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We combine long-term hydro-meteorological data from the small research catchment Wernersbach (WB, 4.6 km², dominated by Norway spruce) in operation since 1967 and from two eddy-covariance (EC) flux towers, all located in the Tharandt Forest, Germany. This combination forms an observatory, addressing actual evapotranspiration ET from a water budget perspective (catchment) and from an energy perspective (EC flux towers). However, obvious differences exist in time resolution. The spruce dominated tower DE-Tha is located a few kilometres east of the catchment. After a windbreak of another spruce stand (situated inside the catchment) and planting of deciduous oaks, the tower DE-Hzd was set up in 2009. We recently reported systematically about the observatory and the long-term water budgets in Pluntke & Bernhofer et al. (https://doi.org/10.1016/j.jhydrol.2022.128873).The catchment and both towers did not show any systematic differences in meteorological data (especially wind-loss corrected precipitation totals are almost identical), allowing us to address observed differences in ET as (i) due to different soil and hydrogeological characteristics as well as (ii) due to methodological aspects. The catchment term ET plus storage, derived from precipitation P minus runoff R, showed the expected high variability with a significant increase over the more than 50 years of operation. The older, spruce-dominated flux-tower DE-Tha showed much lower inter-annual variability in ET with an average annual total of 486 mm (1997 to 2019), but no significant trend. For the same period, average catchment ET was 734 mm/year. The younger flux-tower DE-Hzd showed ET values closer to catchment ET at the very dry end of the ten-year record (2010 to 2019).For the 23 years of parallel measurements, annual ET from EC was about 250 mm lower than catchment ET, despite the careful correction of tower ET for energy balance closure. Catchment ET = P – R might have a small bias towards larger ET, as the subsurface catchment size of WB could be up to 0.4 km² smaller. In addition, precipitation and runoff may contribute to higher catchment ET. However, the difference is too large to be explained by measurement bias alone. Flux tower ET is compared to (i) independent measurements of ET components, and (ii) model output of BR90. There is evidence from interception and transpiration measurements at the flux tower that more than 100 mm of intercepted water could be missing in the annual ET from EC. Model results show a large additional contribution of interception due to negative sensible fluxes in fall and winter. The difference in ET between tower and catchment of 250 mm is probably due to a variety of reasons: overestimation of catchment ET (up to 50 mm), soil characteristics (50-100 mm), and underestimation of tower ET (100-150 mm).We conclude that the EC closure correction during interception events needs to be revisited. Generally, results of ET monitoring of similar evergreen forests in a humid climate should be checked for missing contribution of interception, as EC records might be generally too low. This illustrates the necessity of redundant and complementary measurements when dealing with large system complexity.

Climate changes are expected to trigger changes in all water budget components at any scale. For Central Europe, higher evapotranspiration (ET) rates are already observed, other factors like land use or land cover characteristics change in parallel, but experimental evidence of the interdcations is limited, as it requires challenging long-term measurements. We take advantage of the well-documented hydro-meteorological dataset from the forested research catchment Wernersbach in Saxony, Germany, covering 52 years between 1968 and 2019 (Pluntke & Bernhofer et al., 2023).We analyzed hydro-climatological time-series for linear trends and for breakpoints. Significant positive trends were found for global radiation, mean air temperature and grass-reference evaporation, as well as for the difference between catchment precipitation and runoff (P-R; hydrological estimate of ET). Precipitation increased and runoff decreased over the 52 years, but not significantly.Air temperature and global radiation show significant breakpoints around 1988 and 1996, respectively, with below average conditions before and above average conditions after the breakpoints. Temperature change is associated with global warming, and possibly with the independent regional effect of air pollution. Since the 1960s, large sulphur dioxide emissions from fossil fuel burning led to a high aerosol density in the troposphere reducing solar radiation over most of Europe and North America. While this effect was reduced by filtering the emissions elsewhere in the early 1980s, it continued in neighboring parts of today’s Germany, Poland, and Czech Republic until the early 1990s. Breakpoint of grass reference evaporation coincides with air temperature (1988), and the breakpoint of P-R is a few years later.We attributed changes in ET to changes in land use and climate by applying an adapted Budyko framework and enabled insights into their interactions. The sulphur dioxide emissions triggered widespread forest dieback in regions over 600 m in Saxony. Consequences were decreasing ET in the 1970s/1980s. The Wernersbach catchment (390 m) shows a similar tendency (not significant). Since the 1990s, both climate (increasing atmospheric demand) and land use (healthier forest stands and improved management practices) led to an increase of ET. In 2010s, climate induced damages of forest stands (due to droughts, storms, snow load, and bark beetle infestations) led to a drastic decrease of ET in Wernersbach despite favorable climatic conditions for ET. Since the intensity and frequency of such extreme events are likely part of climate change, they may cause greater regional changes in the water balance than direct effects of climate change, and may cause lasting damage to Ecosystem Services of forests, like flood mitigation, or carbon sequestration.Our results show the need for climate adaptation measures in forests, such as the establishment of a more site-specific mixed forest, and a sustainable forest management. ReferencesPluntke T. & Bernhofer C., Grünwald T., Renner M., Prasse H.: Long-term climatological and ecohydrological analysis of a paired catchment – flux tower observatory near Dresden (Germany). Is there evidence of climate change in local evapotranspiration? J Hydrol 617 (2023), https://doi.org/10.1016/j.jhydrol.2022.128873

