Increasing periods of drought resulting from climate change pose major challenges for parts of Germany, including the state of Brandenburg. Local authorities, along with other stakeholders, can play a pivotal role in preventing and managing water scarcity. This article, therefore, examines in an explorative manner the activities being taken to avoid and manage water shortages, and the conditions that facilitate or hinder them, based on semi-structured interviews with stakeholders from four small municipalities in Brandenburg. The activities and conditions were analysed in terms of five leverage points: 1) awareness of the urgency and goals; 2) cooperation and responsibilities; 3) existence of, access to, and exchange of knowledge; 4) resources and capacities; and 5) strategies and measures. The results show that awareness of water scarcity varies greatly among respondents, with partly low levels. Communication with other relevant stakeholders is often limited. Various data, information resources and guidance exist. They are mentioned in the article but underutilised up to now. Although some initial individual measures have been implemented, there is still a lack of comprehensive concepts. Key obstacles identified include insufficient human and financial resources, unclear responsibilities, and a perceived lack of urgency. These issues are closely linked, resulting in the issue of water shortages not being addressed on a large scale in the four municipalities. The study highlights the need to strengthen small municipalities in terms of both finances and human resources, the positive local effects of developing climate adaptation plans and the need for both comprehensive coordination and the raising of awareness.
In this study, 1,575 runoff series of the CAMELS-DE database are used to investigate the runoff behaviour for intermittency across Germany. The analysis showed that 16 % of the stations had at least one zero-flow period during the investigation period between 1981 and 2020. 20 stations fell dry on average every one to two years, for 3 to 200 days per year, followed by 38 stations with medium intermittent behaviour with zero-flow days every 2 to 5 years. A larger part of the intermittent stations fell dry rarely: 40 stations every 6 to 10 years and 149 every 10 years or more rarely. The remaining fraction, 84 % of all stations of the CAMELS-DE data set, was perennial during the entire investigation period. An assessment of temporal variability of the annual number of zero-flow days revealed an inhomogeneous change behaviour: for each zero-flow frequency category from frequent to rarely intermittent, different temporal change patterns-increase, decrease or no trend-were found in the dataset. For around 76 stations, an increase of zero flow days was detected, which was statistically significant at 21 stations. 52 of the stations exhibited no significant trend over the entire time period, but a clear increase in the years 2018 to 2020. A moderate correlation was detected between the annual number of zero-flow days and the mean spring and summer temperature, as well as between the potential evapotranspiration and the June SPEI-3 drought index for stations with a highly intermittent regime and increasing trend. For the annual number of zero-flow days of all other intermittent stations and climate metrics, correlation was only weak or not detectable. In order to assess potential association between the classification of the runoff regime into intermittent or perennial regimes and the 67 catchment attributes from the CAMELS-DE dataset, random forest analysis was used. It resulted in no clear picture which attributes may explain the tendency towards intermittent runoff. In contrast, a whole range of not directly discharge-related attributes were identified, which included the frequency of dry days and the areal coverages of aquifer, geochemical rock type, land-use and soil parameters. From those identified attributes, catchments with more permeable soils with higher sand and low clay content tended to be characterized by intermittent rather than perennial runoff.
For smaller catchments along the German North Sea coast, there is still a considerable deficit of discharge data. Due to the tidal influence and the hydromorphological characteristics of the watercourses, it is difficult to measure the discharge. This study uses the example of the Maadesiel near Wilhelmshaven to investigate and evaluate the extent to which radar sensors can be used at tide gates to record discharges in the tide gate. It was found that radar sensors are well suited to continuously recording the flow velocities in the Maadesiel tide gate, despite the increased effort required to process the raw data series. In combination with continuous water level measurements on the seaward and inland sides and several comparative flow measurements with an Acoustic Doppler Current Profiler (ADCP), the radar measurement can be calibrated and the flow rate determined with low measurement uncertainty.
