3.5. Overall Social Vulnerability
The overall social vulnerability map is shown in Figure 7
. This map averages rescaled values from the exposure, sensitivity and adaptive capacity components. Generally, high vulnerability was in the eastern districts of the two basins. Areas of low vulnerability are in urban areas such as the big cities of Dar es Salaam, Morogoro and Dodoma, smaller urban centers and highlands in the southwestern districts of Rufiji basin. Districts with high vulnerability were Ulanga, Kilombero, Njombe, Kilolo, Liwale, Morogoro, Rufiji, Kisarawe, Manyoni and Kilosa, Gairo, Mvomero, Bagamoyo, Kibaha, some pockets in Iringa, Kongwa, Kiteto, Handeni Kilindi, Mkuranga, Temeke, Ilala, Kinondoni and Kisarawe.
Land area and population count statistics (Table 3
) revealed that >80% of the land area and >60% of the total population in the two basins were in areas classified as medium-highest vulnerability. This category represents approximately 200,000 km
of land area and close to 8 million people. The highest proportion of land area and population was found in the medium category of 40–60% vulnerability (49% and 46%, respectively), representing approximately 120,000 km
of land area and close to 6 million people.
Our study focused on generating information that would support prioritization of adaptation interventions in Wami-Ruvu and Rufiji basins using a combination of scientific methods and stakeholder engagement to map communities that were vulnerable to climate variability and change. The results show that these communities were found in areas which experience high exposure as a result of large rainfall declines and high variability coupled with higher temperature, higher sensitivity and low adaptive capacity. Overall, vulnerability maps from this study, regular consultations and engagement with local communities and district administrators provided a critical input to the selection of adaptation options that aligned well with community expectations. For instance, the consultations confirmed three villages as hotspots and identified land tenure as a way to support sustainable management of land, water and forest resources. As a result, WARIDI supported a participatory process with local governments and communities to develop and implement village land use plans (VLUPs) and record 1961 Certificates of Customary Rights of Occupancy (CCROs). In other locations, the vulnerability maps were used as one of several criteria for selecting the locations for 50 water projects which will supply clean water to 520,000 people. Communities surrounding the water supply projects were trained on water-efficient agriculture techniques and water conservation, particularly in dryer areas. Additionally, WARIDI worked with local technical assistance entities to train farmers on Climate Smart Agriculture (CSA) approaches such as crop diversification, agroforestry, improving soil organic matter and using small-scale intensified agriculture practices which improve water use efficiency.
Rainfall and temperature are major factors that influence the wellbeing of communities in Tanzania and East Africa in general. Our results show higher declines and higher variability in total annual rainfall over the past 30 years in the eastern parts of the two basins. This result is consistent with previous observations [1
]. Rainfall decline has a direct implication on water availability in the two basins because major sources of water for various user groups come from surface water sources that depend on rainfall for recharge. Additionally, the eastern areas experience high temperatures and higher evapotranspiration. This observation raises concerns that high evapotranspiration and a declining rainfall will continue to exacerbate water stress, affecting surface water availability for both human and livestock, and reducing biomass and crop yields due to increased evapotranspiration [60
]. This concern is further strengthened by observed land cover changes that impact water resources negatively such as deforestation for agricultural expansion. Deforestation removes vegetation cover that enhances water retention for surface water and regulates evapotranspiration. The rate of deforestation in the two basins has increased in the recent past. This has led to sedimentation of fresh water resources, increased surface run-off and flash floods and reduced the rate of infiltration, ultimately reducing base flows in rivers [61
]. Future projections of temperature changes for Tanzania from most global climate models show an increase of 1–2 times the current increases in the near future (2020–2050) and 2–3 times in the mid and far future (2050–2100) for high greenhouse gas concentration scenarios [62
]. Coupled with an increasing demand from high population growth, water security will continue to be a major concern for water user groups in these basins.
