The availability of in situ snow water equivalent (SWE), snowmelt and run-off measurements is still very limited especially in remote areas as the density of operational stations and field ...observations is often scarce and usually costly, labour-intense and/or risky. With remote sensing products, spatially distributed information on snow is potentially available, but often lacks the required spatial or temporal requirements for hydrological applications. For the assurance of a high spatial and temporal resolution, however, it is often necessary to combine several methods like Earth Observation (EO), modelling and in situ approaches. Such a combination was targeted within the business applications demonstration project SnowSense (2015–2018), co-funded by the European Space Agency (ESA), where we designed, developed and demonstrated an operational snow hydrological service. During the run-time of the project, the entire service was demonstrated for the island of Newfoundland, Canada. The SnowSense service, developed during the demonstration project, is based on three pillars, including (i) newly developed in situ snow monitoring stations based on signals of the Global Navigation Satellite System (GNSS); (ii) EO snow cover products on the snow cover extent and on information whether the snow is dry or wet; and (iii) an integrated physically based hydrological model. The key element of the service is the novel GNSS based in situ sensor, using two static low-cost antennas with one being mounted on the ground and the other one above the snow cover. This sensor setup enables retrieving the snow parameters SWE and liquid water content (LWC) in the snowpack in parallel, using GNSS carrier phase measurements and signal strength information. With the combined approach of the SnowSense service, it is possible to provide spatially distributed SWE to assess run-off and to provide relevant information for hydropower plant management in a high spatial and temporal resolution. This is particularly needed for so far non, or only sparsely equipped catchments in remote areas. We present the results and validation of (i) the GNSS in situ sensor setup for SWE and LWC measurements at the well-equipped study site Forêt Montmorency near Quebec, Canada and (ii) the entire combined in situ, EO and modelling SnowSense service resulting in assimilated SWE maps and run-off information for two different large catchments in Newfoundland, Canada.
To assess climate change impact on the hydrology of Izmit Bay, a coupled model chain using the results of four combinations of Global Climate Models (GCMs) and Regional Climate Models (RCMs) and ...consisting two hydrological models (mGROWA and PROMET) and one hydrodynamic model (MIKE 3HD) was established. Climate model data of the 4 GCM-RCM combinations were applied to both hydrological models. The resulting 8 streamflow data of the hydrological models were then applied to the MIKE 3HD to assess possible hydrodynamic situations in Izmit Bay. Related model results indicate a range of possible future streamflow regimes suitable for the analysis of climate change impact on Izmit Bay. In order to evaluate the effects of the hydrological changes only on the bay, the bay was considered as closed in terms of hydrodynamics. There is a clear indication that the climate change induced impacts on streamflow may influence the sea level in the Bay to a minor extent. However, climate change induced water exchange processes in the Bay may have a much bigger influence. Hence, it is suggested that further simulations should be run once the hydrologic regime of the Marmara Sea has been assessed in a broader macro-scale study.
Subepithelial immune complex deposition in glomerular disease causes local inflammation and proteinuria by podocyte disruption. A rat model of membranous nephropathy, the passive Heymann nephritis, ...suggests that Abs against specific podocyte Ags cause subepithelial deposit formation and podocyte foot process disruption. In this study, we present a mouse model in which a polyclonal sheep anti-mouse podocyte Ab caused subepithelial immune complex formation. Mice developed a nephrotic syndrome with severe edema, proteinuria, hypoalbuminemia, and elevated cholesterol and triglycerides. Development of proteinuria was biphasic: an initial protein loss was followed by a second massive increase of protein loss beginning at approximately day 10. By histology, podocytes were swollen. Electron microscopy revealed 60-80% podocyte foot process effacement and subepithelial deposits, but no disruption of the glomerular basement membrane. Nephrin and synaptopodin staining was severely disrupted, and podocyte number was reduced in anti-podocyte serum-treated mice, indicating severe podocyte damage. Immunohistochemistry detected the injected anti-podocyte Ab exclusively along the glomerular filtration barrier. Immunoelectron microscopy localized the Ab to podocyte foot processes and the glomerular basement membrane. Similarly, immunohistochemistry localized mouse IgG to the subepithelial space. The third complement component (C3) was detected in a linear staining pattern along the glomerular basement membrane and in the mesangial hinge region. However, C3-deficient mice were not protected from podocyte damage, indicating a complement-independent mechanism. Twenty proteins were identified as possible Ags to the sheep anti-podocyte serum by mass spectrometry. Together, these data establish a reproducible model of immune-mediated podocyte injury in mice with subepithelial immune complex formation.
