Geomorphic consequences of land cover dynamics in hillslope environments

Land cover dynamics are driving forces for geomorphic processes in mountain landscape inducing beneficial and adverse effects on landscape. Consequently, detecting and monitoring land cover changes are of fundamental relevance in a wide spectrum of useful applications for adjusting soil protection and land management policies. Moreover, they are necessary to identify hillslope denudation, to quantify the soil loss, and to assess changing environmental conditions (vegetation communities and soil properties). Land cover data can be acquired at local, regional and/or global scales using traditional and/or innovative technologies (from field measurements to remote sensing) with different accuracy. Using such information, most investigations have been focusing on analysing, modelling and predicting geomorphic and landform-shaping processes that have a strong impact on both natural ecosystems and cultivated lands in terms of economic, social and environmental implications. In particular, the alterations of soil properties and vegetation cover in terms of soil aggregation, soil detachment, soil reinforcement and/or soil hydrological processes, are often causes of more complex and extremely difficult to predict landscape processes.
Thus, this session aims to group together the most recent scientific research and activities, especially those paying heed to transient or long-term slope failure mechanism as well as surface/subsurface water flow and soil erosion processes. Research abstracts are invited to address:
1. observation of land cover types, land cover changes (urbanization, road building, forest destruction, etc.), and occurrences of geomorphic processes (erosion, landslides, rockfalls) using a wide spectrum of technologies (field instruments, unmanned aerial vehicles and satellite images);
2. investigation on relationship between land cover change and surface processes at different scales (from hillslope to regional scale);
3. assessment of soil instabilities (erosion, landslides, rockfalls) through innovative modelling approaches (statistical, physical-based and numerical);
4. development of guidelines and regulations for practitioners, technicians, policy and decision makers.
We highly welcome pioneering research from all fields, especially from geomorphology, agricultural science, soil science, geotechnics and environmental engineering. Early career scientists are encouraged to contribute to the session with original and advanced studies.

Convener: Alessio CislaghiECSECS | Co-conveners: Lauren ZweifelECSECS, Elmar SchmaltzECSECS, Stefan Steger
| Tue, 24 May, 08:30–10:00 (CEST)
Room 0.16

Session assets

Session materials

Presentations: Tue, 24 May | Room 0.16

Chairperson: Alessio Cislaghi
Virtual presentation
Arthur Depicker, Gerard Govers, Liesbet Jacobs, Matthias Vanmaercke, Judith Uwihirwe, Benjamin Campforts, Désiré Kubwimana, Jean-Claude Maki Mateso, Toussaint Mugaruka Bibentyo, Louis Nahimana, Benoît Smets, and Olivier Dewitte

During the Anthropocene, the impact of humans on Earth surface processes has increased exponentially, often surpassing the importance of natural drivers. Also in mountainous areas, landslide mobilization rates are exacerbated by human disturbances of the landscape such as deforestation, road constructions, and mining processes. However, investigating these interactions remains difficult in many regions due to a lack of sufficiently long observation periods, preferably over a large area, so that the presence of extreme landslide events (triggered by rainfall or earthquakes) does not induce an observation bias. Here, we investigate landslide mobilization rates in the densely populated North Tanganyika-Kivu Rift Region (NTK Rift), a prominent landslide hotspot in Africa. We use ca. 2,400 panchromatic aerial photographs from 1958 in combination with recent satellite imagery to assess the long-term landslide mobilization rates over a large area of ca. 21,000 km2.

By estimating the volume of the deep-seated and shallow rapidly-moving landslides using empirical volume-area scaling relationships, we estimate that the average landslide mobilization rate in the NTK Rift is ca. 31 m3 km-2 year-1 in actively incising, rejuvenating landscapes and ca. 12 m3 km-2 year-1 in relict landscapes. The mobilization rates in the NTK Rift are dominated by the largest landslides. For instance, the 15 largest deep-seated landslides account for 50% of the total rate. Overall, we observe mobilization rates in the NTK Rift that are somewhat lower than what a global model predicts. These relatively low rates could be explained by four factors: (i) the absence of major landslide-triggering earthquakes during our 60-year observation period, (ii) the exclusion of earthflows from our analysis due to a lack of information on the depth and velocity of these instances, (iii) the relatively large size of our study area which reduces biases linked to extreme rainfall, (iv) the fact that the NTK Rift is a mountain range in an extension area, which differs from orogenic mountainous areas, where most landslide mobilization rates are reported; and (v) uncertainties on the global landslide mobilization rate model.

In rejuvenated landscapes, roughly 5% of the sediment mobilization by rapidly-moving landslides is linked to human activity, while in relict landscapes this figure rises to 18%, notably due to mining and road construction. The role of human activity is limited as compared to the recent occurrence of some large landslides, which seem linked to natural causes and dominate the overall mobilization rates. Moreover, the limited role of human activity must be balanced with the fact that the NTK Rift, although highly populated, remains relatively untouched by major road infrastructure constructions. While previous studies have found that deforestation has a large impact on the landside risk (i.e. the incidence of landslide fatalities), its impact on the observed mobilization rates appears to be much less important. The landslides associated with deforestation are commonly shallow debris avalanches with a limited size and rather high mobility.

