Mali – An assessment of vulnerability, climate risks, impacts and trends
The following analyses highlights an approach to assessing vulnerability and climate hazards which supported the ACCCA project:
Climate Change Adaptation from the Bottom Up: Collaboration between Malian Communities and Scientific Organizations to Identify and Implement Responsive Water Management Actions.
The project examines the links between vulnerability and adaptation to climatic changes in the basins of the Sankarani and Baoula rivers to the effects of climatic changes, and also assesses the vulnerability of cotton and corn production to the effects of climate change. The purpose of the project is to help the members of the three pilot communities in southern Mali identify and implement promising water management innovations that could improve household conditions by increasing resilience to climate change.
Study Sites
Who is vulnerable? Where are the most vulnerable regions?
Three case study sites were chosen in three administrative areas of Mali: Kiban (area of Koulikoro), Diouna (area of Ségou) and Massabla dabs the Circle of Bougouni (area of Sikasso), see Figure 1.
The foundation dataset for Mali was used to determine and quantify potential indicators of vulnerable groups. The process begins with vulnerability exposure analysis. This links to a participatory exercise on defining scenarios of the reference vulnerability (changes in the exposure unit), climatic stresses (but also opportunities), and sensitivity of the exposure unit to each stress.
The outcome provides some conclusions regarding coping strategies, vulnerability indicators and adaptation options. Selected graphs and tables are shown here but for the full analysis click here to download the report.
Figure 2: Results of Demographic Health Survey 2001
As risks vary over time and space an underlying this reflects both the changing probability of the risk occurring and the changing scale of consequence when and if the risk occurs. Understanding the underlying dynamics that drive these processes is important. To this end, baseline activities are currently engaged in the quantification of spatial and temporal risks from climate change by leveraging both online and real time access to spatial information with the analytical power of a geographic information system (GIS). The following are examples of these activities: (1) Characterizing vulnerability indicators on a national or regional level, (2) understanding the current trends in these indicators, and (3) analyzing the impacts of climatic changes on populations.
Figure 3: Community Identified Climate Related Hazards. Identified in the ACCCA project
Figure 4: Livelihood zones, production characteristics and hazards
Livelihood zones, production characteristics and the hazards they face. Adapted from FEWS data. The diversity in cropping pattern is very different across regions and within regions. The area comprised betweennorthern Kayes, Koulikoro, Mopti (i.e. Douentza, Koro, Bandiagara, west Tenenkou), southern Tombouctou (southern Gourma-Rharous, west Niafunke), northeastern Niono (Ségou), and southeastern Gao (Meneka) arelargely dependent on rain-fed agriculture. However, since this area falls in the Sahelian zone with a yearly average rainfall of 400mm and high variations in time and in distribution, agricultural production in these areas isuncertain. Around the Delta more opportunities for different types of agriculture exist. Immediately around or in the Delta, at least three types of cropping patterns are practised (irrigation, submersion, and rain-fedagriculture), providing more diversity and lower production risk. The areas concerned are the cercles of Mopti, southern Tenenkou, northeast Youvarou, central Niafunke, Dire, northwest Djenne, Ansongo, Gourma andGao. Further away from the Delta, irrigation is no longer practiced but rain-fed agriculture is combined with rice submersion, and recessional agriculture. These cropping patterns are found in the remaining parts ofNiafunke, Mopti, Youvarou, Bourem and Djenne.
Figure 5. Poverty and Food Aid
Mali with a per capita GDP below 300 US$, or less than 1 dollar per day, is classified among the low incomecountries. In 1998, 69% of the population lived below the poverty line, a problem particularly acute in rural areas where the poverty rate is estimated to be 76%. Physical accessibility remains a problem in the Gao, Kidal and northern Tombouctou regions because of the low population density, limited infrastructures and in some case civil insecurity. In the areas around the Delta and the lakes in Tombouctou, access is a problem especially during the rainy season.
What are the major climate hazards? Where do these occur?
Highlighting the location of specific hotspots in the country where climate-related hazards are experienced or likely to be felt is a key step in identifying intervention areas. The initial screening process begins with this question, which allows the user to reframe the climate change problem in the context of local conditions/constraints and opportunities. This can show whether climate change impacts are likely to be material for a particular development function, activity or service. Moreover, isolating these locations for further examination is a critical starting point. Further analysis of the trends and impacts of these hazards, when combined with key vulnerability indicators will help to narrow down priority zones for specific project targets.
