Human activity influences both the occurrence and impact of landslides in mountainous environments. Population pressure and the associated land-use changes are assumed to exacerbate landslide risk, yet there is a lack of statistical evidence to support this claim, especially in the Global South where historical records are scarce. In this work, we explore the interactions between population, deforestation and landslide risk in the Kivu Rift in Africa. To do so, we develop a holistic landslide risk model that evaluates 58 years of population and forest-cover trends. We show that the current landslide risk in the eastern Democratic Republic of the Congo (DRC) is twice as high as in neighbouring Rwanda and Burundi. Congolese households, on average, populate more hazardous terrain, probably as a result of conflicts and economic pull factors such as mining. Moreover, the recent large-scale deforestation of primary rainforest in the DRC has considerably exacerbated the landslide risk. Our analysis demonstrates how the legacy of deforestation, conflicts and population dynamics is reflected in the landslide risk in the Kivu Rift.
This is a preview of subscription content, access via your institution
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
The 1958 forest-cover data can be accessed at: https://doi.org/10.5281/zenodo.5027117. The 1958 panchromatic orthomosaics will become available at the end of the PAStECA project in March 2022 (http://pasteca.africamuseum.be/data). The landslide inventory is provided by Depicker et al.20 (https://doi.org/10.5194/esurf-9-445-2021) and can be downloaded at: https://doi.org/10.5281/zenodo.5027004. The land-cover data for 1988 and 2001 are provided by Basnet and Vodacek66 (https://doi.org/10.3390/rs70606683). The 2016 land-cover data are provided by ESA and can be accessed at: http://2016africalandcover20m.esrin.esa.int/. The population-density data are derived from the Global Human Settlement Layer that can be accessed at: http://ghsl.jrc.ec.europa.eu/. The Shuttle Radar Topography Mission digital elevation model is provided by the US Geological Survey (https://earthexplorer.usgs.gov/). The seismic data (Peak Ground Acceleration) are provided by Delvaux et al.83 (https://doi.org/10.1016/j.jafrearsci.2016.10.004) upon contacting the corresponding author. The road data can be downloaded from OpenStreetMap (https://www.openstreetmap.org/#map=7/50.510/4.475). The Global Forest Change 2000–2019 data from Hansen et al.71 can be found at: https://data.globalforestwatch.org/documents/14228e6347c44f5691572169e9e107ad/explore. The lithology data are retrieved from the work of Depicker et al.29 (https://doi.org/10.1016/j.geomorph.2019.106886) and can be requested from the author. The raw data used for Figs. 3–5 in this work can be accessed at: https://doi.org/10.6084/m9.figshare.14838825. Source data are provided with this paper.
The Python code used to derive the forest cover from aerial photographs and reconstruct the forest-cover changes can be requested from the corresponding authors.
McBean, G. A. Integrating disaster risk reduction towards sustainable development. Curr. Opin. Environ. Sustain. 4, 122–127 (2012).
Kelman, I. Linking disaster risk reduction, climate change, and the sustainable development goals. Disaster Prev. Manag. 26, 254–258 (2017).
United Nations Department of Economic and Social Affairs World Population Prospects 2019 (United Nations, accessed 16 July 2020); population.un.org/wpp/
Ehrlich, D. et al. Remote sensing derived built-up area and population density to quantify global exposure to five natural hazards over time. Remote Sens. 10, 1378 (2018).
Lambin, E. F. & Meyfroidt, P. Global land use change, economic globalization, and the looming land scarcity. Proc. Natl Acad. Sci. USA 108, 3465–3472 (2011).
Chamberlin, J., Jayne, T. S. & Headey, D. Scarcity amidst abundance? Reassessing the potential for cropland expansion in Africa. Food Policy 48, 51–65 (2014).
Nkonya, E., Mirzabaev, A. & von Braun, J. (eds) Economics of Land Degradation and Improvement—A Global Assessment for Sustainable Development (Springer, 2015).
Young, A. Poverty, hunger and population policy: linking Cairo with Johannesburg. Geogr. J. 171, 83–95 (2005).
Mugagga, F., Kakembo, V. & Buyinza, M. Land use changes on the slopes of Mount Elgon and the implications for the occurrence of landslides. Catena 90, 39–46 (2012).
Sidle, R. C. & Bogaard, T. A. Dynamic Earth system and ecological controls of rainfall-initiated landslides. Earth Sci. Rev. 159, 275–291 (2016).
Kirschbaum, D., Stanley, T. & Zhou, Y. Spatial and temporal analysis of a global landslide catalog. Geomorphology 249, 4–15 (2015).
