271 research outputs found
A step towards a holistic assessment of soil degradation in Europe: Coupling on-site erosion with sediment transfer and carbon fluxes
Soil degradation due to erosion is connected to two serious environmental impacts: (i) on-site soil loss and (ii) off-site effects of sediment transfer through the landscape. The potential impact of soil erosion processes on biogeochemical cycles has received increasing attention in the last two decades. Properly designed modelling assumptions on effective soil loss are a key pre-requisite to improve our understanding of the magnitude of nutrients that are mobilized through soil erosion and the resultant effects. The aim of this study is to quantify the potential spatial displacement and transport of soil sediments due to water erosion at European scale. We computed long-term averages of annual soil loss and deposition rates by means of the extensively tested spatially distributed WaTEM/SEDEM model. Our findings indicate that soil loss from Europe in the riverine systems is about 15% of the estimated gross on-site erosion. The estimated sediment yield totals 0.164 ± 0.013 Pg yr−1 (which corresponds to 4.62 ± 0.37 Mg ha−1 yr−1 in the erosion area). The greatest amount of gross on-site erosion as well as soil loss to rivers occurs in the agricultural land (93.5%). By contrast, forestland and other semi-natural vegetation areas experience an overall surplus of sediments which is driven by a re-deposition of sediments eroded from agricultural land. Combining the predicted soil loss rates with the European soil organic carbon (SOC) stock, we estimate a SOC displacement by water erosion of 14.5 Tg yr−1 . The SOC potentially transferred to the riverine system equals to 2.2 Tg yr−1 (~15%). Integrated sediment delivery-biogeochemical models need to answer the question on how carbon mineralization during detachment and transport might be balanced or even off-set by carbon sequestration due to dynamic replacement and sediment burial
Modelling the effect of land management changes on soil organic carbon stocks in a mediterranean cultivated field
28 Pags.- 5 Tabls.- 4 Figs. The definitive version is available at: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-145XLand management in agricultural lands has important effects on soil organic carbon (SOC) dynamics. These effects are particularly relevant in the Mediterranean region, where soils are fragile and prone to erosion. Increasing interest of modelling to simulate SOC dynamics and the significance of soil erosion on SOC redistribution have been linked to the development of some recent models. In this study, the SPEROS-C model was implemented in a 1.6-ha cereal field for a 150-year period covering 100 years of minimum tillage by animal traction, 35 years of conventional tillage followed by 15 years of reduced tillage by chisel to evaluate the effects of changes in land management on SOC stocks and lateral carbon fluxes in a Mediterranean agroecosystem. The spatial patterns of measured and simulated SOC stocks were in good agreement, and their spatial variability appeared to be closely linked to soil redistribution. Changes in the magnitude of lateral SOC fluxes differed between land management showing that during the conventional tillage period the carbon losses is slightly higher (0.06 g C m−2 yr−1) compared to the period of reduced till using chisel (0.04 g C m−2 yr−1).
Although the results showed that the SPEROS-C model is a potential tool to evaluate erosion induced carbon fluxes and assess the relative contribution of different land management on SOC stocks in Mediterranean agroecosystems, the model was not able to fully represent the observed SOC stocks. Further research (e.g. input parameters) and model development will be needed to achieve more accurate results.This work was funded by the CICYT project (CGL2014-52986-R).Peer reviewe
Unravelling earth flow dynamics with 3-D time series derived from UAV-SfM models
Accurately assessing geo-hazards and quantifying landslide risks in mountainous environments are gaining importance in the context of the ongoing global warming. For an in-depth understanding of slope failure mechanisms, accurate monitoring of the mass movement topography at high spatial and temporal resolutions remains essential. The choice of the acquisition framework for high-resolution topographic reconstructions will mainly result from the trade-off between the spatial resolution needed and the extent of the study area. Recent advances in the development of unmanned aerial vehicle (UAV)-based image acquisition combined with the structure-from-motion (SfM) algorithm for three-dimensional (3-D) reconstruction make the UAV-SfM frame- work a competitive alternative to other high-resolution topographic techniques.