The paper presents an integrated approach for the apportionment of water and sediment sources and pathways in ungauged territories. The approach comprises various elements such as a large-scale semi-distributed hydrological and erosion model (using the SWAT tool), a statistical assessment of regular discharge data, the discrimination of runoff sources using end-member mixing analysis (EMMA), the apportionment of sediment sources using fingerprinting technique and sediment concentration and water discharge hysteresis rating curves analyses. The approach has been applied to Western Dvina River Basin (WDRB). The results discussed in the paper indicate main features of the water and sediment regime. The components of the presented framework provide a guide for detailed water and sediment studies making it an inexpensive way to develop a roadmap to understand important hydrological processes at a watershed scale.

The IWAS project Ukraine deals among others with the water balance in the headwaters of the river Western Bug. During investigations in the sub-catchment Sasiv, a gap in the water balance was detected by Pluntke et al. (Environ Earth Sci, this issue, 2014). The runoff of this sub-catchment is significantly higher than that of any other catchment in the region. Unexpectedly, in 2011 the runoff was observed to be higher than precipitation. We hypothesize additional subsurface flow in the Sasiv catchment from adjacent aquifers. The hydrological model BROOK90 was used to model water flows. In addition to publicly available meteorological input data from the NOAA and ECA&C databases, own precipitation measurements in Sasiv were used. The mean seasonal leaf area index (LAI)—cycle of forest, grass, and agricultural land was determined using satellite data. To improve the output quality, the model was adapted for the superior catchment Kamianka-Buzka/Western Bug (2,500 km2). It was calibrated for the period 2001–2006 and validated for 2007–2011. Infiltration and drainage parameters were unknown, and were therefore calibrated applying Monte Carlo simulations. It was not possible to calibrate the sub-catchment Sasiv (107 km2) due to high deviations of the natural water balance. Thus, the model was calibrated for the superior catchment and afterwards applied to the Sasiv catchment. The monthly estimated inflow was calculated based on, first, a constant term, which is a fixed monthly inflow with its minimum in October (22 mm) and its maximum in May (41 mm). Secondly, a dynamic term was added. Here, different dependencies were tested, e.g., precipitation, soil moisture, groundwater level, and modelled runoff. The best coefficient of determination was achieved using a monthly modelled runoff from the 4 months before the current time. The model showed a good performance in the validation period (R2 = 0.88). On average, the runoff observed in Sasiv consists of 60 percent groundwater inflow. At the gauge Kamianka-Buzka, this fraction is still about 5 %. The determined LAI cycles and the usage of an additional precipitation station near Sasiv significantly improved the quality of the water balance modelling in the Sasiv sub-catchment. The presented hydrological model approach was extended by hydrogeological simulations to enhance the understanding of processes in groundwater and surface water interactions. Therefore, it was a special challenge to model with scarce data the heterogeneous hydrogeological character of the catchment. The multi-level calibration enables a comprehensible estimation of annual groundwater recharge rates (30–700 mm) of the shallow quaternary aquifer, which is drained by the river Bug system.

