Abstract Current debates about the Anthropocene have sparked renewed interest in the relationship between ecology, technology, and coloniality. How do humans relate to one another, to the living ...environment, and to their material or technological artifacts; and how are these relations structured by coloniality, defined not only as a material process of appropriation and subjugation, but also as an exclusionary hierarchy of knowing and being that still pervades contemporary life? While these questions have of course received attention in decolonial theory, they have also captured the interest of scholars who self-identify with the field of political ecology. However, it can be argued that political ecology still primarily adheres to research practices and paradigms that have been developed in the West, regardless of its diversity and dynamism as a field of research. It is therefore suggested that a rapprochement between decolonial theory and political ecology can open up new perspectives on current debates that are emerging around the concept of the Anthropocene. In particular, the article takes the recent interest in the ontological implications of the Anthropocene as a point of departure to bring the decolonial notion of 'border thinking' into a conversation with the so-called 'new materialism' in political ecology. While both approaches are not necessarily opposed to values grounded in rationality, they can be seen as attempts to rethink ontological divisions such as human/nature or subject/object based on 'enchanted' ways of knowing and being-in-the-world. Yet, although enchantment has the potential to counter inherently colonial practices of appropriation, commodification and objectification, it is argued that keeping a moderately critical distance to enchanted narratives is still recommended, not because of the alleged naïveté of such narratives, but rather because enchantments may also function as and through technologies of power. Key words: Anthropocene; political ecology; decoloniality; new materialism; border thinking; ontology; enchantment
Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from ...peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model.
The rapid development of digital technologies such as blockchain and distributed ledger-based systems holds transformative potential for the financial sector. Promising applications include asset ...management as well as peer-to-peer networks for the transparent exchange of data and information. International climate finance stands to benefit in particular ways from these new opportunities in financial technology. Distributed ledger technologies could be leveraged to support climate action, for example by facilitating transparent and standardized transactions, or by enabling more efficient monitoring and accreditation processes. In view of these promising opportunities, we focus our inquiry on the case of the Green Climate Fund to explore how distributed ledger technologies can be used for innovative climate finance. Based on our analysis of different digital system models and potential use cases, we then discuss some of the technical and political challenges that may arise, for example with regard to standards and safeguards, governance processes, country ownership, and further capitalization. Our findings show that distributed ledger-based systems could benefit the work of the fund in key areas such as multi-stakeholder coordination and impact assessment. However, our analysis also points to the concrete limitations of technology driven solutions. Digital technologies are not a standalone solution to persistent resource allocation and governance challenges in international climate finance, especially because the design and deployment of these digital systems is inherently political.
Land cover classification has been widely investigated in remote sensing for agricultural, ecological and hydrological applications. Landsat images with multispectral bands are commonly used to study ...the numerous classification methods in order to improve the classification accuracy. Thermal remote sensing provides valuable information to investigate the effectiveness of the thermal bands in extracting land cover patterns. k-NN and Random Forest algorithms were applied to both the single Landsat 8 image and the time series Landsat 4/5 images for the Attert catchment in the Grand Duchy of Luxembourg, trained and validated by the ground-truth reference data considering the three level classification scheme from COoRdination of INformation on the Environment (CORINE) using the 10-fold cross validation method. The accuracy assessment showed that compared to the visible and near infrared (VIS/NIR) bands, the time series of thermal images alone can produce comparatively reliable land cover maps with the best overall accuracy of 98.7% to 99.1% for Level 1 classification and 93.9% to 96.3% for the Level 2 classification. In addition, the combination with the thermal band improves the overall accuracy by 5% and 6% for the single Landsat 8 image in Level 2 and Level 3 category and provides the best classified results with all seven bands for the time series of Landsat TM images.
ABSTRACT
The near surface air temperature is the primary indicator for climate change. Reanalysis as the surrogates for large‐scale observations are widely used in the Tibetan Plateau because of the ...sparse meteorological network. However, an average bias of −3.54 °C and root‐mean‐square error (RMSE) of 4.31 °C were found between ERA‐Interim monthly 2‐m temperature and observation over the Tibetan Plateau, which indicated that a correction procedure for ERA‐Interim is necessary before local scale applications. To overcome this challenge, a robust elevation correction method is developed to downscale ERA‐Interim 2° × 2° monthly 2‐m temperature data based on ERA‐Interim internal vertical lapse rates. This method is validated against 80 meteorological stations from 1979 to 2013 located in 26 ERA‐Interim grid cells. It is also compared with other four correction methods, which are using different lapse rate schemes such as fixed monthly lapse rates, surface lapse rates calculated from the meteorological stations (within a single grid or with neighbouring sites), as well as a third‐order curvilinear function of ERA‐Interim pressure level data. The results indicate that the correction method using ERA‐Interim internal vertical lapse rates cannot only significantly reduce the bias (89%) and RMSE (62%) for the original ERA‐Interim data, but also capture the inter‐annual variations for the plateau‐wide climatology very well. The seasonal and annual temperature warming trends are also modelled encouragingly compared with other four methods. The strongest advantage of this method is that it is independent of local meteorological stations. Therefore, it is possible to extrapolate ERA‐Interim temperature data for any other high mountain areas where no measurements exist. This work will help the scientific community identify the most proper and easiest method to downscale reanalysis temperature data for climate impact assessments at the site or regional scale.
•Selected use cases show that blockchain is not a niche solution, yet global scalability requires innovations in governance and energy efficiency.•Blockchain can improve malfunctioning, imbalanced or ...ineffective services, financing schemes, and infrastructural systems.•The use of biometrics raises significant concerns as governance processes must be adapted to technological change to avoid creating new risks.•The immutability of decentralized ledgers is problematic from a human rights and privacy perspective.•Anticipatory governance can contribute to effective risk management in networked and decentralized governance arrangements.