The expansion of ground-mounted photovoltaic systems is increasingly raising questions about their hydrological impacts. Since existing models inadequately capture the altered precipitation distribution and re-infiltration caused by solar modules, this study developed a high-resolution two-dimensional model in the modelling programme TELEMAC-2D and enhanced it with an extended infiltration module. The new methodology enables a process-based representation of spatially heterogeneous precipitation patterns as well as the re-infiltration of surface water. Using the Bundorf solar park as a case study, the model's sensitivity to different land-use and soil conditions was investigated. Under the specified assumptions, the simulations show increased runoff peaks immediately after installation of the system, particularly during moderately heavy rainfall events. Ecological measures, such as targeted greening and soil improvement, substantially increase infiltration capacity in the model and can reduce runoff volumes in the long term. Structural interventions, such as retention basins or filled ditches, further enhance retention potential. Overall, the results highlight the capability of the extended hydrodynamic model to reproduce physically plausible process patterns beneath ground-mounted PV systems. Although the findings must be interpreted qualitatively due to the lack of measurement data, the approach demonstrates considerable potential for scenario analysis and for transferability to other sites. The methodology thus provides a robust basis for hydrological assessment and sustainable planning of solar parks.
The combination of anthropogenic drainage measures and increasing drought in forests leads to the need for measures that prevent runoff in the drainage trenches and improve water retention in the area. In order to investigate the potential of different measures, a corresponding area in the Soonwald (Hunsr & uuml;ck) was simulated using the hydro-numerical surface runoff model HydroAS. A high-resolution digital terrain model (DTM) served as the basis for the simulation. Ditch closures, redistribution ditches, retention ditches adapted to forestry (intermediate ditches), and road ditch drainages were selected as measures to be simulated. To model the measures on the DTM, algorithms were developed that alter the height values of the DTM and thus depict the measures. Simulations were then carried out for the different measures, in which precipitation of different intensities was applied to the area. The total retention and the redistribution of water across the area were then evaluated. This showed that the redistribution ditches effectively transferred the water from the drainage ditches, but at the same time, they represent the strongest interferences with the ecosystem. Intermediate ditches and road ditch drainages, on the other hand, seem to be the most suitable for retaining larger amounts of water while maintaining cultivability. Ditch closures represent a less severe intervention in the ecosystem to create local water retention. The choice of method should always be made with the overall objective in mind. The model approach developed can serve as a basis for planning water retention measures in forestry and agriculture in the future.
The risk of sudden flooding in urban areas is omnipresent in Germany. Such events are triggered by convective, high-intensity rainfall events of short duration and small spatial extent. This paper presents methods and exemplary results of the ,,Inno_MAUS" research project, which aims to develop, provide and integrate innovative digital tools for the management of urban flood risks. These tools can be used in real-time forecasting mode as well as for planning, scenario analyses and adaptation concepts. This study focusses on the approaches and results for the ,,scenario mode". The adaptability of the developed tools and their coupling for specific requirements is important for future use in practice. The integration of local data can be done in a flexible and targeted manner, and can also include special data sets as required. AI methods are used in several areas, including extreme rainfall forecast, hydraulic modelling and estimating potential damage. It has been shown that these methods have great potential, but are only useful if very large amounts of data suitable for the specific problem are available. Close cooperation was established with the cities of W & uuml;rzburg and Berlin, as these cities complement each other very well in terms of the dominant urban runoff formation, runoff concentration and damage processes. They also have specialised administrations that are experienced with the challenges of modern urban flood risk management. The article summarises the methods developed and shows exemplary results: center dot Transferable and scalable coupled modelling of extreme rainfall, urban runoff generation including different retention options, urban hydraulics, and damage estimation; center dot Effects of the different retention options in urban landscapes but also in rural areas. These are clearly recognisable in quantitative terms and can be optimised through scenario analyses; center dot Options for rainwater retention through conventional storm water drainage, which combine infiltration-promoting measures such as ,,green infrastructure". In this way, significant retention can be achieved, although the relative effect of the retention decreases with increasing event intensity.
