ICG2022-20

Soil erosion promoted by rainfall constitutes a major land degradation process. The occurrence of heavy, often localized, precipitation can cause severe erosion and increase the risk of flash flooding and debris flow. However, its occurrence in very specific situations, such as in areas affected by forest fires, changes significantly the behavior of the different factors and processes, as well as the conditions related with erodibility, contributing for an increasing erosion risk.

Several studies have shown strong and sometimes extreme responses in runoff generation and soil loss following fires, especially during the first 4 to 6 months after the fire. In Portugal this is a period of greatest vulnerability to erosion because of the maximum fire potential in summer (July–August) and the likelihood of intense post-wildfire rainfall the following autumn–winter (November–January).

In fact, forest fires produce a major impact on soil, being considered the major cause of soil degradation and desertification, and promoting significant changes on landscape features and landforms.

In the present study case, following the October 2017 forest fire in Braga and the subsequent storm that affected the burnt area, it was possible to identify the erosive processes that occurred and their consequences, which are presented in this work. The visual assessment of the erosive action on the slopes in the burned areas detected the development of critical areas with a higher concentration of erosion, in the areas most affected by fire, with steep slopes and where the anthropic action is more active (unpaved forestall roads and other anthropic infrastructures). These effects were surveyed with UAV and modeled in GIS environment. Erosion plots were also used to quantify soil erosion. The evidence found in the area affected by the fire in Braga and in the city itself demonstrates the serious impacts of forest fires on the soil, namely in terms of its erosion and degradation, and consequent impacts on the downstream areas, especially when it comes to urban areas.

This research was funded by Portuguese funds through Fundação para a Ciência e a Tecnologia, I.P., within the scope of the research project “EROFIRE - Post-fire erosion risk assessment using molecular markers”, reference PCIF/RPG/0079/2018.

How to cite: Vieira, A., Bento Gonçalves, A., Novais, J., Folharini, S., and Rocha, J.: Soil erosion after the 2017 forest fire of Braga (Portugal), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-727, https://doi.org/10.5194/icg2022-727, 2022.

European Mediterranean regions are witnessing unprecedented changes owing to the impacts of global change, understood as the set of human influences on the environment and climate change. Under this context, an exacerbation of extreme events such as wildfires is expected. Wildfires are considered one of the most important factors of soil and ecosystems degradation, as soils affected by this phenomenon are erosion-prone due to the removal of vegetation and litter cover and soil physicochemical properties alteration. Fallout-radionuclides (FRNs) can be used as tools to trace soil redistribution due to erosion or deposition. Furthermore, the implementation of a re-sampling approach allows to document changes in soil redistribution under the current context of global change. This study aims to assess soil redistribution rates at different time windows through the use of fallout-radionuclides (¹³⁷Cs and ²¹⁰Pb_ex) in a mid-mountainous Mediterranean catchment affected by recurrent wildfires. Three micro-catchments (MCs) were selected within the Sa Font de la Vila River catchment (4.8 km²); which is characterized by revegetation processes, wildfires recurrence and a huge presence of agricultural terraces: MC1 (1.73 ha; burned in 1994 and 2013), MC2 (2.28 ha; burned in 2013) and MC3 (2.24 ha; non-burned). In order to estimate soil redistribution rates in the short and medium-term after the 2013 wildfire, a resampling approach was carried out, with the first sampling campaign at the end of 2013 and the second one in 2020. In each of these campaigns, the same 80 locations were sampled within the three MCs following a stratified random sampling strategy with 21 bulk cores in MC1, 39 bulk cores in MC2 and 20 bulk cores in MC3. Preliminary results from the 2013 sampling campaign showed the following mean ¹³⁷Cs inventories: 434 Bq m^-2 (MC1), 305 Bq m^-2 (MC2) and 214 Bq m^-2 (MC3); and ²¹⁰Pb_ex inventories: 374 Bq m^-2 (MC1), 607 Bq m^-2 (MC2) and 515 Bq m^-2 (MC3). The diffusion and migration model developed by Walling and He (2001) will be applied to convert the measured inventories into estimates of soil erosion or deposition rates. During the session, the implementation of this experimental design will allow to explain and discuss the main results and conclusions. This study will allow to understand the effects of a wildfire at the short and medium-term in a terraced burned Mediterranean catchment. 