Societies at large still grapple to categorize digital space as a phenomenon. At the same time, scientists and developers are searching for innovative methods to better understand how the fundamental shifts caused by digital change will affect the future of humanity over the coming decades. Interdisciplinary governance research at the intersection of technological and environmental foresight is urgently needed to minimize the risks of technological change and explore how digitalization may support, hinder or re-shape sustainability transformations. In this article, we focus on the case of ‘blockchain’ or distributed-ledger technology (DLT) to investigate how recent digital technologies may support the implementation of sustainable development initiatives. Our investigation is centered on areas of public administration and governance which will most likely see an adoption of DLT over the next two decades, such as digital identity, social service provision, and innovative climate finance. To allow for a meaningful comparison of various use cases, we propose four guiding questions that can help researchers, decision-makers and practitioners to determine whether DLT might be an appropriate choice for the sustainability-related task at hand. Moreover, we illustrate how the initial design and subsequent implementation of DLTs may support more centralized or networked modes of governance.
Abstract
The spatiotemporal distribution of snow affects hydrological and climatological processes at different scales. Accordingly, quantifying geometric features of snow-cover patterns is ...important, providing a valuable complement for snow water equivalent (SWE) modelling. This study on satellite-based morphological analysis originally uses two types of geometric indexes: (1) MN, Minkowski numbers (area (MN1), perimeter (MN2), Euler number (MN3)), and (2) CL, average chord length, to describe the morphology of Sentinel-2-derived snow-covered areas (SCAs), within the high-alpine site Zugspitze for a 5 year period. Results indicate that they capture the seasonal variability of snow-cover patterns, particularly during accumulation and ablation. Being to some degree independent from each other, MN2, MN3 and CL provide additional information upon shape, connectivity and length scale of snow cover, compared to most used indexes (e.g. fractional SCA). Correlation values up to +0.7 for MN2, +0.58 for MN3 and +0.46 for CL were observed with selected topographic characteristics, suggesting a close connection between geometric features of snow cover and ground features. Comparing in situ SWE measurements with MN and CL shows a correlation between −0.5 and +0.5. These indexes can hence be applied in combination with in situ data and/or modelling approaches to improve spatially distributed SWE in high-alpine catchments.
Vegetation is often represented by the leaf area index (LAI) in many ecological, hydrological and meteorological land surface models. However, the spatio-temporal dynamics of the vegetation are ...important to represent in these models. While the widely applied methods, such as the Canopy Structure Dynamic Model (CSDM) and the Double Logistic Model (DLM) are solely based on cumulative daily mean temperature data as input, a new spatio-temporal LAI prediction model referred to as the Temperature Precipitation Vegetation Model (TPVM) is developed that also considers cumulative precipitation data as input into the modelling process. TPVM as well as CDSM and DLM model performances are compared and evaluated against filtered LAI data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The calibration/validation results of a cross-validation performed in the meso-scale Attert catchment in Luxembourg indicated that the DLM and TPVM generally provided more realistic and accurate LAI data. The TPVM performed superiorly for the agricultural land cover types compared to the other two models, which only used the temperature data. The Pearson's correlation coefficient (CC) between TPVM and the field measurement is 0.78, compared to 0.73 and 0.69 for the DLM and CSDM, respectively. The phenological metrics were derived from the TPVM model to investigate the interaction between the climate variables and the LAI variations. These interactions illustrated the dominant control of temperature on the LAI dynamics for deciduous forest cover, and a combined influence of temperature with precipitation for the agricultural land use areas.
West Africa.
The objective of this study was to quantitively evaluate streamflow previously simulated by the Soil and Water Assessment Tool (SWAT) model in an ungauged basin (Ogun River) that was ...calibrated/validated using GLEAM (v3.0a) AET data (Odusanya et al., 2019). To evaluate this simulated streamflow in the ungauged Ogun River Basin, a gauged basin (Ouémé River) was selected based on proximity and on similar catchment attributes. Firstly, the non-unique parameter sets from the SWAT set-up in the ungauged Ogun River Basin were transferred to SWAT that was setup in the neighbouring gauged Ouémé River Basin (referred to as the regionalisation method). Secondly, the SWAT model in the Ouémé River Basin was setup by calibrating the model using the observed streamflow data (referred to as the conventional method).
In the gauged Ouémé River Basin, using the conventional method, a higher streamflow performance was obtained for all non-unique SWAT simulations, compared with the regionalisation method. However, a satisfactory streamflow performance was obtained with the regionalisation method in the south of Ouémé River Basin (Save gauge: highest NSE = 0.79, R2 = 0.81, PBIAS = 2.1, KGE = 0.85) and at the Ouémé River Basin outlet (Bonou gauge: highest NSE = 0.79, R2 = 0.84, PBIAS = −4.5, KGE = 0.84) that had the most similar attributes to the Ogun River Basin. The study findings show that using satellite-based AET data to calibrate a hydrological model can lead to an acceptable model performance in ungauged basins. The regionalisation method was useful for assessing the simulated streamflow in the ungauged basin, especially when catchment similarity is ensured, and parameter non-uniqueness is applied. This research contributes to advancement in alternative means of modelling and evaluation of hydrologic model simulations in an ungauged basin.
•SWAT model was calibrated using satellite-based AET in an ungauged river basin.•Similarity-based regionalisation method was used to select gauged similar river basin.•Non-unique parameter sets were transferred from ungauged basin to gauged basin.•We evaluated the SWAT simulated streamflow using a regionalisation method.•With non-unique parameter sets, SWAT calibrated with satellite-based AET improved streamflow.
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