The spectral information contained in hyperspectral data allows for a more detailed crop and soil parameter retrieval, in turn making possible to derive precise information about plant health ...(nutrient deficiencies, water stress, crop diseases) but also about soil status (from soil moisture to humus content). Thus, smart farming, that is farming practice that wants to account for the whole ecosystem on the field and react precisely to any challenges, can be supported by hyperspectral data with exactly the spatial information it needs.
Rho kinase signaling regulates inflammatory cell migration and chemokine production. We therefore investigated the mechanisms of Rho-kinase-dependent inflammation in lipopolysaccharide (LPS)-induced ...renal failure. C57/BL6 mice received intraperitoneal LPS with or without daily treatment with specific Rho kinase inhibitors (Y-27632 or HA-1077; 5 mg/kg). Rho kinase inhibitors were applied in a preventive (12 or 1 h before LPS) or a therapeutic (6 h after LPS) scheme. Both protected renal function and decreased tubular injury in LPS-treated mice. Enhanced Rho kinase activity was inhibited by HA-1077 in capillary endothelial cells, inflammatory cells, and tubuli by analysis of Rho kinase substrate phosphorylation. Early neutrophil influx was reduced by HA-1077 without reduction of the proinflammatory cytokine TNFalpha. In contrast, HA-1077 decreased the influx of monocytes/macrophages coinciding with reduced expression of the NF-kappaB-regulated chemokines CCL5 and CCL2. We therefore examined NF-kappaB signal transduction and found that NF-kappaB p65 phosphorylation and nuclear translocation were reduced by Rho kinase inhibition. IkappaBalpha degradation was not altered during the first 6 h but was reduced by HA-1077 at later time points. NF-kappaB p50-deficient mice were similarly protected from renal injury by Rho kinase inhibition further supporting the prominent role for p65 in Rho kinase inhibition. Together, these data suggest that Rho kinase inhibition by preventive or therapeutic treatment effectively reduced endotoxic kidney injury in part by attenuation of NF-kappaB p65 activation.
For a sustainable and efficient land management, spatially distributed and up-to-date information on the land surface is of central importance. A continuous flow of land management information is the ...basis to improve decisions on use, cultivation intensity and allocation of resources (e.g. water for irrigation). Remote sensing is in a unique position to contribute to this task as it is globally available and provides specific information about current crop status. The M 4 Land concept is designed to derive information products for a sustainable management of the land surface. In this paper, the methodology and the results for the autonomous development of three products, i.e. land use, crop cycle and intensity of agricultural use, is presented for two test sites and for several years. In the M 4 Land system, a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal and multi-sensoral satellite images.
A method to derive products for a sustainable management of the land surface is developed in the frame of the M 4 Land project ("Model based, Multi-temporal, Multi-scale and Multi-sensoral retrieval ...of continuous land management information"). The system relies on a model-supervised dynamic classification of land cover from multi-temporal satellite data that works automatically without the need for training data or manual data processing. This approach is tested for the first time in a mesoscale setting (300m resolution). The performed model-supervised land cover classification of ENVISAT MERIS data at a test site in Southern Germany in 2010 is promising with an overall accuracy of 84.7%. After the consolidation of the method on this scale further land management products can be developed that are based on the underlying land surface model data.
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