Water level variations and flood zones in Lake Tanganyika and Nyangara marsh: Impact analysis and innovative solutions to prevent future damage

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To prevent such damage, it is necessary to determine exactly which areas are always subject to flooding. This study, based on documentation, field surveys and satellite image processing using remote sensing techniques, aimed to identify the variation in water levels in the Nyangara marsh and Lake Tanganyika over the decade 2011–2021, to map the flood-prone areas in its northern and northeastern parts and to document the impact of these floods on riparian populations, in order to propose possible solutions to avoid damage in future years. Our results show that 2014, 2016 and 2019 were the years with the lowest water levels (especially for the Nyangara marsh), while 2017 and 2021 were the years of heavy flooding with serious negative impacts on riparian populations, namely the loss of inhabited and arable land, the disruption of socio-economic activities and environmental degradation. The survey revealed that the relocation of riverside populations, the creation of a buffer zone between the lake/marsh and dwellings, reforestation and the application of the law relating to the respect of 50m of shoreline are the priority solutions for mitigating the consequences of these floods. In this work, we discuss these proposals from the respondents and highlight more practical flood mitigation strategies adapted to this environment. Disaster Flooding Rural Housing Agriculture Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Aquatic ecosystems represent both a source of wealth and a threat for local residents. The greatest threat of these ecosystems to their riparians is undoubtedly the flooding they cause, which is a source of disease, damage and loss of human life, property and infrastructure, as well as disruption of public services (Talbot et al. 2018 ). Floods are thus classified as the natural hazard that causes the most casualties and damage worldwide (Iratxe and Longuépée 2010 ), to the extent that the duality of aquatic ecosystems as both wealth and threat, long considered beneficial, is now seen as broken (Bravard and Petit 1997 ). Lake Tanganyika, one of the Great Lakes of the East African Rift, shared by 4 countries (Democratic Republic of the Congo, Burundi, Zambia, Tanzania), is located in a climatic zone with two seasons (dry and rainy). Its current water level (773 m above sea level, generally varying by around 1 m between the two seasons) and surface area (32900 km², 45% of which is in the Democratic Republic of the Congo (DRC), 41% in Tanzania, 8% in Burundi and 6% in Zambia) are the result of major variations over the course of its history (Alin et al. 2003; Cohen et al. 2005 ; Nicholson 1999 ). In the early years of its existence, 12 million years ago, the Lake reached the volcanic dam south of present-day Lake Kivu (Fermon 2007 ). As the bottom of the plain continued to collapse, climatic variations caused most of the Ruzizi plain to gradually flood, leaving vestiges of the former Lake Tanganyika in the form of all the natural ponds (Kyamvubu, Nyangara, Ntangaro, etc.) and marshes found in the Ruzizi plain. Over the last 2800 years, the Lake level has been relatively stable, fluctuating between 765 and 775 meters above sea level for most of this period (Cohen et al. 1997 ). Between 1900 and 2000 years ago, the Lake level fluctuated by around one metre (Fermon 2007 ), which represents an appreciable quantity of water given the lake's vast surface area; a quantity that can overflow and swallow up houses. This research is part of the same context, as well as that of Objective 11 of the Sustainable Development Goals (SDG), which speaks of sustainable cities and communities. It aims to assess the various variations in water levels in the extreme northern part of Lake Tanganyika and the Nyangara marshes over the decade 2011–2021, and to analyze the impact of these fluctuations on the local populations, in order to propose possible solutions for a better future. It is well known that assessing the impact of flooding provides elements for decision-making, enabling public policy on risk prevention and protection against flooding to be directed and/or modified (Hubert and Ledoux 1999 ). The main problem of this research is based on the following questions: (1) what are the dynamics of the water level of Lake Tanganyika and Nyangara marsh during the decade 2011–2021? (2) What is the distance (zone) often affected by variations in the water level of Lake Tanganyika and the Nyangara marshes, and what is its impact on riparian populations? and (3) What are the possible solutions to avoid and/or reduce the damage caused by these different variations in water level, in order to improve the development and urbanization of the town of Uvira and its surroundings? Methods Study area This study was carried out in the extreme southern part of the Ruzizi Plain, which is located in a narrow, elongated geomorphological flat about 30 km wide and 70 km long. This flat area is bordered to the east by the Mirwa escarpments and to the west by the steep slopes of the Mitumba mountains, which often exceed 100% (Fig. 1 ). As elsewhere in the Ruzizi plain, this zone is characterized by contrasting altitudes ranging from 767 m to 3291 m from east on the Ruzizi to west in the Mountains Mitumba chain (Nacishali 2020 ). Its geomorphology is in the western branch of the East African Rift, characterized by a stepped fault morphology consisting of a succession of horsts and grabens (Ilunga 1991 ). Its relief is characterized by two clearly distinct geomorphological complexes: the coastal plain and the eastern slopes of the Mitumba Mountains (Ilunga 2006 ). Due to its latitude of between 3°21' and 3°27' south, this area lies entirely within the equatorial zone, with an average temperature of around 30°C at the level of Lake Tanganyika. However, due to its altitude, two main seasons dominate in this region: the rainy season from October/November to May, characterized by light winds, high humidity, heavy rainfall and frequent thunderstorms; and the dry season from June to September/October, with moderate rainfall accompanied by strong, regular southerly trade winds (Fermon 2007 ). The average annual temperature is 24.2° and the annual thermal amplitude is very low, around 0.7°C (Ilunga 1991 ). As for the soil, the major pedogenetic process is ferruginization, characterized by the coexistence of kaolinite and type 2/1 clays such as illites and montmorillonite, which justify the presence of clay horizons (Bt) (Nacishali 2020 ). Analysis of Landsat images revealed that 40–60% of the land originally covered by forest, and around 100% in the northern basin, had been cleared, as evidenced by progressive erosion, incision of watercourses and gully formation, all of which are features associated with deforestation. Within this environment, the study area covers 39.3539 km² and is located between 29°09'06'' and 29°12'36'' east longitude and between 03°18'36'' and 03°21'24,12'' south latitude. Methodology The results presented in this study were obtained through the concomitant use of documentary techniques, the use of Geographic Information System (GIS) tools to map the area affected by water level variations in Lake Tanganyika and the Nyangara marshes, and a survey of local populations to ascertain their perceptions of flooding. Geographic Information System (GIS) After checking the periods that have marked this area on Google Earth over the past decade (2011–2022), we downloaded 5 Landsat 8 satellite images from the Multispectral Scanner sensor (MMS, resolution: 80m). These images were processed by Envi software, which, together with the color composition into different classes, enabled us to perform a supervised classification. In our case, 10 coherent thematic classes differentiated the main components of the environment, which were then combined into 5 classes: water, wetlands, vegetation, fields and housing + soil. We then used the vectors (shp) to determine the surface area of each class. For greater precision, field data, thematic maps and high-resolution satellite imagery (Google Earth) were used to generate control points and serve as a qualitative tool for validating the results. The layout of the various maps generated and the determination of the surface areas of the different zones were carried out in Qgis. Field survey The survey covered the population of the northern part of the Uvira town, precisely in the commune of Kavimvira and the Kagando groupement, which borders Lake Tanganyika and the Nyangara marshes, and is therefore exposed to the harmful effects of their overflowing waters. The inclusion criterion for the sample was to be at least 30 years old. A survey questionnaire consisting of 15 questions divided into 4 groups was drawn up and administered to a random sample of 95 people out of an estimated population of 10242. This sample size was calculated using the Bouchard (2010) formula with a margin of error of 5%: \(\text{N}.