How to cite: Company, J., Fortesa, J., García-Comendador, J., and Estrany, J.: Effects of wildfires recurrency on soil erosion in a terraced burned Mediterranean catchment, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-621, https://doi.org/10.5194/icg2022-621, 2022.

Wildfires have a long history in the Mediterranean and Atlantic coastal regions, and such devastating events are anticipated to increase in parallel with changing climatic conditions. Wildfires play an important role in short-term ecological and geomorphological changes, as they can instantly affect vegetation, soil properties, and drainage properties. In comparison to unburned conditions, wildfire alters the erosional response of hillslopes, increasing the potential for runoff and sediment flux, as reported in many studies. Specifically, wildfire-affected steep hillslopes can promote the initiation of debris flows which may cause substantial sediment delivery and increase hazard levels for society and infrastructure downstream of burned areas.

In this study, we report the erosional response of hillslopes and spatial probability debris flows after the July 10, 2019, Dalaman, Göcek (Muğla) wildfire, which was effective in a total of 15 km² forested area. We used different ground and remote sensing methods covering two years of field observation and measurements from shortly after the event. In our study, in which we compared the results obtained by conventional field-based assessments with Unmanned Aerial Vehicle (UAV) measurements, we quantified that the erosion is localized spatially in the middle and upper parts of the basins and led to an average erosion rate of more than 10 mm in two years. In addition, we revealed that the susceptibility of the debris flows after the fire has increased significantly, primarily concentrated in the far north of the fire-affected hillslope sections. We concluded that the spatial probability of debris-flow events and their runouts would increase their impacts by significantly affecting the excavation of hillslope materials, mainly boosted by salvage logging after the event. Moreover, our preliminary findings show that accurate estimates of the magnitude of post-wildfire debris flow and erosion potential are essential to comprehend immediate hazards as well as long-term geomorphic changes.

This study has been produced benefiting from the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not mean that the content of the publication is approved in a scientific sense by TUBITAK.

How to cite: Gorum, T., Yildiz, C., Ozcan, O., Comert, R., and Yetemen, O.: Assessment of Increased Debris Flow Hazard After Wildfires: Lessons from the Dalaman Fire, Eastern Mediterranean, Turkey, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-83, https://doi.org/10.5194/icg2022-83, 2022.

Wildfires have become an increasing threat for Mediterranean ecosystems, due to increasing climate change induced wildfire activity and changing land management practises. In addition to the initial risk, wildfires can alter the soil in various ways depending on fire severity and cause enhanced post-fire erosion. Usually, post-fire erosion studies focus on a short time window and lack the attention for sediment dynamics at larger spatial scales. Yet, these large spatial and temporal scales are fundamental for a better understanding of long-term destructive effects of multiple recurring wildfires on post-fire erosion processes and catchment sediment dynamics. In this study the landscape evolution model LAPSUS was used to simulate erosion and deposition in the 404 km² Águeda catchment in northern-central Portugal over a 41 year (1979-2020) timespan, including eight wildfires each burning more than 1000 ha. To include variation in fire severity and its impact on the soil four burnt severity classes, represented by the difference Normalized Burn Ratio (dNBR), were parameterized. Although model calibration was difficult due to lack of spatial and temporal measured data, the results show that long-term post-fire net-erosion rates were significantly higher in the wildfire scenarios (5.95 ton ha^-1 yr^-1) compared to those of a non-wildfire scenario (0.58 ton ha^-1 yr^-1). Furthermore, erosion values increased with burnt severity and multiple wildfires increased the overall catchment sediment build-up. Simulated erosion patterns showed great spatial variability with large deposition and erosion rates inside streams. This variability made it difficult to identify land uses that were most sensitive for post-fire erosion, because some land-uses were located in more erosion-sensitive areas (e.g. streams, gullies) or were more affected by high burnt severity levels than others. Despite these limitations, LAPSUS performed well on addressing spatial sediment processes and can contribute to pre-fire management strategies, by identifying locations at risk for post-fire erosion.