Sensitivity was observed to be higher in rural areas than in urban areas. Notably, malaria was dominant in the southern districts and along the coast south of Dar es Salaam city. Malaria is documented as a leading cause in child mortality in Tanzania, accounting for nearly a fifth of all deaths compared to other diseases, and the mortality rate has shown an increasing trend [63
]. Temperature increase in the two basins has provided previously malaria free areas with conducive environments for vector carrying mosquitoes to thrive. We observed a positive correlation between malaria susceptibility and maximum temperature meaning, that areas that experience higher temperatures have a higher malaria risk. Steady population growth in both basins will further increase the number of people exposed to malaria.
Regionally, climate change has been attributed as a contributing factor to impacts on human health through increases in climate sensitive diseases like malaria [64
] and other water-borne diseases such as diarrhea and cholera. Some of these impacts are already being experienced in some of the highlands in the rural areas of southern Tanzania such as Njombe, Kilolo and Mufindi which have witnessed increases in malaria and are some of the areas in the basins with low adaptive capacity to cope with malaria risk [66
]. This information was corroborated by district officers during the validation exercises where warmer temperatures in these highland areas have been witnessed. Our results also show that availability of health infrastructure such as health centers is lacking or sparsely distributed in rural areas, leading to isolation of some communities from access to health services. Adequate preparedness for climate impacts on the health of communities in the basins will require local government agencies and other development agencies to strategically increase coverage of health services in rural areas in the two basins. This kind of intervention would minimize the isolation of vulnerable communities from health services. This will ensure that these communities have access to health services during crises occasioned by climate extremes such as floods and droughts and other longterm climate change impacts.
Enhancing the adaptive capacity of Wami-Ruvu and Rufiji basin communities to cope with climate shocks will require interventions in a number of areas. Agriculture is one of the major livelihoods in these basins, especially in the southern highlands of Rufiji basin. We observed that many rural areas were in locations that had potential for high crop yields but were in remote areas, taking longer duration to reach major market centers. This physical isolation can lead to negative consequences on availability of food for urban populations, precipitating increases in food prices. Rural farmers who cannot access markets for their produce can also suffer negative economic impacts, consequently affecting household income. The latter is a critical factor to the resilience of households during seasons that experience shocks such as droughts that affect crop yields. Overall, negative impacts on agricultural areas can have detrimental effects on the health and household vulnerability and likely undermine the ability to cope with future climate shocks. It is critically important for government and development partners to enhance the adaptive capacity of vulnerable communities in these basins to current impacts of rainfall declines on smallholder agriculture and availability of water resources for farming while also mitigating likely impacts from projected increases in temperature in the near future.
Our results provided an independent validation of selected districts and provided further evidence that a combination of quantitative and qualitative criteria can be used for prioritizing development assistance effectively. These results supported WARIDI’s rationale for focusing on agricultural livelihoods and water resources management in each district hotspot. They also led to the development of district action plans for integrating climate change into district-wide development plans including interventions in agriculture, forestry, health, water, tourism and wildlife, and were used during facilitated discussions with national ministries including the Ministry of Water, Ministry of Agriculture, Ministry of Natural Resources and Tourism, Presidents Office—Regional Administrative and Local Government and local government authorities. It is worth noting that, while most of the interventions were in districts captured by our vulnerability maps as being hotspots, a good number fell in the lower categories of overall vulnerability. This can be partly explained by the choice of indicators which was influenced by our focus on social vulnerability. Our analysis captured various aspects in which different water user groups, largely comprised of the human population, are impacted by climate variability and other environmental changes. We defined these impacts as those that relate to health, wellbeing and livelihoods.