Overall, our results significantly contribute to a better understanding of landslide mobilization and its controlling factors, especially by proving much-needed long-term observations for a currently under-researched type of environment.

How to cite: Depicker, A., Govers, G., Jacobs, L., Vanmaercke, M., Uwihirwe, J., Campforts, B., Kubwimana, D., Maki Mateso, J.-C., Mugaruka Bibentyo, T., Nahimana, L., Smets, B., and Dewitte, O.: Landslide mobilization rates in the Anthropocene: insights from a 60-year observation period in the North-Tanganyika-Kivu Rift region, Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10284,, 2022.

Virtual presentation
Renée A. Heijenk, Claire Dashwood, Faith E. Taylor, Joanne L. Wood, Christian Arnhardt, and Bruce D. Malamud

Here we present a methodology for the mapping of landslide domains, using as a case study East Sikkim district (964 km2, population of 283,583 in 2011), a landslide-prone region in northeast India. Landslide domains are defined as regions with similar physical and environmental characteristics that specifically drive landslide dynamics. The methodology given here is more systematic than what has previously been used and draws on information on landslide factors inferred from landscape variables. Commonly used landslide factors are divided into three groups: preconditioning, preparatory, and triggering factors. Elevation data, geology, and landslide inventory information are used to provide information on the landslide factors in the study region. Data from the neighbouring and geologically similar regions of East Sikkim district are used to enhance landslide inventory information in the study region, effectively doubling the number of landslides in the inventory from 210 to 440 mapped landslides. We iterate over each of the landslide factor groups and for each iteration either map a new landslide domain boundary or enrich the information of the landslide domains. As a result, we map four landslide domains in East Sikkim district, India, with a size ranging from 81 km2 to 394 km2. The domains have been further enriched using information on rainfall and earthquakes. Each landslide domain describes the typology of landslides and the general geomorphology and land use. The landslide domains in East Sikkim district can be used for (i) describing landslide processes homogenously; (ii) illustrating landslide processes for training or stakeholder engagement; and (iii) as a starting point for the construction of landslide susceptibility maps and landslide early warning that actively draws from the landslide processes that can be found in the region.

How to cite: Heijenk, R. A., Dashwood, C., Taylor, F. E., Wood, J. L., Arnhardt, C., and Malamud, B. D.: Developing a methodology for the delineation of regions into landslide domains with a case study in East Sikkim, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7579,, 2022.

Virtual presentation
Anuska Narayanan and Sagy Cohen

The Amazon River Basin is the largest river system in the world, accounting for one-fifth of global freshwater discharge and supplying 40% of the Atlantic Ocean’s sediment flux. Though the Amazon is most often recognized for its rich biological diversity, it also performs a suite of ecosystem functions such as river flow regulation, local climate modulation, and carbon sequestration. Despite its ecological importance, the Amazon experiences thousands of kilometers of deforestation annually with recent rates increasing to levels unseen since the late 2000s. These increased rates of deforestation within the basin have led to changes in sediment concentration within its river systems, affecting not only the ecological balance within the system but also the availability of water to those dependent on river flows. Furthermore, sediment plays an important role in river channel morphology and landscape development, effectively influencing the future topography of the basin. Therefore, it is important to closely examine the relationship between deforestation and suspended sediment in order to characterize the extent of influence anthropogenic activities, such as deforestation, have on rivers.

In this study, we analyze the impact of deforestation from 2001 to 2020 on suspended sediment throughout the Amazon River Basin. These effects are studied by quantifying the spatiotemporal relationships between observed suspended sediment (at gage sites and using a basin wide remote sensing product) and changes in land cover over time. We hypothesize that deforestation will lead to significant increases in suspended sediment flux in adjacent streams and that the effect of deforestation on suspended sediment flux will decrease significantly downstream. 

How to cite: Narayanan, A. and Cohen, S.: Sediment Response to Deforestation within the Amazon River Basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8786,, 2022.

Virtual presentation
Hosea Opedes, Jantiene Baartman, Sander Mücher, and Frank Mugagga