\text{C}=\frac{\text{n}}{1+\text{n}/\text{N}}\) with N.C corrected sample size, N: population size corresponding to 10242 inhabitants in our case and n: sample size for an infinite universe corresponding to 96 according to Bouchard (2010). In addition to this survey, a meeting was held with 25 people over the age of 50 to gather further information to inform our judgement. This age criterion was the most important, as we found that this was the only category of respondents who claimed to have experienced other periods of rising water levels in Lake Tanganyika. The various data obtained in the field were processed using SPSS and Ms Excel software. Results Remote sensing results Analysis of remote sensing data shows that water levels in both Lake Tanganyika and Nyangara Marsh are highly variable from year to year, with variations in Nyangara Marsh being more considerable in absolute terms than those in Lake Tanganyika (Table 1 ). Table 1 Change in surface area (in Km²) covered by water from 2011 to 2021 2014 2016 2017 2019 2021 Lake Tanganyika 4.390 4.286 4.408 4.385 4.872 Nyangara marsh 0.959 1.261 2.540 0.997 1.290 From these results, it can be seen that the Nyangara marsh can easily see the surface area of its water increase from one to over 2.65 times during periods of high flooding (even 2017). Although less variable in absolute terms (i.e. only a difference of 0.586 Km² between the low-water period, i.e. 2016, and the high-water period, i.e. 2012) than that of the Nyangara marshes, it can still be seen that the rising waters of Lake Tanganyika sometimes affect dwellings located on the south side of the road leading to Bujumbura (Burundi's capital city) (Fig. 2 ), more than 145 m from the north shore of Lake Tanganyika. The years 2014, 2016 and 2019 were characterized by a sharper drop in the water level of the Nyangara marsh, leaving wetlands that bear witness to previous periods of high flooding (Fig. 2 ) and which, at certain times, are colonized by vegetation and/or remain as areas with clay deposits that later develop desiccations characteristic of a long dry season. This drop in water level was highlighted by 82.4% of our respondents, who stated that the water level had fallen, particularly in the Nyangara marshes and on Lake Tanganyika, and cited the lack of rainfall during this period as the cause. Although marked by a significant withdrawal of water, the years 2016, 2019 mark vast expanses of wetlands. This wetland is also observed in 2021, which bears witness to the fluctuating surface area of the Nyangara marsh. In our interviews with older people (over 50 years), the surface areas occupied in 2016 and 2021 were considered to be the normal (average) level of this marsh. During the years considered for this study, 2017 was the year in which Nyangara marsh extinguished the largest area, i.e. 2.540 km² equivalent to twice its normal area. With regard to the limits reached by variations in the water levels of these two aquatic ecosystems, Figs. 3 and 2 show that, over the last 10 years, the waters of Lake Tanganyika have, in the years 2017 and 2021, risen to flood the south-eastern part of the study area, mainly affecting the side of the border between the Uvira town and the Bujumbura city, but also the village of Gatumba on the Burundian side (Figs. 4 and 5 ), which are among the areas most likely to be flooded once the Tanganyika floods (Fig. 4 ). Indeed, this mapping shows that the area most affected by flooding on Lake Tanganyika is located on its eastern side, affecting the Gatumba area the most (Fig. 4 ). As for the Nyangara marsh, the areas most affected are located on the north and south sides of the marsh (Fig. 4 ). Some water lines extend towards the west (Fig. 4 ). The red zone extends along both sides, with an average distance of 150 m and an area of 0.959 km². There is a large wetland zone located to the north of the marsh, which is susceptible to flooding, mainly affecting the fields of the Kagando/Kiliba housing estate (Fig. 4 ). This zone covers an area of 0.586 km² with an average length of 125 m, making the road to Bujumbura vulnerable. A large wetland area to the east of the Lake submerges the entire road leading to Bujumbura. From the center to the west, a red column extends as far as Kavimvira, making riverside infrastructures more vulnerable (Fig. 5 ). Local people's perceptions of flooding and possible solutions The results of surveys of the local population exposed to flooding from rising Lake Tanganyika and the Nyangara marshes show that the Nyangara marshes have never completely disappeared during the various fluctuations in water levels, as attested by 77.9% of those surveyed (Table 2 ). Fifty-five point eight percent of this same population believe that this variation is regular and is related to the variation in the water level of Lake Tanganyika, as stated by 41.1% of respondents (Table 2 ). Table 2 Respondents' knowledge of historical water level variations in Nyangara marsh and Lake Tanganyika Questions Responses Number % Has the level of Lake Tanganyika and/or the Nyangara marshes risen again in the last decade or so? Yes 74 77.9 No 14 14.7 Abstention 7 7.4 Is this variation in water level regular over time? Yes 53 55.8 No 8 8.4 Abstention 34 35.8 Do the waters of the Nyangara marshes rise and fall at the same rate as those of Lake Tanganyika? Yes 39 41.1 No 20 21.1 Abstention 36 37.9 As for the causes of flooding, 7 causes were cited by respondents who had been flooded at least once, including the 3 most frequent: heavy rainfall during the rainy season, deforestation and sediments (91.6%-51.6%-50.5% of respondents respectively) (Table 3 ). Table 3 Causes and consequences of flooding in the study area Questions Responses Number % Flood victims Yes 70 73.7 No 15 15.8 Abstention 10 10.5 Causes of flooding Heavy rains 87 91.6 Flat relief 35 36.8 Deforestation 49 51.6 Tectonics 7 7.4 Sediments 48 50.5 Climate disturbance 34 35.8 Anarchic buildings 31 32.6 Others (religious beliefs, bad wind, etc.) 8 8.4 Consequences of flooding Environmental degradation 93 97.9 Loss of basic infrastructures 48 50.5 Disruption of daily activities 70 73.7 Food insecurity 42 44.2 Social insecurity, 70 73.7 Loss of property 93 97.9 Loss of human life 41 43.2 Others (illnesses, etc.) 1 1.1 In terms of the consequences of flooding reported by people living near these entities, we count the degradation of the aquatic environment (97.9% of respondents) and the loss of property (97.9% of respondents) (Table 3 ). The loss of human life was also mentioned, and was characterized above all by the drowning of young children. Finally, 96.8% of those surveyed confirmed that flooding from Lake Tanganyika and the Nyangara marsh was responsible for a number of socio-economic impacts on the lives of the people of Kamvinvira and the Kagando/Kiliba township (Table 4 ). Table 4 Socio-economic impact of rising lake and marsh levels Questions Responses Number % Do floods have an impact on socio-economic activities? Yes 92 96.8 No 1 1.1 Abstention 2 2.1 Socio-economic activities affected Education 87 91.6 Health 63 66.3 Transport and commerce 74 77.9 All activities 38 40.0 Others 64 67.4 Reaction from authorities, local organizations and private individuals. Medical assistance to victims 76 80.0 Distribution of food and other necessities 16 16.8 Relocation and offering shelter to victims 6 6.3 No reaction at all 69 72.6 Table 4 shows that the activities most disrupted by flooding