How to cite: Follmi, D., Baartman, J., Benali, A., and Nunes, J. P.: How do large wildfires impact sediment redistribution over multiple decades? A landscape evolution modelling assessment in a Mediterranean watershed., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-429, https://doi.org/10.5194/icg2022-429, 2022.

Soil erosion increases after forest fires contributing to the mobilization, transport, and deposition of sediments and nutrients in watersheds. This scenario interferes with water quality. Faced with a climate change scenario, forest fires in the Mediterranean region tend to increase, consequently, soil erosion must increase together, aggravating water availability. Measures to minimize the effects of soil erosion in watersheds must be used to guarantee the water security of the population and protected areas play an important role in this context. This study analyzed 761 sub-watersheds in northern Portugal, to evaluate machine learning models in watersheds with recurrent fires. The analyzed area has a high recurrence of forest fires and where important districts of the country such as Porto and Braga with high population density are located, in addition to protected areas where springs of watercourses that integrate important watersheds such as Douro, Cávado, Ave, and Mondego. The parameters analyzed were: total burned area of ​​the sub-watershed in the period 1975-2020 (variable target), soil erosion by water in Europe - Revised Universal Soil Loss Equation (RUSLE2015), Topographic Wetness Index (TWI), and the morphometric parameters: Area (A), Perimeter (P), Length (L), Width (W), Orientation (O), Elongation ratio (Re), Circularity ratio (Rc), Compactness coefficient (Cc), Form factor (Ff), Shape factor ( Sf), Altitude, Slope, Curvature. These data was analyzed with the machine learning Generalized Linear Models (GLM), Support Vector Machine Linear (SVMLinear), Support Vector Machine Polynomial (SVMPoly) and Random Forest (RF). The analysis was developed in R language using the classification and regression training caret package. The average R² for each model was RF (0.97), SVMpoly (0.96), SVMLinear (0.78) and GLM (0.78). In an analysis of boxplot plots of R², Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) the RF and SVMpoly models recorded lower dispersion of R² and lower values ​​of MAE and RMSE. While the GLM and SVMlinear models showed greater data dispersion in the three accuracy measures of the models. Regarding the analyzed parameters, those that registered the greatest importance were A, Cc, P, Rc, W, RUSLE2015, and TWI, indicating that an analysis that considers morphometric parameters, together with soil erosion data by water and soil moisture is an important indicator in the analysis of soil erosion in watersheds. The study was developed within the scope of the CLICTOUR project (Project NORTE-01-0145-FEDER-000079), supporting fund European Regional Development Fund.

Keywords: Soil erosion, sub-watersheds, machine learning, burned areas, water security.

How to cite: Folharini, S., Marques, T., Silva, S., Novais, J., Bento-Gonçalves, A., and Vieira, A.: Machine learning applied to soil erosion analysis in sub-watersheds with burned areas, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-560, https://doi.org/10.5194/icg2022-560, 2022.

The Nechako River Basin, located in central British Columbia, Canada is a 52,000 km², regulated basin that has been significantly impacted by large-scale landscape changes. These changes began with the construction of the Kenney dam in 1952 but are evidenced primarily by the Mountain Pine Beetle epidemic, industrial forestry and agriculture, and sizable and severe wildfires. In 2018 wildfires burned 3,682 km² within the basin and due to the severity of the fires, much of the burned area was completely denuded of vegetation. The NRB is important for chinook and sockeye salmon as well as the Nechako White Sturgeon and thus, potential changes to the sediment regime as a result of increased erosion after the aforementioned landscape changes and exacerbated by wildfire could have deleterious effects on fish health and populations. In particular, sediment is known in the NRB to clog spawning habitat, leading to reduced juvenile success. Therefore, this study aimed to use polycyclic aromatic hydrocarbons (PAHs), compounds that are produced during the combustion of organic material, to trace sediment sources in the Nechako River and its tributaries that were most impacted by the 2018 fires. Additionally, this research aims to determine the utility of PAHs as a novel tracer for future source apportionment studies.