Analyzing the dominant forms and extent of land cover changes in the Mount Elgon region is important for tracking conservation efforts and sustainable land management. Mount Elgon's rugged terrain limits monitoring these changes over large areas. With conducive climatic conditions, highly fertile and productive soils; Elgon is one of the densely populated rural mountainous regions in East Africa. The demand for more agricultural land and space for settlement has led to continued vegetation clearance and encroachment of the park. These pressures combined with the loss of vegetation cover have led to the continued occurrence of natural hazards, especially landslides and soil erosion events. Recent studies have given focus to these hazards and coping strategies. However, monitoring changes in land cover and associated driving factors are fundamental towards the improvement of land use, land restoration, and vegetation recovery in Mount Elgon. This study used multitemporal satellite imagery, aerial photographs, field surveys, and expert interviews to analyze and quantify the land cover flows in the upper Manafwa watershed of Mount Elgon, for 42 years covering an area of  319.73km2. The study employed remote sensing techniques and geographic information system and software to map land cover changes for four stages (1978-1988, 1988-2001, 2001-2010, and 2010-2020). The study considered nine land cover classes; tropical high forest well-stocked, grassland, shrubs, bushland, bare & sparsely vegetated surfaces, tropical high forest low-stocked, agriculture, planted forest, and built-up. The maximum likelihood classifier of supervised classification and post-classification comparison technique was used in land cover classification and change detection analysis. The classified maps of 2020, 2010, 2001, 1988 and 1978 achieved high accuracy values of 93%, 89%, 89%, 88% and 83% respectively. Results showed conversion of tropical high forest well-stocked (22%), grassland (6.89%), shrubs (6.21%), bushland (4.29%), and bare & sparsely vegetated surfaces (1%) into agriculture (19.8%), tropical high forest low-stocked (10.29%), planted forest (5.83%) and built-up (4.46%) most especially at the peripheries of the park from 1978 to 2020. These dynamics are due to rapid population growth and increasing demand for agriculture space. Regreening as a restoration effort has led to an increase in land area for planted forests, attributed to an improvement in conservation efforts jointly implemented by the concerned stakeholders and native communities. Landsat satellite imagery provides information on change detection which is resourceful to tracking conservation efforts. The trend of land cover flows found in this study, especially illustrations of areas of deforestation and loss of natural vegetation cover classes provides resourceful information for policymakers and responsible authorities to further take appropriate decisions and actions to revert the situation and reduce encroachment into the National Park. Near real-time monitoring systems of human disturbances in conservation areas should also be incorporated and actions are taken to minimize forest encroachment. These findings could further, enhance the implementation of rigorous conservation efforts when coupled with in-depth studies on associated determinants of these changes.

How to cite: Opedes, H., Baartman, J., Mücher, S., and Mugagga, F.: Monitoring land cover changes and farming dynamics in the fringes of Mount Elgon National Park, Uganda., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-311,, 2022.

Presentation form not yet defined
Michele D'Amico, Emanuele Sapino, and Enrico Quaglino

The Kerio Valley (Elgeyo-Marakwet and Baringo county, Kenya) is part of the East African Rift Valley system; it is characterized by steep slopes and a large elevation gradient between the plateau and the valley floor. The study area is the Kimwarer river basin, between 2838 and 1202 m a.s.l.. The summit plateau is above 2500-2700 m, characterized by rolling hills and a cool/humid climate; potential vegetation is montane rainforest; most of it has been transformed into corn, tea and hay fields. Below the plateau, the Elgeyo Escarpment is steep and dissected by V-shaped valleys and active/inactive landslide scars, descending to 1300-1400 m a.s.l.. The potential vegetation is montane rainforest above ~2000 m, deciduous Acacia woods/shrublands below. Cultivations are increasingly substituting forests even in the steepest slopes. The Kerio Valley floor includes floodplains and low-steepness alluvial fans; the potential Acacia savannah has been mostly substituted by corn crops, later abandoned because of extreme soil erosion, resulting in a semi-desert habitat.

The soil types follow elevation and topography: organic carbon-rich Ferralsols are common on the high plateau, stony Umbrisols, Cambisols, Phaeozems are common in the high slopes of the escarpment, while Kastanozems are common in the low slopes; shallow remnants of Plinthosols and Vertisols are common in the valley floor.

Land-use change in the Kerio Valley floor happened during the ‘80s, when local people moved from pastoralism to agriculture; original Acacia savannah was disrupted by ploughing to permit cropping during the rainy seasons. Soil maps performed during that period describe soils as Ferralsols, with rooting depth limitations by lateritic crusts below 1-2 m. At present, the lateritic crust outcrops over large surfaces, and 2-5 m deep, 10-20 m large gullies cover >50% of the surface. The cultivations are thus being abandoned. The soil loss might be estimated conservatively ~100 t/ha/y; this is an extremely high value considering the almost flat surface. The average soil loss calculated by an adapted RUSLE method is 51 t/ha/y; there is an important underestimation by the model.

The erosion is much weaker in the upland Ferralsols, where soil is protected by high organic matter content and by the high productivity of the vegetation, helped by the absence of a truly dry season and the smaller evapotranspiration.

On the slopes of the escarpment, deforestation happened mostly after 2010, as visible from aerial photos. Umbrisols with thick A horizons are dominant under natural vegetation, but are not observed in deforested areas, evidencing a fast loss of the 30-50 cm A horizon (>320 t/ha/y). Deeper, less resistant horizons are exposed, and rills, gullies and mudflows develop after most rainstorms, with variations depending on soil type. The RUSLE model predicts average losses ~350 t/ha/y, with much higher values on the steep slopes.

The rainfall erosivity-R factor is high in tropical areas, and a preservation of a vegetation cover is necessary to impede a complete soil loss in just a few years. It is also extremely important to preserve the surface, organic-matter rich soil horizons, influencing soil erodibility-K factor.

How to cite: D'Amico, M., Sapino, E., and Quaglino, E.: Land cover change and fast soil degradation in the East African Rift Valley, Kenya, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13112,, 2022.