The increasing frequency and intensity of heavy rainfall events and flash floods require water-sensitive urban development. Detailed data bases for determining potential hazard areas and the identification of emergency drainage routes are an elementary component for preparing for the consequences of heavy rainfall. To this end, the FloReST project developed innovative technological solutions that enable high-resolution flow path identification and allow risk communication tailored to the various needs. These smart tools were tested at the P & uuml;tzfeld test site in the Ahr valley. In the first step, 2D HN models were refined and potential hazard areas identified. At a particularly high-risk site in P & uuml;tzfeld, con-tactless flow path identification was implemented by thermal tracer experiments. Furthermore, mobile video recordings enabled the small-scale recording of surface structures. In addition, so-called smart tools were developed, which complement the detailed identification of flow paths, allow for a creation of a high-resolution data basis for the assessment of emergency drainage routes and preventing the consequences of heavy rainfall. An interactive app for involving and informing the population is another smart tool that innovatively complements the "classic" methods, such that a holistic approach is pursued with the help of innovative risk communication. The data generated using the smart tools is then additionally collated in a central data platform and made available on a user-specific basis. The testing of the various smart tools shows the relevance of high-resolution emergency drainage routes designation in combination with an innovative risk communication to strengthen resilience in the event of heavy rainfall.
The ,,ZwillE" project is part of the funding program ,,Water Extreme Events (WaX)" of the Federal Ministry of Research, Technology, and Space (BMFTR, formerly the Federal Ministry of Education and Research, BMBF). It has developed a digital twin for Stadtentw & auml;sserung Hannover (SEH, Hanover city drainage), covering the areas of the sewer network, wastewater treatment plants and surface waters. The goal of the Digital Twin is to map the entire system in real-time in order to better manage the effects of extreme water events. Its focus is on reducing combined sewer overflows and providing information on flood risks. The identification of problem areas and necessary adaptations is also intended. To ensure sufficient data availability from the sewer network, additional measurement stations and sensors were installed. Radar precipitation measurements and short-term forecasts are used, both for the integrated simulation of the sewer network and treatment plant within the SIMBA# simulation system and for flood riskassessments. SIMBA# serves as the simulation core of the Digital Twin, enabling the real-time modelling of the water system and the generation of visualizations and forecasts. A methodology for the automated creation of real-time capable sewer network models from detailed models was adapted and applied to Hannover's sewer network. This allows for statements and forecasts to be made regarding expected combined sewer discharges, and enables proactive interventions to reduce such discharges. For a rapid flood risk assessment, an empirical-statistical method was developed for use in the Digital Twin. This method uses radar precipitation data and precomputed flood maps to generate a city-wide flood map for a current rainfall situation within a processing time of less than five minutes. An evaluation based on ten real heavy rainfall events demonstrated that the method yields good results compared to reference simulations with a coupled surface and sewer network model. The method allows both for the rapid representation of changing weather conditions and the generation of forecast maps based on ensemble predictions. The measurement data and simulation results are integrated into the Digital Twin via a data and communication infrastructure and made available to users through an integrated front-end. The visualization concept includes multiple levels, providing users with both a quick overview of the system as a whole, and detailed insights into specific areas. The Digital Twin was initially implemented as a demonstrator, allowing historical events to be simulated. In the next step, a prototype of the Digital Twin was developed for real-time operation. It is currently being implemented at the control rooms of SEH to be tested internally in operation.
The increase in extreme weather conditions poses considerable challenges for municipal water management. As part of the project ,,Extreme weather management with digital multiscale methods" (EXDIMUM), supported by the Federal Ministry of Research, Technology, and Space (BMFTR, formerly the Federal Ministry of Education and Research, BMBF), practical methods for tracking, modelling, and visualizing heavy rainfall and drought events were developed and tested in a study area around the city of Goslar in the Harz Mountains. The interdisciplinary collaboration of experts from water management, algorithmics, remote sensing, software development, and hydrology enabled the use of a wide range of data sources: For example, multispectral SAR (Synthetic Aperture Radar) data from remote sensing was used to record land use and deadwood areas, together with hydrological parameters for large-scale, long-term simulation of water runoff and the effects of tree mortality. In addition, wireless sensor networks were established to record water levels, precipitation, soil moisture, and the status of culvert grates. With the help of hydraulic and hydrodynamic models as well as algorithmic geometry techniques such as quadtree-based dynamic resolution, the efficiency of heavy rainfall runoff simulations was significantly increased compared to previously used methods. With comparable accuracy, computation times shorter than the duration of the event are achievable, i.e., real-time computation has become possible in principle. An accompanying dashboard enables the integration and visual presentation of remote sensing, sensor, and simulation results.The real-time operation of the sensor network proved successful in monitoring the flood event in December 2023 in Goslar and contributes to improved planning of measures in disaster scenarios.