are education (91.5%), as schools become shelters for flood victims, and some education workers (pupils and teachers) are also victims. Transport and commerce come in second place, as roads are cut off and goods cannot be transported to market. Health is deteriorating in this area due to the lack of shelter and poor housing conditions in places where people gather (in schools and churches). This problem was declared and confirmed by 66.3% of our respondents. Discussion As already noted by Nicholson ( 1999 ), Alin et al. (2003) and Cohen et al. ( 2005 ), and as evidenced by the respondents' answers in this study, the level of Lake Tanganyika remains variable over time. The vast majority of respondents (51.6%) attributed these variations to extensive deforestation on the slopes overlooking the Lake and the Nyangara marshes. Indeed, it has been shown that over the last four decades, almost 100 percent of the originally forested land in the northern watershed of Lake Tanganyika had been completely cleared (Cohen 1991 ) by the ever-growing population in search of firewood, charcoal and land for subsistence farming or grazing (Fermon 2007 ), transforming these areas into vast cultivated areas and grasslands (Azanga et al. 2016 ). This subsistence farming, carried out in disregard of all the cultivation techniques appropriate to these types of sites, deforestation and clearing cause severe soil erosion in this area (Mwenyemali and Kahindo 2014 ). The eroded soil ends up in Lake Tanganyika, its tributary rivers and the Nyangara marshes. This ever-increasing sedimentation in the lake (Tiercelin and Mondregeur 1991) and Nyangara marshes reduces their depths, thus raising their water levels and causing flooding. It is therefore understandable that with this relatively horizontal central topography (Ilunga 1991 ) and a water level oscillation of around one meter (Fermon 2007 ), the Ruzizi plain, and principally our study area, remains prone to flooding whenever above-average rainfall is recorded. Some of these floods could cause the waters of the Tanganyika and Nyangara rivers to mix, thus cutting off the Uvira-Bujumbura road, as was the case in 2021 (observed in this study) and in 1960 and 1963 (testimonies of old interviewees). Floods are never without consequences; consequences well documented elsewhere (Talbot et al. 2018 ; Njogu 2021 ). In the case of our study area, the education system and churches proved to be the most affected. Indeed, schools and churches are among the real estate infrastructures that are flooded and therefore unusable. Unfortunately, during the floods the schools and churches that remain safe from the floods are directly requisitioned by the emergency services of non-governmental organizations (NGOs) and religious confessions rather than those of the public sector (the State), and transformed into places of refuge and cantonment, demonstrating that the DRC, and the Uvira town in particular, is not deviating from the general pattern of developing countries faced with floods and many other natural disasters, i.e. reacting to the consequences rather than being proactive in managing these disasters (Njogu 2021 ). As a result, the State is obliged to spend more than necessary to stem the effects of flooding, as was the case in Kenya, for example (Njogu 2021 ). In our study area, however, it is NGOs, religious confessions, people of good will and local associations that come to the aid of flood victims; their assistance is limited to medical aid and food and goods. As a result, the road and commercial infrastructures (markets and stores) also damaged by the floods are never rebuilt, with serious repercussions for the economy of the study area and the social well-being of the population. Last but not least, these floods cause ecological disruption, forcing certain animals, such as hippos, to leave the Ruzizi River to find themselves in the midst of the population, creating conflicts between humans and wild animals. As far as possible solutions are concerned, contrary to the proposals put forward by several environmental civil society players and political-administrative authorities, as well as by some of the respondents to this study, to relocate the inhabitants of areas affected by and/or likely to be flooded by Lake Tanganyika and/or the Nyangara marshes, we believe that this is not the appropriate solution. Indeed, Lake Tanganyika and the Nyangara marshes are part of Uvira's immediate and daily environment, and contribute to its beauty and vitality. Uvira is not the only coastal city in the world, and not even the only coastal city on Lake Tanganyika. Yet, unlike other coastal cities on Lake Tanganyika such as Bujumbura, Kigoma, Mpulungu, etc., floods are very often reported here. While the topographical features of the Uvira town make it particularly vulnerable to this kind of disaster (Mwenyemali and Kahindo 2014 ), it remains true that they need to be prevented and mitigated by adopting a multifaceted approach involving people from different specialties (politicians, urban planners, environmentalists, biologists, geologists, agronomists, rural development technicians, etc.) having to come from the scientific world, politics, NGOs, churches and local communities. In concrete terms, this involves (1°) reducing erosion in the Lake Tanganyika watershed by developing soil conservation measures (hedges around fields, terraced cultivation, retention of eroded material using gabions and/or protection of bare soil by mulching), training the population in appropriate cultivation practices on sloping sites, and banning construction on the mountainsides overlooking Lake Tanganyika; (2°) the sustainable management of timber resources by protecting the forest relics in the Lake Tanganyika watershed and, on the other hand, its enhanced reforestation through the development of agroforestry and the planting of trees generating sustainable timber not originating from forests; (3°) the strict application of regulations concerning respect for the 50m shoreline of Lake Tanganyika, so that people who have taken up residence and infrastructures built in this zone are obligatorily relocated without any excuse, by trying to establish responsibilities for the allocation of plots of land in these areas, so that these relocations can take place in strict compliance with the law. Conclusion The Nyangara marsh has seen several variations in water level over the decade 2011–2021. And these variation are very often associated with those of Lake Tanganyika, which is in permanent communication with the latter. During periods of high water, flooding causes a wide range of damage, including loss of property and destabilization of aquatic ecosystems, leading to social and economic disruption for the population living in the area. Although the negative impacts of these floods are considerable, the local authorities seem to be unconcerned. Only a multifaceted approach involving people from different specialties and sectors of life should make it possible to curb the consequences of these floods, and at best to prevent them in time. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing interests The authors have no relevant financial or non-financial interests to disclose. Author contributions Mashauri Ndabaga : Conceptualized the study, designed the methods and study design, performed fieldwork and data analyses, drafted the original manuscript Ahimidiwe Bagi Nelson : Performed fieldwork, edited and commented on the manuscript Mulungula Pascal Masilya: Conceptualized the study, designed the methods and study design, performed data analyses, edited and commented on the manuscript. Acknowledgments We would like to thank all the respondents who willingly gave up some of their precious time to provide us with the information we needed. References Ahmad QK (2006) Changement climatique, inondations et gestion des crues : le cas du Bangladesh. Hérodote 121 :73-94 Alin SR, Cohen AS (2003) Lake-level history of Lake Tanganyika, Est Africa, for the past 2500 years based on astracode-inferred water-depth. Paleogeogr. Paleoclimatol. 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Flood Risk Manag. 