One subproject within the project IWAS aims at the identification of effective and sustainable measures to improve the water quality of the river basin Western Bug in the Ukraine in preparation of changes of climate, land use and socio-economy. An important part of the system analysis is the quantification of water balance components. Rare and uncertain data impede hydrological modelling in the region. Approaches to reduce the modelling uncertainty are needed. In this work, we focus on the reduction of uncertainty that results from precipitation observations and parameter estimation during the calibration process. The main aim is to set up a well performing model for water balance simulations. The semi-physically based model Soil and Water Assessment Tool (SWAT) was applied. A calibration and uncertainty reduction strategy was set up that consists of time- and spatial-scale dependencies as well as alternative precipitation inputs. The single models that were set up and calibrated with alternative precipitation inputs are treated as an ensemble and were averaged with different methods. Nine parameters were chosen from the completed sensitivity analysis for all calibration approaches. The calibration strategy revealed the benefit of applying a complex bottom-up calibration that starts with sub-basins and ends with the entire basin. Not only performance improved significantly, but also water balance gaps were identified and henceforth reduced. The usage of daily runoff data in the calibration procedure did not enhance simulations in comparison to monthly data. Simulations improved and parameter uncertainty was reduced applying the SWAT model variants, where precipitation was included in calibration and by the ensemble averaging of the different models. Nevertheless, chosen uncertainty measures are not optimal and indicate that parameter uncertainty is still high. This is attributed to the low density of precipitation stations in the region, their low representativity, and scarce data situation in general. Differences between modelled and observed runoff are large in some occasions and can not be balanced completely by the applied methods. Although this approach reached its limit, it was demonstrated that simulations can be improved and modelling uncertainty can be reduced with an appropriate calibration strategy, with extended precipitation information and the application of an ensemble approach.

Today, integrated water resources management (IWRM) is an important approach for sustainable management and protection of catchment areas. One of the core challenges for a successful IWRM program is the assessment of climate change impacts on the quantity and quality of water resources as well as related socioeconomic sectors. In this context, the climate impact on the hydrology of the catchment “Inflow Reservoir Dobrotvir” situated in Western Ukraine was investigated. The results of the regional climate model CCLM (COSMO—Climate Limited-area Modeling) were used to evaluate the climate conditions for two 30-year future periods in the framework of the future emissions scenarios A2 and B1 as laid out by the IPCC. Based on the projected climatic conditions, a hydrologic impact study was conducted using the Soil Water Assessment Tool (SWAT). Signals of possible future climate and future water budgets were analyzed having the period 1961–1990 as a reference for current climatic conditions. Climatic and hydrologic indices were calculated to assess possible risks and opportunities for the water management sector. In a more generic manner, the implications of climatic changes for the sectors of agriculture, forestry, ecology, energy business and human health were examined with respective literature. Increasing temperatures, declining summer rainfalls and a decreasing climatic water balance were the primary simulated results for the period 2071–2100. These meteorological conditions lead to decreasing soil water content as well as decreasing runoff and groundwater recharge through nearly all seasons. Reduced water yields may affect the energy sector, water supply and water quality negatively. Water stress, especially in summer, might cause declining yields in agriculture and forestry. By contrast, rising temperatures will lead to an extended growing season, which represents an opportunity for higher agricultural and silvicultural yields. However, rising temperatures may also cause indirect effects such as higher risks of pest infestation and germs, which can have a negative impact on a variety of the evaluated socioeconomic sectors. In this work, the impact of possible future scenarios on climate and hydrology as well as resulting risks and opportunities have been identified to serve as a basis for further investigations.

This study aims to analyze and improve modelled extreme precipitation. It was conducted in the German Federal State of Saxony using the WEREX V data set. WEREX V is a model that statistically downscales Global Circulation Model (GCM) data. Inputs for the WEREX V model included GCMs ECHAM 5, HadCM3C and HadGEM2 (sometimes downscaled with Regional Climate Models RCMs REMO, RACMO and CCLM), SRES scenarios A1B and E1, and different model runs. The output of analysis was shown by a boxplot since the WEREX V data set has 120 future projections of precipitation. The model results were verified against observed data obtained from representative meteorological stations, and systematical deviations or biases were identified. To improve the model results, two bias correction methods were applied with special emphasis given to the reproduction of precipitation extremes. Empirical quantile mapping and gamma quantile mapping methods were applied. The ability of the WEREX V ensemble to capture extreme precipitation values varied; this was described in terms of biases. All of the identified correction methods were capable of reducing the bias related to the intensity of extreme precipitation occurrence during the calibration period. The performance of empirical quantile mapping is better than gamma quantile mapping to reduce biases (median value) and uncertainty (inter quartile range value). Penelitian ini bertujuan untuk mengoreksi bias curah hujan ekstrim keluaran model. Wilayah kajian dalam penelitian ini adalah negara bagian Saxony, German sedangkan data model yang digunakan adalah data WEREX V. Dataset WEREX V adalah data GCM yang yang didownscale secara statistic. Adapun GMC yang digunakan adalah ECHAM 5, HadCM3, HadGem2 dan beberapa RCM (REMO, RAMCO, dan CCLM) dengan menggunakan skenarios SRES A1B and E1. Karena dataset WEREX V terdiri dari 120 data model, maka boxplot digunakan untuk menggambarkan hasil analisis baik untuk identifikasi maupun koreksi bias. Hasil keluaran model dibandingkan dengan data pengamatan (observasi) dari stasiun meteorologi. Dari hasil perbandingan ini, bias akan dideteksi. Untuk meningkatkan akurasi model, bias dikoreksi menggunakan dua metode yaitu Emperical quantile mappinh (EQM) dan Gamma quatile mapping (gamma). Kemampuan model (data WEREX V) untuk menggambarkan curah hujan ekstrim berbeda antar stasiun hal ini digambarkan dengan nilai bias yang berbeda. Metode EQM dan Gamma mampu mengurangi bias maupun ketidakpastian model (uncertainty). Performa EQM lebih baik dibandingkan Gamma. Secara umum EQM mampu mengurangi bias maupun ketidakpastian model.

