Category: Climate risk profile

Water shortage has been an issue in Tanzania for decades and is likely to continue in the future. Several studies show that climatic changes in Tanzania have resulted in a decrease in total precipitation, a shift of the onset of the rainy season and an increase in the frequency and duration of droughts [14][15]. These changes have materialised, for example, in the extreme decrease of water levels of Lake Victoria and Lake Tanganyika, and the 7-km recession of Lake Rukwa over the past 50 years [16]. Additional challenges related to water availability include an increasing demand associated with agricultural expansion and intensification and with the domestic needs of a growing population [17]. Unreliable precipitation in the highland areas has been the main driver for shifting agricultural production towards lower wetland areas, which offer comparatively fertile soils and year-round water availability [18]. However, the conversion of wetlands in favour of agricultural production has negative trade-off effects on affected ecosystems.

Per capita water availability

Current projections of water availability in Tanzania display high uncertainty under both GHG emissions scenarios. Assuming a constant population level, multi-model median projections suggest no change in per capita water availability over Tanzania by the end of the century under RCP6.0 and only a slight decrease under RCP2.6 (Figure 9A). Yet, when accounting for population growth according to SSP2 projections⁴, per capita water availability for Tanzania is projected to decline by 76 % under both RCPs by 2080 relative to the year 2000 (Figure 9B). While this decline is primarily driven by population growth rather than climate change, it highlights the urgency to invest in water saving measures and technologies for future water consumption.

Spatial distribution of water availability

Projections of future water availability from precipitation vary depending on the region and scenario (Figure 10). Under RCP2.6, water availability will decrease by up to 25 % in northern and south-eastern Tanzania, with most models agreeing on this trend. The picture for RCP6.0 is different: The model agreement on the direction of change is low for all parts of Tanzania.

⁴ 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

[14] U. Adhikari, A. P. Nejadhashemi, M. R. Herman, and J. P. Messina, “Multiscale Assessment of the Impacts of Climate Change on Water Resources in Tanzania,” J. Hydrol. Eng., vol. 22, no. 2, pp. 1–13, 2017.
[15] A. E. Majule and M. A. Lema, “Impacts of Climate Change, Variability and Adaptation Strategies on Agriculture in Semi Arid Areas of Tanzania: The Case of Manyoni District in Singida Region, Tanzania,” African J. Environ. Sci. Technol., vol. 3, no. 8, pp. 206–218, 2009.
[16] Vice President’s Office Division of Environment, “National Adaptation Programme of Action (NAPA),” Dodoma, Tanzania, 2007.
[17] K. Velempini, T. A. Smucker, and K. R. Clem, “Community-Based Adaptation to Climate Variability and Change: Mapping and Assessment of Water Resource Management Challenges in the North Pare Highlands, Tanzania,” African Geogr. Rev., vol. 37, no. 1, pp. 30–48, 2018.
[18] R. Y. M. Kangalawe, “Climate Change Impacts on Water Resource Management and Community Livelihoods in the Southern Highlands of Tanzania,” Clim. Dev., vol. 9, no. 3, pp. 191–201, 2017.

Temperature

In response to increasing greenhouse gas (GHG) concentrations, air temperature over Tanzania is projected to rise (Figure 2). Compared to pre-industrial levels, median climate model temperature increases over Tanzania amount to approximately 1.4 °C in 2030, 1.7 °C in 2050 and 1.6 °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 1.4 °C in 2030, 1.7 °C in 2050 and 2.5 °C in 2080.

Very hot days

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 substantially and with high certainty, in particular over eastern Tanzania (Figure 3). Under the medium / high emissions scenario RCP6.0, the multi-model median, averaged over the whole country, projects 6 more very hot days per year in 2030 than in 2000, 11 more in 2050 and 22 more in 2080. In some parts, especially in eastern Tanzania, this amounts to about 100 days per year by 2080.

Sea level rise

In response to globally increasing temperatures, the sea level off the coast of Tanzania is projected to rise (Figure 4). Until 2050, similar sea levels are projected under both emissions scenarios. Under RCP6.0 and compared to year 2000 levels, the median climate model projects a sea level rise by 11 cm in 2030, 21 cm in 2050 and 41 cm in 2080. This threatens Tanzania’s coastal communities and may cause saline intrusion in coastal waterways and groundwater reservoirs, rendering water unusable for domestic use and harming biodiversity.

Precipitation

Future projections of precipitation are less certain than projections of temperature change due to high natural year-to-year variability (Figure 5). Out of the three climate models underlying this analysis, none of the models projects a clear trend in mean annual precipitation over Tanzania under RCP6.0. Under RCP2.6, two models project a decrease, while for one model, the trend remains unclear. Median model projections for RCP2.6 show a decrease in precipitation by 42 mm until 2080, while median model projections for RCP6.0 show almost no change in precipitation by 2080 compared to year 2000.

Heavy precipitation events

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. This tendency is also found in climate projections for Tanzania (Figure 6), with climate models projecting a slight increase in the number of days with heavy precipitation, from 8 days per year in 2000 to 9 days per year in 2080 under RCP6.0. Under RCP2.6, the number of days with heavy precipitation does not change.

