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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    World journal of microbiology and biotechnology 4 (1988), S. 139-142 
    ISSN: 1573-0972
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Description / Table of Contents: Résumé Dix digesteurs ont été construits au Paraguay jusqu'ici. Neuf sont opérationnels, six sont du type indien et deux du type chinois. Le lisier de bovin est le substrat le plus utilisé. Les utilisations du biogaz sont l'éclairage, la cuisine, la réfrigération et la production d'électricité. Un nouveau projet a comme objectifs (1) l'installation d'un centre permettant la poursuite de recherches et (2) le développment de la technologie dans les zones rurales.
    Abstract: Resumen En Paraguay se han construido hasta el momento diez digestores de los cuales nueve son operativos, el diseño de seis de estos digestores es indio y el de otros dos es chino. El sustrato utilizado más comunmente es estiercol de ganado. Los aparatos que funcionan con biogas son lámparas, fogones, neveras y generadores eléctricos. Se está desarrollando un nuevo proyecto relativo a la energía de la biomasa que permitira la realización de un centro para le experimentación en la producción de biogas y el inicio de su difusión en las zonas rurales.
    Notes: Summary Ten digesters have already been built in Paraguay of which nine are operational, six are of the Indian design and two of the Chinese design. Cattle manure is the most common substrate. Biogas appliances are lamps, stove burners, refrigerators and electricity generators. A new biomass energy project is developing to implement a biogas centre for biogas production experiments and to start the diffusion in rural areas.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2022-03-29
    Description: A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation. High computational costs for modeled processes and assimilation algorithms has led to Earth system specific reanalysis products for the atmosphere, the ocean and the land separately. Recent developments include the advanced uncertainty quantification and the generation of biogeochemical reanalysis for land and ocean. Here, we review atmospheric and oceanic reanalyzes, and more in detail biogeochemical ocean and terrestrial reanalyzes. In particular, we identify land surface, hydrologic and carbon cycle reanalyzes which are nowadays produced in targeted projects for very specific purposes. Although a future joint reanalysis of land surface, hydrologic, and carbon processes represents an analysis of important ecosystem variables, biotic ecosystem variables are assimilated only to a very limited extent. Continuous data sets of ecosystem variables are needed to explore biotic‐abiotic interactions and the response of ecosystems to global change. Based on the review of existing achievements, we identify five major steps required to develop terrestrial ecosystem reanalysis to deliver continuous data streams on ecosystem dynamics.
    Description: Plain Language Summary: A reanalysis is a unique set of continuous variables produced by optimally merging a numerical model and observed data. The data are merged with the model using available uncertainty estimates to generate the best possible estimate of the target variables. The framework for generating a reanalysis consists of the model, the data, and the model‐data‐fusion algorithm. The very specific requirements of reanalysis frameworks have led to the development of Earth‐compartment specific reanalysis for the atmosphere, the ocean and land. Here, we review atmospheric and oceanic reanalyzes, and in more detail biogeochemical ocean and terrestrial reanalyzes. In particular, we identify land surface, hydrologic, and carbon cycle reanalyzes which are nowadays produced in targeted projects for very specific purposes. Based on a review of existing achievements, we identify five major steps required to develop reanalysis for terrestrial ecosystem to shed more light on biotic and abiotic interactions. In the future, terrestrial ecosystem reanalysis will deliver continuous data streams on the state and the development of terrestrial ecosystems.
    Description: Key Points: Reanalyzes provide decades‐long model‐data‐driven harmonized and continuous data sets for new scientific discoveries. Novel global scale reanalyzes quantify the biogeochemical ocean cycle, terrestrial carbon cycle, land surface, and hydrologic processes. New observation technology and modeling capabilities allow in the near future production of advanced terrestrial ecosystem reanalysis.
    Description: European Union's Horizon 2020 research and innovation programme
    Description: Deutsche Forschungsgemeinschaft
    Description: U.S. Department of Energy
    Description: Emory University's Halle Institute for Global Research and the Halle Foundation Collaborative Research
    Description: NSF
    Description: NASA
    Description: Natural Environment Research Council
    Description: European Union'’s Horizon 2020 research and innovation programme
    Description: NSERC Discovery program, the Ocean Frontier Institute, and MEOPAR
    Description: Research Foundation Flanders (FWO)
    Description: Helmholtz Association
    Description: NASA Terrestrial Ecosystems
    Keywords: ddc:550
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2020-02-12
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 4
    Publication Date: 2020-02-12
    Keywords: 550 - Earth sciences
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 5
    Publication Date: 2023-07-11
    Description: The objective of this study is to validate actual evapotranspiration (Aet) simulation (1982 – 2011) over three agro-climatic regions (Sahel, Savannah, and Guinea) within Nigeria. For this investigation, the mesoscale hydrologic model (mHM) was calibrated for streamflow simulation using CHIRPS and ERA5 rainfall datasets in three basins (Jamaare, Hadejia, and Kaduna) in Nigeria. Model parameter sets obtained from these simulations were each used to set up mHM for Aet simulation over Nigeria and the three regions. Model results were compared against estimates from Aet-based products (GLEAM3.5a and FLUXNET). deseasonalized monthly Aet time series plots for all agro-climatic regions and the whole Nigeria domain in comparison to both gridded datasets (GLEAM3.5a and FLUXNET) gave satisfactory correlation scores, especially with the GLEAM3.5a. In the Savannah region, all parameter sets gave satisfactory correlation values (r 〉 0.5) except that from the Kaduna basin forced with ERA5. Results in the Sahel for all model setups are acceptable (r 〉 0.5) but poorly correlated (r 〈 0.5) with both observed datasets in the Guinea region except when using parameters from Jamaare and Hadejia driven with ERA5 and when using model default parameters. For the whole Nigeria domain, simulated Aet results showed satisfactory performance ( r 〉 0.5) mostly in comparison with the GLEAM3.5a, both for all chirps-driven datasets and for the model default setup. This study demonstrates the potential of using the GLEAM3.5a product for water resources modeling in data-scarce locations such as Nigeria.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 6