In contrast to fluvial floods, the key hazard posed by pluvial flash floods is unconfined overland flow, which occurs away from rivers. Therefore, neither the existing classification schemes for fluvial floods nor a simple analysis of precipitation, e.g. according to the heavy rain index (HRI), are appropriate to assess the hazard posed by pluvial flash floods or to issue warnings for flash floods. The pluvial flood index (PFI) presented and applied in this study addresses this problem, as it refers to the hazard of unconfined overland flow and accounts for hydrological and hydraulic factors influencing pluvial floods. The PFI is based on pluvial flood hazard areas (PFHA), defined as areas in which pedestrians or vehicles are exposed to a hazard because the water level, flow velocity and/or the discharge surpasses the critical limits.The relative share of PFHA in a reference area is classified by threshold values into four classes of PFI ranging from "0-no to minor hazard"to "3-very great hazard".The PFI is therefore a robust, dimensionless metric, which can be used to inform the general public about the potential occurrence and magnitude of a pluvial flash flood. To analyse the practical applicability of the PFI and its calculation, this study applies the methodology to four past events in four different federal states of Germany and evaluates the resulting PFI on a qualitative basis by means of damage reports and in part by discharge records. In the first step, the hydrological model LARSIM (Large Area Runoff Simulation Model) serves to determine the spatially nuanced surface runoff generation. In a second step, the simplified hydraulic model AccRo (Accumulated Runoff Model) is applied to simulate the overland flow accumulation and determine the resultant maximum water levels, flow velocities and specific discharges. The PFI derived on this basis for all four events is plausible. The results also illustrate the additional benefit of the PFI in comparison with the sole application of the heavy rain index. It furthermore becomes clear that it is possible and recommended to combine PFI-based warnings with fluvial flood warnings for events, which possess characteristics of both pluvial flash floods and fluvial river flooding. The two models used in the present study, LARSIM and AccRo, are adequately accurate for determining the PFI for the analysed events. At the same time, they are very computationally efficient, making an operational real-time forecast possible in the future. Even though there remains a need for further research on this topic and an optimisation of the details, the PFI and the applied tools provide a reasonable basis for a nuanced operational pluvial flash flood warning.
Against the backdrop of climatic and anthropogenic influences on water balance, there is an increasing need to manage rainwater and soil water effectively. One way to retain water on agricultural land is to dam existing drainage ditches or drainage pipes so as to retain soil water in arable land, or to release it in the appropriate weather conditions. At the end of 2023, such a drainage control system was installed in an agricultural field near M & uuml;ncheberg in Brandenburg as part of the SpreeWasser:N project, and its influence on the soil water balance was investigated over the course of a year. During the winter months, a significant accumulation of water of over 140 cm above the original drainage level initially occurred. The measurements show that the water level rises sharply within a few minutes, especially in the event of summer showers. A drawdown test estimated the total storage capacity of the 16,7 ha drainage system to be 6,000 m(3), the impoundment area of which is largely located in the eastern area due to the gradient and the inclination of the drainage pipes. During dry periods, the water level sinks about 1 cm of water per day. The rate of loss depends on the water levels in the drainage storage system and the potential evapotranspiration, however. The measurement of soil moisture reveals a correlation between soil moisture at the beginning of a rain event and the water level's reactivity to precipitation. At the measurement locations above the impoundment area, soil moisture increases with depth; this is probably not exclusively due to the impoundment of the drainage system, however.
Urban flooding as a result of heavy rainfall occurs all over Germany, causing high property damage every year. Such pluvial flooding can occur practically anywhere, even away from waterbodies, which makes it difficult to map areas at risk. In addition, flooding not only causes material damage to buildings, but can also disrupt infrastructure functions. Worst case, it can endanger people. However, observed careless behaviourduring pluvial floods, such as driving and walking through flooded streets and underpasses, shows that the population is not well aware of potential impacts. This paper therefore presents a more comprehensive mapping approach that considers different pluvial flood impacts and can complement municipal risk communication. The methodology was co-developed by both scientists and local decision-makers. This involved analysing potential impacts on various elements at risk including buildings, infrastructure, vehicles and people at both the micro-scale, e.g. individual buildings, and the meso-scale, e.g. districts.The approach was developed and implemented using a pilot region in Berlin, taking into account the needs of municipal emergency management, the availability of data throughout Germany and the methodological feasibility, so that the procedure is in principle transferable to other municipalities.