Soil moisture

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 into higher potential evapotranspiration. Annual mean top 1-m soil moisture projections for Tanzania show a decrease of 4 % under both RCP2.6 and RCP6.0 by 2080 compared to the year 2000 (Figure 7). However, looking at the different models underlying this analysis, there is large year-to-year variability and modelling uncertainty, which makes it difficult to identify a clear trend.

Potential evapotranspiration

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 Tanzania indicate a stronger and more continuous rise of potential evapotranspiration under RCP6.0 than under RCP2.6 (Figure 8). Under RCP6.0, potential evapotranspiration is projected to increase by 2.7 % in 2030, 3.8 % in 2050 and 7.1 % in 2080 compared to year 2000 levels.

³ Changes are expressed relative to year 1876 temperature levels using the multi-model median temperature change from 1876 to 2000 as a proxy for the observed historical warming over that time period.

Climate change threatens the health and sanitation sector through more frequent incidences of heatwaves, floods, droughts and storms. Among the key health challenges in Mali are morbidity and mortality through vector-borne diseases, such as malaria, waterborne diseases related to extreme weather events (e.g. flooding), such as diarrhoea, respiratory diseases, malnutrition, HIV / AIDS, meningitis, injury and mortality through extreme weather events [31]. Climate change can impact food and water supply, which can increase the risk of malnutrition, hunger and death by famine. Scientific investigations found a link between extreme weather events and mortality patterns in Mali: Precipitation events of more than 10 mm per day were negatively associated with survival of children under five years of age, while colder temperatures were associated with lower mortality rates among the general population [32], [33].

Furthermore, climate change is likely to lengthen transmission periods and alter the geographic range of diseases, such as malaria or meningitis. Malaria continues to be the primary cause of morbidity and mortality in Mali, particularly among children under the age of 5 [34]. In some regions, malaria risk will likely increase, for instance, due to higher occurrence of flooding, but overall risk is projected to fall due to rising temperatures [35], [36]. Temperature increases could also lead to more frequent outbreaks of meningitis [37]. Mali 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. Access to health care in Mali remains limited and is being further complicated by armed conflict: According to Médecins Sans Frontières (MSF), many public and humanitarian health organisations have limited or even closed down their operations due to armed conflicts [38].

Exposure to heatwaves

Rising temperatures will result in more frequent heatwaves in Mali, leading to increased heat-related mortality. Under RCP6.0, the population affected by at least one heatwave per year is projected to increase from 2 % in 2000 to 16 % in 2080 (Figure 17).

Heat-related mortality

Furthermore, under RCP6.0, heat-related mortality will likely increase from 2.5 to about 12 deaths per 100 000 people per year, which equals a factor of more than five 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

[31] Centers for Disease Control and Prevention, “CDC in Mali,” Atlanta, Georgia, 2018.
[32] P. Han and J. Foltz, “The Impacts of Climate Shocks on Child Mortality in Mali,” Madison, WI, 2013.
[33] B. Bakshi, R. J. Nawrotzki, J. R. Donato, and L. S. Lelis, “Exploring the Link Between Climate Variability and Mortality in Sub-Saharan Africa,” Int. J. Environ. Sustain. Dev., vol. 18, no. 2, pp. 206–237, 2019.
[34] U.S. President’s Malaria Initiative, “Mali Country Profile,” Washington, D.C., 2017.
[35] 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.
[36] 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.
[37] 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.
[38] Médecins Sans Frontières, “Violence in Central Mali Has Reached Unprecedented Levels,” 2019. Online available: https://www.msf.org/mali-conflict-curfew-and-floods-put-healthcare-out-reach [Accessed: 24-Feb-2020].

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 [28]. 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 plants 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.

Species richness

Model projections of species richness (including amphibians, birds and mammals) and tree cover for Mali are shown in Figure 15 and 16, respectively. Under RCP6.0, species richness is projected to decrease by 10 % in the southern half of Mali by 2080 compared to the year 2000. In the centre, however, species richness is projected to increase by up to 30 % (Figure 15). All models agree on this trend.

Tree cover

In terms of tree cover, model agreement is lower: Models project increases in tree cover of up to 1.5 % in parts of southern Mali under RCP6.0 (Figure 16). Projections of both species richness and tree cover under RCP2.6 are subject to high modelling uncertainty.

Although these results suggest a positive picture for climate change impacts on tree cover, 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 [29]. For example, rapid growth of agricultural production and logging have resulted in high rates of deforestation: Mali has lost 330 000 ha of forest cover in the period from 2001 to 2018, which is equivalent to a 13 % decrease since 2000 [30]. Given Mali’s rapid population growth, this trend is likely to continue and will impact animal and plant biodiversity.

References

[28] T. M. Shanahan, K. A. Hughen, N. P. McKay, J. T. Overpeck, C. A. Scholz, W. D. Gosling, D. William, 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.
[29] 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.
[30] Global Forest Watch, “Mali.” Online available: https://www.globalforestwatch.org [Accessed: 25-Feb-2020].

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).

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].

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.

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.

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

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

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.

Temperature

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

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

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

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

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

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.

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

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

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].

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

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

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.