Froude, M. J. & Petley, D. N. Global fatal landslide occurrence from 2004 to 2016. Nat. Hazard Earth Syst. Sci. 18, 2161–2181 (2018).
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M. & Guzzetti, F. A review of statistically-based landslide susceptibility models. Earth Sci. Rev. 180, 60–91 (2018).
Guzzetti, F., Reichenbach, P., Cardinali, M. & Ardizzone, A. Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72, 272–299 (2005).
Corominas, C. et al. Recommendations for the quantitative analysis of landslide risk. Bull. Eng. Geol. Environ. 73, 209–263 (2014).
Ray, R. L., Jacobs, J. M. & Ballestero, T. P. Regional landslide susceptibility: spatiotemporal variations under dynamic soil moisture conditions. Nat. Hazards 59, 1317–1337 (2011).
Reichenbach, P., Busca, C., Mondini, A. C. & Rossi, M. The influence of land use change on landslide susceptibility zonation: the Briga Catchment test site (Messina, Italy). Environ. Manage. 54, 1372–1384 (2014).
Hua, Y., Wang, X., Li, Y., Xu, P. & Xia, W. Dynamic development of landslide susceptibility based on slope unit and deep neural networks. Landslides 18, 281–302 (2021).
Montgomery, D., Schmidt, K., Greenberg, H. & Dietrich, W. Forest clearing and regional landsliding. Geology 28, 311–314 (2000).
Depicker, A. et al. Interactions between deforestation, landscape rejuvenation, and shallow landslides in the North Tanganyika–Kivu Rift region, Africa. Earth Surf. Dyn. 9, 445–462 (2021).
Knapen, A. et al. Landslides in a densely populated country at the footslopes of Mount Elgon (Uganda): characteristics and causal factors. Geomorphology 73, 149–165 (2006).
Kucsicsa, G. et al. Assessing the potential future forest-cover change in Romania, predicted using a scenario-based modelling. Environ. Model. Assess. 25, 471–491 (2020).
Dolidon, N., Hofer, T., Jansky, L. & Sidle, R. in Landslides: Disaster Risk Reduction (eds Sasa, K. & Canuti, P.) 633–649 (Springer, 2009).
Moos, C. et al. Ecosystem-based disaster risk reduction in mountains. Earth Sci. Rev. 177, 497–513 (2018).
de Jesús Arce-Mojica, T., Nehren, U., Sudmeier-Rieux, K., Miranda, P. J. & Anhuf, D. Nature-based solutions (NbS) for reducing the risk of shallow landslides: where do we stand? Int. J. Disaster Risk Reduct. 41, 101293 (2019).
Maes, J. et al. Landslide risk reduction measures: a review of practices and challenges for the tropics. Prog. Phys. Geogr. 41, 191–221 (2017).
Monsieurs, E. et al. Landslide inventory for hazard assessment in a data-poor context: a regional-scale approach in a tropical African environment. Landslides 15, 2195–2209 (2018).
Delvaux, D. & Barth, A. African stress pattern from formal inversion of focal mechanism data. Tectonophysics 482, 105–128 (2010).
Depicker, A. et al. The added value of a regional landslide susceptibility assessment: the western branch of the East African Rift. Geomorphology 353, 106886 (2020).
Dewitte, O. et al. Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika–Kivu Rift region. Landslides 18, 161–177 (2021).
Emberson, R., Kirschbaum, D. & Stanley, T. New global characterisation of landslide exposure. Nat. Hazards Earth Syst. Sci. 20, 3413–3424 (2020).
National Contingency Plan for Floods and Landslides (Ministry in Charge of Emergency Management of the Republic of Rwanda, 2018); https://www.minema.gov.rw/fileadmin/user_upload/Minema/Publications/Contingency_Plans/Contingency_Plan_for_Floods_nd_Landslides.pdf
Aleman, J. C., Jarzyna, M. A. & Staver, A. C. Forest extent and deforestation in tropical Africa since 1900. Nat. Ecol. Evol. 2, 26–33 (2018).
Ellis, E. C., Goldewijk, K. K., Siebert, S., Lightman, D. & Ramankutty, N. Anthropogenic transformation of the biomes, 1700 to 2000. Glob. Ecol. Biogeogr. 19, 589–606 (2010).
Stebbing, E. P. Forests of the Belgian Congo. Nature 172, 1177 (1953).
Kleinschroth, F., Laporte, N., Laurance, W. F., Goetz, S. J. & Ghazoul, J. Road expansion and persistence in forests of the Congo Basin. Nat. Sustain. 2, 628–634 (2019).