14(4):e12746. https://doi.org/10.1111/jfr3.12746 Talbot CJ, Bennett EM, Cassell K, Hanes DM, Minor EC, Paerl H, Raymond PA, Vargas R, Vidon PG, Wollheim W, Xenopoulos MA (2018) The impact of flooding on aquatic ecosystem services. Biogeochemistry 141:439-46. https://doi.org/10.1007/s10533-018-0449-7 Tiercelin JJ, Mondeguer A (1991) The geology of the Tanganyika trough. In: Coulter GW (ed) Lake Tanganyika and its Life. Oxford University Press, London, pp 7-48 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4248196","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":292636309,"identity":"c46137a0-1abc-4b4c-948d-078256a1c86a","order_by":0,"name":"Mashauri Ndabaga","email":"","orcid":"","institution":"Institut Supérieur Pédagogique de Bukavu: Institut Superieur Pedagogique de Bukavu","correspondingAuthor":false,"prefix":"","firstName":"Mashauri","middleName":"","lastName":"Ndabaga","suffix":""},{"id":292636310,"identity":"cad8d8a9-23a4-4cbd-82cb-ba3320af228d","order_by":1,"name":"Ahimidiwe Bagi Nelson","email":"","orcid":"","institution":"Institut Supérieur Pédagogique de Bukavu: Institut Superieur Pedagogique de Bukavu","correspondingAuthor":false,"prefix":"","firstName":"Ahimidiwe","middleName":"Bagi","lastName":"Nelson","suffix":""},{"id":292636311,"identity":"5688a12d-907f-43b6-8127-1bab3487f8e3","order_by":2,"name":"Masilya Mulungula Pascal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYNCCAiBmZm5gYKhgYDAACVQQ1AJSxswI1HIGquUMUVoYgFoY24jQYs5+/OGHHwbb5OXbGdskfs47LG/O3nyA4eAe3Fose3KMJXsMbhtuOMzYJtm77bDhzp5jCQwHnuFx0oEcNgYeg9uMG5iBtvBuO8y44UaOAfOHA3i0nH/+jPGPwW37+c1AW/7OOWwP0sJwAJ+WGwlmzEBbEhuADpPmbTicSFCL5Yw3xtIyBreTgX5ptpY5lp684cyxhAP4tJjzpz/8+Kbitu38/sMHb76psbbdcLz54AO8DkNis0gwMDSDWXg0oGph/sDAUIdP8SgYBaNgFIxQAABe+V2NjDBZxwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6205-2004","institution":"Institut Supérieur Pédagogique de Bukavu: Institut Superieur Pedagogique de Bukavu","correspondingAuthor":true,"prefix":"","firstName":"Masilya","middleName":"Mulungula","lastName":"Pascal","suffix":""}],"badges":[],"createdAt":"2024-04-10 15:25:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4248196/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4248196/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55380875,"identity":"5b816c9f-f17c-4ec4-aabd-72a64e311b3c","added_by":"auto","created_at":"2024-04-26 13:48:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":661379,"visible":true,"origin":"","legend":"\u003cp\u003eMorphological situation of the Ruzizi plain (adapted from Nacishali 2020)\u003c/p\u003e","description":"","filename":"Fig1.tiff.png","url":"https://assets-eu.researchsquare.com/files/rs-4248196/v1/3029b9b9828fd92095aca3d6.png"},{"id":55380873,"identity":"e50baa68-a27e-4a4d-8730-c8139ad83aa7","added_by":"auto","created_at":"2024-04-26 13:48:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":772848,"visible":true,"origin":"","legend":"\u003cp\u003eMap of areas affected by flooding in the Nyangara marshes and Lake Tanganyika from 2014 to 2021\u003c/p\u003e","description":"","filename":"Fig2.tiff.png","url":"https://assets-eu.researchsquare.com/files/rs-4248196/v1/fec98c3ef1d2e57a966a4cea.png"},{"id":55380872,"identity":"5b1ed2be-dec0-4a79-90df-f91177c5e1a1","added_by":"auto","created_at":"2024-04-26 13:48:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":406188,"visible":true,"origin":"","legend":"\u003cp\u003eCharacteristic limits reached by water level variation in Lake Tanganyika and Nyangara marsh between 2011 and 2021\u003c/p\u003e","description":"","filename":"Fig3.tiff.png","url":"https://assets-eu.researchsquare.com/files/rs-4248196/v1/581f3b3f9914b9aad23abfb6.png"},{"id":55380876,"identity":"a92df78a-20f6-4e4d-9c8a-c3b80ccf4b1c","added_by":"auto","created_at":"2024-04-26 13:48:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":751952,"visible":true,"origin":"","legend":"\u003cp\u003eFlood zone and buffer zone delimitation map for the northern part of Lake Tanganyika and Nyangara marsh\u003c/p\u003e","description":"","filename":"Fig4.tiff.png","url":"https://assets-eu.researchsquare.com/files/rs-4248196/v1/cc8b3cdba86ee3c74d4cca25.png"},{"id":55380874,"identity":"2c8f1085-d1b7-4e88-8f1d-79d6385d192f","added_by":"auto","created_at":"2024-04-26 13:48:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":449904,"visible":true,"origin":"","legend":"\u003cp\u003eIn Kiliba, a pupil on his way to school by pirogue after the Nyangara swamp overflowed (left image) and at the Gatumba border between the Uvira town and Bujumbura city, the Migration General Management offices of the Democratic Republic of the Congo were completely swallowed up in the 2022 flood (right image)\u003c/p\u003e","description":"","filename":"Fig5.tiff.png","url":"https://assets-eu.researchsquare.com/files/rs-4248196/v1/2108850ee78b59b263b79f38.png"},{"id":57147492,"identity":"31fd9c02-c40d-4f31-8be9-198ce76353b2","added_by":"auto","created_at":"2024-05-25 22:55:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4123929,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4248196/v1/11b62d0c-31c6-47ad-b27f-5a3b72bbe3d1.pdf"}],"financialInterests":"","formattedTitle":"Water level variations and flood zones in Lake Tanganyika and Nyangara marsh: Impact analysis and innovative solutions to prevent future damage","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAquatic ecosystems represent both a source of wealth and a threat for local residents. The greatest threat of these ecosystems to their riparians is undoubtedly the flooding they cause, which is a source of disease, damage and loss of human life, property and infrastructure, as well as disruption of public services (Talbot et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Floods are thus classified as the natural hazard that causes the most casualties and damage worldwide (Iratxe and Longu\u0026eacute;p\u0026eacute;e \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), to the extent that the duality of aquatic ecosystems as both wealth and threat, long considered beneficial, is now seen as broken (Bravard and Petit \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1997\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLake Tanganyika, one of the Great Lakes of the East African Rift, shared by 4 countries (Democratic Republic of the Congo, Burundi, Zambia, Tanzania), is located in a climatic zone with two seasons (dry and rainy). Its current water level (773 m above sea level, generally varying by around 1 m between the two seasons) and surface area (32900 km\u0026sup2;, 45% of which is in the Democratic Republic of the Congo (DRC), 41% in Tanzania, 8% in Burundi and 6% in Zambia) are the result of major variations over the course of its history (Alin et al. 2003; Cohen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Nicholson \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). In the early years of its existence, 12\u0026nbsp;million years ago, the Lake reached the volcanic dam south of present-day Lake Kivu (Fermon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). As the bottom of the plain continued to collapse, climatic variations caused most of the Ruzizi plain to gradually flood, leaving vestiges of the former Lake Tanganyika in the form of all the natural ponds (Kyamvubu, Nyangara, Ntangaro, etc.) and marshes found in the Ruzizi plain. Over the last 2800 years, the Lake level has been relatively stable, fluctuating between 765 and 775 meters above sea level for most of this period (Cohen et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Between 1900 and 2000 years ago, the Lake level fluctuated by around one metre (Fermon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), which represents an appreciable quantity of water given the lake's vast surface area; a quantity that can overflow and swallow up houses. This research is part of the same context, as well as that of Objective 11 of the Sustainable Development Goals (SDG), which speaks of sustainable cities and communities. It aims to assess the various variations in water levels in the extreme northern part of Lake Tanganyika and the Nyangara marshes over the decade 2011\u0026ndash;2021, and to analyze the impact of these fluctuations on the local populations, in order to propose possible solutions for a better future. It is well known that assessing the impact of flooding provides elements for decision-making, enabling public policy on risk prevention and protection against flooding to be directed and/or modified (Hubert and Ledoux \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main problem of this research is based on the following questions: (1) what are the dynamics of the water level of Lake Tanganyika and Nyangara marsh during the decade 2011\u0026ndash;2021? (2) What is the distance (zone) often affected by variations in the water level of Lake Tanganyika and the Nyangara marshes, and what is its impact on riparian populations? and (3) What are the possible solutions to avoid and/or reduce the damage caused by these different variations in water level, in order to improve the development and urbanization of the town of Uvira and its surroundings?