Within the IWRM research project IWAS, we generated regional climate projections via dynamic downscaling for the catchment area of the Western Bug river in the border area of Poland, Belarus, and Ukraine. Data sources used are WMO meteorological station data and global climate ERA40 reanalysis data for an evaluation run, as well as global simulations from the ECHAM5 model for a twentieth-century control run and for the IPCC emission scenarios A2 and B1. We evaluated the performance of the regional climate model CCLM on the basis of simulated 2m temperature and precipitation. Furthermore, we analyzed the hydro-climatic conditions of the past and their projected future changes in the catchment based on 2m temperature, precipitation, potential evaporation and climatic water balance. The latter is discussed as an indicator for potential water availability in the region. Our evaluation, like many other studies, attests that the CCLM performs well for 2m temperature. Precipitation is not modelled adequately for the Western Bug basin. Remarkably, the precipitation bias is five times higher in the ECHAM5-driven control run than in the ERA40-driven evaluation run. Despite all the uncertainties, the significance of the modelled changes clearly suggests robust model results for the last three decades of this century. Up to the end of the century, both scenarios A2 and B1 lead to highly significant warming for each month in the long-term mean, with highest warming rates in winter. Instead, precipitation does not change significantly in the long-term yearly mean, but the intra-annual distribution of monthly precipitation sums shifts, with an increase in winter and a strong decrease in summer. Combined, this leads to a changed climatic water balance with a stronger deficit in summer and a higher gain in winter. Particular in the south-eastern part, the summer deficit cannot be compensated within the annual cycle. This might have serious implications for many socio-economic sectors.

Climate change is one of the key factors influencing the quantity and quality of water resources in hydrologically sensitive regions. In order to downscale global climate simulations from horizontal resolutions of about 125–200 km to about 7 km, a double nesting strategy was chosen. The modelling approach was implemented with the Regional Climate Model CCLM (COSMO-Climate Local Model) with a first nesting covering a central part of Europe and with a second nesting covering parts of Poland, Belarus, and the Ukraine. A control run—driven by global reanalysis data—was evaluated by comparing the model results with corresponding reference data. Long-term yearly and monthly mean differences of temperature and precipitation were statistically assessed. As reference data for the first nesting, the gridded CRU data set with a horizontal resolution of about 55 km was used. Station data of the NOAA and ECA databases were interpolated to provide an appropriate reference data set for the second nesting. Both nestings overestimated long-term yearly precipitation means. Seasonal evaluation of the first nesting showed positive precipitation biases for spring and winter months and negative biases in summer. Furthermore, differences in the spatial precipitation patterns occured, especially in the high mountain area of the Carpathians. The second nesting overestimated precipitation in spring and summer with smaller biases than in the first nesting. Long-term area means of temperature were properly reproduced. The first nesting showed an overestimation for all months with maximal deviations in summer and spring. In contrast, the second nesting was slightly too warm for summer and autumn and too cold for winter and spring.

An approach to combine gauge and radar data and additional quality information is presented. The development was focused on the improvement of the diagnostic for temporal (one hour) and spatial (1×1 km2) highly resolved precipitation data. The method is embedded in an online tool and was applied to the target area Saxony, Germany. The aim of the tool is to provide accurate spatial rainfall estimates. The results can be used for rainfall run-off modelling, e.g. in a flood management system. Quality information allows a better assessment of the input data and the resulting precipitation field. They are stored in corresponding fields and represent the static and dynamic uncertainties of radar and gauge data. Objective combination of various precipitation and quality fields is realised using a cost function. The findings of cross validation reveal that the proposed combination method merged the benefits and disadvantages of interpolated gauge and radar data and leads to mean estimates. The sampling point validation implies that the presented method slightly overestimated the areal rain as well as the high rain intensities in case of convective and advective events, while the results of pure interpolation method performed better. In general, the use of presented cost function avoids false rainfall amount in areas of low input data quality and improves the reliability in areas of high data quality. It is obvious that the combined product includes the small-scale variability of radar, which is seen as the important benefit of the presented combination approach. Local improvements of the final rain field are possible due to consideration of gauges that were not used for radar calibration, e.g. in topographic distinct regions.

