Stochastic precipitation modeling using circulation patterns to analyze climate impact on floods

This paper presents the conditioning of a precipitation model to objectively classified circulation patterns (CP). The application of CPs is considered useful with regards to model accuracy improvement and preparation of a downscaling model by using CPs classified with climate model data. As this study aims to produce rainfall as input for derived flood frequency analyses, the validation focuses on extreme values and precipitation events. The analysis is carried out by modifications of a well tested alternating renewal precipitation model

Spatial interpolation of hourly rainfall – effect of additional information, variogram inference and storm properties

Hydrological modelling of floods relies on precipitation data with a high resolution in space and time. A reliable spatial representation of short time step rainfall is often difficult to achieve due to a low network density. In this study hourly precipitation was spatially interpolated with the multivariate geostatistical method kriging with external drift (KED) using additional information from topography, rainfall data from the denser daily networks and weather radar data. Investigations were carried out for several flood events in the time period between 2000 and 2005 caused by different meteorological conditions. The 125 km radius around the radar station Ummendorf in northern Germany covered the overall study region. One objective was to assess the effect of different approaches for estimation of semivariograms on the interpolation performance of short time step rainfall. Another objective was the refined application of the method kriging with external drift. Special attention was not only given to find the most relevant additional information, but also to combine the additional information in the best possible way. A multi-step interpolation procedure was applied to better consider sub-regions without rainfall. <br><br> The impact of different semivariogram types on the interpolation performance was low. While it varied over the events, an averaged semivariogram was sufficient overall. Weather radar data were the most valuable additional information for KED for convective summer events. For interpolation of stratiform winter events using daily rainfall as additional information was sufficient. The application of the multi-step procedure significantly helped to improve the representation of fractional precipitation coverage

A space-time hybrid hourly rainfall model for derived flood frequency analysis

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.BMBF/FKZ:033068

Statistical approaches for identification of low-flow drivers: temporal aspects

The characteristics of low-flow periods, especially regarding their low temporal dynamics, suggest that the dimensions of the metrics related to these periods may be easily related to their meteorological drivers using simplified statistical model approaches. In this study, linear statistical models based on multiple linear regressions (MLRs) are proposed. The study area chosen is the German federal state of Lower Saxony with 28 available gauges used for analysis. A number of regression approaches are evaluated. An approach using principal components of local meteorological indices as input appeared to show the best performance. In a second analysis it was assessed whether the formulated models may be eligible for application in climate change impact analysis. The models were therefore applied to a climate model ensemble based on the RCP8.5 scenario. Analyses in the baseline period revealed that some of the meteorological indices needed for model input could not be fully reproduced by the climate models. The predictions for the future show an overall increase in the lowest average 7-day flow (NM7Q), projected by the majority of ensemble members and for the majority of stations.</p

Dynamics of intracellular mannan and cell wall folding in the drought responses of succulent <i>Aloe</i> species

Plants have evolved a multitude of adaptations to survive extreme conditions. Succulent plants have the capacity to tolerate periodically dry environments, due to their ability to retain water in a specialized tissue, termed hydrenchyma. Cell wall polysaccharides are important components of water storage in hydrenchyma cells. However, the role of the cell wall and its polysaccharide composition in relation to drought resistance of succulent plants are unknown. We investigate the drought response of leaf-succulent Aloe (Asphodelaceae) species using a combination of histological microscopy, quantification of water content, and comprehensive microarray polymer profiling. We observed a previously unreported mode of polysaccharide and cell wall structural dynamics triggered by water shortage. Microscopical analysis of the hydrenchyma cell walls revealed highly regular folding patterns indicative of predetermined cell wall mechanics in the remobilization of stored water and the possible role of homogalacturonan in this process. The in situ distribution of mannans in distinct intracellular compartments during drought, for storage, and apparent upregulation of pectins, imparting flexibility to the cell wall, facilitate elaborate cell wall folding during drought stress. We conclude that cell wall polysaccharide composition plays an important role in water storage and drought response in Aloe

Impact‐based forecasting for pluvial floods

Pluvial floods in urban areas are caused by local, fast storm events with very high rainfall rates, which lead to inundation of streets and buildings before the storm water reaches a watercourse. An increase in frequency and intensity of heavy rainfall events and an ongoing urbanization may further increase the risk of pluvial flooding in many urban areas. Currently, warnings for pluvial floods are mostly limited to information on rainfall intensities and durations over larger areas, which is often not detailed enough to effectively protect people and goods. We present a proof-of-concept for an impact-based forecasting system for pluvial floods. Using a model chain consisting of a rainfall forecast, an inundation, a contaminant transport and a damage model, we are able to provide predictions for the expected rainfall, the inundated areas, spreading of potential contamination and the expected damage to residential buildings. We use a neural network-based inundation model, which significantly reduces the computation time of the model chain. To demonstrate the feasibility, we perform a hindcast of a recent pluvial flood event in an urban area in Germany. The required spatio-temporal accuracy of rainfall forecasts is still a major challenge, but our results show that reliable impact-based warnings can be forecasts are available up to 5 min before the peak of an extreme rainfall event. Based on our results, we discuss how the outputs of the impact-based forecast could be used to disseminate impact-based early warnings