Gachuruzi, S. B. The impact of refugees on the environment: the case of Rwandan refugees in Kivu, Zaire. Refuge 15, 24–26 (1996).
Huggins, C. & Clover, J. (eds) From the Ground Up: Land Rights, Conflict and Peace in Sub-Saharan Africa (ISS, 2005).
Garrett, N., Sergiou, S. & Vlassenroot, K. Negotiated peace for extortion: the case of Walikale territory in eastern DR Congo. J. East. Afr. Stud. 3, 1–21 (2009).
Butsic, V., Baumann, M., Shortland, A., Walker, S. & Kuemmerle, T. Conservation and conflict in the Democratic Republic of Congo: the impacts of warfare, mining, and protected areas on deforestation. Biol. Conserv. 191, 266–273 (2015).
Muñoz-Torrero Manchado, A. et al. Three decades of landslide activity in western Nepal: new insights into trends and climate drivers. Landslides 18, 2001–2015 (2021).
Chaney, N. W., Sheffield, J., Villarini, G. & Wood, E. F. Development of a high-resolution gridded daily meteorological dataset over sub-Saharan Africa: spatial analysis of trends in climate extremes. J. Clim. 27, 5815–5835 (2014).
Omondi, P. A. O. et al. Changes in temperature and precipitation extremes over the Greater Horn of Africa Region from 1961 to 2010. Int. J. Climatol. 34, 1262–1277 (2014).
Leurquin, P. P. Agricultural change in Ruanda–Urundi: 1945–1960. Food Res. Inst. Stud. 4, 1–51 (1963).
Meditz, S. W., Merrill, T. & Library of Congress, Federal Research Division (eds) Zaire: A Country Study 4th edn (Library of Congress, 1994).
GHS Population Grid, Derived from GPW4, Multitemporal (1975, 1990, 2000, 2015) (European Commission, JRC, accessed 12 August 2020); http://data.europa.eu/89h/jrc-ghsl-ghs_pop_gpw4_globe_r2015a
Kanyamibwa, S. Impact of war on conservation: Rwandan environment and wildlife in agony. Biodivers. Conserv. 7, 1399–1406 (1998).
Ordway, E. M. Political shifts and changing forests: effects of armed conflict on forest conservation in Rwanda. Glob. Ecol. Conserv. 3, 448–460 (2015).
Michellier, C., Pigeon, P., Kervyn, F. & Wolff, E. Contextualizing vulnerability assessment: a support to geo-risk management in central Africa. Nat. Hazards 82, S27–S42 (2016).
Banerjee, O. et al. Economic, land use, and ecosystem services impacts of Rwanda’s Green Growth Strategy: an application of the IEEM + ESM platform. Sci. Total Environ. 729, 138779 (2020).
Vervisch, T., Titeca, K., Vlassenroot, K. & Braeckman, J. Social capital and post-conflict reconstruction in Burundi: the limits of community-based reconstruction. Dev. Change 44, 147–174 (2013).
Reyntjens, F. The Great African War—Congo and Regional Geopolitics, 1996–2006 (Cambridge Univ. Press, 2009).
De Putter, T. & Delvaux, C. Certifier les ressources minérales dans la région des Grands Lacs. Polit. Etrang. 2, 99–112 (2013).
Nassar, N. T. Shifts and trends in the global anthropogenic stocks and flows of tantalum. Resour. Conserv. Recycl. 125, 233–250 (2017).
Maps of Conflict Minerals in Eastern DRC—A0 Posters (International Peace Information Service, accessed 25 September 2020); https://ipisresearch.be/publication/map-conflict-minerals-eastern-drc-a0-posters/
van Acker, F. Where did all the land go? Enclosure & social struggle in Kivu (D.R. Congo). Rev. Afr. Polit. Econ. 32, 79–98 (2005).
Luethje, F., Kranz, O. & Schoepfer, E. Geographic object-based image analysis using optical satellite imagery and GIS data for the detection of mining sites in the Democratic Republic of the Congo. Remote Sens. 6, 6636–6661 (2014).
Tyukavina, A. et al. Congo Basin forest loss dominated by increasing smallholder clearing. Sci. Adv. 4, eaat2993 (2018).
Günter, S., Weber, M., Erreis, R. & Aguirre, N. Influence of distance to forest edges on natural regeneration of abandoned pastures: a case study in the tropical mountain rain forest of southern Ecuador. Eur. J. For. Res. 126, 67–75 (2007).
Pollock, W. & Wartman, J. Human vulnerability to landslides. GeoHealth 4, e2020GH000287 (2020).
Vlassenroot, K. & Raeymaekers, T. Conflict and Social Transformation in Eastern DR Congo (Academia Press, 2005).