Soil sampling was undertaken in autumn 2018, immediately post-fire at five sites that were burned and five sites that were unburned. Samples at the unburned sites consisted of the topsoil (0-2 cm) and subsoil (2-10 cm), while burned sites included the burned organic layer, burned topsoil layer, and the subsoil layer. Bank samples from the mainstem and tributaries were collected in 2020 and 2021, along with resampling of the topsoil at the burned sites. Additionally, because the burning of fossil fuels also produces PAHs, road deposited sediment was collected in 2021 as another potential source. Sediment samples were collected biweekly from autumn 2018 to autumn 2021 throughout the ice-free period (generally May-October), using time-integrated passive samplers. Both the soil and sediment samples were sieved to 1 mm and analysed for loss on ignition, particle size, colour, and the 16 priority PAHs as outlined by the US EPA. Using MixSIAR, source apportionment results showed that on the Nechako River mainstem, the primary source of sediment was unburned material, and more specifically, bank material. This follows findings from recent research undertaken in the basin, but further modeling is being undertaken to determine if these findings match those using colour as the primary tracer. Ultimately, the use of PAHs as a novel tracer, particularly in wildfire prone areas, seems promising, though more studies are needed. Additionally, because PAHs are known to be toxic compounds, there is an added benefit in their use as a tracer to also determine their spatial and temporal pervasiveness post-wildfire, particularly with respect to the health of the aquatic ecosystem.

How to cite: Kieta, K., Owens, P., and Petticrew, E.: Tracing sediment sources after wildfire using polycyclic aromatic hydrocarbons, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-509, https://doi.org/10.5194/icg2022-509, 2022.

The ash produced by forest fires is a complex mixture of organic and inorganic particles with various properties. Ash and char are broad indicators for evaluating the impacts of fire on nutrient cycling and ecosystem recovery. Numerous studies suggested assessing fire severity by changes in ash characteristics. Traditional methods for fire severity are based on in situ observations, i.e. a visual approximation of changes in the forest floor and soil which are time-consuming and subjective. These measures primarily reflect the level of consumption of organic layers, the deposition of ash, particularly its depth and colour, and fire-induced changes in the soil. Numerous recent studies on fire severity suggested using remote sensing techniques combined with field observations via machine learning and spectral induces approaches to obtain practical tools for assessing the fire effects on ecosystems. While index thresholding can be easily implemented, its effectiveness over large areas is limited pattern coverage of forest type and fire regimes.

On the other hand, the machine learning algorithms allow multivariate classifications, but in the case of processing space-time series analysis, learning becomes complex and time-consuming. Therefore, there is no complete agreement on a quantitative index determining the severity metric. Given that wildfires play a significant role in controlling forest carbon storage and cycling, this study presents the potential of low-cost multispectral imagery across visible and near-infrared regions collected by the unmanned aerial systems to determine fire severity according to the colour and chemical properties of the vegetation ash. The use of multispectral imagery data might reduce impreciseness caused by manual colour matching and produce a vast and accurate spatial-temporal severity map. The suggested severity map is based on deep learning algorithms' spectral information used to evaluate chemical changes in fuels. These methods quantify total carbon content and assess the corresponding fire intensity required to form a particular residue. By designing three different learning algorithms (PLS-DA, ANN, and 1-D CNN) for two datasets (RGB images and Munsell colour versus UAS-based multispectral imagery) the multispectral prediction results show an excellent performance, which, therefore, shows that the deep network-based near-infrared remote sensing technology has a future potential to become an alternative and reliable fire severity monitoring method.

How to cite: Wittenberg, L., Hamzi, S., Roberts, D., Ichoku, C., Shtober‐Zisu, N., and Brook, A.: Total Carbon content assessed by UAS near-infrared imagery as a new fire severity metric, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-259, https://doi.org/10.5194/icg2022-259, 2022.