\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eThis study was carried out in the extreme southern part of the Ruzizi Plain, which is located in a narrow, elongated geomorphological flat about 30 km wide and 70 km long. This flat area is bordered to the east by the Mirwa escarpments and to the west by the steep slopes of the Mitumba mountains, which often exceed 100% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs elsewhere in the Ruzizi plain, this zone is characterized by contrasting altitudes ranging from 767 m to 3291 m from east on the Ruzizi to west in the Mountains Mitumba chain (Nacishali \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Its geomorphology is in the western branch of the East African Rift, characterized by a stepped fault morphology consisting of a succession of horsts and grabens (Ilunga \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Its relief is characterized by two clearly distinct geomorphological complexes: the coastal plain and the eastern slopes of the Mitumba Mountains (Ilunga \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Due to its latitude of between 3\u0026deg;21' and 3\u0026deg;27' south, this area lies entirely within the equatorial zone, with an average temperature of around 30\u0026deg;C at the level of Lake Tanganyika. However, due to its altitude, two main seasons dominate in this region: the rainy season from October/November to May, characterized by light winds, high humidity, heavy rainfall and frequent thunderstorms; and the dry season from June to September/October, with moderate rainfall accompanied by strong, regular southerly trade winds (Fermon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The average annual temperature is 24.2\u0026deg; and the annual thermal amplitude is very low, around 0.7\u0026deg;C (Ilunga \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). As for the soil, the major pedogenetic process is ferruginization, characterized by the coexistence of kaolinite and type 2/1 clays such as illites and montmorillonite, which justify the presence of clay horizons (Bt) (Nacishali \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Analysis of Landsat images revealed that 40\u0026ndash;60% of the land originally covered by forest, and around 100% in the northern basin, had been cleared, as evidenced by progressive erosion, incision of watercourses and gully formation, all of which are features associated with deforestation. Within this environment, the study area covers 39.3539 km\u0026sup2; and is located between 29\u0026deg;09'06'' and 29\u0026deg;12'36'' east longitude and between 03\u0026deg;18'36'' and 03\u0026deg;21'24,12'' south latitude.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMethodology\u003c/h2\u003e \u003cp\u003eThe results presented in this study were obtained through the concomitant use of documentary techniques, the use of Geographic Information System (GIS) tools to map the area affected by water level variations in Lake Tanganyika and the Nyangara marshes, and a survey of local populations to ascertain their perceptions of flooding.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGeographic Information System (GIS)\u003c/h2\u003e \u003cp\u003eAfter checking the periods that have marked this area on Google Earth over the past decade (2011\u0026ndash;2022), we downloaded 5 Landsat 8 satellite images from the Multispectral Scanner sensor (MMS, resolution: 80m). These images were processed by Envi software, which, together with the color composition into different classes, enabled us to perform a supervised classification. In our case, 10 coherent thematic classes differentiated the main components of the environment, which were then combined into 5 classes: water, wetlands, vegetation, fields and housing\u0026thinsp;+\u0026thinsp;soil. We then used the vectors (shp) to determine the surface area of each class. For greater precision, field data, thematic maps and high-resolution satellite imagery (Google Earth) were used to generate control points and serve as a qualitative tool for validating the results. The layout of the various maps generated and the determination of the surface areas of the different zones were carried out in Qgis.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eField survey\u003c/h2\u003e \u003cp\u003eThe survey covered the population of the northern part of the Uvira town, precisely in the commune of Kavimvira and the Kagando groupement, which borders Lake Tanganyika and the Nyangara marshes, and is therefore exposed to the harmful effects of their overflowing waters. The inclusion criterion for the sample was to be at least 30 years old.\u003c/p\u003e \u003cp\u003eA survey questionnaire consisting of 15 questions divided into 4 groups was drawn up and administered to a random sample of 95 people out of an estimated population of 10242. This sample size was calculated using the Bouchard (2010) formula with a margin of error of 5%: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{N}.\\text{C}=\\frac{\\text{n}}{1+\\text{n}/\\text{N}}\\)\u003c/span\u003e\u003c/span\u003e with N.C corrected sample size, N: population size corresponding to 10242 inhabitants in our case and n: sample size for an infinite universe corresponding to 96 according to Bouchard (2010).\u003c/p\u003e \u003cp\u003eIn addition to this survey, a meeting was held with 25 people over the age of 50 to gather further information to inform our judgement. This age criterion was the most important, as we found that this was the only category of respondents who claimed to have experienced other periods of rising water levels in Lake Tanganyika.\u003c/p\u003e \u003cp\u003eThe various data obtained in the field were processed using SPSS and Ms Excel software.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eRemote sensing results\u003c/h2\u003e\n\u003cp\u003eAnalysis of remote sensing data shows that water levels in both Lake Tanganyika and Nyangara Marsh are highly variable from year to year, with variations in Nyangara Marsh being more considerable in absolute terms than those in Lake Tanganyika (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eChange in surface area (in Km\u0026sup2;) covered by water from 2011 to 2021\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2014\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2016\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2017\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2019\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLake Tanganyika\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.390\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.286\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.408\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.385\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.872\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNyangara marsh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.959\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.261\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.540\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.997\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.290\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFrom these results, it can be seen that the Nyangara marsh can easily see the surface area of its water increase from one to over 2.65 times during periods of high flooding (even 2017). Although less variable in absolute terms (i.e. only a difference of 0.586 Km\u0026sup2; between the low-water period, i.e. 2016, and the high-water period, i.e. 2012) than that of the Nyangara marshes, it can still be seen that the rising waters of Lake Tanganyika sometimes affect dwellings located on the south side of the road leading to Bujumbura (Burundi's capital city) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), more than 145 m from the north shore of Lake Tanganyika.