    Publication Date: 2023-09-08
    Description: The Central Highlands of Vietnam, located in an area susceptible to extreme weather conditions brought on by El Niño, has endured severe droughts during the dry seasons, leading to significant environmental and socio-economic consequences in recent decades. This study, conducted as part of the Drought-ADAPT project (https://www.bmbf-client.de/en/projects/drought-adapt), aims to assess the regional water resources with a focus on both surface water and groundwater for the present period and future projection scenarios. Therefore, the grid-based mesoscale Hydrological Model was implemented for the region encompassing two major river basins Sesan and Seprok, tributaries of the Mekong. The model, mHM-2S, that was driven by daily weather data from either ERA5 reanalysis dataset or the regional climate model REMO, considered various dominant hydrological processes and the impact of multiple large hydroelectric reservoirs in the area. The calibration of mHM-2S was performed with a multi-objective approach, fitting not only observed stream flow at several gauges but also aligning groundwater storage information derived from the GRACE/G3P gravity-based groundwater product. The refined mHM-2S was then used to estimate the regional water resources in terms of means and variations of seasonal discharge, total and groundwater storages under future climate forcings, land-use changes as well as various reservoir operational plans.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 7
    Publication Date: 2023-11-15
    Description: The July 2021 devastating floods in Central Europe, particularly in the river catchments in Western Germany, have resulted in a large number of death toll and vast economic damage. The BMBF-funded joint project KAHR (https://hochwasser-kahr.de) deals with the effects of this flood and develops scientific knowledge to assist the reconstruction process in flood-prone area in Western Germany, with a focus on the fast-reacting catchments of Ahr, Erft, and Rur. Therefore, small-scale flood modeling with high spatial and temporal resolution is employed to understand past floods and to develop future flood management strategies in these regions. Here, we apply the mesoscale hydrological model mHM at hourly timesteps and around 1 km spatial resolution for the three flood-prone catchments. We are able to accurately capture the dynamics of the extreme flood events for the recent period including the flood in 2021. To assess the present and future flood risk, a regional weather generator and a disaggregation procedure are applied to generate 10,000 years of synthetic hourly meteorological data. These data are used to force the mHM model to simulate the long time series of river discharge. Major flood events are extracted from this synthetic dataset to investigate the spatial-temporal characteristics of extreme flood events and associated flood risks under future climate conditions.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 8
    Publication Date: 2023-12-11
    Description: The disastrous consequences of the July 2021 flood in Western Europe have again demonstrated that current flood risk management is too strongly focused on design events. For instance, the 100-year flood is often used as the target safety level for flood defense, and events beyond such design scenarios are neglected. This disregard of ‘High-Impact / Low-Probability’ (HILP) events would not be advisable in a stationary system, but is even more inappropriate given the widespread climatic, environmental and socio-economic changes. We discuss methods to develop HILP flood scenarios, such as downward counterfactuals and perfect storms. Taking the Ahr catchment as an example, which experienced massive destruction and more than 130 fatalities during the 2021 flood, we demonstrate how a flood risk model chain can be used to develop HILP scenarios. The model chain, consisting of hydrological, hydrodynamic and damage models, is driven by a stochastic weather generator, which generates a very long time series of synthetic weather. In combination with modifying processes along the model chain, for instance, assuming failure of early warning, this setup allows (1) understanding how HILP events could evolve, and (2) generating a large range of flood scenarios beyond design events.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 9
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    In:  XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
    Publication Date: 2023-12-11
    Description: Extreme floods are evoked by a variety of factors, including high precipitation volume and/or intensities and specific pre-event conditions in the catchments. Due to that, each extreme regional flood is characterized by event-specific spatio-temporal variability in flood-inducing characteristics. Thus, the flood conditions vary along the course of large rivers and could be higher/lower, in particular after large confluences.In this study, we analyse event characteristics of extreme floods along the Danube river basin. In order to extend the limited number of extreme flood events in historical data, we apply the mesoscale Hydrological Model mHM for the region. mHM is calibrated and validated to a large set of about a hundred gauges in Germany with a focus on peak flow. The model is fed by the stochastic regional weather generator RWG which allows the generation of long synthetic weather data. Through simulations of these two combined models, a set of 60,000 years of synthetic stream flow data series is derived at several gauges. In the next step, a large number of extreme flood events with different characteristics are derived. This event-rich dataset is then used for the analysis to enhance the understanding of large regional floods and to trace the flood characteristics back to the meteorological and catchment event conditions in the catchment.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 10
    Publication Date: 2024-03-04
    Description: This dataset comprises event peak flows, representing extreme floods at 516 stations in Germany. The data generation process involves several key steps. Initially, observed rainfall events associated with 10 historical flood disasters from 1950 to 2021 are undergone spatial shifts. These shifts involve three distances (20, 50, and 100 km) and eight directions (North, Northeast, East, Southeast, South, Southwest, West, Northwest), resulting in 24 counterfactual precipitation events. Including the factual (no shift) event, a total of 25 distinct shifting events are considered. Subsequently, these shifted fields are used as atmospheric forcing for a mesoscale hydrological model (mHM) set up and calibrated for the entire Germany. The model produces daily stream flows across its domain, from which the event peak flows are derived. This dataset is expected to provide a valuable resource for analyzing and modeling the dynamics extreme flood events in Germany.
    Type: info:eu-repo/semantics/workingPaper
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