidated Appeal Process: Niger,” Geneva, Switzerland, 2012.
[35] WHO, “World Malaria Report 2019,” Rome, Italy, 2019.
[36] R. Boyce, R. Reyes, M. Matte, M. Ntaro, E. Mulogo, J. P. Metlay, L. Band, and M. J. Siedner, “Severe Flooding and Malaria Transmission in the Western Ugandan Highlands: Implications for Disease Control in an Era of Global Climate Change,” J. Infect. Dis., vol. 214, pp. 1403–1410, 2016.
[37] C. Caminade, A. E. Jones, R. Ross, and G. Macdonald, “Malaria in a Warmer West Africa,” Nat. Clim. Chang., vol. 6, no. November, pp. 984–985, 2016.
[38] A. F. Abdussalam, A. J. Monaghan, D. F. Steinhoff, V. M. Dukic, M. H. Hayden, T. M. Hopson, J. E. Thornes, and G. C. Leckebusch, “The Impact of Climate Change on Meningitis in Northwest Nigeria: An Assessment Using CMIP5 Climate Model Simulations,” Weather. Clim. Soc., vol. 6, no. 3, pp. 371–379, 2014.
[39] A. M. Molesworth, L. E. Cuevas, S. J. Connor, A. P. Morse, and M. C. Thomson, “Environmental Risk and Meningitis Epidemics in Africa,” Emerg. Infect. Dis., vol. 9, no. 10, pp. 1287–1293, 2003.
[40] WHO, “Meningococcal Disease – Niger (Update),” 2015. Online available: https://www.who.int/csr/don/23-july-2015-niger/en [Accessed: 21-Jan-2020].

Niger: Ecosystems

Climate change is expected to have a significant influence on the ecology and distribution of tropical ecosystems, though the magnitude, rate and direction of these changes are uncertain [31]. With rising temperatures and increased frequency and intensity of droughts, wetlands and riverine systems are increasingly at risk of being converted to other ecosystems, with plant populations being succeeded and animals losing habitats. Increased temperatures and droughts can also impact succession in forest systems while concurrently increasing the risk of invasive species, all of which affect ecosystems. In addition to these climate drivers, low agricultural productivity and population growth might motivate further agricultural expansion, resulting in increased deforestation, land degradation and forest fires, all of which will impact animal and plant biodiversity.

Species richness

Figure 15: Projections of the aggregate number of amphibian, bird and mammal species for Niger for different GHG emissions scenarios.

Model projections of species richness (including amphibians, birds and mammals) and tree cover for Niger are shown in Figure 15 and 16, respectively. The models applied for this analysis show particularly strong agreement on the development of species richness under RCP6.0: Northern Niger is expected to gain up to 20 % of animal species due to climate change, while southern Niger is expected to lose around 20 %.

Tree cover

Figure 16: Tree cover projections for Niger for different GHG emissions scenarios.

With regard to tree cover, model results are far less certain and of low magnitude. For RCP2.6, there is model agreement in very few areas showing no change in tree cover. Under RCP6.0, tree cover is projected to increase by only 0.5 % in central Niger by 2080 (Figure 16).

It is important to keep in mind that the model projections exclude any impacts on biodiversity loss from human activities such as land use, which have been responsible for significant losses of global biodiversity in the past, and are expected to remain its main driver in the future [32]. In recent years, Niger’s vegetation has experienced profound disturbances due to population pressure and increasing demand for farmland and firewood, leaving large parts of Niger’s soils severely degraded [25]. According to an ICRISAT report, around 80 000 to 120 000 ha of land are annually degraded in Niger [33].

References

[31] T. M. Shanahan, K. A. Hughen, N. P. McKay, J. T. Overpeck, C. A. Scholz, W. D. Gosling, C. S. Miller, J. A. Peck, J. W. King, and C. W. Heil, “CO2 and fire influence tropical ecosystem stability in response to climate change,” Nat. Publ. Gr., no. July, pp. 1–8, 2016.
[32] IPBES, “Report of the Plenary of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services on the work of its seventh session,” n.p., 2019.
[33] B. V. Bado, P. Savadogo, and M. L. S. Manzo, “Restoration of Degraded Lands in West Africa Sahel: Review of Experiences in Burkina Faso and Niger,” n.p., 2016.