\u003c/p\u003e\n\u003cp\u003eThe years 2014, 2016 and 2019 were characterized by a sharper drop in the water level of the Nyangara marsh, leaving wetlands that bear witness to previous periods of high flooding (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) and which, at certain times, are colonized by vegetation and/or remain as areas with clay deposits that later develop desiccations characteristic of a long dry season. This drop in water level was highlighted by 82.4% of our respondents, who stated that the water level had fallen, particularly in the Nyangara marshes and on Lake Tanganyika, and cited the lack of rainfall during this period as the cause. Although marked by a significant withdrawal of water, the years 2016, 2019 mark vast expanses of wetlands. This wetland is also observed in 2021, which bears witness to the fluctuating surface area of the Nyangara marsh. In our interviews with older people (over 50 years), the surface areas occupied in 2016 and 2021 were considered to be the normal (average) level of this marsh.\u003c/p\u003e\n\u003cp\u003eDuring the years considered for this study, 2017 was the year in which Nyangara marsh extinguished the largest area, i.e. 2.540 km\u0026sup2; equivalent to twice its normal area.\u003c/p\u003e\n\u003cp\u003eWith regard to the limits reached by variations in the water levels of these two aquatic ecosystems, Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e show that, over the last 10 years, the waters of Lake Tanganyika have, in the years 2017 and 2021, risen to flood the south-eastern part of the study area, mainly affecting the side of the border between the Uvira town and the Bujumbura city, but also the village of Gatumba on the Burundian side (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e), which are among the areas most likely to be flooded once the Tanganyika floods (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIndeed, this mapping shows that the area most affected by flooding on Lake Tanganyika is located on its eastern side, affecting the Gatumba area the most (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). As for the Nyangara marsh, the areas most affected are located on the north and south sides of the marsh (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Some water lines extend towards the west (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The red zone extends along both sides, with an average distance of 150 m and an area of 0.959 km\u0026sup2;. There is a large wetland zone located to the north of the marsh, which is susceptible to flooding, mainly affecting the fields of the Kagando/Kiliba housing estate (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). This zone covers an area of 0.586 km\u0026sup2; with an average length of 125 m, making the road to Bujumbura vulnerable.\u003c/p\u003e\n\u003cp\u003eA large wetland area to the east of the Lake submerges the entire road leading to Bujumbura. From the center to the west, a red column extends as far as Kavimvira, making riverside infrastructures more vulnerable (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n\u003ch2\u003eLocal people's perceptions of flooding and possible solutions\u003c/h2\u003e\n\u003cp\u003eThe results of surveys of the local population exposed to flooding from rising Lake Tanganyika and the Nyangara marshes show that the Nyangara marshes have never completely disappeared during the various fluctuations in water levels, as attested by 77.9% of those surveyed (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Fifty-five point eight percent of this same population believe that this variation is regular and is related to the variation in the water level of Lake Tanganyika, as stated by 41.1% of respondents (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eRespondents' knowledge of historical water level variations in Nyangara marsh and Lake Tanganyika\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eQuestions\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eResponses\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eNumber\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eHas the level of Lake Tanganyika and/or the Nyangara marshes risen again in the last decade or so?\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAbstention\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eIs this variation in water level regular over time?\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAbstention\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eDo the waters of the Nyangara marshes rise and fall at the same rate as those of Lake Tanganyika?\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAbstention\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e37.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs for the causes of flooding, 7 causes were cited by respondents who had been flooded at least once, including the 3 most frequent: heavy rainfall during the rainy season, deforestation and sediments (91.6%-51.6%-50.5% of respondents respectively) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCauses and consequences of flooding in the study area\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eQuestions Responses\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eFlood victims\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAbstention\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eCauses of flooding\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeavy rains\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFlat relief\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeforestation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTectonics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSediments\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClimate disturbance\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAnarchic buildings\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers (religious beliefs, bad wind, etc.)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eConsequences of flooding\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEnvironmental degradation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoss of basic infrastructures\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDisruption of daily activities\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFood insecurity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSocial insecurity,\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoss of property\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLoss of human life\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers (illnesses, etc.)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn terms of the consequences of flooding reported by people living near these entities, we count the degradation of the aquatic environment (97.9% of respondents) and the loss of property (97.9% of respondents) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The loss of human life was also mentioned, and was characterized above all by the drowning of young children.\u003c/p\u003e\n\u003cp\u003eFinally, 96.8% of those surveyed confirmed that flooding from Lake Tanganyika and the Nyangara marsh was responsible for a number of socio-economic impacts on the lives of the people of Kamvinvira and the Kagando/Kiliba township (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSocio-economic impact of rising lake and marsh levels\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eQuestions\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eResponses\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eDo floods have an impact on socio-economic activities?\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e96.