Jochen Seidel

Abstract

Study region: The study region is Germany and two sub-regions in Germany, i.e. the state of Rhineland-Palatinate and the city of Reutlingen. Study focus: Opportunistic rainfall sensors, namely personal weather stations and commercial microwave links, together with rain gauge data from the German Weather Service, were used in different combinations to derive rainfall maps with a geostatistical interpolation framework for Germany. This kriging type framework considered the uncertainty of opportunistic sensors and the line structure of commercial microwave links. The resulting rainfall maps were compared to two gauge-adjusted radar products and evaluated to three reference gauge datasets in the respective study regions on both daily and hourly basis. New Hydrological Insights for the Region: The interpolated rainfall products from opportunistic sensors provided good agreement to the reference rain gauges. The dataset combinations including information from the opportunistic sensors performed best. The addition of rain gauges from the German Weather Service did not consistently lead to an improvement of the interpolated rainfall maps. On the country-wide, daily scale the interpolated rainfall maps performed well, but the gauge-adjusted radar products were closer to the reference. For the regional and local scale in Rhineland-Palatinate and Reutlingen with an hourly resolution, the interpolated rainfall maps outperformed the interpolated product from DWD rain gauges and showed a similar agreement to the reference as the radar products.

Abstract

In this study, the applicability of data from private weather stations (PWS) for precipitation interpolation was investigated. Due to unknown errors and biases in these observations, a two-step filter was developed that uses indicator correlations and event-based spatial precipitation patterns. The procedure was tested and cross validated for the state of Baden-Württemberg (Germany). The biggest improvement is achieved for the shortest time aggregations.

Abstract

Abstract A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large-scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph-based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space–time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods

Abstract

The rapidly growing urban centres throughout the world are facing serious problems due to the fast-changing developments in all of their environmental spheres (nature, society, politics, culture and economics). Therefore, strategic planning becomes even more important in order to develop strategies that allow cities to adapt to new challenges and to prevent or to mitigate negative trends. This paper presents a transdisciplinary approach to water management, which combines adaptation and application of methods from hydrology, social sciences, water engineering and modelling; furthermore, this approach also involves stakeholders in this process. This methodology assists cities in addressing risks by elaborating solutions, which are characterised by ownership and acceptance of the stakeholders involved. The presented methodology proposed here has been applied to the water system of the desert megacity of Lima/Peru. As a city of almost 10 million inhabitants and with an annual rainfall of about 10 mm per year, Lima presents a unique case with particular challenges regarding water supply. In order to assess the changes in precipitation and temperature for the next decades, two global circulation models and three scenarios have been used. Changes in discharge was addressed using the conceptual rainfall-runoff model HBV applied in both the Atlantic and Pacific catchments relevant to the capital city Lima in terms of water supply. A scenario methodology, combining qualitative and quantitative elements, based on the Cross-Impact Balance Analysis, has been developed and applied. From the millions of theoretically possible combinations of future developments of “descriptors” (driving forces) of the water system, four have been identified as the (only) consistent potential developments of the future. Local stakeholders, stemming from a wide range of institutions have been actively involved in the definition of these driving forces and the set of scenarios. The evaluation of these scenarios and potential options to adapt the water system to future developments was carried out by modelling and simulation, using a purpose-built, yet general, simulator which represents the entire water and wastewater system and includes the important inherent feedback loops (e.g. water demand by irrigation, reuse of treated and untreated wastewaters). The setup of the simulator and the implemented models was done in a way that the simulator formed an integral element in the design of strategies and measures, derived by this innovative combination of qualitative scenario building, quantitative modelling and stakeholder participation. As a core result of this process, the Action Plan “Lima 2040” has been developed and adopted, in which the signatories (the main institutions and organisations responsible for the water sector of Lima) commit themselves to specific actions to be implemented over the years to come.