Nutrient retention due to sedimentation in running waters has been little studied. The knowledge about the processes of self-purification is important for the management of rivers. The principal aim of our investigations was to quantify nutrient retention by sedimentation within and adjacent to stands of submerged macrophytes. In addition, we examined the relationship between deposition and sedimentation patterns and the flow regime. In the summer of 2001, investigations were performed in the lower River Spree with sediment traps and sediment cores and measurement of flow velocities. The spatial distribution of macrophytes was described and related to sedimentation and flow patterns. Water and sediment samples were analysed for total phosphorus and total organic nitrogen concentrations. Macrophytes significantly enhanced water residence time by factors between 2 and 18. Trapping rates were high within and downstream of macrophyte stands due to the prevailing quiescent conditions. Trapping rates were low in regions not covered by macrophytes, where flow velocities were high. Calculated deposition of organic matter due to trapping rates accounted for 15–49% of observed deposition between May and September, the vegetation period. The difference between calculated and observed deposition can partly be attributed to an incomplete erosion of the organic sediments between October and April. Between May and September, nitrogen and phosphorus were retained by deposition by as much as 2.5% and 12.2%, respectively (% of total load). Therefore, macrophytes considerably contributed to total monthly phosphorus retention (up to 25%) by increasing deposition of particulate organic matter.

Two of the processes that influence the ecological behaviour of lakes are sedimentation and resuspension of fine particulate matter. It is well known that water plants reduce current velocity and alter turbulence structure and, therefore, affect particle transport. Very little is known about short-term sedimentation onto the sediment surface and settling of particles onto plant leaves in submerged macrophyte stands. Therefore, investigations were carried out in a flume. Lake conditions – as they occur in littoral sites not exposed to waves – were simulated by keeping the flow velocity low. Artificial plants without biofilm were used to keep the experiments as simple as possible. As an innovation in sedimentation research, the short-term sedimentation rate onto plant leaves was quantified. To determine current velocities and turbulence, we applied a three-dimensional velocity meter. There was a reduction of current velocity, an increase of shear stress and a doubling of particle retention within the macrophyte stand in all experiments. Rates of sedimentation, both onto leaf surfaces and onto the bottom in the stand, varied significantly in dependence on particle concentration, particle composition and outside flow velocity. Multiple regressions could explain only a part of the measured variance, which is probably due to still insufficient measurements of controlling variables, and processes, such as particle sliding from leaves. No significant spatial pattern of sedimentation in the stand was found. Our measurements showed that plant leaves effectively detain fine particles, even when lacking a biofilm. Our results make clear that sedimentation onto plant leaves must not be neglected when quantifying particle retention in submerged macrophyte stands.

Within the context of flood forecasting we deal with the improvement of regionalisation methods for the generation of highly resolved (1 h, 1×1km2) precipitation fields, which can be used as input for rainfall-runoff models or for verification of weather forecasts. Although radar observations of precipitation are available in many regions, it might be necessary to apply regionalisation methods near real-time for the cases that radar is not available or observations are of low quality. The aim of this paper is to investigate whether past precipitation information can be used to improve regionalisation of rainfall. Within a case study we determined typical precipitation Background-Fields (BGF) for the mountainous and hilly regions of Saxony using hourly and daily rain gauge data. Additionally, calibrated radar data served as past information for the BGF generation. For regionalisation of precipitation we used de-trended kriging and compared the results with another kriging based regionalisation method and with Inverse Distance Weighting (IDW). The performance of the methods was assessed by applying cross-validation, by inspection and by evaluation with rainfall-runoff simulations. The regionalisation of rainfall yielded better results in case of advective events than in case of convective events. The performance of the applied regionalisation methods showed no significant disagreement for different precipitation types. Cross-validation results were rather similar in most cases. Subjectively judged, the BGF-method reproduced best the structures of rain cells. Precipitation input derived from radar or kriging resulted in a better matching between observed and simulated flood hydrographs. Simple techniques like IDW also deliver satisfying results in some occasions. Implementation of past radar data into the BGF-method rendered no improvement, because of data shortages. Thus, no method proved to outperform the others generally. The decision, which method is appropriate for an event, should be made objectively using cross-validation, but also subjectively, using the expert knowledge of the forecaster.