In this study, we aim at gaining in-depth knowledge of the Schimbrig earthflow located in the foothills of the Central Swiss Alps by monitoring ground surface displacements at very high spatial and temporal resolution using the efficiency of the UAV-SfM framework. We produced distinct topographic datasets for three acquisition dates between 2013 and 2015 in order to conduct a comprehensive 3-D analysis of the landslide. Therefore, we computed (1) the sediment budget of the hillslope, and (2) the horizontal and (3) the three-dimensional surface displacements. The multitemporal UAV-SfM based topographic reconstructions allowed us to quantify rates of sediment redistribution and surface movements. Our data show that the Schimbrig earthflow is very active, with mean annual horizontal displacement ranging between 6 and 9 m. Combination and careful interpretation of high-resolution topographic analyses reveal the internal mechanisms of the earthflow and its complex rotational structure. In addition to variation in horizontal surface movements through time, we interestingly showed that the configuration of nested rotational units changes through time. Although there are major changes in the in- ternal structure of the earthflow in the 2013–2015 period, the sediment budget of the drainage basin is nearly in equilibrium. As a consequence, our data show that the time lag between sediment mobilization by landslides and enhanced sediment fluxes in the river network can be considerable
Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions
Agricultural terraced landscapes, which are important historical heritage sites (e.g., UNESCO or Globally Important Agricultural Heritage Systems (GIAHS) sites) are under threat from increased soil degradation due to climate change and land abandonment. Remote sensing can assist in the assessment and monitoring of such cultural ecosystem services. However, due to the limitations imposed by rugged topography and the occurrence of vegetation, the application of a single high-resolution topography (HRT) technique is challenging in these particular agricultural environments. Therefore, data fusion of HRT techniques (terrestrial laser scanning (TLS) and aerial/terrestrial structure from motion (SfM)) was tested for the first time in this context (terraces), to the best of our knowledge, to overcome specific detection problems such as the complex topographic and landcover conditions of the terrace systems. SfM–TLS data fusion methodology was trialed in order to produce very high-resolution digital terrain models (DTMs) of two agricultural terrace areas, both characterized by the presence of vegetation that covers parts of the subvertical surfaces, complex morphology, and inaccessible areas. In the unreachable areas, it was necessary to find effective solutions to carry out HRT surveys; therefore, we tested the direct georeferencing (DG) method, exploiting onboard multifrequency GNSS receivers for unmanned aerial vehicles (UAVs) and postprocessing kinematic (PPK) data. The results showed that the fusion of data based on different methods and acquisition platforms is required to obtain accurate DTMs that reflect the real surface roughness of terrace systems without gaps in data. Moreover, in inaccessible or hazardous terrains, a combination of direct and indirect georeferencing was a useful solution to reduce the substantial inconvenience and cost of ground control point (GCP) placement. We show that in order to obtain a precise data fusion in these complex conditions, it is essential to utilize a complete and specific workflow. This workflow must incorporate all data merging issues and landcover condition problems, encompassing the survey planning step, the coregistration process, and the error analysis of the outputs. The high-resolution DTMs realized can provide a starting point for land degradation process assessment of these agriculture environments and supplies useful information to stakeholders for better management and protection of such important heritage landscapes
Peat soil thickness and carbon storage in the Belgian High Fens: insights from multi-sensor UAV remote sensing
editorial reviewedPeatlands are known to store a large amount of carbon, but global warming and associated changes in hydrology have the potential to accelerate peatland carbon emissions. An in-depth understanding of carbon dynamics within these peatlands is therefore important. However, peatlands are complex ecosystems, and acquiring accurate and reliable estimates of how much carbon is stored underneath the Earth’s surface is inherently challenging even at small scales. Here, Unmanned Aerial Vehicles (UAVs) equipped with RGB, multispectral, thermal infrared, and LiDAR sensors were combined with Ground Penetrating Radar (GPR) technology and traditional field surveys, to provide a comprehensive 4D monitoring of a peatland landscape in the Belgian High Fens. Data was collected along a hillslope-floodplain transition. We aimed to establish links between the above- and below-ground factors that control soil carbon status, identify the key drivers of carbon storage as well as explore the potential of UAV remote sensing for spatial mapping of peat depth and carbon stock. Our results indicated that peat thickness widely varied (0.2 to 2.1 m) at small scales and is negatively correlated with elevation (r= -0.39, p<0.001). We found that soil organic carbon (SOC) stock is spatially organized, as abundant carbon was observed at the summit and shoulder of the hill, with an average storage of 670.93 ± 108.86 t/ha and 601.47 ± 133.40 t/ha, respectively. Moreover, the carbon storage exhibited heterogeneity under different vegetation types, with trees having the highest mean SOC stocks at 722.21 ± 37.92 t/ha. Through multiple linear regression, we identified 6 environmental variables that can explain 71.44% of SOC stock variance. Clay content is the most critical factor, accounting for nearly 40% of the variance, followed by topography. Contributions from land surface temperature and vegetation remain below 10%. In addition, UAV data provided accurate estimations of both peat depth and SOC stock, with RMSE and R2 values of 0.13 m and 0.88 for the peat depth test dataset, and 114.42 t/ha and 0.84 for the SOC stock. Our study bridged the gap between surface observations and the hidden carbon reservoir below, this not only allows us to improve our ability to assess the spatial distribution of C stocks but also contributes to our understanding of the drivers of C turnover in these highly heterogeneous landscapes, providing insights for environmental science and climate projections
Nutrients and dissolved organic carbon dynamics in response to environmental drivers in a Belgian peatland
editorial reviewe
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