Nomadic communities are difficult to detect in the written and material record historians and archaeologists traditionally use to study the past. Contrary to settled grain cultivators, who were easy target for state taxation and were often recorded in a variety of documents, or who left easy to detect traces of permanent villages, nomads often remained outside of the radar of the traditional sources. Nomadic communities, however, profoundly transformed landscapes they lived in. These landscapes, in turn, produced different environmental signals that are preserved in the sedimentary records. Pollen data, in particular, make it possible to reconstruct the presence and activities of nomads in a given area, filling in the gaps in the historical and archaeological record. In our short presentation, we will look at high resolution pollen evidence from Macedonia (Northern Greece) that could be used to trace the presence of transhumant nomads in this region in the last two millennia. We will show how the paleoenvironmental reconstruction can be connected to otherwise fragmentary and problematic written information to create a consilient reconstruction of the past, recovering the presence of diverse groups that inhabited the Northern Greek landscape in the medieval and early modern times.

How to cite: Izdebski, A. and Liakopoulos, G.: Detecting the undecteable: transhumant nomads in palynological data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20730, https://doi.org/10.5194/egusphere-egu24-20730, 2024.

The considerable research on the effects of the 1815 Tambora eruption (Behringer 2015) has shown not only to what extent large tropical volcanic eruptions can transform a society but also how advantageous it is for research when geosciences and humanities interlink.

While single eruption events such as Parker in 1640/1641 have already been analysed (Stoffel et al. 2022), there has been less focus on the potential teleconnections of multiple eruptions on one single study area. This paper looks at the climatic and societal impacts of three tropical volcanic eruptions – Huaynaputina (1600), Komaga-take/Parker (1640/1641) and the 1690s unknown event – on Fribourg, a region in the western part of the Swiss Confederation.

To answer this research question meticulously, a transdisciplinary approach is required – both in method and sources. Daring to bridge geosciences and humanities, as part of the VICES research project we developed a data processing tool called ClimeApp, which facilitates the usage of climate data and makes transdisciplinary interaction more accessible, especially for researchers from the humanities (http://mode-ra.unibe.ch/climeapp).

Using ClimeApp, the climatological impact of these 17^th century eruptions will be assessed with modern climate reconstruction data from the state-of-the-art ModE-RA project (Valler et al. 2024). Novel archive material from municipal institutions – such as the Hôpital des bourgeois de Fribourg – allows us subsequently to determine the annually recorded harvest yields especially of the viti- and caseiculture. Additionally, essential archival sources, such as the Ratsmanuale (protocols) and the Mandatenbücher (regulations), depict whether the municipality of Fribourg deployed any measures or coping mechanisms in the wake of these volcanic eruptions. This combination of climatological data and historical sources enables us to look for potential interrelations between these climate anomalies and the effect they had on society.

The paper exemplary highlights on one side the advantages of research collaboration between two disciplines and on the other side sheds light on the possible impacts of multiple volcanic eruptions spanned over the period of almost hundred years on the same study region.

How to cite: Bartlome, N. E. and Warren, R. M.: Visible or negligible? Impacts of the 17th century volcanic eruption on climate and society in early modern Switzerland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17186, https://doi.org/10.5194/egusphere-egu24-17186, 2024.

Human displacements, especially those driven by violent conflicts forcing sudden population migrations, wield profound and enduring impacts on landscapes, instigating substantial disruptions to the natural environment. Beyond immediate destruction, these consequences pose challenges to ecosystem health, food security, and biodiversity conservation, particularly exacerbated in the absence of effective governance. Traditional land management practices, agriculture, and conservation efforts are disrupted, constraining the implementation of long or medium-term conservation practices in agriculture. These disruptions may contribute to increased erosion and sediment transport, depleting soil nutrients and resulting in natural disasters such as flash floods, landslides, and water quality degradation. This phenomenon is particularly pronounced in regions experiencing high rainfall intensity, coupled with inadequate land use and agricultural management practices. Understanding the primary factors behind the last decades escalation in land degradation and subsequent sediment export is crucial to prevent further ecosystem degradation and heightened instability in conflict-affected areas. To address this, we have developed an integrated approach involving core sampling, sediment fingerprinting techniques, high-resolution sediment sampling, and automated remote sensing routines to pinpoint hotspot areas and track conservation efforts. Using the Lake Kivu region as a case study, situated on the border between Rwanda and the Democratic Republic of the Congo, an area marked by prolonged violent conflict since the early 1990s, we evaluate the applicability of this combined approach.

