ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Other Sources  (5)
  • 631.4  (3)
  • integrated flood risk management  (2)
  • Blackwell Publishing Ltd  (5)
  • Nature Publishing Group
Collection
  • Other Sources  (5)
Source
Keywords
Publisher
Language
Years
  • 1
    facet.materialart.
    Unknown
    Synthetic resampling strategies and machine learning for digital soil mapping in Iran (2021)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2021-07-04
    Description: Most common machine learning (ML) algorithms usually work well on balanced training sets, that is, datasets in which all classes are approximately represented equally. Otherwise, the accuracy estimates may be unreliable and classes with only a few values are often misclassified or neglected. This is known as a class imbalance problem in machine learning and datasets that do not meet this criterion are referred to as imbalanced data. Most datasets of soil classes are, therefore, imbalanced data. One of our main objectives is to compare eight resampling strategies that have been developed to counteract the imbalanced data problem. We compared the performance of five of the most common ML algorithms with the resampling approaches. The highest increase in prediction accuracy was achieved with SMOTE (the synthetic minority oversampling technique). In comparison to the baseline prediction on the original dataset, we achieved an increase of about 10, 20 and 10% in the overall accuracy, kappa index and F‐score, respectively. Regarding the ML approaches, random forest (RF) showed the best performance with an overall accuracy, kappa index and F‐score of 66, 60 and 57%, respectively. Moreover, the combination of RF and SMOTE improved the accuracy of the individual soil classes, compared to RF trained on the original dataset and allowed better prediction of soil classes with a low number of samples in the corresponding soil profile database, in our case for Chernozems. Our results show that balancing existing soil legacy data using synthetic sampling strategies can significantly improve the prediction accuracy in digital soil mapping (DSM). Highlights Spatial distribution of soil classes in Iran can be predicted using machine learning (ML) algorithms. The synthetic minority oversampling technique overcomes the drawback of imbalanced and highly biased soil legacy data. When combining a random forest model with synthetic sampling strategies the prediction accuracy of the soil model improves significantly. The resulting new soil map of Iran has a much higher spatial resolution compared to existing maps and displays new soil classes that have not yet been mapped in Iran.
    Description: Alexander von Humboldt‐Stiftung http://dx.doi.org/10.13039/100005156
    Description: German Research Foundation http://dx.doi.org/10.13039/501100001659
    Description: Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
    Keywords: 631.4 ; covariates ; imbalanced data ; machine learning ; random forest ; soil legacy data
    Type: article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 2
    facet.materialart.
    Unknown
    Impact of biochar on nutrient supply, crop yield and microbial respiration on sandy soils of northern Germany (2021)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2021-06-16
    Description: The application of biochar to agricultural soils to increase nutrient availability, crop production and carbon sequestration has gained increasing interest but data from field experiments on temperate, marginal soils are still under‐represented. In the current study, biochar, produced from organic residues (digestates) from a biogas plant, was applied with and without digestates at low (3.4 t ha−1) and intermediate (17.1 t ha−1) rates to two acidic and sandy soils in northern Germany that are used for corn (Zea mays L.) production. Soil nutrient availability, crop yields, microbial biomass and carbon dioxide (CO2) emissions from heterotrophic respiration were measured over two consecutive years. The effects of biochar application depended on the intrinsic properties of the two tested soils and the biochar application rates. Although the soils at the fallow site, with initially low nutrient concentrations, showed a significant increase in pH, soil nutrients and crop yield after low biochar application rates, a similar response was found at the cornfield site only after application of substantially larger amounts of biochar. The effect of a single dose of biochar at the beginning of the experiment diminished over time but was still detectable after 2 years. Whereas plant available nutrient concentrations increased after biochar application, the availability of potentially phytotoxic trace elements (Zn, Pb, Cd, Cr) decreased significantly, and although slight increases in microbial biomass carbon and heterotrophic CO2 fluxes were observed after biochar application, they were mostly not significant. The results indicate that the application of relatively small amounts of biochar could have positive effects on plant available nutrients and crop yields of marginal arable soils and may decrease the need for mineral fertilizers while simultaneously increasing the sequestration of soil organic carbon. Highlights A low rate of biochar increased plant available nutrients and crop yield on marginal soils. Biochar application reduced the availability of potentially harmful trace elements. Heterotrophic respiration showed no clear response to biochar application. Biochar application may reduce fertilizer need and increase carbon sequestration on marginal soils.
    Description: German Academic Exchange Service http://dx.doi.org/10.13039/501100001655
    Description: Institute Strategic Programme grants, “Soils to Nutrition”
    Keywords: 631.4 ; black carbon ; carbon sequestration ; corn ; digestate ; heterotrophic respiration ; marginal soils ; microbial biomass
    Type: article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 3
    facet.materialart.