Niger: Infrastructure

Climate change is expected to significantly affect infrastructure in Niger through extreme weather events. High precipitation amounts can lead to the flooding of roads, while high temperatures can cause roads, bridges and protective structures to develop cracks and degrade more quickly. This will require earlier replacement and lead to higher maintenance and replacement costs. Roads serve communities to trade goods and access healthcare, education, credit and other services. The absence of railways, low navigability of the Niger River and a limited number of airport facilities increase Niger’s reliance on road transportation [26]. Overall, Niger has one of the lowest road densities in Africa with 13 km/1 000 km² [27]. Investments will have to be made to build climate-resilient road networks.

Extreme weather events will also have devastating effects on human settlements and economic production sites, especially in urban areas with high population densities like Niamey, Zinder or Maradi. Informal settlements are particularly vulnerable to extreme weather events: Makeshift homes are often built in unstable geographical locations including steep slopes or river banks, where flooding can lead to loss of housing, contamination of water, injury or death. Dwellers usually have a low adaptive capacity to respond to such events due to high levels of poverty and lack of risk-reducing infrastructures. For example, heavy rains during the 2019 rainy season caused flooding in several localities across Niger, affecting 256 000 people (67 % in the regions of Maradi, Zinder and Agadez) and leaving 22 000 houses destroyed [28]. In the 1998-2014 period, a total of 1.6 million people were affected by flooding in Niger [29]. Flooding and droughts will also affect hydropower generation: Niger is currently investing in hydropower projects including the construction of the Kandadji Dam on the Niger River. However, variability in precipitation and climatic conditions could severely disrupt hydropower generation.

Projections of river flood events are subject to substantial modelling uncertainty, largely due to the uncertainty of future projections of precipitation amounts and their spatial distribution, affecting flood occurrence (see also Figure 4). While the absolute value of 0.14 % is small to begin with, median projections still indicate more than a doubling of national road exposure to floods by mid-century (Figure 12). Although median projections decline again towards the end of the century, they are subject to high modelling uncertainty with the very likely range indicating that road exposure to floods can settle anywhere between a threefold increase and a twofold decrease by 2080 (from 0.07–0.4 % in 2000 to 0.03–1.3 % in 2080). Similarly, median projections of urban land area exposed to floods at least once a year show almost no change (Figure 13), with a very likely range of 0.0–0.3 % by 2080 under RCP6.0. However, it should be noted that projections show the exposure of roads to river floods and exclude, for instance, exposure to floods from excessive precipitation, which is a common phenomenon in Niger, mostly due to its dry, impermeable soils and lack of vegetation [29].

Figure 12: Projections of major roads exposed to river floods at least once a year for Niger for different GHG emissions scenarios.
Figure 13: Projections of urban land area exposed to river floods at least once a year for Niger for different GHG emissions scenarios.

With the exposure of the GDP to heatwaves projected to increase from around 1.7 % in 2000 to 6 % (RCP2.6) or 11 % (RCP6.0) by 2080 (Figure 14), policy planners are strongly advised to start identifying heat-sensitive economic production sites and activities, and integrating climate adaptation strategies such as improved solar-powered cooling systems, “cool roof” isolation materials or switching the operating hours from day to night [30].”

Figure 14: Exposure of GDP in Niger to heatwaves for different GHG emissions scenarios.

References

[26] R. E. Namara, B. Barry, E. S. Owusu, and A. Ogilvie, “An Overview of the Development Challenges and Constraints of the Niger Basin and Possible Intervention Strategies,” Colombo, Sri Lanka, 2011.
[27] C. Domínguez-Torres and V. Foster, “Niger’s Infrastructure: A Continental Perspective,” Washington, D.C., 2011.
[28] OCHA, “Niger: Situation des inondations,” Niamey, Niger, 2019.
[29] E. Fiorillo and V. Tarchiani, “A Simplified Hydrological Method for Flood Risk Assessment at Sub-Basin Level in Niger,” in Renewing Local Planning to Face Climate Change in the Tropics, M. Tiepolo, A. Pezzoli, and V. Tarchiani, Eds. Cham: Springer Nature, 2017, pp. 247–263.
[30] M. Dabaieh, O. Wanas, M. A. Hegazy, and E. Johansson, “Reducing cooling demands in a hot dry climate: A simulation study for non-insulated passive cool roof thermal performance in residential buildings,” Energy Build., vol. 89, pp. 142–152, 2015.

Niger: Agriculture

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

Figure 10: Projections of crop land area exposed to drought at least once a year for Niger for different GHG emissions scenarios.

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

Figure 11: Projections of crop yield changes for major staple crops in Niger for different GHG emissions scenarios assuming constant land use and agricultural management, relative to the year 2000.

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.