The preliminary results from the multiple techniques independently suggest an increasing trend in exported sediment over the last decade. This trend is particularly pronounced in areas characterized by high instability and economic challenges. In contrast, relatively more stable regions exhibit a stabilization in sedimentation rates. This stability is attributed primarily to the implementation of conservation practices and the presence of robust transport infrastructures, both playing crucial roles in landscape conservation. Results underscore the method's effectiveness in elucidating lasting effects on landscapes impacted by 'polycrisis', necessitating consolidated and comprehensive responses over mere technical solutions. The research objective is to target specific areas within conflict-affected regions, with a focus on mitigating environmental degradation and associated challenges.

How to cite: Lizaga, I., Latorre, B., Bagalwa, M., Nkuba, B., Bodé, S., Katcho, K., Ciraba, H., Evrard, O., Büscher, K., Vlassenroot, K., Van Oost, K., Blake, W., Navas, A., and Boeckx, P.: Long-term Monitoring of Environmental and Geophysical Impacts in Conflict-Endured Zones: A Landscape Perspective on Kivu Lake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12062, https://doi.org/10.5194/egusphere-egu24-12062, 2024.

A particular challenge threatening global food security is the threat of armed conflict. In particular, the Panjshir valley of northeastern Afghanistan continues to experience acute food insecurity due to intense armed conflict. In this rural valley, conflict driven displacement leads to agricultural land abandonment and decreases in crop yields. These decreases in local food production have an outsized impact on food security, due to the region’s dependence on subsistence agriculture. Despite the consensus that armed conflict has a significant negative impact on the population’s food security, the exact mechanics of how conflict impacts food security remains unclear. 

To quantify armed conflict’s impact on local food production, I compare trends in vegetation health between agricultural plots in high-conflict and no-conflict landscapes with similar altitudinal gradients. I focus on the period during the Soviet occupation of Afghanistan from 1980-1989, which saw nine major military offensives occur in the Panjshir valley. I use Landsat 5 (1984-2012) to obtain the Normalised Difference Vegetation Index (NDVI) values for agricultural plots that have been designated as control (no conflict) and treatment (high conflict). These plots are delineated using HEXAGON KH-9 declassified spy imagery, and assigned conflict intensity designations based on explosive ordnance disposal (EOD) data from The HALO Trust, a non-governmental organisation which carries out unexploded ordnance clearance in Afghanistan. Residual Trend analysis (RESTREND) is applied to Landsat NDVI values to distinguish between the shifts in vegetation health that are anthropogenically and climatically driven. 

This research provides a deeper understanding of how past conflict has acted as a driver of food insecurity in the region. Additionally, it allows for future work to build off of these findings and predict how current and future conflict might have an impact. These findings can inform humanitarian and development aid policy, while the methodology can be applied to other contexts where conflict is present. 

How to cite: Allen, J.: Detecting Disturbance to Agricultural Productivity from Historical Armed Conflict in Afghanistan: The Panjshir Offensives, 1980-1985, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13525, https://doi.org/10.5194/egusphere-egu24-13525, 2024.

The war in Ukraine, which has been going on since February 2022, has dealt a severe blow to the country's agricultural sector. Millions of hectares of agricultural land have been destroyed by shelling, explosions, and landmines. This has raised concerns about food security in the international community, as Ukraine was a leading producer and exporter of wheat, maize, barley, and sunflower oil before the war. In order to determine the extent of the damage and develop the necessary recovery measures, as well as to formulate effective resource management strategies to ensure the sustainability of the agricultural sector, it is critical to accurately assess and locate the damaged agricultural areas.