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAbstention\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eSocio-economic activities affected\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEducation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHealth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTransport and commerce\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAll activities\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e67.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eReaction from authorities, local organizations and private individuals.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedical assistance to victims\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDistribution of food and other necessities\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRelocation and offering shelter to victims\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo reaction at all\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows that the activities most disrupted by flooding are education (91.5%), as schools become shelters for flood victims, and some education workers (pupils and teachers) are also victims. Transport and commerce come in second place, as roads are cut off and goods cannot be transported to market.\u003c/p\u003e\n\u003cp\u003eHealth is deteriorating in this area due to the lack of shelter and poor housing conditions in places where people gather (in schools and churches). This problem was declared and confirmed by 66.3% of our respondents.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs already noted by Nicholson (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), Alin et al. (2003) and Cohen et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and as evidenced by the respondents' answers in this study, the level of Lake Tanganyika remains variable over time. The vast majority of respondents (51.6%) attributed these variations to extensive deforestation on the slopes overlooking the Lake and the Nyangara marshes. Indeed, it has been shown that over the last four decades, almost 100 percent of the originally forested land in the northern watershed of Lake Tanganyika had been completely cleared (Cohen \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) by the ever-growing population in search of firewood, charcoal and land for subsistence farming or grazing (Fermon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), transforming these areas into vast cultivated areas and grasslands (Azanga et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This subsistence farming, carried out in disregard of all the cultivation techniques appropriate to these types of sites, deforestation and clearing cause severe soil erosion in this area (Mwenyemali and Kahindo \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The eroded soil ends up in Lake Tanganyika, its tributary rivers and the Nyangara marshes. This ever-increasing sedimentation in the lake (Tiercelin and Mondregeur 1991) and Nyangara marshes reduces their depths, thus raising their water levels and causing flooding. It is therefore understandable that with this relatively horizontal central topography (Ilunga \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) and a water level oscillation of around one meter (Fermon \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), the Ruzizi plain, and principally our study area, remains prone to flooding whenever above-average rainfall is recorded. Some of these floods could cause the waters of the Tanganyika and Nyangara rivers to mix, thus cutting off the Uvira-Bujumbura road, as was the case in 2021 (observed in this study) and in 1960 and 1963 (testimonies of old interviewees).\u003c/p\u003e \u003cp\u003eFloods are never without consequences; consequences well documented elsewhere (Talbot et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Njogu \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the case of our study area, the education system and churches proved to be the most affected. Indeed, schools and churches are among the real estate infrastructures that are flooded and therefore unusable. Unfortunately, during the floods the schools and churches that remain safe from the floods are directly requisitioned by the emergency services of non-governmental organizations (NGOs) and religious confessions rather than those of the public sector (the State), and transformed into places of refuge and cantonment, demonstrating that the DRC, and the Uvira town in particular, is not deviating from the general pattern of developing countries faced with floods and many other natural disasters, i.e. reacting to the consequences rather than being proactive in managing these disasters (Njogu \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As a result, the State is obliged to spend more than necessary to stem the effects of flooding, as was the case in Kenya, for example (Njogu \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In our study area, however, it is NGOs, religious confessions, people of good will and local associations that come to the aid of flood victims; their assistance is limited to medical aid and food and goods. As a result, the road and commercial infrastructures (markets and stores) also damaged by the floods are never rebuilt, with serious repercussions for the economy of the study area and the social well-being of the population. Last but not least, these floods cause ecological disruption, forcing certain animals, such as hippos, to leave the Ruzizi River to find themselves in the midst of the population, creating conflicts between humans and wild animals.\u003c/p\u003e \u003cp\u003eAs far as possible solutions are concerned, contrary to the proposals put forward by several environmental civil society players and political-administrative authorities, as well as by some of the respondents to this study, to relocate the inhabitants of areas affected by and/or likely to be flooded by Lake Tanganyika and/or the Nyangara marshes, we believe that this is not the appropriate solution. Indeed, Lake Tanganyika and the Nyangara marshes are part of Uvira's immediate and daily environment, and contribute to its beauty and vitality. Uvira is not the only coastal city in the world, and not even the only coastal city on Lake Tanganyika. Yet, unlike other coastal cities on Lake Tanganyika such as Bujumbura, Kigoma, Mpulungu, etc., floods are very often reported here. While the topographical features of the Uvira town make it particularly vulnerable to this kind of disaster (Mwenyemali and Kahindo \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), it remains true that they need to be prevented and mitigated by adopting a multifaceted approach involving people from different specialties (politicians, urban planners, environmentalists, biologists, geologists, agronomists, rural development technicians, etc.) having to come from the scientific world, politics, NGOs, churches and local communities. In concrete terms, this involves (1\u0026deg;) reducing erosion in the Lake Tanganyika watershed by developing soil conservation measures (hedges around fields, terraced cultivation, retention of eroded material using gabions and/or protection of bare soil by mulching), training the population in appropriate cultivation practices on sloping sites, and banning construction on the mountainsides overlooking Lake Tanganyika; (2\u0026deg;) the sustainable management of timber resources by protecting the forest relics in the Lake Tanganyika watershed and, on the other hand, its enhanced reforestation through the development of agroforestry and the planting of trees generating sustainable timber not originating from forests; (3\u0026deg;) the strict application of regulations concerning respect for the 50m shoreline of Lake Tanganyika, so that people who have taken up residence and infrastructures built in this zone are obligatorily relocated without any excuse, by trying to establish responsibilities for the allocation of plots of land in these areas, so that these relocations can take place in strict compliance with the law.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe Nyangara marsh has seen several variations in water level over the decade 2011\u0026ndash;2021. And these variation are very often associated with those of Lake Tanganyika, which is in permanent communication with the latter. During periods of high water, flooding causes a wide range of damage, including loss of property and destabilization of aquatic ecosystems, leading to social and economic disruption for the population living in the area. Although the negative impacts of these floods are considerable, the local authorities seem to be unconcerned.