Variations in sub-daily precipitation at centennial scale

Due to data availability long-term variations in precipitation rates are mostly studied based on daily precipitation recordings. Recent research suggests, however, that variations in sub-daily precipitation are subject to higher dynamics compared to daily precipitation and a more rapid intensification is likely. Here we show that both observational data with at least 58 years of sub-daily precipitation records and a dynamical downscaling approach with low spatial resolution based on atmospheric re-analysis data confirm these expectations with consistent results. High percentiles of precipitation are subject to multi-decadal oscillations and increased during the last 150 years. We found an increase of 4% K−1 (daily), 12% K−1 (hourly), and 13% K−1 (10 min), which is consistent with Clausius–Clapeyron- (CC) and super CC-scaling, respectively. These findings highlight that dynamical downscaling can help to reliably shed light on sub-daily precipitation variations if small timescales are considered in the experiments

Detailed Simulation of Snow Processes in Hydrological Modelling

In dieser Arbeit wird eine neue Methode zur Anwendung von prozessorientierten Schneemodellen auf der Einzugsgebietsskala vorgeschlagen. Es soll die Frage beantwortet werden, ob ein atmosphärisches Modell die geeignete Datengrundlage für die Anwendung prozessorientierter Schneemodelle auf der Skala eines Einzugsgebietes liefert. Anstelle von Punktbeobachtungen werden die meteorologischen Randbedingungen mit Hilfe eines atmosphärischen Modells aus globalen Eingangsdaten abgeleitet (dynamisches Downscaling). Alle auf diese Weise abgeleiteten historischen meteorologischen Daten stehen damit in Raum und Zeit in einem korrekten physikalischen Zusammenhang - eine Grundvoraussetzung für die prozessorientierte Schneemodellierung. Mit Hilfe von drei unabhängigen prozessorientierten Schneemodellen auf der Punkt- und Einzugsgebietsskala als Komponenten eines hydrologischen Modellsystems wird dies untersucht. Zusätzlich wird aus Vergleichsgründen das Temperatur-Index-Verfahren eingesetzt. Die Untersuchungen wurden für das Einzugsgebiet der Sieber (44 Quadratkilometer) im Harz durchgeführt. Im Vergleich mit hochaufgelösten Beobachtungsdaten konnten mit den Schneemodellen gute Ergebnisse für unterschiedliche meteorologische Situationen auf der Punkt- und Einzugsgebietsskala erzielt werden. Sowohl für den Kalibrierungs- als auch für den Validierungszeitraum ergaben die Simulationen auf der Einzugsgebietsskala Modelleffizienzen von über 0,8 bei Zeitreihenvergleichen für einen Zeitschritt von 1 h. Die Fragestellung wurde dabei auf die Variablen Temperatur, Luftfeuchte, Strahlung und Windgeschwindigkeit eingeschränkt, da die Variable Niederschlag nur unter Einschränkungen auf den gewünschten Skalen abgeleitet werden konnte. Daher wurden den Simulationen beobachtete Niederschlagszeitreihen zugrunde gelegt. Für Gebiete ohne Beobachtungen kann mit der hier entwickelten Methodik der Einfluss der saisonalen Schneedecke auf den Wasserhaushalt realistisch quantifiziert werden.In this study, a new approach to provide meteorological forcing data for process based snow models at the catchment scale is proposed. Instead of using point observations, the meteorological variables are derived by means of dynamic downscaling using a local atmospheric model driven by globally available input data. All meteorological variables of historical weather conditions are physically consistent in time and space, which is a basic requirement for process based snow models. The question, if spatial meteorological data obtained from a local atmospheric model are sufficient to drive process based snow models, is studied. To test the proposed methodology, simulations with three independent process based snow models are carried out at the point and catchment scale. For purposes of comparison, the common but very simplified temperature index method is applied likewise. The study area is the Sieber catchment (44 square kilometers) in the Harz Mountains in Germany. Compared to time series with high temporal resolution the tested snow models performed well under different meteorological conditions at the point and catchment scale. It was possible to achieve model efficiencies greater than 0.8 at catchment scale for both the calibration and the validation period on an hourly time step, if downscaled spatial data for temperature, humidity, radiation and wind speed were applied. For the study area, precipitation could not be downscaled with a high accuracy compared to observations. Consequently, observed precipitation time series were used instead. In conclusion, the proposed methodology can efficiently be used for areas without observations to simulate seasonal snow cover in a realistic manner

Unprecedented Retention Capabilities of Extensive Green Roofs—New Design Approaches and an Open-Source Model