    Unknown
    The potential of ryegrass as cover crop to reduce soil N2O emissions and increase the population size of denitrifying bacteria (2021)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2021-07-05
    Description: Nitrogen (N) fertilization is the major contributor to nitrous oxide (N2O) emissions from agricultural soil, especially in post‐harvest seasons. This study was carried out to investigate whether ryegrass serving as cover crop affects soil N2O emissions and denitrifier community size. A microcosm experiment was conducted with soil planted with perennial ryegrass (Lolium perenne L.) and bare soil, each with four levels of N fertilizer (0, 5, 10 and 20 g N m−2; applied as calcium ammonium nitrate). The closed‐chamber approach was used to measure soil N2O fluxes. Real‐time PCR was used to estimate the biomass of bacteria and fungi and the abundance of genes involved in denitrification in soil. The results showed that the presence of ryegrass decreased the nitrate content in soil. Cumulative N2O emissions of soil with grass were lower than in bare soil at 5 and 10 g N m−2. Fertilization levels did not affect the abundance of soil bacteria and fungi. Soil with grass showed greater abundances of bacteria and fungi, as well as microorganisms carrying narG, napA, nirK, nirS and nosZ clade I genes. It is concluded that ryegrass serving as a cover crop holds the potential to mitigate soil N2O emissions in soils with moderate or high NO3− concentrations. This highlights the importance of cover crops for the reduction of N2O emissions from soil, particularly following N fertilization. Future research should explore the full potential of ryegrass to reduce soil N2O emissions under field conditions as well as in different soils. Highlights This study was to investigate whether ryegrass serving as cover crop affects soil N2O emissions and denitrifier community size; Plant reduced soil N substrates on one side, but their root exudates stimulated denitrification on the other side; N2O emissions were lower in soil with grass than bare soil at medium fertilizer levels, and growing grass stimulated the proliferation of almost all the denitrifying bacteria except nosZ clade II; Ryegrass serving as a cover crop holds the potential to mitigate soil N2O emissions.
    Description: China Scholarship Council http://dx.doi.org/10.13039/501100004543
    Description: The National Science Project for University of Anhui Province
    Keywords: 551.9 ; 631.4 ; denitrification ; perennial ryegrass (Lolium perenne L.) ; soil bacteria ; soil CO2 emissions ; soil N2O emissions
    Type: article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 4
    facet.materialart.
    Unknown
    The ‘Flood Resilience Rose’: A management tool to promote transformation towards flood resilience (2021)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2021-09-29
    Description: Coping with the growing impacts of flooding in EU countries, a paradigm shift in flood management can be observed, moving from safety‐based towards risk‐based approaches and holistic perspectives. Flood resilience is a common denominator of most of the approaches. In this article, we present the ‘Flood Resilience Rose’ (FRR), a management tool to promote harmonised action towards flood resilience in European regions and beyond. The FRR is a result of a two‐step process. First, based on scientific concepts as well as analysis of relevant policy documents, we identified three ‘levels of operation’. The first level refers to the EU Floods Directive and an extended multi‐layer safety approach, comprising the four different layers of protection, prevention, preparedness and recovery, and related measures to be taken. This level is not independent but depends both on the institutional (second level) and the wider (third level) context. Second, we used surveys, semi‐structured interviews and group discussions during workshops with experts from Belgium, Denmark, Germany, the Netherlands and the United Kingdom to validate the definitions and the FRR's practical relevance. The presented FRR is thus the result of rigorous theoretical and practical consideration and provides a tool capable to strengthen flood risk management practice.
    Description: European Regional Development Fund http://dx.doi.org/10.13039/501100008530
    Keywords: 551.48 ; flood defence measures ; governance and institutions ; integrated flood risk management ; resilience
    Type: map
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
  • 5
    facet.materialart.
    Unknown
    Toward an adequate level of detail in flood risk assessments (2023)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Flood risk assessments require different disciplines to understand and model the underlying components hazard, exposure, and vulnerability. Many methods and data sets have been refined considerably to cover more details of spatial, temporal, or process information. We compile case studies indicating that refined methods and data have a considerable effect on the overall assessment of flood risk. But are these improvements worth the effort? The adequate level of detail is typically unknown and prioritization of improvements in a specific component is hampered by the lack of an overarching view on flood risk. Consequently, creating the dilemma of potentially being too greedy or too wasteful with the resources available for a risk assessment. A “sweet spot” between those two would use methods and data sets that cover all relevant known processes without using resources inefficiently. We provide three key questions as a qualitative guidance toward this “sweet spot.” For quantitative decision support, more overarching case studies in various contexts are needed to reveal the sensitivity of the overall flood risk to individual components. This could also support the anticipation of unforeseen events like the flood event in Germany and Belgium in 2021 and increase the reliability of flood risk assessments.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: BMBF http://dx.doi.org/10.13039/501100002347
    Description: Federal Environment Agency http://dx.doi.org/10.13039/501100010809
    Description: http://howas21.gfz-potsdam.de/howas21/
    Description: https://www.umwelt.niedersachsen.de/startseite/themen/wasser/hochwasser_amp_kustenschutz/hochwasserrisikomanagement_richtlinie/hochwassergefahren_und_hochwasserrisikokarten/hochwasserkarten-121920.html
    Description: https://download.geofabrik.de/europe/germany.html
    Description: https://emergency.copernicus.eu/mapping/list-of-components/EMSN024
    Description: https://data.jrc.ec.europa.eu/collection/id-0054
    Description: https://oasishub.co/dataset/surface-water-flooding-footprinthurricane-harvey-august-2017-jba
    Description: https://www.wasser.sachsen.de/hochwassergefahrenkarte-11915.html
    Keywords: ddc:551.48 ; decision support ; extreme events ; integrated flood risk management ; risk assessment
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    CITATION GEO-LEO
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...