Temporally consistent climate data are important in climate vulnerability mapping and risk management [67
]. Institutions in Tanzania led by TMA are increasing their capacity to collect and archive weather and climate data for use in climate risk and hydrological assessments. However, the capacity to analyze these data and integrate satellite Earth observations into their assessments is often limited with efforts have been ongoing to improve this capacity [69
]. We used the co-development approach because it provided an opportunity for institutions in the CDT to collaborate in data analysis. It also acted as a means to build capacity of staff at institutions responsible for making data and information used in this study available for decision makers. This approach enabled technical experts in the CDT to work together by using good quality rainfall and temperature data that were generated through blending of station data with satellite proxies to produce vulnerability indices. The co-development team had an equally important role of providing insights on local conditions and supporting the linkage between WARIDI and other local stakeholders in government and other agencies.
Our data integration techniques involved combining high resolution satellite data with coarser resolution socioeconomic data. One advantage with satellite data is that they are consistent and cover vast areas. However, many of these data are proxies for factors that influence vulnerability. On the other hand, socioeconomic data provide data collected directly from household surveys. This means data are collected directly from subjects of a vulnerability study, thus providing better estimates of local conditions. However, even these have disadvantages because publicly available data are often aggregated at administrative units. In our case, most socioeconomic data were at the ward or district level. Comparatively, a grid pixel from the remote sensing data was 25 km
while the average size of wards and districts was 403 km
and 8705 km
, respectively. Artifacts may arise from integrating data at different spatial scales such as abrupt discontinuities across borders may draw attention in differences between areas that are not necessarily present on the ground [43
]. These caveats notwithstanding, the combination of remote sensing and household survey data is gaining popularity as one of the fast growing approaches being used in vulnerability mapping. Various publications have provided more critical perspectives on these approaches and describe in depth their limitations [13
Other data integration challenges exist in vulnerability mapping. A major problem that data analysts in vulnerability mapping studies encounter is dealing with extreme values in data that may impact statistical operations. Through truncation or winsorization, analysts may overcome this challenge by limiting extreme values through statistical transformations. However, this winsorization has the potential to bias results. We encountered this challenge in the population and access to markets indicators and addressed it by combining expert judgement and existing literature on approaches to determining truncation thresholds. For instance, we limited the maximum amount of time to access major towns to 3 h based on international- and country-based recommended practices on access to health services. The World Health Organization (WHO) recommends that access to critical care should be within 2 h while some studies in sub-Saharan Africa have shown that many countries in Africa are yet to achieve this goal to guarantee universal access to healthcare [70
]. By involving locally-based experts with sufficient knowledge of the geography of the study area and by subjecting our mapping outputs to validation by local communities, we were able to partially address the potential biases introduced by the data winsorization. We believe that the effect of data winsorization can only be fully assessed through a rigorous sensitivity analysis and validation. The interpretation of a vulnerability map should consider the fact that sections of the population may feel excluded from developmental programs because of the category they fall in from a mapping perspective, while it may not necessarily mean that they are not vulnerable; rather, the severity is not as high as that of populations in other higher categories. It is important to subject vulnerability maps to rigorous validation with people who understand the target region well to ensure that areas that do not look vulnerable on the map, but are on the ground, are captured when developing and selecting adaptation interventions.
Vulnerability maps can provide objective information for selection of sites for adaptive interventions but only if they are participatory and evidence-based. While they are useful in providing a systematic and reliable way to prioritize adaptation intervention sites, independently, they cannot be sufficient to ensure success in a resilience building activity. Building resilience is an incremental process that is influenced by political interests, availability of budget, motivation of local stakeholders and other factors. Our study provides evidence that the uptake of mapping results into decision making is highly dependent on a participatory process that gets buy-in from communities, key thematic experts, local government, and other stakeholders. The goal of a vulnerability mapping exercise is to identify locations or sections of populations that are most vulnerable and require development assistance to cope with existing and emerging stressors. However, this prioritization risks the shortcomings of excluding other sections of the population that may be identified as having lower vulnerability. It is important that development assistance activities using vulnerability mapping to inform decisions take into consideration both short- and long-term vulnerabilities to the population.