Translating indicators of vulnerability for specific exposure units/stresses (e.g populations at risk of drought) into vulnerability maps, and then defining hotpots and indicators of aggregate vulnerability using foundation datasets such as the one available for Mali the following figures, which highlight the zones within the country that face exposure to specific hazards.
Figure 6: Exposure to floods, calculated from large flood events in historical record
Figure 7: Exposure to droughts in Mali based on events in the historical record
Climatic variability poses significant repercussions for agricultural production, but its spatial and temporal manifestations are considerably varied. The issues before agricultural policy in the face of climate change are complex enough that misunderstanding the full ramifications of events such as temperature extremes, or for that matter, a trend through a specific period such as the 1990s, will have significant impact at the farm level. Disease, pests, droughts and large storms, these are issues of great importance to agriculture and they appear to vary both in space and in time. Understanding local patterns in the context of the immediate region will help guidethe development of viable coping mechanisms, from agronomic practices to crop insurance, in the face of uncertainty regarding both the direction of climate change trends and its magnitude.
The diagnostic capacity to investigate these impacts can be significantly increased by coupling detailed historical meteorological data with innovative analytic methods. On the basis of available data and information, it is possible to analyze the conditions and trends in climate parameters, from the most basic data (e.g. maximum and minimum temperature and rainfall), to more elaborate indicators (duration of the growing season), to complex indices (satisfaction index of water requirements for the growing season) to allow the identification of important thresholds and trigger points on short and medium time scales. This information can be used to assess potentially impacts and identify anticipatory adaptation measures.
A useful starting point is to develop a seasonal calendar for the region (as illustrated below). The seasonal calendar presented here provides guidance for the identification of climate relevant time periods (key dates in terms of climatic thresholds) for cropping cycles. Further exploration, for example, of a changing onset of the growing season would focus attention on the months of April through May, for this particular case.
Figure 8: Seasonal agricultural calendar for maize growing regions. Adapted from FEWS data
Figure 9: San, distribution of days when maximum temperature exceeds 39 degrees during growing season
Analysing the impact of climate change
Climate related stresses can cause major adverse impacts on several sectors, including food productionand agriculture, human health, and water availability, quality and accessibility, among others.Guiding questions:
- Where are these impacts known to occur?
- Where are the impacts of these hazards likely to be felt?
Information on the impacts of hazards can be drawn from:
- Communities
- Disaster preparedness and action plans.
- Inventories, maps and data related to the impact of past hazards.
- IPCC Assessment Reports
Impacts on the population can be mapped to show the number of people potentially affected by specifichazard events. In order to better define project priorities and outputs, it is necessary to specify theimpacts of climate-related hazards on target sectors/areas. The characterization of adverse effects shouldfollow the treatment of issues, whether by sector or vulnerable group, or otherwise. Characterization ofclimate-related effects could be carried out by sectors: Food Production and Agriculture, Human Health,Water availability, quality and accessibility, and Loss of Life and Livelihood. Table 3 provides anexample summary table for impact assessment using this categorization for Mali.
Table 1: Categorising the adverse effects of climate-related hazards. Examples provided by the ACCCA study
Understanging climate trends
A first step in assessing these potential impacts is to highlight or estimate the major current and expectedtrends (direction, magnitude, and extent) of climate-related hazards. The purpose of addressing thefollowing questions is to assess the range of future conditions. This step provides a link between the currentvulnerability (hazards experienced so far), trends in hazards and the need for urgent action. If the trendsobserved above are consistent with the range of scenarios for future climate change, then the rationale forurgent action is much stronger.
Guiding questions:.- What are the documented historical trends in these hazards?- Is the nature and location of these hazards changing, and if so, how?- What kinds of predictions have been made on these hazards for the area in question?The choice of method and data to be used to offer validation and support for observed and predicted trends inclimate-related hazards will among countries and sectors, reflecting data quality and availability, as well asthe time constraints of the project. A useful starting point for evaluating climatic trends is to map key variables and then to categorize these trends as those conforming either to: deviations from normal values or geographic/ temporal shifts in occurrences. An example, drawn from a preliminary analysis of the Mali ACCCA project, is available in the table below.
Figure 10: Decadal Changes in Various Rainfall-Related Events. Notes: the distribution of total monthly rainfall continues to shift towards later in the year the rainy season from April-May to May-June. In addition, the CSIRO model data suggest a reduction in total monthly rainfall during critical cultivation and harvest periods in August to November.
Table 2: Summary table of trends in climate related threats