The crystal structure of human Rogdi provides insight into the causes of Kohlschutter-Tonz Syndrome

Kohlschutter-T&amp;ouml;nz syndrome (KTS) is a rare autosomal-recessive disorder of childhood onset characterized by global developmental delay, spasticity, epilepsy, and amelogenesis imperfecta. Rogdi, an essential protein, is highly conserved across metazoans, and mutations in Rogdi are linked to KTS. However, how certain mutations in Rogdi abolish its physiological functions and cause KTS is not known. In this study, we determined the crystal structure of human Rogdi protein at atomic resolution. Rogdi forms a novel elongated curved structure comprising the ?? domain, a leucine-zipper-like four-helix bundle, and a characteristic ??-sheet domain. Within the ?? domain, the N-terminal H1 helix (residues 19-45) pairs with the C-terminal H6 helix (residues 252-287) in an antiparallel manner, indicating that the integrity of the four-helix bundle requires both N- and C-terminal residues. The crystal structure, in conjunction with biochemical data, indicates that the ?? domain might undergo a conformational change and provide a structural platform for protein-protein interactions. Disruption of the four-helix bundle by mutation results in significant destabilization of the structure. This study provides structural insights into how certain mutations in Rogdi affect its structure and cause KTS, which has important implications for the development of pharmaceutical agents against this debilitating neurological disease

Klimafolgenabschätzungen in der Wasserwirtschaft und deren Nutzen für die Praxis

KlimafolgenClimate ImpactsDer globale Klimawandel kann regional unterschiedliche Auswirkungen haben. Während sich die wissenschaftliche Forschung vor allem mit der Analyse der Daten beschäftigt, ist die fachliche Praxis darum bemüht, die Ergebnisse zu interpretieren und Handlungsempfehlungen daraus abzuleiten. Im Zuge des Projektes KliBiW (Globaler Klimawandel – Wasserwirtschaftliche Folgenabschätzung für das Binnenland) wurden die Auswirkungen des Klimawandels auf die Hochwasser- und Niedrigwasserverhältnisse in Niedersachsen untersucht. Hierzu wurden die Daten von zwei regionalen Klimamodellen (WETTREG2006 und REMO), beide angetrieben durch das Globalmodell ECHAM5/MPI-OM, räumlich interpoliert und die Niederschläge zum Teil zeitlich disaggregiert, um hoch aufgelöste Klimainformationen bereitzuhalten. Anschließend erfolgte die Kopplung mit einem hydrologischen Modellsystem (PANTA RHEI), das bereits in der Hochwasservorhersagezentrale des NLWKN im Einsatz ist. Über Langzeitsimulationen wurden zukünftige Veränderungen in den Abflussverhältnissen räumlich und zeitlich differenziert für das Aller-Leine Gebiet identifiziert. Als Betrachtungszeiträume dienten eine nahe Zukunftsphase (2021 – 2050) und eine ferne Zukunftsphase (2071 – 2100). Die Veränderungen verschiedener hydrologischer Hoch- und Niedrigwasser-Kenngrößen wurden gegenüber einem Kontrollzeitraum (1971 – 2000) aufgezeigt. Die Auswertungen an 8 Pegeln in Einzugsgebieten >1.000 km² auf Tageswertbasis und an 6 Pegeln in Einzugsgebieten <1.000 km² auf Stundenwertbasis zeigten, dass sich die Hochwassersituation zukünftig verschärfen kann. Während kleinere Hochwässer häufiger auftreten können, nehmen die Scheitelabflüsse insbesondere in der fernen Zukunft zu. Aussagen zu größeren Ereignissen sind aufgrund der großen Bandbreite der Ergebnisse jedoch mit erheblichen Unsicherheiten behaftet. Die Niedrigwasserverhältnisse zeigten eine Abnahme der Abflüsse, speziell im Sommer, sowie eine Zunahme der Dauer undnder Volumendefizite bei Trockenperioden. Hierbei erschien die Variabilität und Ausprägung der Trockenheit in kleineren Einzugsgebieten etwas größer. Die Nutzung dieser Erkenntnisse stellt die fachliche Praxis vor die Herausforderung, die Ergebnisse zu interpretieren und zu kommunizieren. Unsicherheiten in den Modellketten müssen berücksichtigt und, wenn möglich, quantifiziert werden. Die abgeleiteten hydrologischen Konsequenzen des Klimawandels können z.B. Anwendung finden in der gesetzlich geforderten Berücksichtigung der Auswirkungen des Klimawandels auf die Risikogebiete entsprechend der Hochwasserrisikomanagement-Richtlinie (2007/60/EG). Dieser Beitrag gibt einen Überblick über wasserwirtschaftlich relevante Auswertungen von Klimamodelldaten auf unterschiedlichen räumlichen Skalen und zeigt anhand ausgewählter Beispiele auf, wie primär im wissenschaftlichen Kontext erhobene Ergebnisse effektiv für praxisrelevante Fragestellungen genutzt werden können