Abstract

AbstractSeasonal climate forecasts for an early warning of climate anomalies are produced by regional climate outlook forums (RCOF) worldwide. This study presents a verification of one of the earliest RCOF products, the precipitation outlook for the West African monsoon peak period (July–September). The basis of this outlook is countrywide precipitation forecasts from various statistical (downscaling) models, which are subjectively reinterpreted by experts on the basis of information from observed SST pattern analysis and global forecasts. The forecast quality was analyzed from 1998 to 2013 using a novel database of rain gauge measurements established for several West African countries, among other references. The analysis indicated skill for above normal and below normal on different spatial scales but also showed typical limitations of seasonal forecasting such as lack of sharpness and poor skill for near normal. A specific feature of the RCOF product is a strong overforecasting of near normal, very likely a result of the risk aversion of experts. To better illustrate the usefulness of the outlooks, they were evaluated with respect to a binary warning system by determining the maximum economic value Vmax. This verification indicated moderate valuable precipitation warnings for dry (Vmax = 0.39) and wet (Vmax = 0.34) years for four climatological zones (Sahel, Sudan–Sahel, Sudan, and Guinean) and five river basins (Volta, Senegal, and three Niger subbasins) but with strong regional differences (0.14 < Vmax < 0.54). The bootstrap analysis illustrated large uncertainties, indicating the relevance of uncertainty margins when seasonal forecast products with small sample sizes like RCOF outlooks are evaluated.

Abstract

In den letzten Jahren werden vermehrt ensemble-basierte Niederschlagsvorhersagen von numerischen Wettervorhersagemodellen als Antrieb für die operationelle Hochwasserwarnung in Deutschland eingesetzt. Allerdings sind Studien zur Qualität ensemble-basierter Niederschlagsvorhersagen für Indikatoren der Hochwasserfrühwarnung wie den Gebietsniederschlag relativ selten. In dieser Studie wurde daher eine Evaluierung von COSMO-DE-EPS Niederschlagsvorhersagen für den Gebietsniederschlag und dessen räumliche Variabilität von elf kleinräumigen Flussgebieten (42 km² bis 746 km²) in Rheinland-Pfalz durchgeführt. Als Untersuchungszeitraum diente die Starkregen- und Hochwasserperiode im Frühsommer 2016. Für kürzere Vorhersagereichweiten (< 15 h) zeigte sich selbst für den stündlichen Gebietsniederschlag eine verhältnismäßig gute zeitliche Übereinstimmung der Vorhersagen im Vergleich zu Radar- und interpolierten Stationsbeobachtungen als Referenz. Es wurden somit relativ zuverlässige Niederschlagsvorhersagen von COSMO-DE-EPS während dieser Starkregenperiode für die Untersuchungsgebiete bereitgestellt. Allerdings offenbarte die Untersuchung auch mehrere Schwächen des Vorhersagesystems, die in zukünftigen Studien näher untersucht werden sollten. Die Genauigkeit der Vorhersagen wurde mit kürzer werdender Reichweite kaum besser, obwohl die Ensemblestreuung deutlich abnahm. Des Weiteren tendierten alle Ensemblemitglieder in den meisten Situationen dazu unterhalb der Beobachtungen (negativer Bias) zu liegen, auch bei hohen Reichweiten. Diese Unterschätzung ist als besonders kritisch anzusehen, da ein Extremereignis zu spät oder gar nicht erkannt werden könnte. Eine Untersuchung der räumlichen Niederschlagsvariabilität ergab, dass die Ensemblemitglieder die beobachtete Variabilität der Niederschlagsfelder in den Flussgebieten deutlich besser reproduzieren konnten als der Ensemblemittelwert. Dies ist auch zu erwarten, da durch die Mittelung eine Glättung des Niederschlagsfeldes erfolgt, die sich besonders bei hohen Reichweiten aufgrund der größer werdenden Ensemblestreuung stark auswirkt. Ein Hochwasservorhersagesystem sollte daher nicht auf den Ensemblemittelwert der Vorhersagen basieren, sondern das gesamte Niederschlagsensemble bei der Weiterverarbeitung in hydrologischen Vorhersagen berücksichtigen.