Green roofs are a proven measure to increase evapotranspiration at the expense of runoff, thus complementing contemporary stormwater management efforts to minimize pluvial flooding in cities. This effect has been quantified by numerous studies, ranging from experimental field campaigns to modeling experiments and even combinations of both. However, up until now, most green roof studies consider standard types of green roof dimensions, thus neglecting varying flow length in the substrate. For the first time, we present a comprehensive investigation of green roofs that involves artificial rainfall experiments under laboratory conditions (42 experiments in total). We consider varying flow length and slope. The novelty lies especially in the consideration of flow lengths beyond 5 m and non-declined roofs. This experimental part is complemented by numerical modeling, employing the open-source Catchment Modeling Framework (CMF). This is set-up for Darcy and Richards flow in the green roof and calibrated utilizing a multi-objective approach, considering both runoff and hydraulic head. The results demonstrate that through maximizing flow length and minimizing slope, the runoff coefficient (i.e., percentage of rainfall that becomes runoff) for a 100 years design rainfall is significantly decreased: from ~30% to values below 10%. These findings are confirmed through numerical modeling, which proves its value in terms of achieved model skill (Kling-Gupta Efficiency ranging from 0.5 to 0.95 with a median of 0.78). Both the experimental data and the numerical model are published as open data and open-source software, respectively. Thus, this study provides new insights into green roof design with high practical relevance, whilst being reproducible

Event generation for probabilistic flood risk modelling: Multi-site peak flow dependence model vs. weather-generator-based approach

Flood risk assessment is an important prerequisite for risk management decisions. To estimate the risk, i.e. the probability of damage, flood damage needs to be either systematically recorded over a long period or modelled for a series of synthetically generated flood events. Since damage records are typically rare, time series of plausible, spatially coherent event precipitation or peak discharges need to be generated to drive the chain of process models. In the present study, synthetic flood events are generated by two different approaches to modelling flood risk in a meso-scale alpine study area (Vorarlberg, Austria). The first approach is based on the semi-conditional multi-variate dependence model applied to discharge series. The second approach relies on the continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator and using an hourly disaggregation scheme. The results of the two approaches are compared in terms of simulated spatial patterns of peak discharges and overall flood risk estimates. It could be demonstrated that both methods are valid approaches for risk assessment with specific advantages and disadvantages. Both methods are superior to the traditional assumption of a uniform return period, where risk is computed by assuming a homogeneous return period (e.g. 100-year flood) across the entire study area. © Author(s) 2020

Assessment of uncertainties in a complex modeling chain for predicting reservoir sedimentation under changing climate

Long-term predictions of reservoir sedimentation require an objective consideration of the preceding catchment processes. In this study, we apply a complex modeling chain to predict sedimentation processes in the Banja reservoir (Albania). The modeling chain consists of the water balance model WaSiM, the soil erosion and sediment transport model combination RUSLE-SEDD, and the 3d hydro-morphodynamic reservoir model SSIIM2 to accurately represent all relevant physical processes. Furthermore, an ensemble of climate models is used to analyze future scenarios. Although the capabilities of each model enable us to obtain satisfying results, the propagation of uncertainties in the modeling chain cannot be neglected. Hence, approximate model parameter uncertainties are quantified with the First-Order Second-Moment (FOSM) method. Another source of uncertainty for long-term predictions is the spread of climate projections. Thus, we compared both sources of uncertainties and found that the uncertainties generated by climate projections are 408% (for runoff), 539% (for sediment yield), and 272% (for bed elevation in the reservoir) larger than the model parameter uncertainties. We conclude that (i) FOSM is a suitable method for quantifying approximate parameter uncertainties in a complex modeling chain, (ii) the model parameter uncertainties are smaller than the spread of climate projections, and (iii) these uncertainties are of the same order of magnitude as the change signal for the investigated low-emission scenario. Thus, the proposed method might support modelers to communicate different sources of uncertainty in complex modeling chains, including climate impact models

Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale

Increasing urbanisation in combination with a rise in the frequency and intensity of heavy rain events increase the risk of urban flooding. Flood Regulating Ecosystem Services (FRES) address the capacity of ecosystems to reduce the flood hazard and lower damage. FRES can be estimated by quantification of supply (provision of a service by an ecosystem) and demand (need for specific ES by society). However, FRES for pluvial floods in cities have rarely been studied and there is a gap in research and methods on FRES supply and demand quantification. In this study, we assessed FRES of an urban district in the City of Rostock (Germany) for a one-hour heavy rainfall event using the hydrological model LEAFlood. The hydrological model delivered the FRES supply indicators of soil water retention and water retained by canopies (interception). An intersection of the potential demand (based on indicators of population density, land reference value, monuments and infrastructure) and the modelled surface water depth revealed the actual demand. Comparing the actual demand and supply indicated the budget of FRES to identify unmet demand and supply surplus. Results show highest mean FRES supply on greened areas of forests, woodlands and green areas, resulting in a supply surplus. Whereas, sealed areas (paved surface where water cannot infiltrate into the soil), such as settlements, urban dense areas, traffic areas and industry, have an unmet demand resulting from low supply and relatively high actual demand. With the hydrological model LEAFlood, single landscape elements on the urban scale can be evaluated regarding their FRES and interception can be considered. Both are important for FRES assessment in urban areas. In contrast to flood risk maps, the study of FRES gives the opportunity to take into account the contribution of nature to flood regulation benefits for the socio-economic system. The visualisation of FRES supply and demand balance helps urban planners to identify hotspots and reduce potential impacts of urban pluvial flooding with ecosystem-based adaptations

Robust vegetation parameterization for green roofs in the epa stormwater management model (SWMM)

In increasingly expanding cities, roofs are still largely unused areas to counteract the neg-ative impacts of urbanization on the water balance and to reduce flooding. To estimate the effect of green roofs as a sustainable low impact development (LID) technique on the building scale, different approaches to predict the runoff are carried out. In hydrological modelling, representing vegetation feedback on evapotranspiration (ET) is still considered challenging. In this research article, the focus is on improving the representation of the coupled soil–vegetation system of green roofs. Relevant data to calibrate and validate model representations were obtained from an existing field campaign comprising several green roof test plots with different characteristics. A coupled model, utilizing both the Penman–Monteith equation to estimate ET and the software EPA stormwater management model (SWMM) to calculate the runoff, was set up. Through the application of an automatic calibration procedure, we demonstrate that this coupled modelling approach (Kling–Gupta efficiency KGE = 0.88) outperforms the standard ET representation in EPA SWMM (KGE = −0.35), whilst providing a consistent and robust parameter set across all green roof configurations. Moreover, through a global sensitivity analysis, the impact of changes in model parameters was quantified in order to aid modelers in simplifying their parameterization of EPA SWMM. Finally, an improved model using the Penman–Monteith equation and various recommendations are presented

Zur Nutzung knapper Wasserressourcen : Beispiele aus ariden Regionen in Brasilien und Kenia

Wasser ist ein kostbares Gut - vor allem in Ländern mit wenig Niederschlag. Durch Klimawandel und gesellschaftliche Veränderungen unterliegt das wasserwirtschaftliche System sich ständig ändernden Dynamiken, die nur durch interdisziplinäre wasserwirtschaftliche Analysen und Prognosen erfasst werden können. Wissenschaftler vom Institut für Hydrologie und Wasserwirtschaft sowie vom Institut für Didaktik der Naturwissenschaften geben einen Einblick in ihre Arbeit

Das Schmelzen der Wassertürme : Was der Verlust von Gletschereis für Folgen hat

Schwindendes Gletscher- und Meereseis ist schon länger bekannt als ein klarer und besorgniserregender Effekt des Klimawandels. Larissa van der Laan und Prof. Dr.-Ing. Kristian Förster vom Institut für Hydrologie und Wasserwirtschaft zeigen anhand von Klima- und hydrologischen Daten, wie der Verlust messbar ist und welche Folgen er für die Wasserversorgung in den Alpen haben kann

What can we learn from comparing glacio-hydrological models?

Glacio-hydrological models combine both glacier and catchment hydrology modeling and are used to assess the hydrological response of high-mountain glacierized catchments to climate change. To capture the uncertainties from these model combinations, it is essential to compare the outcomes of several model entities forced with the same climate projections. For the first time, we compare the results of two completely independent glacio-hydrological models: (i) HQsim-GEM and (ii) AMUNDSEN. In contrast to prevailing studies, we use distinct glacier models and glacier initialization times. At first glance, the results achieved for future glacier states and hydrological characteristics in the Rofenache catchment in ötztal Alps (Austria) appear to be similar and consistent, but a closer look reveals clear differences. What can be learned from this study is that low-complexity models can achieve higher accuracy in the calibration period. This is advantageous especially when data availability is weak, and priority is given to efficient computation time. Furthermore, the time and method of glacier initialization play an important role due to different data requirements. In essence, it is not possible to make conclusions about the model performance outside of the calibration period or more specifically in the future. Hence, similar to climate modeling, we suggest considering different modeling approaches when assessing future catchment discharge or glacier evolution. Especially when transferring the results to stakeholders, it is vital to transparently communicate the bandwidth of future states that come with all model results. © 2020 by the authors