Evaluation of presumably disease causing SCN1A variants in a cohort of common epilepsy syndromes

Objective: The SCN1A gene, coding for the voltage-gated Na+ channel alpha subunit NaV1.1, is the clinically most relevant epilepsy gene. With the advent of high-throughput next-generation sequencing, clinical laboratories are generating an ever-increasing catalogue of SCN1A variants. Variants are more likely to be classified as pathogenic if they have already been identified previously in a patient with epilepsy. Here, we critically re-evaluate the pathogenicity of this class of variants in a cohort of patients with common epilepsy syndromes and subsequently ask whether a significant fraction of benign variants have been misclassified as pathogenic. Methods: We screened a discovery cohort of 448 patients with a broad range of common genetic epilepsies and 734 controls for previously reported SCN1A mutations that were assumed to be disease causing. We re-evaluated the evidence for pathogenicity of the identified variants using in silico predictions, segregation, original reports, available functional data and assessment of allele frequencies in healthy individuals as well as in a follow up cohort of 777 patients. Results and Interpretation: We identified 8 known missense mutations, previously reported as pathogenic, in a total of 17 unrelated epilepsy patients (17/448; 3.80%). Our re-evaluation indicates that 7 out of these 8 variants (p.R27T; p.R28C; p.R542Q; p.R604H; p.T1250M; p.E1308D; p.R1928G; NP-001159435.1) are not pathogenic. Only the p.T1174S mutation may be considered as a genetic risk factor for epilepsy of small effect size based on the enrichment in patients (P = 6.60 7 10-4; OR = 0.32, fishers exact test), previous functional studies but incomplete penetrance. Thus, incorporation of previous studies in genetic counseling of SCN1A sequencing results is challenging and may produce incorrect conclusions

Paediatric autoimmune encephalopathies:Clinical features, laboratory investigations and outcomes in patients with or without antibodies to known central nervous system autoantigens

Objective: To report the clinical and investigative features of children with a clinical diagnosis of probable autoimmune encephalopathy, both with and without antibodies to central nervous system antigens. Method: Patients with encephalopathy plus one or more of neuropsychiatric symptoms, seizures, movement disorder or cognitive dysfunction, were identified from 111 paediatric serum samples referred from five tertiary paediatric neurology centres to Oxford for antibody testing in 2007-2010. A blinded clinical review panel identified 48 patients with a diagnosis of probable autoimmune encephalitis whose features are described. All samples were tested/retested for antibodies to N-methyl-D-aspartate receptor (NMDAR), VGKC-complex, LGI1, CASPR2 and contactin-2, GlyR, D1R, D2R, AMPAR, GABA(B)R and glutamic acid decarboxylase. Results Seizures (83%), behavioural change (63%), confusion (50%), movement disorder (38%) and hallucinations (25%) were common. 52% required intensive care support for seizure control or profound encephalopathy. An acute infective organism (15%) or abnormal cerebrospinal fluid (32%), EEG (70%) or MRI (37%) abnormalities were found. One 14-year-old girl had an ovarian teratoma. Serum antibodies were detected in 21/48 (44%) patients: NMDAR 13/48 (27%), VGKC-complex 7/48(15%) and GlyR 1/48(2%). Antibody negative patients shared similar clinical features to those who had specific antibodies detected. 18/34 patients (52%) who received immunotherapy made a complete recovery compared to 4/14 (28%) who were not treated; reductions in modified Rankin Scale for children scores were more common following immunotherapies. Antibody status did not appear to in fluence the treatment effect. Conclusions: Our study outlines the common clinical and paraclinical features of children and adolescents with probable autoimmune encephalopathies. These patients, irrespective of positivity for the known antibody targets, appeared to benefit from immunotherapies and further antibody targets may be defined in the future