Nutrients are discharged into surface waters and groundwater via runoff components. As part of the Germany-wide RELAS project, the runoff components total runoff, surface runoff, drainage runoff, natural interflow, direct runoff from urban areas and groundwater recharge were modelled with the water balance model mGROWA for the period 1991 to 2020 at a spatial resolution of 100 m x 100 m. The regional interaction of climate and topography, but also of soil, geology and land use, results in total runoff ranging from less than 100 mm/a in the Leipzig lowland bay to more than 1,200 mm/a in the Alps. In all solid rock regions, natural interflow dominates direct runoff. Runoff from drainage systems is widespread in locations influenced by groundwater or waterlogging in unconsolidated rock regions, such as the North German lowlands. At sites remote from groundwater in flat unconsolidated rock regions, total runoff is classified as groundwater recharge in the model. The modelled runoff in daily resolution was aggregated to mean long-term values and then evaluated for plausibility by comparing it with the observed runoff from more than 1,100 gauging stations in river basins. The results indicated a very good agreement nationwide across all catchments.The model results thus provide a reliable basis for modelling pathway-specific nutrient inputs.
The majority of peatlands in Brandenburg are currently heavily drained due to melioration measures, including the southern Randowbruch region in Uckermark. Peatlands play a crucial role in climate change as significant sources of greenhouse gas emissions. Reducing these emissions, as well as sequestering greenhouse gases in biomass, can only be achieved under wet peatland conditions. This paper is concerned with a project to develop a management concept which centralizes the rehydration of the peatland of the southern Randowbruch. The catchment area of the Randow has a long and strongly anthropogenic history of melioration. The peatland, which formed during the Vistula Ice Age about 18,000 years ago in the washout channel of a glacier, has been continuously drained and made agriculturally usable during the last 300 years by targeted human interventions. The draining measures reached their peak in the 1960s and 70s and have remained unchanged since then. The Randow lowland, characterized by its peatland areas, is strongly influenced by groundwater dynamics. Therefore, a robust simulation of the regional water balance in its full complexity requires consideration of the interactions between groundwater and surface water. For this reason, the foundation of the management concept is a coupled modelling approach, integrating the eco-hydrological modelling system ArcEGMO with the groundwater modelling software FEFLOW. In this framework, FEFLOW is responsible for calculating groundwater flow, while ArcEGMO simulates the soil water balance and surface water system.
Concentrations of phosphorus (P) in surface waters in Northwest Germany are exceeding reference values. This circumstance is already leading to ecosystem changes through eutrophication, which also affect the North Sea, causing a significant and long-term problem. The aim of this study, therefore, was to identify the nutrient sources in agriculturally used grassland with their associated discharge paths - surface drainages (Gr & uuml;ppe), subsurface drainages and ditches - while also considering fertilization and seasonal variability. The area of research encompassed the coastal landscapes of drained peatlands, i.e. bog or fen; marsh and geest, as well as their organo-mineral transitions. Between 2019 and 2022, soils as well as surface drainage, subsurface drainage and ditch water were sampled at 49 sites in different landscapes in the Jade catchment. Overall, the bog soil samples showed the significantly highest P contents with 178 mg PO43--P kg-1, followed with decreasing contents by the geest, fen and marsh soil. The significant highest concentrations in the connected discharge paths were measured, on the one hand, in the surface drainage discharge of the geest, with 0.5 mg PO43--P L-1, and on the other hand, in the subsurface drainage discharge of the bogs, with 1.8 mg PO43--P L-1. In general, significantly higher discharge concentrations were found in surface drainages compared to subsurface drainages. At the same time, the bog sites showed significantly higher concentrations in adjacent ditches with 0.8 mg PO43--P L-1 and therefore posed the largest risk of P contamination for surface waters. Overall, this study shows that both the soils and the management influence the P contents of soils as well as the P concentrations in discharge and ditch water. Nevertheless, no direct influence of discharge concentrations on ditch concentration was found. When the seasonal variability of P concentrations in the ditches is considered, it can be seen that turnover processes within the ditches have an influence on dissolved P concentrations. This reflects the complexity of grassland-ditch systems.