\u003c/p\u003e \u003cp\u003eOnly a multifaceted approach involving people from different specialties and sectors of life should make it possible to curb the consequences of these floods, and at best to prevent them in time.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMashauri Ndabaga :\u0026nbsp;\u003c/strong\u003eConceptualized the study, designed the methods and study design, performed fieldwork and data analyses, drafted the original manuscript\u003cstrong\u003e\u0026nbsp;Ahimidiwe Bagi Nelson :\u0026nbsp;\u003c/strong\u003ePerformed fieldwork, edited and commented on the manuscript\u003cstrong\u003e\u0026nbsp;Mulungula Pascal Masilya:\u0026nbsp;\u003c/strong\u003eConceptualized the study, designed the methods and study design, performed data analyses, edited and commented on the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the respondents who willingly gave up some of their precious time to provide us with the information we needed.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad QK (2006) Changement climatique, inondations et gestion des crues : le cas du Bangladesh. H\u0026eacute;rodote 121 :73-94\u003c/li\u003e\n\u003cli\u003eAlin SR, Cohen AS (2003) Lake-level history of Lake Tanganyika, Est Africa, for the past 2500 years based on astracode-inferred water-depth. Paleogeogr. Paleoclimatol. Paleoecol.199 (1-2): 31-49\u003c/li\u003e\n\u003cli\u003eAzanga E, Majaliwa ., Kansiime F, Mushagalusa N, Karume K, Tenywa MM (2016) Land-use and land cover, sediment and nutrient hotspot areas changes in Lake Tanganyika Basin. Afr. J. Rural Dev. 1(1) : 75-90\u003c/li\u003e\n\u003cli\u003eBourchard A (2010) Recherche de l\u0026rsquo;\u0026eacute;chantillon : probl\u0026eacute;matique \u0026agrave; l\u0026apos;indice de la d\u0026eacute;termination de l\u0026apos;\u0026eacute;chantillon. I.D.E, Paris\u003c/li\u003e\n\u003cli\u003eBravard JP, Petit F (1997) Les cours d\u0026rsquo;eau : dynamique du syst\u0026egrave;me fluvial. Armand Collin, Paris \u003c/li\u003e\n\u003cli\u003eCohen AS (1991) Report on the first International Conference on the conservation and biodiversity of Lake Tanganyika. March, 1991. Bujumbura. Biodiversity Support Program \u003c/li\u003e\n\u003cli\u003eCohen AS, Talbot MR, Awramik SM, Dettman DL, Abell P (1997) Lake level and paleoenvironmental history of Lake Tanganyika, Africa, as inferred from late Holocene and modern stromatolites. Geol. Soc. Am. Bull.109: 444-460\u003c/li\u003e\n\u003cli\u003eCohen AS, Palacios-Fest MR, Msaky ES, Alin SR, McKee B, O\u0026rsquo;Reilly CM, Dettman DL, Nkotagu H, Lezzar KE(2005) Paleolimnological investigations of anthropogenic environmental change in Lake Tanganyika : IX. Summary of paleorecords of environmental change and catchment deforestation at Lake Tanganyika and impacts on the Lake Tanganyika ecosystem. J Paleolimnol. 34(1): 125-145\u003c/li\u003e\n\u003cli\u003eFermon Y (2007) \u0026Eacute;tude de l\u0026rsquo;\u0026eacute;tat des lieux de la partie nord du lac Tanganyika dans le cadre du Programme P\u0026ecirc;che d\u0026rsquo;Action Contre la Faim en R\u0026eacute;publique D\u0026eacute;mocratique du Congo. Uvira : Rapport de mission. Action Against Hunger, USA\u003c/li\u003e\n\u003cli\u003eHubert G, Ledoux B (1999) Le Co\u0026ucirc;t du risque : l\u0026rsquo;\u0026eacute;valuation des impacts socio-\u0026eacute;conomiques des inondations. Presses de l\u0026rsquo;Ecole Nationale des Ponts et Chauss\u0026eacute;es, Paris\u003c/li\u003e\n\u003cli\u003eIlunga L (1991) Morphologie, volcanisme et s\u0026eacute;dimentation dans le rift du Sud-Kivu. Bulletin de la Soci\u0026eacute;t\u0026eacute; G\u0026eacute;ographique de Li\u0026egrave;ge 27 : 209-228\u003c/li\u003e\n\u003cli\u003eIlunga L (2006) Etude des sites majeurs d\u0026apos;\u0026eacute;rosion \u0026agrave; Uvira (R.D. Congo). Geo-eco-trop. 30 (2) :1-12\u003c/li\u003e\n\u003cli\u003eIratxe CM, Longu\u0026eacute;p\u0026eacute;e J (2010) Risque d\u0026rsquo;inondation et d\u0026eacute;veloppement durable. In : Zuindeau B. (ed) D\u0026eacute;veloppement durable et territoire. Presses Universitaires du Septentrion, Villeneuve d\u0026apos;Ascq, France, pp 315-326 \u003c/li\u003e\n\u003cli\u003eMwenyemali B, Kahindo D (2014) Impact de la topographie sur les catastrophes naturelles observ\u0026eacute;es dans la cit\u0026eacute; d\u0026rsquo;Uvira, Nord-Ouest du lac Tanganyika. Cahier du Ceruki 46 : 228-238\u003c/li\u003e\n\u003cli\u003eNacishali J (2020) Cartographie de l\u0026rsquo;\u0026eacute;rosion hydrique des sols et priorisation des mesures de conservation dans le territoire d\u0026rsquo;Uvira (R\u0026eacute;publique D\u0026eacute;mocratique du Congo). https://doi.org/10.4000/vertigo.28888\u003c/li\u003e\n\u003cli\u003eNicholson SE (1999) Historical and modern fluctuations of Lakes Tanganyika and Rukwa and their relationship to rainfall variability. Climatic Change 41: 53-71\u003c/li\u003e\n\u003cli\u003eNjogu HW (2021) Effects of floods on infrastructure users in Kenya. J. Flood Risk Manag. 14(4):e12746. https://doi.org/10.1111/jfr3.12746\u003c/li\u003e\n\u003cli\u003eTalbot CJ, Bennett EM, Cassell K, Hanes DM, Minor EC, Paerl H, Raymond PA, Vargas R, Vidon PG, Wollheim W, Xenopoulos MA (2018) The impact of flooding on aquatic ecosystem services. Biogeochemistry 141:439-46. https://doi.org/10.1007/s10533-018-0449-7\u003c/li\u003e\n\u003cli\u003eTiercelin JJ, Mondeguer A (1991) The geology of the Tanganyika trough. In: Coulter GW (ed) Lake Tanganyika and its Life. Oxford University Press, London, pp 7-48\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Disaster, Flooding, Rural, Housing, Agriculture","lastPublishedDoi":"10.21203/rs.3.rs-4248196/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4248196/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe water level of Lake Tanganyika has constantly fluctuated over time, flooding certain areas variably during periods of high water, causing immeasurable material and human damage. To prevent such damage, it is necessary to determine exactly which areas are always subject to flooding. This study, based on documentation, field surveys and satellite image processing using remote sensing techniques, aimed to identify the variation in water levels in the Nyangara marsh and Lake Tanganyika over the decade 2011\u0026ndash;2021, to map the flood-prone areas in its northern and northeastern parts and to document the impact of these floods on riparian populations, in order to propose possible solutions to avoid damage in future years.\u003c/p\u003e \u003cp\u003eOur results show that 2014, 2016 and 2019 were the years with the lowest water levels (especially for the Nyangara marsh), while 2017 and 2021 were the years of heavy flooding with serious negative impacts on riparian populations, namely the loss of inhabited and arable land, the disruption of socio-economic activities and environmental degradation.\u003c/p\u003e \u003cp\u003eThe survey revealed that the relocation of riverside populations, the creation of a buffer zone between the lake/marsh and dwellings, reforestation and the application of the law relating to the respect of 50m of shoreline are the priority solutions for mitigating the consequences of these floods. In this work, we discuss these proposals from the respondents and highlight more practical flood mitigation strategies adapted to this environment.\u003c/p\u003e","manuscriptTitle":"Water level variations and flood zones in Lake Tanganyika and Nyangara marsh: Impact analysis and innovative solutions to prevent future damage","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-26 13:48:04","doi":"10.21203/rs.3.rs-4248196/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"141b3524-45a2-447b-8962-3d9ae2723803","owner":[],"postedDate":"April 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-25T22:47:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-26 13:48:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4248196","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4248196","identity":"rs-4248196","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}