Lehmann, P., Von Ruette, J. & Or, D. Deforestation effects on rainfall-induced shallow landslides: remote sensing and physically-based modelling. Water 55, 9962–9976 (2019).
Meyfroidt, P. & Lambin, E. F. Global forest transition: prospects for an end to deforestation. Annu. Rev. Environ. Resour. 36, 343–371 (2011).
Willemen, L. et al. How to halt the global decline of lands. Nat. Sustain. 3, 164–166 (2020).
Corbane, C. et al. A global cloud free pixel-based image composite from Sentinel-2 data. Data Brief 31, 105737 (2020).
Basnet, B. & Vodacek, A. Tracking land use/land cover dynamics in cloud prone areas using moderate resolution satellite data: a case study in Central Africa. Remote Sens. 7, 6683–6709 (2015).
ESA Climate Change Initiative–Land Cover Project 2017. 20 m Resolution (European Space Agency, 2016).
He, F., Li, S. & Zhang, X. A spatially explicit reconstruction of forest cover in China over 1700–2000. Glob. Planet. Change 131, 73–81 (2015).
Bolliger, J., Schmatz, D., Pazúr, R., Ostapowicz, K. & Psomas, A. Reconstructing forest-cover change in the Swiss Alps between 1880 and 2010 using ensemble modelling. Reg. Environ. Change 17, 2265–2277 (2017).
Hosmer, D. W. & Lemeshow, S. Applied Logistic Regression 2nd edn (John Wiley & Sons, 2000).
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Rosa, I. M., Purves, D., Souza, C. & Ewers, R. M. Predictive modelling of contagious deforestation in the Brazilian Amazon. PLoS ONE 8, e77231 (2013).
Poor, E. E., Jati, V. I., Imron, M. A. & Kelly, M. J. The road to deforestation: edge effects in an endemic ecosystem in Sumatra, Indonesia. PLoS ONE 14, e0217540 (2019).
USGS Shuttle Radar Topography Mission, Global Land Cover Facility. 1 Arc-Second (Univ. of Maryland, 2006).
Fawcett, T. An introduction to ROC analysis. Pattern Recognit. Lett. 27, 861–874 (2006).
Brenning, A. Improved spatial analysis and prediction of landslide susceptibility: practical recommendations. In Landslides and Engineered Slopes: Protecting Society Through Improved Understanding. Proc. 11th International and 2nd North American Symposium on Landslides and Engineered Slopes (eds Eberhardt, E. et al.) 789–794 (CRC Press/Balkema, 2012).
McFadden, D. in Frontiers in Econometrics (ed. Zarembka, P.) 105–142 (Academic Press, 1973).
McFadden, D. in Behavioural Travel Modelling (eds Hensher, D. & Stopher, P.) 279–318 (Croom Helm, 1978).
Rosa, I. M., Smith, M. J., Wearn, O. R., Purves, D. & Ewers, R. M. The environmental legacy of modern tropical deforestation. Curr. Biol. 26, 2161–2166 (2016).
Broeckx, J. et al. Landslide susceptibility and mobilization rates in the Mount Elgon region, Uganda. Landslides 16, 571–584 (2019).
Hungr, O., Lerouel, S. & Picarelli, L. The Varnes classification of landslide types, an update. Landslides 11, 167–194 (2014).
Harrell, F. E. Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis 2nd edn (Springer, 2003).
Delvaux, D. et al. Seismic hazard assessment of the Kivu Rift segment based on a new seismotectonic zonation model (western branch, East African Rift system). J. Afr. Earth Sci. 134, 831–855 (2017).
This study was supported by the Belgium Science Policy Office (BELSPO) through the PAStECA project (BR/165/A3/PASTECA) entitled ‘Historical Aerial Photographs and Archives to Assess Environmental Changes in Central Africa’ (http://pasteca.africamuseum.be/). We further wish to thank F. Canters, F. Makanzu Imwangana, A. M. C. Umutoni, G. Sakindi, J. van Vliet and T. De Putter for their insightful discussions and recommendations regarding this research.
The authors declare no competing interests.
Peer review information Nature Sustainability thanks Fritz Kleinschroth, Faith E. Taylor and Anthony Vodacek for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Depicker, A., Jacobs, L., Mboga, N. et al. Historical dynamics of landslide risk from population and forest-cover changes in the Kivu Rift. Nat Sustain 4, 965–974 (2021). https://doi.org/10.1038/s41893-021-00757-9
This article is cited by
Impact of landslide size and settings on landslide scaling relationship: a study from the Himalayan regions of India
Nature Sustainability (2021)