Remote sensing, with its advantages in speed, coverage, and objectivity over ground-based methods, combined with machine learning, offers opportunities for the automatic detection of damaged fields across the entire territory of Ukraine and tracking the dynamics of damage development almost in real-time. This research demonstrates the potential of remote sensing and machine learning in detecting and analyzing damaged agricultural fields in Ukraine because of the military conflict.

We utilize freely available two-week composites from the Sentinel-2 satellite with a spatial resolution of 10 meters. The search for damaged fields is conducted in the cloud environment of Google Earth Engine using a random forest binary classifier trained on a manually collected sample by three independent experts. The input parameters for the classifier include static indicators (minimum, average, maximum, variance) of two spectral bands (B2, B3) and two vegetation indices (NDVI and GCI), which have been experimentally found to be the most informative for detecting field damage. Additionally, within the classified damaged fields, we identify local damages using an anomaly detection method. This involves measuring the deviation of values of individual pixels from the mean value of all pixels within a specific field in the spectra of the above-mentioned bands and vegetation indices.

The developed classifier achieves an accuracy of 0.9 for both recall and precision. The anomaly analysis method proves sensitive to the vegetation period and the geographical location of the study area. However, with careful selection of the threshold coefficient, the developed method demonstrates sufficiently accurate results and allows the recognition of craters with an estimated area >50 m².

The results highlight substantial losses to Ukraine's agricultural sector due to the war. It was determined that from the beginning of the conflict until December 4, 2023, more than 1.5 million agricultural fields in Ukraine were damaged, constituting approximately 5.65% of the total sown area. The most affected crops were wheat (489,529 ha or 5.78% of the total cultivated area for this crop), sunflower (115,358 ha or 1.56% of the cultivated area), maize (61,123 ha or 1.2%), and rapeseed (42,783 ha or 2.65%).

Our methods are applicable to large territories for detecting damages to various agricultural crops. The research will be valuable for assessing and restoring damaged lands, as well as for developing strategies for adaptation and resilience of the agricultural sector to other similar crisis situations.

How to cite: Drozd, S., Kussul, N., and Yailymova, H.: Evaluating the Impact of Armed Conflict on Agricultural Sector in Ukraine through Remote Sensing and Machine Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10494, https://doi.org/10.5194/egusphere-egu24-10494, 2024.

Since the beginning of the full-scale aggression on 24 February, 2022, primary targets for missiles attacks of Russian Federation were the objects of energy sector of Ukraine.  According to the reports of the State Environmental Inspection of Ukraine, more than 30 units comprising oil depots, product warehouses, refineries, gas stations were destroyed during the March 2022 only. Most of these objects were oil depots.  The purpose of this investigation was an environmental impact assessment of the missile attacks on the petroleum depots. We analysed the cases of destruction of oil depots in Okhtyrka (Okhtyrkanaftogaz), Chernihiv (Aystra), Kalynivka (KLO) and Kryachki (AS Investment), which were completely or partially destroyed. The results of field research, satellite monitoring data, data of the State Environmental Inspection and other state bodies were used for the analysis.

As a result of the attacks, a significant part of petroleum products burned, which caused atmospheric air pollution by combustion products (carbon monoxide (CO), carbon dioxide (CO2), soot (C), nitrogen dioxide (NO2), sulphur dioxide (SO2), marginal hydrocarbons (С12-C19)). The estimated volume of emissions at the Kalynivka oil depot alone is more than 30 metric tons of carbon dioxide equivalent (mt CO2e). Spills of oil products caused pollution and partial burning of the surface layer of soils (at all bases) and penetration of oil products into groundwater with further migration over considerable distances (Kalynivka oil depot). The article presents the results of the monitoring and quantitative assessment of the soil and ground water pollution by oil derivatives as well as plant biodiversity assessment on the territory suffered from the incidents.

How to cite: Karamushka, V., Boychenko, S., and Havryliuk, R.: Environmental consequences resulted from the oil depots’ deterioration by the RF’s missile attacks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-478, https://doi.org/10.5194/egusphere-egu24-478, 2024.