The water balance of wet grassland sites is characterised by high groundwater levels near the surface. It is affected by the water resources management of the existing ditches and weirs.The change of climatic conditions during the last decades, with increasing temperatures and more and more extreme meteorological conditions, causes greater water table depths with increasing frequency, especially in dry years in the eastern regions of Germany, where precipitation is generally lower. Investigations with a weighable groundwater lysimeter station in the Spreewald wetland show that an improved water retention in the wet grassland sites during winter and spring can improve the water budget. The increased target water level, a precondition for water retention, is affecting the vegetation composition and leads to more wetland typical species such as sedges. These species have a higher biomass production than existing extensive wet grassland species, leading to higher evapotranspiration. In very dry years, this can lead to very deep water table depths in the summer months despite an improved water retention in winter and early spring. The crop coefficients derived in this study can be used to estimate the actual evapotranspiration and water demand. This allows decision-makers to take vegetation effects into account when planning restoration measures and water management improvements at wetland sites.
The prolonged dry spell from 2014 to 2020 in Saxony was the reason for comprehensive analyses of low flow series in terms of probabilistic statistics with regard to the seven low flow parameters NM7Q, NM15Q, NM30Q, maxD, maxV, sumD and sumV, calculated at 34 gauging stations, with the last four parameters derived based on the Q80 threshold value. Low flow series are often characterised by stochastic dependencies. Failure to account for this phenomenon, which is inconsistent with classical probability theory, leads, for example, to over-rejecting null hypotheses of statistical tests, underestimating confidence intervals, and overestimating return periods of runs, i.e. sequences of successive dry years. This study demonstrates how stochastic dependencies can be integrated into low-flow statistics in a manner similar to instationary extreme value analysis. In addition to these extended univariate probability approaches, cross-duration NMxQ considerations, copula-based two-dimensional probability models, and models to characterise return periods of runs are presented.
The simulation and forecasting of catchment runoff is a central task of hydrological modelling. For this purpose, process-based, conceptual and data-based methods are used, and especially the latter method has shown rapid development in recent years. In this context, the aim of this study is to investigate the potential of Long Short-Term Memory (LSTM) models for long-term simulation and for shortterm forecasting of catchment runoff. For these purposes, LSTM models are trained for four gauging stations in Baden-Wurttemberg using hydro-meteorological input variables, and applied for four years of continuous runoff simulation and 72-hour short-term flood forecast tests based on measured meteorological driving data. The model results are compared with measurements from gauging stations and with the results of the well-established process-based water balance model LARSIM. The results of this study show that the most effective parameters for the LSTM's simulation quality are i) input sequence length, ii) choice of input variables, and iii) choice of the objective function for training. With respect to i), 3 months turned out to be the optimum trade-off between simulation quality and training time, with respect to ii) using aggregated time series data in addition to the hourly input data improved the simulation quality, and with respect to iii) a modified mean squared error with an additional weighting of the highest error improved the simulation quality especially for high discharges. Further modifications and manipulations of the input variables such as quantile mapping and stratified sampling did not result in any improvements. Long-term simulations by LSTMs are very good (Nash-Sutcliffe efficiencies of 0.84 to 0.90) and comparable in quality to LARSIM. The LSTMs also achieve very promising results in simulating observed flood peaks, comparable in quality to the LARSIM simulations. Two LSTM variants were established for short-term discharge forecast: Recursive LSTM, which uses its own streamflow simulation from the previous time step as an input, and multi-LSTM, in which separate LSTMs are trained for each forecast depth. It was shown that the Recursive LSTMs are less robust than the multi-LSTMs, mainly due to the effect of error propagation. With the multi-LSTMs short-term forecast tests achieved results comparable in quality to those of LARSIM. Based on these results, we propose to further explore and investigate the potential of machine learning methods for hydrological runoff simulation and forecasting, for example by combining the strengths of process-based and data-based models in hybrid systems.
